According to a recent report, digitally matured organizations are those who take the road less traveled i.e. their business processes are different than the majority. However, doing things differently is not enough, planning and implementing things differently is the key to success.

Most prudent companies realize how important it is to have a focused and customized digital strategy to excel in a connected world; thereby most digitally matured organizations have a well defined digital strategy in place.

Before embarking on this journey, assessing the organization’s digital maturity will help enterprises in analyzing where to start their digital transformation journey and how to go about creating a ‘digital roadmap’ for the future.

How can organizations start assessing their digital maturity?

Which are the areas to focus on while creating a digital transformation plan?

These are some of the critical questions that we as a digital advisory can help you answer. The right digital partner can help organizations visualize, mobilize and realize their digital transformation strategy.

What does this imply?

So, where do organizations take the first leap of visualizing their digital future?

At Robosoft, we follow a 5As framework to help find some truly comprehensive solutions that can scale an organization’s digital journey.

The 5 A’s framework – Access, Autonomy, Alliance, Agility and Algorithms

Digital Maturity Assessment – Using 5 A’s Framework

Let’s delve deeper into each of these dimensions.

Access

Today millennials desire access over ownership. With a change in consumer behavior we are rapidly moving towards an access economy.

Access economy is the one where resources are shared – tangible or intangible both – it may mean sharing of the workforce, workspace or even knowledge sharing. With this shift businesses too are imbibing processes and technologies to adapt to an access economy.

What does this mean for enterprises?

• Collaborative working ecosystems
• Optimal usage of resources
• Faster processes

The mantra is ‘value unused is waste’ and that represents a shift in cultural consciousness towards valuing experiences rather than goods. Uber the world’s largest taxi services own no vehicles, Airbnb owns no real estate, Alibaba has no inventory, the advent of sharing or access economy has truly changed the rules of the game.

Here are a few examples of organizations across industries leveraging the access economy-

• Mahindra has recently invested in 2 start-ups Trringo and Smartshift. Trringo is an online platform that gives farmers pay-per-use access to expensive farming equipment. Smartshift is a load exchange platform that connects small commercial vehicle owners with people looking to transport their goods within the city.

• With the dual goal of reducing vacant warehouse space and reaching customers in a new way across mainland Europe, the Middle East, and Africa, DHL Supply Chain has pioneered a platform called DHL Spaces to broker unused warehouse space.

Access economy helps is improving the efficiency of resources and optimizing their usage to increase productivity. Co-working spaces companies like WeWork are helping enterprises optimize their fixed space costs and platforms like Upwork are helping organizations in hiring resources as per the need.

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Autonomy

In a digital economy, consumers seek customization alongside flexibility and autonomy. They like making informed decisions with all the information about a product or service, available on the digital platform. It is thereby upon enterprises to leverage digital media to empower consumers in making more informed choices.

While consumers prefer autonomy, they do not want to lose human contact entirely. They reach out to consumer groups for advice and seek assistance before and after a purchase. The need for the human element is also pushing enterprises to custom-build their bots via technologies like machine learning, AI, NLP, etc.

So how can organizations empower their customers at every step of the customer journey?

• Pre-sales

As per this excerpt, 57% of a sale is made even before the actual purchase. It’s thereby crucial for enterprises to ensure their presence on the right digital platforms at the right time, with essential information about their key offerings.

• Sales

Consumers expect convenient & faster services. This is one of the reasons why e-commerce growth has rapidly scaled in the past few years. Even at physical touch points enterprises are offering options for self-service. For instance, McDonald’s has introduced kiosks at their outlets for consumers to order & receive their food much faster.

• Post-sales

In a self-service economy, customers turn to other customers for feedback, reach out to groups and seek assistance with a faulty product or service. Chatbots help in addressing their grievances in real-time.

However, autonomy is not something that is only desired by customers, but it is sought by employees as well. When it comes to creating a digitally matured organization, creating autonomous processes across stakeholders – internal and external is the key.

Alliance

‘If you want to go fast, go alone. If you want to go far, go together.’

Today economy collaboration has become a critical factor for success. Here are some examples of collaborations that are thrusting the business ecosystem way ahead.

• Home Depot, is working with manufacturers to ensure that the connected home products it sells are compatible with the Wink connected home system, thereby creating its own connected home ecosystem, with a wide range of services that are easy to install.

• Philips’ healthcare practice is collaborating with Salesforce to build a platform that they believe will reshape and optimize the way healthcare is delivered. The platform will create an ecosystem of developers, building healthcare applications to enable collaboration and workflow between doctors and patients across the entire spectrum of care, from self-care and prevention to diagnosis and treatment through recovery and wellness.

The norms of competition to have changed drastically. Netflix is a competitor for Inox, Uber is a competitor for automotive companies, so on and so forth. Businesses will have to move beyond the traditional industry silos and build well-collaborated ecosystems, creating new opportunities for innovation. However, every business will need to team up with other players; competition or outside the industry, basis what their core objectives are. Identifying what kind of collaborations and to what extent is the key to developing a robust digital strategy.

Agility

An agile approach is not just limited to software development. It’s an integral part of every business. In the broadest sense, agility refers to an enterprise having an operational structure that gives it the tools to react quickly and efficiently to the ebb and flow of your market. To achieve this type of responsiveness, you need a huge degree of adaptability and flexibility at every level of your organization.

Fast moving, flexible and robust firm capable of rapid response to unexpected challenges, events and opportunities. Built on policies and processes that facilitate speed and change, it aims to achieve continuous competitive advantage in serving its customers. Agile enterprises use diffused authority and flat organizational structure to speed up information flows among different departments and develop close, trust-based relationships with their customers and suppliers.

An agile business model should be all-encompassing. The IT architecture needs to be adaptable and transformative to respond to market trends as they occur. Internal teams need to operate on an almost ad hoc basis if need be, without being bogged down by outdated hierarchical structures and poor digital tools that only slow down operational responsiveness.

Becoming agile is more about adopting a mindset that determines how people work across every aspect of the business.

To deploy an agile system, organizations will have to alter their operating model. For instance, software firms do not go about launching a full-blown product, rather they create an MVP, which allows them to test, experiment and improve, more often and faster. When it comes to adopting an agile system, it encompasses three aspects of the business – Decision making, Learning & Processes.

Algorithms

In a digital economy, data is the new oil. However, as pointed out in this Forbes article “data inherently is dumb”. So, data alone isn’t enough, we need to enhance it to make the most of it. And, thereby algorithms have become more important than ever. We need algorithms to analyze and bring relevant insights from data to the forefront. And, this is how business leaders will be able to identify specific areas to address.

The Airline industry has been using algorithms to set their passenger fares for ages now. There are a lot of variables that come into picture when setting airline prices like class, the position of seat in the aircraft, the rate at which the tickets are being booked, the time of the year, etc. The yield management program used by the industry constantly monitors supply and demand to get the highest revenue for a given seat inventory. E-commerce websites such as Amazon and Alibaba use the algorithmic business model, mainly for pricing, inventory and seller matching.

However, the level of advancement of an algorithm and the degree to which an organization should invest in algorithms will depend on their industry, business objectives and where they are in their digital journey.

Conclusion

When it comes to creating a digital strategy the ‘one size fits all’ approach doesn’t work. Every organization will have its trajectory while going digital. However, where your organization stands when it comes to the 5As as mentioned in this article will be a critical aspect of defining the journey ahead.

When Apple launched Siri in 2011, no one predicted the success of voice technology. 8 years later, almost 100 million mobile phones have a voice assistant. While Industry leaders such as Google and Amazon hold a major market share, voice technology is useful across varied industry channels. From banking to the corporate sector, every industry is observing an increasing number of voice integrations to fulfill customer demands.

Let’s explore why voice is popular, its applications, the technical aspects, and best practices.

Why Voice is Popular

The increased awareness, ever-changing user-demand, and improved user-services through voice integration have triggered a digital shift. The increasing need for speed, convenience, efficiency, and accuracy has added to the increased demand for voice optimization in mobile and other devices. Voice assistants are being integrated into several IoT devices such as appliances, thermostats, and speakers which offer an ability to connect to the user.

Here are some reasons why voice technology is popular in multiple operating devices.

• On average, we can speak 130 words per minute and write only 40 words per minute. This count can be more or less dependent on the user but the idea behind using voice is clear. The speed of speaking is 3 times more than the speed of writing. Users can save time that they have to spend typing.

• In 2012, the speech errors were 33%, and in 2017, it was reduced to 5%. Due to evolving and improving technology, voice search has become more accurate. So, whenever a user speaks something to instruct the device, it is highly likely for the device to understand the instructions clearly without errors.

• It is easier to access voice technology through hardware. Due to the high adoption rate and easy availability, several users have smart devices such as smartphones, smartwatches, and smart speakers. The accessibility of voice search and integration is also high, which justifies the popular demand.

Voice Assistant: Use Cases

Voice technology is not just valuable in the entertainment industry. Healthcare can benefit from voice integration as it will help patients manage their health data, improve claims management, and seamlessly deliver first-aid instructions.

Let’s explore further to find out where voice technology can be utilized.

Enterprise Support

Consider the following two scenarios, in which you will also find two separate use cases of voice for the enterprise.

1. A sales representative is on the market run and he is making notes of the activities and important pointers as he hops from client to client. He is writing it all down but at the back of his mind, he is thinking of how he would have to populate the fields of his office software with this data at a later stage. This is tiring to even think of, right?
2. Everybody is using office supplies and no one is making an effort to replace anything. This goes on until the inventory runs dry and there are no office supplies to use anymore. Assigning this task to a person is such a waste of manpower because his time can be better utilized.

In the first case, the sales representative can directly utilize the smartphone to populate the software field. As he speaks, everything is entered directly to the database, which can be edited later, but the major part of the job is immediately accomplished.

In the second case, Echo Dot can be utilized as a shared device to order inventory supply. You have to maintain the inventory levels and feasibility of the purchase but wouldn’t it be nice to ask Echo to order a box of pens?

Healthcare Support

Voice assistants can lead to seamless workflows in the healthcare industry. Here’s how:

1. There are multiple healthcare devices to help you monitor your health. For example, a diabetes monitor which can be integrated into your Alexa. The solution can help you follow your medication, diet, and exercise properly – everything through voice.
2. Similar to health management, non-adherence to medication is a reason for declining health. Voice control can be integrated into Alexa to remind elders to take medication on time.
3. Alexa Skills are also being utilized to deliver first-aid instructions through voice. When in an emergency, you don’t have to read it, you only have to hear it and move ahead.

Banking Support

The application of voice technology in banking is obvious. You can check your account balance, make payments, pay bills, and raise a complaint. Although these are basic functionalities to help users accomplish the task in less time without any hassles.

In an advanced version, voice technology in banking is currently being explored in collaboration with NLP (Natural Language Processing) and machine learning. In the future, users can expect advanced support from the voice assistant. You can ask the assistant if you are investing in the right fund and the assistant will present statistics to help you understand the situation.

Automobile Support

Another known application of Alexa Skills and Google Voice is in the automobile industry. It is possible to utilize voice technology integration to offer roadside assistance. The voice commands will help you execute emergency automobile tasks without reading it online or even typing it in the search engine. You only have to call out your phone and ask for help.

Application Chatbots

Amazon Lex is a valuable service offered by Amazon to create voice and text conversational interfaces in an application. This service has a deep learning functionality is achieved through automatic speech recognition, which can automatically convert speech to text. Further, the Amazon Lex has natural language processing abilities which offer engaging customer interfaces for high user satisfaction. Both these features of Amazon Lex makes it easier for developers to create conversational bots in the application.

Google Voice and Alexa Skills

Alexa Skills and Google Voice are extensions that help build voice-enabled applications. These are the tools that enable us to make virtual assistants and speakers.

Alexa Skills

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1. In Alexa, headspace is a known skill. Headspace Campfire, Headspace Meditation, and Headspace Rain are all different skills.
2. To invoke these skills, the user has to speak an invocation phrase. This can be anything but we are using Headspace as the invocation phrase as an example here. This phrase is necessary as your skills discovery is dependent on the phrase.
3. It is compared on the web and searches with different utterances such as ask headspace, tell headspace or open headspace. Sometimes, it can trigger even when you say, “Alexa, I need to relax.”
4. The intent of the voice command is to achieve the task a user is trying. Start meditation. The start is the intent here.
5. If a user says start <game>, the start is the intent and <game> is the slot.
6. It is also possible to execute a command with intent such as Alexa, launch headspace. This is similar to opening the home page on the browser.
7. A Fulfilment is an API logic to execute the action or intent such as start <game>.
8. Lastly, Alexa has its built-in intent which is not governed by an external function. If you say, “Alexa, stop,” that is an internal command.

Google Voice

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Google Voice is similar to Alexa Skills with some minor differences:

1. In Google Voice, headspace offers actions (similar to intent), conversation logic is a dialog flow, and the agent is at backends such as headspace meditation or headspace rain.
2. Agent in Google accomplishes actions – “Ok Google, start headspace meditation.”
3. You can also use “Ok Google, launch headspace” to start an action with no intent.
4. Google has in-built intents like “Ok Google, help me relax” which gives Google several options and one of these is headspace.

VUX Design Research

When you are building actions or skills in Google or Alexa, it is necessary to know various research outcomes given below:

1. Understand how different types of users are interacting with the platform or a specific category.
2. Understand the intent of the user and know the why of using the voice assistant.
3. Understand how actions and skills are performed with the help of different phrases or utterance.

1. Be Specific – Every user can consume more graphical information compared to voice. No one can sit through the voice commands for a long time. So, ensure that your app is visually appealing.
2. The introduction is the Key – When the user starts the action with no intent, “Alexa, launch headspace,” introduce yourself. Welcome them and help them adjust to your application.
3. Prompt Again – When the user stops responding, prompt again. But, do this without overdoing it, just a short re-prompt is enough.
4. Include Error Messages – You need to include error and help messages to pass certification. For example, ask the user to keep the mic close for the response (tip).
5. Include Invalid Inputs – When the voice command is unclear, have invalid responses stored for better interaction.
6. Immediate Response – Avoid delays. You can’t give a 10-second speech before playing the song user wants. If the user says, “Play XYZ,” simply say “Playing XYZ” and just play. When the user says pause, Pause.
7. Don’t Include Unavailable Intents – Do not include any intent on the app which is not feasible for voice commands. This can lead to certification rejection.

How to Set Up Voice Skills?

Alexa Skill

1. Start by signing in or logging in to your dashboard and then click on ‘Get Started’ under Alexa Skills Kit. After that, click ‘Add new skill’.

2. As we are creating a custom skill, click on the ‘Custom interaction model’ and add name and invocation name. Name is defined for your dashboard and invocation name is defined to activate the skill on Amazon Echo. Once you have entered the skill information, move to the interaction model and ‘Launch Skill Builder’. Here, add the intent name and utterances. The intent is the intention of the user behind a skill.

For example, if the intent is ‘Hello World’, utterances can be, ‘Hi’, ‘Howdy’, etc.

Save this model and go to ‘Configuration’ to switch to AWS lambda.

3. Now, go to the lambda page and select ‘Create function’. There are several templates for ‘Alexa-SDK’, in our example, we will use ‘Alexa-skill-kit-SDK-factskill’.

Enter the name of the function and select ‘Choose an existing role’ from the drop-down. The existing role is ‘lambda_basic_execution’.

In the ‘Add triggers’, you will find ‘Alexa skill kit’ which will help you add ‘Alexa skill kit’ trigger to the created lambda function.

4. Before moving forward, create a test function and copy the ARN endpoint for the next step.

5. Lastly, complete the process by going to ‘Configuration’ and completing the Endpoint section by selecting ‘AWS Lambda ARN’ and pasting the copied ARN here. Click on the ‘Enable’ switch and you are done.

Google Voice

1. Create a Dialogflow account or log in to an existing account. Click on ‘Create Agent’ and add details such as name, Google project, etc.

2. Go to Intent and click on ‘Create intent’. Give your intent a name and add utterances or sample phrases. (Similar to what we discussed above).

3. In the ‘Response’ field, type the message that you wish for your intent to respond with.

1. Asynchronous Information Gathering

Voice applications are hosted on the cloud and asynchronous gathering of information can improve response time. When extracting information, there are several data points, which are on different server endpoints. If there is latency, you can reduce the experience immediately. Your user would have to watch the Light on Alexa Spin until the data is fetched. This is why it is best to use an API to bring data from various endpoints to one endpoint for real-time interaction.

2. Mapping Conversations

Your answers on Alexa should be updated. If you are confused about what to add, look at the FAQ section of your website. If there are FAQs that can’t be added without graphical representation, it is best to not add these.

3. Support Linguistics

Different users can express themselves differently. For instance, you may ask, “Alexa, book a cab to XYZ,” but your friend may say, “Please book me a ride to the airport.” The difference in linguistics is natural to most of us and we don’t want to change it just to interact with an application. If the application itself adjusts to our linguistics, that is something useful. So, add these utterances in your voice assistant to improve the experience of your users.

4. Use Short Responses

If your responses are long, your users will soon lose interest. It is hard to concentrate when the voice assistant is delivering long commands. Users get impatient and leave the conversation in between. Ensure that your voice responses are short and sweet. Also, understand that the sentence that seems shorter in writing may be irritatingly long with voice. So, take extra measures to remove these responses.

5. Use minimum Choices

If you are giving your user choices, stick to maximum 3 choices. Fewer choices are always better, so keep your options to a minimum, always. If you have more choices, it would be hard for the user to recall 1st choice when the assistant is reading out 3rd or 4th choice.

6. Reduce Pressure

Reduce the pressure on the audience by improving your response time and responses. If your voice assistant stays quiet for a very short duration after speaking, you can put the user under stress. Allow a considerable time or even if you have to keep the wait time short, the next sentence should be supporting. For example, would you like me to repeat the list?

Challenges of Voice Assistants

Voice Tech is Ambiguous

Voice tech is often ambiguous because it fails to reveal what users can achieve with it. With visual tech, it is possible to extract functionality through buttons, images, labels, etc. However, something like this is not possible with voice.

Further, hearing something and retaining it is usually harder than reading and seeing something to retain it. That is why it is hard to know what could be the best way to deliver options if the application has several options for a particular action.

Privacy Concerns

Privacy is a reason of concern for every business and more so for ones that offer voice assistants.

Why? Let’s find out:

While Siri is programmed to your voice and it activates whenever you say ‘Hey Siri’, anyone can ask a question. Siri just doesn’t know the difference between your voice and someone else’s voice.

How it can impact us? Of course, it affects permissions.

Think of a child ordering several toys from Alexa. This would happen without parent authorization. This also means that anyone can misuse your credit card if they are anywhere near your Alexa. Voice technology and assistants are convenient but security concern is a major issue.

Conclusion

The consumer-led era today demands platforms and technologies that can simplify and step up the customer service experience. Voice technology is revolutionizing customer experience and enabling personalization at a whole new level. Proactive strategies based on customer feedback, browsing, and purchase trends have become much easier to implement, enforcing companies to upgrade their customer experience models backed by technology.

Factors like speed, convenience, and personalization are key differentiators that influence customer decisions and buying behavior. And Voice Technologies like, Google Voice and Alexa Skills are facilitating this process matchlessly. With most businesses switching to technology-based solutions, Voice Technology is likely to play a crucial role for organizations driven by customer service excellence.

Java has automatic memory management. It performs routine garbage collection to clean up unused objects and free up the memory. However, it is very important for us to know how the garbage collector works in order to manage the application’s memory effectively. Thus avoiding OutOfMemoryError and/or StackOverflowError exceptions.

Let’s start with the memory structure first. For effective memory management, JVM divides memory into Stack and Heap.

Stack Memory

Java Stack memory is used for the execution of the thread. They contain method-specific values which that are short-lived and references to the other objects in the heap that are getting referred from the method.

Example:

public void methodA() {     
      int a = 10;
      methodB(a);
}
public void methodB(int value) {
      int b = 10;
      //Rest of the code.
}

Stack Memory

From the above picture, it is clear that local variables of the respective method will be created in the same frame. For example, variable “b” of “methodB” can be accessed by “methodB” only and not by “methodA”, as “methodA” is in separate frame. Once the “methodB” execution is completed, the control will go to the calling function. In this case, it’s “methodA”. Thus, the frame for “methodB” will be removed from the stack and all the variables in that frame will also be flushed out. Likewise, for “methodA”.

Heap Memory

Java heap space is used to allocate memory to the objects. Whenever we create Java/Kotlin objects, these will be allocated in the Heap memory.

Garbage collection process runs in the heap memory. Let’s go through the basic garbage collection process and structure of the heap memory in detail

Garbage Collection Process

Garbage Collection is a process of cleaning up the heap memory. Garbage collector identifies the unreferenced objects and removes them to free the memory space.

The objects that are being referenced are called ‘Live objects’ and those which are not referenced are called ‘Dead objects’.

This process can be triggered at any time and we don’t have any control over it. We can also request the system to initiate GC process in case we want to. But there is no guarantee that it will be initiated by the system, it is up to the system to decide.

Let’s go through the basic process involved in Garbage collection.

Step 1 : Marking

Most of us think that Garbage Collector marks dead objects and removes them. In reality, it is exactly the opposite. Garbage Collector first finds the ‘Live objects’ and marks them. This means the rest of the objects that are not marked are ‘Dead objects’.

Step 2 : Normal Deletion

Once Garbage Collector finds the ‘Dead objects’, it will remove them from the memory.

Step 3 : Deletion with Compacting

Memory allocator holds the reference of the free memory space and searches for the same whenever new memory has to be allocated. In order to improve performance, it is better if we move all the referenced objects to one place. Thus, this step helps in improving the memory allocation process.

Basic GC process

This algorithm is called a mark-sweep-compact algorithm.

As the number of objects increase, the above process i.e., Marking, Deletion and Deletion with compacting is inefficient. As per the empirical analysis, most objects are short-lived. Based on this analysis, the heap structure is divided into three generations.

Heap Structure

The heap structure is divided into three divisions namely, Young Generation, Tenured or Old Generation, and Permanent Generation.

Heap Structure

Young Generation – This is where all the new objects are allocated and aged. This generation is split into Eden Space and two Survivor spaces.

Eden Space – All new objects are allocated here. Once this space is full, minor Garbage Collection will be triggered. As mentioned, when the Garbage Collection is triggered, it first marks all the live objects in Eden Space and moves them to one of the Survivor spaces. Thus, Eden space is cleared so that the new objects can be allocated there again.

Survivor Space – After Minor GC, the live objects from Eden space will be moved to one of the survivor spaces S0 or S1.

The below diagram describes the Garbage Collection process in Young Generation.

GC process in Young Generation

Let’s see how the object is allocated and either flushed (Garbage Collection Process) or moved to an older generation in detail. Each point below explains the respective state number mentioned in the above diagram:

1. Initially, all objects are allocated in Eden Space.
2. Once Eden Space is full, Minor GC will be triggered. Minor GC is always “Stop the World Event”. This means that when this process is executed, the application thread will be stopped.
3. The first step in GC Process as mentioned is Marking. Garbage Collector identifies live objects and marks them. As shown in the above picture, two of the objects are referenced while others are unreferenced objects.
4. Once marking is done, live objects in Eden Space are copied to one of the Survivor spaces and the rest of the objects are removed. Thus, clearing Eden Space. This algorithm is called a mark-copy algorithm. In order to understand the aging of the objects, let’s consider the age of the object in S0 as 1.

This shows the state of Young Generation after Step (4)

1. Now, if new objects are to be created then these will be allocated in Eden Space.
2. Once again Eden Space is full, which in turn triggers Minor GC. Here, objects in the Eden Space and Survivor space S0 are scanned. Garbage collector marks all the live objects in Eden Space and S0. As shown in the diagram, at this stage Eden space and S0 have one live object.
3. In Step (7), the marking process is completed. Thus GC will move all the objects from Eden Space and S0 to S1. This clears both Eden Space and S0. Let’s calculate the age of the object. The age of the object moved from S0 to S1 will be incremented by 1. Thus, its age will be 2. The age of the object which is moved from Eden Space to S1 will be 1.
4. Now, if new objects are to be created, they will be allocated in Eden Space of the young generation.
5. Once again Eden Space is full, which in turn triggers Minor GC. Here, objects in the Eden Space and Survivor space S1 are scanned. Garbage collector marks all the live objects in Eden Space and S1. As shown in the diagram, at this stage Eden space and S1 have two live objects.
6. All the live objects from Eden space and S1 will be moved to S0. The age of the objects moving from S1 to S0 will thus be 3 and 2 respectively as shown in the diagram. This means that in this process, age will be incremented by 1. The objects moving from Eden Space to S0 will be 1.
7. This stage shows the object moving from the young generation to the old generation. Let’s set the threshold for the age of the object to move to the old generation to 9. Consider the scenario where the age of the object is 9 in the young generation. As the age of the object has met the threshold, this object will be moved to the Old Generation.

Note: Observe that, at any given time only one survivor space has objects. Also, note that the age of the object keeps increasing when switching between the survivor spaces.

Old Generation – Here, long-surviving objects will be stored. As mentioned, a threshold will be set to the object, on meeting which it is moved from the young generation to old or tenured generation. Eventually the old generation needs to be collected. This event is called a major garbage collection.

Major garbage collection are also Stop the World events. Often a major collection is much slower because it involves all live objects. So for responsive applications, major garbage collections should be minimized. Also note, that the length of the Stop the World event for a major garbage collection is affected by the kind of garbage collector that is used for the old generation space.

Note: Responsiveness means how fast an application can respond. The applications that focus on responsiveness, should not have large pause times. This in-turn means, memory management should be done effectively.

Permanent generation – This contains metadata required by the JVM to describe the classes and methods used in the application. The permanent generation is populated by the JVM at runtime based on the classes in use by the application. In addition, Java SE library classes and methods may be stored here.

Types of Garbage Collectors

1. Serial GC
2. Parallel GC
3. Concurrent Mark and Sweep (CMS) collector
4. G1 Collector

These garbage collectors have their own advantages and disadvantages. As Android Runtime (ART) uses the concept of CMS collector, we will only discuss Concurrent Mark and Sweep (CMS) Collector here.

GC Algorithms

An important aspect to remember is that, usually two different GC algorithms are needed – one for the Young generation and the other for the Old generation.

We have seen the core concepts of GC process. Let’s move to the specific GC type which is used as default by Android Runtime.

The default GC type used by ART is CMS Collector. Let’s look into it further in detail.

Concurrent Mark & Sweep (CMS) Collector

This collector is used to avoid long pauses during the Garbage collection process. It scans heap memory using multiple threads. It uses parallel Stop the World mark-copy algorithm in the young generation and concurrent mark-sweep algorithm in the Old Generation.

As discussed, Minor GC occurs in young generation whenever Eden Space is full. And this is “Stop the World event”.

GC process in Old generation is called Major GC. This garbage collector attempts to minimize the pause duration that occurs during the GC process by doing most of the Garbage Collection work concurrently with the application threads.

We can split the Major GC into the following phases:

Phase 1 – Initial marking

This is one of the “Stop the World” events in CMS. In this phase, the objects that are either direct GC roots or are referenced from some live objects in the Young Generation are all marked. The latter is important since the Old Generation is collected separately.

Note: Every application will have a starting point from where objects get instantiated. These objects are called “roots”. Some objects are referenced with these roots directly and some indirectly. GC tracks the live objects from those GC roots.

Phase 2 – Concurrent Marking

During this phase the Garbage Collector traverses the Old Generation and marks all live objects, starting from the roots found in the previous phase of “Initial Mark”. This phase runs concurrently with the application thread. Thus, the application thread will not be stopped.

Phase 3 – Concurrent pre-clean

This is again a concurrent phase running in parallel with the application thread. While marking the live objects in the previous phase, there is a possibility that few of the references would be changed. Whenever that happens, the JVM marks the area of the heap called “Card” that contains the mutated object as “dirty”. This is known as Card Marking.

In the pre-cleaning phase, these dirty objects are accounted for, and the objects reachable from them are also marked. The cards are cleaned when this is done.

Phase 4 – Concurrent Abortable Preclean

This phase again runs in parallel with the application thread. The purpose of this phase is to mark most of the live objects, so that the next phase will not take much time to complete. This phase iterates through the old generation objects to identify the live objects. The duration of this phase depends on a few of the abortion conditions such as the number of iterations, elapsed wall clock time, amount of useful work done etc. When one of the mentioned conditions is met, this phase will be stopped.

Phase 5 – Final remark

This is the second and last stop-the-world phase during the event. The goal of this stop-the-world phase is to finalize marking all live objects in the Old Generation. Since the previous preclean phases were concurrent, they may have been unable to keep up with the application’s mutating speeds. A stop-the-world pause is required to finish the marking.

Usually CMS tries to run final remark phase when Young Generation is as empty as possible in order to eliminate the possibility of several stop-the-world phases happening back-to-back.

Phase 6 – Concurrent Sweep

The purpose of this phase is to sweep off the dead objects in the old generation. As the final marking is done, there is no dependency on the application thread now. Thus, this phase runs concurrently with the application thread.

Phase 7 – Concurrent reset

This phase which runs concurrently with the application thread, resets the inner data structures of the CMS algorithm, preparing them for the next cycle.

ART GC Overview

As described, ART uses CMS as the default GC type. CMS tries to reduce pause time by doing most of the work concurrently to the application thread. The basic GC algorithm remains the same. However, ART further optimizes the algorithm process which uses mostly sticky CMS and partial CMS. In addition to the CMS plan, ART performs heap compaction when the app is moved from background to foreground.

Sticky CMS is ART’s non-moving generational garbage collector. It scans only the portion of the heap that was modified since the last GC and can reclaim only the objects allocated since the last GC. As it frees the memory objects allocated only since the last GC, this is much faster and has less pause time.

Partial CMS means it collects all the spaces except for image spaces and zygote spaces.

ART also introduced a new bitmap-based memory allocator called RosAlloc (Runs of slots allocator). This outperforms DIMAlloc by adding thread-local buffers for small allocation sizes.

Overall, the ART improves the CMS GC plan further to optimize the performance of the system.

Restricted App Memory

The heap size limit for an application varies from device to device. To maintain a functional multi-task environment, Android sets a hard limit on the heap size of the app.If an app tries to allocate more memory when it has reached max heap capacity, then it will throw an OutOfMemoryError. However, one can call getMemoryStatus() to know about the memory status of the app’s heap. Also, if the pause time of the GC process is more, then there is a high chance of “Application Not Responding” error. Either way, it results in a bad user experience.

When a user switches between the apps, Android keeps Apps that are not in the foreground in Least-Recently-Used (LRU) Cache. This means that, when the user switches back to the previous app the state/process will be restored. Thereby, improving the user experience.

As an app process is cached, if it retains memory of the objects which are no longer used then it affects the overall performance of the system. When the system runs low on memory, it starts clearing the processes in LRU starting from the least recently used app. Also, the garbage collector estimates which app is consuming most of the resources and tends to kill the process.

Thus, less memory the app consumes, the more likely it is to remain in the LRU cache which inturn increases user experience.

In addition, we need to avoid memory leaks. A memory leak happens when you hold on to the object long after its purpose has been served. This means that if the object which is no longer needed is not unreferenced, then the garbage collector still thinks it as referenced one, due to which it will never be garbage collected.

Tools to detect memory leaks

As discussed, we need to avoid memory leaks to run applications effectively. There are tools to monitor memory usage and detect memory leaks. A few examples include, Android Profiler and Leak Canary.

Android profiler tool provides real-time data to help understand the CPU, Memory, Network and Battery usage of the app. Android profiler is compatible with Android 5.0 and above.

Leak Canary is a memory leak detection library in Android. This library runs along with the app, dumps memory when needed, looks for potential memory leaks and gives a notification with a clean and useful stack trace to find the root cause of the leak.

Conclusion

Even though garbage collection is quite fast, it still can affect app performance. One cannot control when garbage collection will be triggered. Thus, it is very important for us to know how the GC process works and what should be avoided to improve app performance.

‘Walk a mile in their shoes’ is often used an expression to convey that the design thinking process is built on empathy. As Design Thinking professionals we work on diverse projects and user needs. Sometimes, we may not be able to fully understand the motives, pressures of others’ lives.

Is it really possible for an urban male executive to truly feel how it is to be a single working mom or experience the challenges of say, working in an oil rig? I can never truly feel how it is to be a doctor using a critical patient information app, that too in the pressure of a hospital scenario. I can at best, get a peek into their lives in such a situation.

Hence, in my view, we have to understand ‘empathy’ within a context and realize its limitations as we are all shaped by our own influences, limitations, experiences and biases. That’s where Usability Testing comes into play as it can provide first hand information and insights for actual users.

Design Thinking is a holistic problem-solving framework and involves these key stages:

• Empathize: Understand the user’s needs and problems
• Define: Analyze the observations to define the problems
• Ideate: Think of solution to each aspect of the problem
• Prototype: Develop solution prototype for each aspect of the problem
• Test: Test the product using the best solutions identified

The last phase is as critical as any other as it provides directions to product owners, strategists and designers for iterations and tweaks. Also as Design Thinking can play a role in transformation of any process – business development, operations, finance, marketing or product development it can truly impact business growth. In that context direct feedback from actual users eliminates guess work. It can also save expensive re-work in correcting flaws well before they are discovered in the marketplace.

Usability Testing: the fundamentals

The key intent of a Usability Test is to test the functionality of designs with real users in order to get a flavor of ease of use, navigation and other parameters. However, instead of leaving it all to observation and gut feel, the process involves thorough documentation and follows a process. A website, mobile app or any other digital product could be tested through this method.

There are two types of methods:

(a) In-person testing in a laboratory environment and (b) remote testing using a set of software tools. The former has an observer who is silent throughout the process and only monitors the behaviour of users and then reports the outcome. In the latter case, the screen activity, facial expressions are recorded by automated software applications.

The process involves 6 broad stages:

User groups: the participant characteristics are naturally determined by the product intent. As a thumb rule, the sample size should have 9 participants per country (2 pilot, 5 regular and 2 backup).

Tasks: we need to identify key user journeys based on the objective of the app or the digital product. It could be completing a transaction for a banking product or completing a survey in a website.

An example task scenario for a restaurant table reservation app could be:

• Finding a restaurant
  You live in Charlotte and would like to reserve a table at an upscale restaurant to mark a special occasion

• Choosing the location
  You would like to find a restaurant which is not very far from your place of living

• Finding types of cuisines
  Since it is a special occasion, you’d like to experiment with gourmet food, maybe an exotic cuisine which you have not tried before

• Making a reservation
  You have identified a suitable restaurant and would like reserve a table for two

• Receiving confirmation and viewing a reservation
  Once booked you would like to receive a confirmation alert and also view the upcoming reservation

• Editing your reservation
  You would like to change the timing of your reservation and increase the number of guests to 4.

Metrics: we then need to create standards of measurement by which design, ease of use, efficiency and performance can be assessed. The metrics could be objective (metrics that you can measure without relying on subjective interpretation) or subjective (metrics that rely on subjective interpretation of the test participant)

Environment: this includes creating a setup to make the users feel comfortable and have all the necessary equipment at hand. These could include relevant devices, documentation for ratings and a suitable lab test location.

Usability tests: among the various methods used are Task Sheets, heat maps, observations and rating charts. A task sheet typically records the success rate (2 = Success; 1 = Needed Support; 0 = Failed) and time taken to complete a task. While Heat Maps provide a high level overview of the drop and success rate, observations add the human angle by noting facial expressions and other emotional reactions. Finally, asking the users to rate their experience while using the product gives testers and stake holders a feel of the ease of use.

Test Reports: a typical test report will include an executive summary, goal of the test, methods used, data overviews, walk-through of the results of each task and actual quotes (positive & negative) from the users.

Usability Testing is increasingly being adopted by enterprises to minimize risks and validate product features before launch. Across the globe, there are several venues, including academic institutions which host Usability Testing Labs. Moving forward, co-working spaces which offer cost savings and convenience through shared infrastructure equipment, utilities etc., could offer such services to enterprises – all it takes is a room and some basic equipment.

The benefits of Usability Testing

More than ever before, customer experience defines business success today. A poor experience on a website, mobile app or any other digital product can mean loss of a customer forever. Very rarely do customers give brands a second chance to serve them.

At Robosoft, we believe in simplifying lives through delightful digital experiences. A robust Usability Testing exercise gives enterprises a better chance of providing a great customer experience, the new battleground. It can help get validation from actual users and get a first hand feedback if it meets their expectations. It can point to barriers which need to be overcome, help point out errors and assumptions. Those working on any creation can get far too attached to it and lose a sense of objectivity – they may not see the features and navigation methods the same way as the actual user.

Usability testing is a great way to manifest empathy, which is the starting point to any Design Thinking effort. In other words, it is a small but effective investment in the larger scheme of things – well worth the effort in crafting delightful digital experiences.

Can you imagine taking financial advice from sophisticated robots and AI-based apps before making an investment on a real-time basis? This will be the norm sooner than you can imagine. Online banking has become the primary interface channel for most consumers today. It is now becoming evident that the mounting pace of technological reforms is the most powerful force driving the financial services ecosystem globally.

The banking industry has seen radical technology-led transformations over the last decade. Most banking executives look to their IT support teams to maximize efficiency and facilitate groundbreaking innovation, while supporting the legacy systems & lowering costs. In the interim, FinTech start-ups are exploiting established markets and winning with customer- friendly solutions. Customers today have a slew of options and have scaled their expectations demanding agile, responsive, real-time, seamless, innovative and an integrated experience. And the pace of change & technology trends shows no sign of slowing.

As per a trend analysis from Gartner, within 12 years, “80% of financial firms will run out of business or be rendered inoperable due to changing customer expectations, competition and technology advancements.”

In 2018 alone, banks worldwide had planned to invest $9.7bn to improve and enhance their customer-facing digital banking tools. In the coming years, digital solutions in banking will include more nuanced approaches with big data, advanced analytics, and new platforms that automate tasks—enabling banks to increase both personalization and quality of customer service. To stay relevant to the ever evolving customer who is increasingly aware, time poor and tech savvy banks need to reevaluate customer interaction frameworks for a more personalized, flexible and value-driven experience.

Trends Impacting the Financial Services Industry

According to a research from Atos, the most transformational challenges and opportunities for the future of banking include, response to customer needs, cost optimization, creation of new revenue streams, developing security & compliance systems, expanding digitalization and innovation. All of these have a few things in common: a customer-centric approach, real -time & intelligent data integration & an open platform foundation. While some of these transformations would require modernization of outdated technologies & rethinking the traditional legacy models, the others would demand strategic partnerships & collaboration with Fin-tech firms. But there’s one thing that’s certain – the need for transformation. Financial firms that use advanced digital tools could potentially see a 30% reduction in IT costs if implemented effectively.

The choice is clear – lead the industry with customer-friendly digital experiences or be led by the competition.

The banking landscape is set to evolve at a greater magnitude in the next few years. While safety-features like biometrics and cryptography will explore ways to arrest scams faster, technology applications will make banking more of a virtual experience without having to visit one. The good news is that many of the new technologies that are threatening the banking industry today also present significant opportunities. Organizations that can capture analytics, data and technologies to enhance user experience can inspire customer trust which is the key contributor to success.

Here are 6 technologies banks must consider, to deliver an exemplary customer experience:

1. Personalize with AI

The benefits of using Artificial Intelligence in banks and credit unions include optimizing back-end operations, data management, customer experience, compliance, product delivery and risk management. It’s not just about products and services on a well-integrated digital interface anymore; customers expect personalized experiences that are aligned with their preferences and behavior patterns. In other words, they expect you to give them practical & profitable alternatives that they did not think of themselves. Customers want you to assess their financial moves and reward them regardless of the platform they use. Bank of America piloted its popular chatbot, Erica, in late 2017 and boasts of 6 million users as of March 2019. With AI-backed models, the potential to transform banking experiences with a holistic overview of the customer behavior is truly exponential. What’s needed is a robust integration of an AI model infused with human expertise to provide personalized experiences for different customer prototypes.

2. Voice-ready banking

Just as how voice assistant Alexa was unfathomable a decade ago, so will be the trend for banking experiences without voice-first devices, where more than 50% of banking interactions will be voice-based.

As per a report from Analyst Firm Juniper Research, voice-based commerce will reach $80 billion by 2023. Voice-first devices are becoming an integral tool with consumers accomplishing tasks such as shopping, banking and home automation more seamlessly, due to which many banks and credit unions are taking to voice-first applications. Moving from the basic dialogues & account inquiries to more sophisticated transactions like executing payments, account transfers & setting account alerts using voice commands.

3. Instant Payment Gateways

The payments industry is by far one of the most dynamic areas of innovation in the banking industry. With the heightened surge of instant payment platforms, banks can influence greater customer satisfaction with customers expecting faster & seamless payment experiences.

Today, instant payment methods are available across most countries and a few where banks collaborate to offer an instant P2P payment experience, catering to a larger customer base. While large fintech firms, tech players and financial institutions continue to innovate based on evolving customer expectations and technology advances, this industry will soon be a part of everything customers do. Innovative payment trends will occur in conjunction with the Internet of Things (IoT), point of sale (POS), mobile wallets, cryptocurrencies, and blockchain. By diversifying and infusing instant payment capabilities across the e- and m-commerce space, banks and credit unions have a greater scope to build an innovative portfolio of customer-friendly services. And organizations that value customer payment insights as an intellectual organizational asset, can further segment and create personalized customer experiences basis their core behavior patterns.

4. Robotic Process Automation (RPA)

The robotic process automation refers to the use of virtual assistants that can perform repetitive and laborious tasks; making it ideal for the banking industry. As per a report from P&S Market Research, the global RPA market is expected to reach $8.6 billion by 2023. RPA in banking can disrupt the business-process-outsourcing models, as it minimizes costs while maximizing productivity.

The robotic process automation (RPA) is assisting banks to create meaningful customer engagement that is real time, quick, efficient and productive. It helps in executing pre-programmed rules across structured & unstructured data, for both customer-facing and back-office functions. RPA helps in minimizing costs & simplifies compliance with detailed logs to extract automated reports & enables automated decisions, based on previous data patterns, eliminating room for human error.

Deutsche Bank is deploying RPA to manage repetitive tasks more efficiently. It has reported 30- to 70-percent automation in areas where software is integrated and noted a remarkable decrease in the time required for employee training. With effective RPA implementation, banks can reduce manual work and enable banking executives to focus on the more complex strategy driven tasks.

5. Open Banking with API Platforms

Open Banking is based on open application programming interfaces (APIs), that allow trusted third-party developers to build services & technology interface for financial institutions.

APIs help to develop innovative products for a better customer experience, where the bank serves as a platform, over which third party companies build applications using the bank’s data. In this context, the Mastercard offering is designed to assist open banking efforts in better connectivity, consulting, dispute resolution and security & compliance. Emphasizing how Europe and its regulators inspired the Open Banking and the associated PSD2 regulatory regime, the Mastercard service is currently focused around UK & Poland and includes several payment and financial service providers including Alior Bank and Kikapay. Mastercard’s vision is to develop a host of Open banking services with optimal standards of clarity and consistency. If you are looking to deliver financial innovations, API partnerships are the fastest way to get there.

6. Wearable Technology

Being able to pay with just a gesture takes a lot more than a gadget on your wrist. It requires a huge amount of data available anytime, anywhere. The device needs to store payment & location information while authenticating the user, to avoid fraudulent transactions. This is possible through a host of technologies like sensors, communication devices, servers, analytics engines, and decision-making aids that gather data and analyze it before making any decisions.

Wearables offer extensive personalization with an individual focus to every single customer. Banks can use Bluetooth beacons for personal greetings every time a customer enters or exits a location via their smart watches. Smart glasses can help bank tellers process customer banking information while simultaneously doing other customer service tasks, as per a report from Deloitte. The ever-evolving consumer behavior and smart device trends are scaling the consumer banking experience to a whole new level of convenience. Wearable Technology helps to seek customer insights through interaction with other apps, services and technology. Embracing the technology crossover for instance is an ideal method to achieve this. Delivering a bank statement to a customer’s Apple watch or enabling them to make voice-based transactions while driving are two examples of how the banking interactions can be a part of the customer life cycle without being intrusive.

The Way Forward

The pace of the banking technology landscape is increasing and shows no sign of slowing. To excel in this rapidly evolving ecosystem, financial institutions need to devise a clear strategy with a laser-sharp focus on customer preferences; even if this means partnering with FinTech firms or adapting strategies from other industries. Here’s what you can get started with:

1. Minimize costs by simplifying legacy systems
2. Develop technological capabilities that can help predict customer intent & retrieve behavior patterns
3. Build an integrated & user-friendly architecture to connect to anything, anywhere

While all these priorities are equally important and most certainly achievable, to stay relevant, the trick is to combine short-term & long-term initiatives that are aligned to your overall brand vision.

Summary

Even with the best of technologies in place, no one can predict what the future holds for the banking industry. What seems certain however, is that the disruption in the banking sector will continue at a steady pace and banks will continue to transform and embrace digital technologies that are here to simplify the customer experience. Developing a proactive approach rather than responding to trends will define your success in the long run. There is no single technology that is a universal solution, finding the right combination that aligns with your vision will determine your success in the near future.

Personalization has inherently been associated with digital commerce where technology and data often go hand-in-hand. But owing to the proliferation of new-age tech inside brick-and-mortar stores, the trend is now seeping into retail.

In the past, in-store personalization was mainly attributed to a sales assistant interacting with customers and asking them relevant questions to map their shopping behaviors and needs. Modern-day technologies have been able to capture and scale this behavior towards better avenues of segmentation, customization, and contextualization. Armed with a plethora of solutions, retailers are now able to combine historical cross-platform knowledge of every visitor with a real-time context. A study from Accenture reiterates the importance of such a strategy. According to it, 75% of the customers are more likely to buy from a retailer that leverages personalization elements such as their name, personal recommendations, and preferences.

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The same research also reveals that most of the consumers comfortably share their data with businesses that are transparent about how they use their data and lets them control how the data is used.

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Even after all this, there is a knowledge gap between the expectations of the market and the response from retailers. For instance, research by Retail Week in the UK revealed that only 14% of retailers consider personalization as an essential consumer experience strategy.

Key Technologies Personalizing Retail

To successfully leverage personalization, it requires a prompt understanding of the customers and their needs in a way that collects, analyzes, and streamlines data. Here’s a look at the various technologies are helping retail companies in this regard:

1. Artificial Intelligence and Machine Learning

Retailers are leveraging AI and Machine Learning to Automate workflows and drive better decisions. With AI, they are now able to track the buying behaviors and lifestyle choices of customers, automate redundant tasks, and improving the productivity of employees. Emerging AI trends in retail include:

• Customer Insights and Journey Mapping: Natural Language Processing and Machine Learning can sift through copious amounts of customer data to understand them better and accordingly personalizing product recommendations, designs, and end-to-end shopping experiences.

• Virtual Personal Assistants (VPAs): VPAs such as conversational chatbots can now address customer queries in real-time and at scale. Digital retailers can cater to thousands of customer queries simultaneously, boosting response time and query resolution.

• Predictive Analytics: By analyzing data about historical sales, marketing campaigns, website interactions, and customer support, prescriptive and predictive modeling is being used in marketing, merchandising, and even hiring.

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Case Study: Sephora is equipping its employees with hand-held devices that can scan the faces of customers, capture their exact skin tone, and recommend products by matching it with relevant shades. The AI-powered device even creates a four-digit code that is known as the Color IQ of the customer. All associated data with every ID is then securely stored to personalize future shopping experiences.

2. Voice Recognition Technology

With numerous voice-powered devices such as Amazon Alexa, Apple Home Pod, and Google Home being launched by tech giants, use cases of voice technology in retail have been on the rise. It is revolutionizing shopping by making it more accessible and conversational. This has presented retailers unique opportunities to target more customers by optimizing their digital listings for voice searches. Marketing opportunities that retailers can leverage in this regard include:

• SEO Optimization: By targeting long-tail keywords that are more oriented towards conversational searches, retailers can optimize their SEO scores and increase their voice search rankings on SERPs.

• Platform Listings: Product listings on e-commerce websites such as Amazon and Flipkart can also be optimized to improve the chances of being recommended by voice search assistants such as Alexa.

• Content Marketing: By creating niche content that is specifically targeted for voice searches, retailers can increase the organic footfall on their websites and shift their marketing stance towards inbound.

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Case Study: Coffee giant Starbucks has embraced voice recognition by going a step ahead and including the capability in the My Starbucks Barista app. Customers can directly place their orders with voice commands before they visit their local Starbucks and find their orders waiting for them.

3. Mobile Point-of-Sale Terminals

Research suggests that in the United States alone, more than 50% of all digital shopping would be executed via mobile devices. Retailers are catching on with this trend and leveraging Mobile POS (mPOS) devices inside their stores that are blending the boundaries between digital and in-store shopping.

A mPOS is a smartphone, tablet, or a wireless device that functions as an electronic point of sale terminal. It enables sales associates to conduct financial transactions. Various benefits of this technology include:

• Reduced queuing and idle time of customers, especially during times of peak footfall.

• The system can easily collect and store personal information of customers such as their email IDs. Feeding the data in the ERP system and connecting it with marketing campaigns, such as a loyalty program, can then help to retarget these customers in the future.

• Since the mPOS devices run on a high-caliber point of sale software, they include an added level of security that is backed by reliable servers.

Case Study: Apple has been successful in eliminating cash registers from its stores around the world with the implementation of mPOS. Every store associate is equipped with a mobile device that includes the information of customers and multiple digital payment capabilities. This has helped them to eliminate checkout lines and improve customer experience in a manner that fares well with their brand strategy.

4. Computer Vision and Sensor Fusion

Powered by computer vision, deep learning, heavy-surveillance and sensors, retail giants like Amazon have been working towards the implementation of a next-gen shopping ecosystem. This is being executed with the aim of eliminating redundant steps associated with purchases, checkout, supply chain, and inventory management.

Interestingly, the result amalgamation of these technologies has been dubbed as ‘Just Walk Out’ and works similar to that of a self-driving car. In order to remove human cashiers from the workflow of such a store, it leverages a high level of surveillance on all shoppers. Although there is no intervention of facial recognition technology, the store would use hundreds of cameras to monitor the activities of shoppers.   Powered by computer vision, the core system would be able to identify every object in front of it. As soon as customers pick up products and place them in their shopping carts, the same would be placed in their virtual carts as well. It can even remove the item from this digital cart if a product is put back on the shelf.

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Case Study: Amazon Go stores are leveraging these technologies to extend a cashless and instant shopping experience to their customers. Powered by deep learning and a plethora of smart algorithms, the system is able to identify customers with the help of advanced pattern recognition that draws conclusions from vast datasets. As a result, customers are automatically charged from their credit cards or digital wallets as soon as they walk out of the stores.

5. Robotic Process Automation (RPA)

RPA in the retail industry is paving the way for better productivity by catering to administrative processes such as product scanning, data analytics, and inventory management. This results in better customer relationship management, easier and quicker auditing, reduction in administrative costs, and more. The various use cases of the technology in retail include:

• Returns Processing: With the ability to make automated changes to the inventory database and billing details, RPA can drive redundant tasks like product returns.

• Workflow Management: Management of shifts, measurement of time and attendance, auditing of sales activities, performance monitoring, and payroll management can be easily executed.

• Customer Support Management: Sending real-time updates to customers, extending round the clock customer support, and capturing feedback from customers after the sale.

• ERP Integration: Tracking price changes, generating reports, monitoring employee vacancies, managing billing, and more.

• Supply Chain Management: Automation of emails among customers, suppliers, and distributors along with monitoring inventory levels and tracking shipments.

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Case Study: Walmart is leveraging RPA along with smart robots to patrol stores and automatically scan shelves for missing items. This will allow them to identify the products that need to be restocked while also identifying pricing details and misplaced items.

6. Indoor Positioning Systems (IPS) and Geofencing

IPS is another leading technology that is overhauling the retail industry by empowering brands to stitch together digital and physical shopping experiences. With IPS, retailers can:

• Track the movement and location of customers inside their brick-and-mortar stores.
• Help customers by empowering them to find their way around it and locate the products.
• Send personalized discounts and offers to customers based on their shopping needs and preferences.
• Boost the conversion rates of customers by making physical shopping more targeted and personalized.

On the other hand, Geofencing creates a virtual boundary around a physical location. The boundary then acts as a trigger system when customers cross it. For instance, as soon as a customer walks into the store of a particular brand, the app on his/her phone can identify this and automatically switch to the in-store mode. A navigation map can then pop up that displays the exact location of all product types inside the store.

Case Study: Aswaaq, a leading supermarket chain in Dubai, has equipped its stores with a connected lighting system that communicates with its customers. It enables them to find items that are on their shopping lists with an accuracy of 30 cms through the brand’s app.

The Verdict

Successfully mapping the present technological backdrop in retail and planning for future disruptions requires meticulous knowledge about consumer behaviors. Retailers that are able to use data as a precursor to change management while adopting these technologies would be able to foster a sustainable technological ecosystem.

We all have experienced that annoying feeling when we get too many notifications, seeking actions for tasks that are not particularly important at that moment. Timely notifications are integral to the overall proposition of a platform, but they are fast becoming intrusive in nature. Today’s apps and websites send notifications regarding things that often don’t really require our immediate attention, and they send them repeatedly. These frequent and thoughtless notifications don’t mean anything to the user after a point. We just shut ourselves and cancel them out completely.

The next logical question would be — how do we, as designers, design notification systems, which serve the primary goal of increasing user engagement without disturbing users with unimportant pieces of information?

Firstly, it is important to understand that there are many variables that can affect how people may feel and respond to notifications. A person’s attitude towards a notification on any given day can depend on many factors such as:

• What is the notification?
• How is the tone of voice?
• What is the person doing when he/she receives the notification?
• What time of the day are they getting the notification?
• How many times are they getting notified?
• What is the location of the person when he/she receives the notification?

Before we proceed further, I want to share with you some personal experiences of different notification systems.

Exhibit A

A notification sent by Ola cabs

Let’s breakdown this notification that I got from Ola Cabs:

• It is asking me if I fancy an international trip at an hour when I am most probably having my lunch.
• I usually travel in the mornings or evenings via Ola. Getting this message at a time when I am most likely to book a cab, would have made me interested in it.
• And at that moment, let’s say I was more interested in going to Bangkok than Nepal. So clearly, I ignored the notification.

Exhibit B

Box8 message

• A notification to save money on lunch, around month end is relevant. I usually order my lunch between 11:30 am – 12:00 pm. And this notification from Box8 meals was timed well. In terms of content, the message or value was conveyed easily.

• Another factor to decide the importance of this message for me would be my location. This message wouldn’t be of any importance to me if I was at a location where Box8 meals are not available.

As designers, it becomes imperative to consider factors like timing and location of the user that affect their decision, in a positive manner and design notification systems that are pleasing and non-intrusive in nature.

Exhibit C

Picture this — it’s Monday morning, I am late for work. Just as I reached the railway station, I realize that my pass has expired. I need to renew it online or stand in a long queue to buy one. I quickly fill in all the details to buy the pass online. To make the payment, I need to login to my digital wallet. I enter my number and wait to get an OTP.

And the platform sends me this notification:

OTP notification for railway pass booking

As you can see, the notification has been constructed in such a way that the OTP number is not visible here. To see the number, I had to leave the platform and open my messages to get the OTP. This may not be a big deal, but it did increase the journey time.

Once I logged in, I proceeded with the payment through my debit card. Another OTP was sent to my phone. But this time I got the following message:

Bank OTP notification for railway pass booking

The above notification was created in a way that the first thing I read was the OTP number (which was the only piece of information that mattered to me). And finally, the transaction was successful.

Like me, I am sure many of you have had some bad experiences (and sometimes good too) with notifications on different digital platforms. As designers, we are constantly striving to improve users’ experience on our digital platforms, and notifications are an integral part of this structure.

I am going to share with you a framework for designing effective and meaningful notification systems.

Framework for Notification System

In order to build a notification system that is engaging and does not irk users to the point that they uninstall the application, there are few parameters or “steps” that we can follow:

Identify the intent and value of the notification

The foremost thing to be done is to understand the intent and value of a particular notification to the user. There is no point in wasting a user’s time with meaningless content. A person wouldn’t mind being interrupted as long as what they are getting in return is valuable and interesting. It is human nature to ignore things that are of no value to them. In this context, it is crucial to understand users’ needs and goals.

Nowadays, data analytics plays an important role in helping designers understand users habits and behavior on digital platforms. For example: Discovery+, Amazon Prime, Netflix and Hotstar do a great job of personalizing their push notifications. They use push notifications to let users know when their favorite shows or movies are available. They also analyze the type of content users are watching or the shows they follow and recommend similar content.

Recommendations on Discovery+ based on titles you have watched

Origin of the notification

Based on the structure of the digital platform, there are multiple channels through which notifications are directed to the user. The source of these channels is the point of origin for notifications.

Instagram notification for likes on picture

For example on Instagram, notifications regarding the number of likes your picture gets are part of the activity update channel. These updates are then shown in the notification center as a collective figure.

Building the Message

This section is about the message that is to be delivered to the user through the digital platform. The message content will help the user understand the purpose of the notification and what needs to be done on the platform to achieve his/her goal. Here are a few points that can help build personalized notifications:

A. Information (What)

Users appreciate information that is directly related to their personal interests. They tend to ignore the high frequency of notifications delivering valuable information. While building the information section, we first start with “What”; What information are we passing to the user that would help achieve their goal?

Once you have figured out the “What”, it is time to focus on the tone of voice of the information to be conveyed. It plays an important role in the overall user experience. Language used in the communication is an opportunity through which you can connect the user with the brand. It will help build trust and make the user more attached to your platform. To determine your tone of voice, consider these questions:

• How is this message going to affect the user?
• What emotions do you want the user to feel while using your platform?
• What situation is the user in at the moment?
• How can you maintain the user’s state of mind or put them in a better one?

Based on the situation, the tone of voice of the message could be serious, authoritative, or even instructive in nature. Take for example, a banking or finance services applications. Sense of security among users is of primary importance to the brand. Hence, they have to take extra care when giving instructions and write content in a manner which exudes a sense of security.

Users also welcome a break from the mundane and enjoy the experience when brands go for a playful and lighter tone of voice. I ordered one of my meals from Box8 and they added a playful touch to the notification regarding my delivery by using the word “Sooperman”.

Box8 delivery update

B. Timing and Location (When)

In order to deliver a successful notification strategy, it’s necessary to provide customers with the right message at the right time. But timing means much more than simply segmenting your users by time zones, or customizing messages according to the seasonal calendar. It means delivering information at the precise moment a customer is likely to take action. Nobody likes to be disturbed in the middle of the night because of a notification to avail discount on a purchase on an eCommerce site.

While figuring out the timing, we must also consider the frequency of notifications. Is it something crucial that the user needs to see twice everyday or would one message a day suffice?

Insider Notification

Let’s consider this message from Insider – it references topical subjects like Avengers and Game of Thrones in the message. The tone of voice no doubt may be great, but the timing of this message could have been planned better. I got this notification on a Saturday morning, when I am not at work and am most likely sleeping. Most of my weekend plans are made on Friday, at work. Had I received this message on Friday, I would definitely have booked something via the app. Notifications at the wrong time are completely useless. Untimely pings get ignored and the sound they create dilutes user interest and may even cause frustration.

Another important variable to consider is the location of the user. Users tend to use an app more if it sends them push notifications triggered by their selected hometown. Let’s say I have recently relocated to Mumbai from my hometown. What if food ordering apps used my location to notify me about the best deals on food near my location or the must-visit restaurants in the new city.

C. Type of notification (How)

Once you have figured out the “what” and “when”, the next step is to figure out the type of notification which is the “how”. In general, notifications can be categorized in the following categories:

User Generated Notifications: This type of notifications are targeted towards specific people. Their content is created by an action of a user on the app. Mobile messaging or WhatsApp messaging are examples for this category.

Context Generated Notifications: These notifications are generated by the digital platform based on user permission. One example of this could be the location based notifications from Zomato or Swiggy, where the apps send you offers and recommendations based on current location.

System Generated Notifications: These notifications are generated by the digital platform based on application needs. These type of notifications can help in re-engagement or some users may term it as spam based on the value they provide.

Push Notifications: All the above notification types can be push notifications also. They ideally appear on the locked screen or at the top without interrupting the user’s activity. These messages have a limited word count as well. Push notifications are of two types. One that requires you to take immediate action and the second one is passive notification. Most of the examples shown above are passive notifications. The image below shows a notification of a Medium article that seeks an immediate reaction:

Push notification with action

Earlier we only had mobile apps and desktop notifications to design for the user. But the introduction of smart wearables like smartwatches and apple watches have widened the spectrum. These watches are capable of concisely showing the push notifications in a much smaller and personal screen.

Voot notification on a smart watch

Discovery+ notification on an Apple watch

Output

“Output” is the part where the notification will be displayed on the digital platform. The output section can showcase notifications from multiple sources or just one. Some digital platforms have a separate notification center, where all the notifications are shown to the user, eg. Pinterest and Facebook or LinkedIn. They bundle information about who liked your posts, what people you are following are doing, etc. into a single notification center.

Single Notification Center Platforms: Facebook & Pinterest

Single Notification Center Platform: LinkedIn

On other digital platforms, every notification is connected to a navigation option which is the origin of the notification as well. For example, WhatsApp has navigation channels like Status, Calls, Chats that are both, the origin and output points for respective notifications.

WhatsApp Navigation Channel

Final Thoughts

We, as users, have learnt to identify and avoid notifications, just as we have learned to identify and avoid ads. As designers we need to understand that, if not carefully designed, notifications can become less effective in engaging users with your platform. We need to design notification systems in a manner that messages sent by brands bring value to the users journey.

The framework explained above can be used to design an effective and meaningful notification system for any digital platform. Think of it as a template, that could be applied to any user journey on your platform to enhance its overall notification experience.

For the last 10 years or so, blockchain technology has gained great visibility and ‘buzz’ in media. Originally meant to serve as the underlying technology for the cryptocurrency Bitcoin, it has been portrayed as a panacea for many industries or at least as a ‘must-have’ for enterprises. Aside from the hype, it has received its share of ridicule too from different quarters. So what is the reality? What are the use case of blockchain across industries? Let’s start with the basics:

What is blockchain?

Blockchain is a universally distributed open ledger system. It comprises a sequential list which records every transaction that has ever occurred in a process. A blockchain is made up of many blocks containing user transactions – and each block points to the previous block. The process of adding new blocks is called mining – a concept made popular in the context of Bitcoin, the crypto currency system. It needs to be clarified that blockchain is not  bitcoin – the technology behind the latter is blockchain. Interestingly, blockchain is referred to as a meta technology as it impacts other technologies. Over the years many blockchain systems have been developed: Ethereum, Hyperledger Fabric and Ripple to name a few.

Some of the hallmarks of blockchain which play a role in its acceptance include:

• Distributed trust
• Chronological nature and time stamp
• Immutability
• Cryptographic seal

Blockchain: impact beyond finance

The popular perception is that blockchain technology is utilized only by the finance industry. However, the basic nature of the technology makes it suitable for usage across domains.

The blockchain is an incorruptible digital ledger of economic transactions that can be programmed to record not just financial transactions but virtually everything of value.

~ Don & Alex Tapscott, authors Blockchain Revolution (2016).

A few major applications of blockchain include:

• Smart Contracts: any contractual transaction and agreement which is digital
• Record Keeping: usage across healthcare, real estate, voting
• Securities: global payments, P2P lending
• Digital Currency: equity markets, crowdfunding

There are several types of blockchain systems including:

• Ethereum: Mature Smart Contracting Cross-Industry Platform
• Hyperledger Fabric: B2B-focused Modular Blockchain Platform
• R3 Corda: an Operating System for Financial Services
• Ripple: Enterprise Blockchain Solution for Global Payments
• Quorum: Enterprise-focused Version of Etheruem

Let’s look at some use cases across select domains:

Retail

Blockchains can help retailers that offer gift cards and loyalty programs make those systems cheaper and more secure. Gyft, an online platform for buying, sending and redeeming gift cards that is owned by First Data, has partnered with blockchain infrastructure provider Chain to run gift cards for thousands of small businesses on the blockchain — the new program is called Gyft Block.

Travel

Singapore Airlines launched KrisPay – a digital blockchain wallet that allows frequent fliers to convert air-miles into digital currency. It will enable travelers to spend their air miles at retail establishments, hotels, petrol stations and other partner merchants.

Logistics

Moving freight is a complex process involving different parties with different priorities. An IoT enabled blockchain can store the temperatures, position, arrival times, and status of shipping containers as they move through the system. Indelible blockchain transactions ensure that all parties can trust the data and take action to move the product quickly and efficiently.

Banking

Majority of banking systems are built on a centralized database, which makes them more susceptible to attacks as all information is stored locally in one place. Also, many banking systems are outdated and are, therefore, more vulnerable to new forms of cyber-attacks. With banking systems built on top of blockchain technology chances of fraud and data theft can be reduced as the distributed ledger technology encrypts and verifies every single bit of data in a transaction.

Automobile Industry

Volkswagen AG is testing three concrete potential applications for distributed ledger technology: mileage clocking system, protecting cars from hackers (for Porsche) and streamlining business contact between providers and customers of electric charging stations.

Real Estate

Blockchain can play a role in buying property to conducting due diligence to enabling crowd-sourced investments. For example, Hilton Worldwide has begun using a blockchain-based property management system. The Dubai Land Department authority used blockchain in Ownership verification, property sale by the developer and smart leasing process.

While Blockchain has use cases across domains its use in Digital Health, Pharma & Life Sciences can perhaps be the most impactful. Currently the healthcare industry faces three major challenges in data collection, data accessibility and data privacy.  To illustrate, counterfeit drugs is a major problem in the healthcare industry: 10% to 30% of the drugs sold in developing countries are counterfeit. WHO estimates that 16% of counterfeit drugs contain the wrong ingredients, while 17% contain the wrong levels of necessary ingredients. Blockchain technology can play a role in drug traceability as the manufacturer produces the drug and marks it with a unique code after which a hash is produced. According to a definition, hashing is the process of taking an input of any length and turning it into a cryptographic fixed output through a mathematical algorithm. Various subsequent steps between the wholesaler, pharmacist and the patient are then added to the blockchain.

Applications of blockchain in healthcare include:

• Solving for Interoperability
• Securing supply chain
• Giving patients control of their data
• GDPR and HIPAA compliance
• Smart contracts and automation
• Accelerating clinical trials and R&D

Clinical trials have data management issues leading to inefficiencies in time management. Blockchain can solve such issues by standardizing data sharing. Robosoft’s Blockchain Solution utilizing distributed ledger scripted smart contracts based on Hyperledger Fabric offers guaranteed anonymity required for PHI, fully audited verification of data and more.

As a Top App Development Companies for enterprises, we truly appreciate the role of emerging technologies in crafting digital experiences. Among emerging technologies which have the potential to deeply impact the digital experience and the process behind it, blockchain seems to garner great share of voice. Connect with us to discover how blockchain can play a role in your enterprise.

Rapid advances in technology have permeated several sectors that anchor a country’s economy. This is a precedent that can also be applied to the real estate industry. Real estate, an asset class worth USD 217 trillion globally, has gradually embraced disruptive technology. It is a dynamic catalyst that will transform the way businesses are conducted in the future. Today, the growing influence of millennials and an investment boom in real estate technology has reshaped this industry around the world, including the Middle East.

Benefits of Technology in Real Estate

Digital transformation in real estate has made it easier for buyers to connect with sellers online and establish meaningful connections. Some of the benefits include:

1. Online 3D Tours

Technology allows global investors to get 3D views of the entire property, which gives the feel of a personal tour, all this at a single click and from anywhere in the world.

2. Real-Time Data

Real estate investors are no longer just looking at the price of a property. Factors such as return on investment, cash flow, and capitalization rate have become critical for investors to make informed decisions. To access such data in real-time, disruptive technologies provide all information at your fingertips. With growing accessibility to such data, the real estate industry has become more transparent and regulated.

3. Portal and Apps

The advent of real estate apps and portals have made it convenient for buyers to search for properties they like, instead of aimlessly driving around the neighborhood. Real estate portals powered by predictive analytics offer personalized and highly-customized data and are rapidly gaining popularity.

Technology in Real Estate in the Middle East

There are nearly 15,000 real estate offices in the Middle East, offering various types of properties, according to Global Real Estate Experts. In an article by Forbes, the UAE is leading the way to embrace digital transformation in the region, creating initiatives aimed at promoting innovation and driving the adoption of digital technologies in the real estate industry. More specifically, Dubai is working towards a strategy focused on blockchain technology to transform its real estate market and implement impactful tech reforms.

According to a plan shared by the Smart Dubai Office, blockchain technology is expected to be implemented for all government documents by 2020. This is a significant step for the real estate sector as most of its investors are seeking innovative ways. According to a study by HSBC, a whopping 72% of buyers in the UAE prefer using technology to gather information about the property, while 67% use technology to check the value of their home, and 64% look at prices of potential homes.

Saudi Arabia, not far behind in its quest to adopt technology in real estate, intends to build its own smart city called Neom. This smart city is part of the kingdom’s Vision 2030, a plan to lower the country’s dependence on oil, diversify its economy, and build public service sectors. Neom will incorporate various smart city technologies and also act as a tourist destination.

How Technology will Transform the Real Estate Industry

Blockchain

Blockchain technology has gained prominence in real estate because it helps lower the fees and processes associated with the industry. It reduces the intermediaries involved and streamlines processes for investors purchasing commercial real estate. This disruptive technology in real estate creates computer-based processes to eliminate paper title deeds, paper licenses, etc. for seamless cross-border transactions. Several companies in Dubai, such as ValuStrat, have integrated blockchain ledgers for the government to issue instant online title deed for properties. However, despite all these benefits, blockchain’s adoption rate seems rather unclear in the near future.

Augmented Reality and Virtual Reality

According to International Data Corporation, in Africa and the Middle East, the VR and AR technologies market is likely to increase from $181.59 million in 2017 to $6 billion in 2020. The use of VR is increasing as it allows visitors and investors to virtually check the properties regardless of their geographic location. The VR experience is not just limited to property touring. It also enables users to visualize any space with various customized design elements, thereby helping the interior design process. Dubai’s real estate giant Jumeirah Group is one of the many companies in the Arabian Gulf Region that are gradually embracing VR or 360 videos to provide virtual tours to buyers and promote their properties.

Smart Cities and Buildings

Smart buildings and cities are no longer a thing of the future. A smart building refers to a structure that deploys technology to automate operations such as lighting, security, and heating. Controlled partly by the Internet of Things (IoT) such technologies help boost efficiency and reduce energy waste. Technology giants like Google, Amazon, and Apple are aggressively investing in the concept of smart home technologies to transform the way people live.

IoT has also paved the way for the Smart City concept, which is being envisioned by the Kingdom of Saudi Arabia for Neom. The primary aim of smart cities is to enhance the quality of life using technology. A smart city integrates IoT solutions with information and communication technology to monitor its assets such as schools, water, libraries, waste management, etc. Technology in real estate can also help control parking, streetlights, and monitor air quality and noise.

3D Printing and Robotics

Construction technology, popularly known as ConTech, is revolutionizing the future of construction in real estate. Presently, construction is heavily dependent on manual processes to operate heavy machines. But companies like Komatsu have created unmanned bulldozers and drones to construct buildings and monitor the construction site.

Unmanned drones are capable of monitoring deliveries, inventory, and progress at the site and then create a 3D map of it. The information gathered by these drones is then used to instruct unmanned bulldozers to allot courses around the site. Construction technology in real estate removes worker safety issues, allowing robots to do manual work while humans focus on more strategic tasks. In 2018, HE Saif Bader Al Qubaisi, General Manager of Abu Dhabi City Municipality, launched the trial phase of using drones in engineering inspection of construction sites in Abu Dhabi.

Project Management Software

Several project management software solutions such as Re-Leased, ProofHub, Qube Project Manager are being deployed in real estate to assist in construction management. This is done to boost efficiency, clarity, and accountability of stakeholders involved in the project and aid in real-time conversations between them.

Chatbots

AI-driven chatbots are not new, with several industries leveraging them to enhance sales and marketing performance. Most of the real estate companies with an online presence have started using chatbots to help investors with standard information related to the property, along with pictures and videos without any human intervention. Since chatbots are 24×7 available, they provide support around the clock and assist buyers in filling contact forms even during odd hours of the day. Chatbots lower the overhead marketing and sales cost and results in higher conversion rates.

Property Management Software

Property management software is being implemented to monitor the performance and downtime of building equipment. This information is given to helpdesk support services and used by maintenance teams to carry out day to day tasks. Property management software tracks the asset’s performance to make the whole process efficient.

Final Thoughts

Technology in real-estate has slowly pervaded the industry, with advancements in nearly all sectors. The efficient adoption of relevant technologies can make or break companies in the future. While the pace at which it is being adopted differs hugely across different parts of the world, one thing is for sure, it will become indispensable in the coming years.

Retaining customers and building customer lifetime value is a crucial aspect to increase conversions. Digital disruption with the advent of Artificial Intelligence and Machine Learning has resulted in a unique challenge for marketers. Though it allows them to provide customers with experiences like never before, it also opens a myriad of options for consumers to choose from. This may have made customer retention a tricky task for organizations. After all, repeat purchases from existing customers is a sign of a healthy brand, since acquiring new customers can be expensive and may often impact the bottom line. While expanding the value and building lasting loyalty cannot be created overnight, disruptive technologies can help.

Let’s understand how organizations around the world are deploying cognitive technologies such as AI to create brand loyalty and adopt agile strategies using their existing data.

Current Scenario

Most organizations understand the importance of collecting data and do it through several digital marketing strategies. But analyzing and implementing this data still remains a distant dream. At best, companies analyze data in silos for a specific campaign. The result is that these organizations only influence a few touchpoints of the buyer’s journey while focusing on specific data related to online conversion rates. To combat this problem, businesses have slowly started embracing AI and ditching data processing through traditional methods.

Harnessing the Power of AI

There are several ways in which organizations can harness the power of AI to empower decision making. The low hanging fruits such as sales forecasting and cross-sell/up-sell can help companies showcase proof-of-concept while understanding how vital it is to change the company culture for it to be successful. A mindset shift is required if teams want to adopt agile strategies by acting on crucial insights and create longer customer lifetime value. Some of the ways that AI can be incorporated into effective decision making include:

Sales forecasting

Traditionally considered a nightmare by management teams, AI algorithms can predict revenues for the upcoming quarter with higher accuracy. This helps the sales team and leadership to take a data-driven decision and achieve operational excellence.

Cross-sell/up-sell

Cross-selling and or up-selling is the easiest way to increase marketing ROI. To determine which customer segments will have a bigger value, use AI to identify the clients that are likely to upgrade or broaden their purchases across various products/services.

Price optimization

AI-enabled campaigns can help you identify what type of promotions incite buyers to make a purchase.

Up the Ante on Digital Marketing

2019 is the year to up the game in terms of digital marketing. Customers are no longer going to just click targeted ads based on their demographic information. As such, several organizations have started using AI to detect how consumers are engaging with content across different touchpoints. It also identifies marketing messages that may boost audience engagement. These insights are instrumental in refining marketing campaigns and boost overall ROI.

By mapping out the factors that affect customer lifetime value, both marketing and sales teams can create customer loyalty and advocacy programs targeting their most valued customers. AI is no longer being used to only improve the value, it is also forcing marketers to use it as a major KPI metric. Since AI is vital to understand the impact of several aspects of customer behavior, it also helps the team fine-tune their strategies and make metric-driven decisions for improved user experience.

How AI Increases Customer Lifetime Value

Create Personalised Experiences

AI’s ability to analyze data makes it possible for marketers to deliver personalized experiences to customers and make them feel special. Armed with insights from AI algorithms, teams can deliver relevant content that can further strengthen the relationship and build customer loyalty. Not so long ago, Netflix and Spotify started using AI-driven insights to provide recommendations to its customers, and today, all other brands are trying to provide the same level of personalized recommendations to its customers.

More Sales

AI can transform the way organizations engage customers with their products. By taking advantage of data, AI can be used to create a holistic and hyper-targeted approach that compels customers to purchase more. E-commerce giant, Amazon does a great job by suggesting other products, based on the historical preferences of the customer. As teams gain a deeper understanding of personal preferences, they can deliver tailor-made offers for their customers. In other words, AI equips organizations with tools to create trust and change short-term sales pitches into long-term loyalty.

Renew Faster

When customers are made to feel more valued and understood, they tend to stick around and become advocates of the brand. And as an AI-empowered marketer, the insights will predict what your customers might need next. By incentivizing longer-term commitments, businesses can grow their customer lifetime value at a fraction of the cost when acquiring a new customer.

Visual Search

Customers are gradually moving away from text-based search to more visual searches thanks to advances in AI image recognition and analysis. Platforms like Pinterest and technology such as Google Lens are making it possible for brands to improve merchandising and provide a personalized shopping experience. US retail giant Target’s partnership with Pinterest in 2017 shows their determination to integrate visual search in their e-commerce experience. The partnership allows users to take a picture of an item and find similar products on Target’s website.

Evangelize Eagerly

Implementing AI demands marketers to focus more on lifetime value. When this shift happens, customers see brands as an indispensable entity and start loving it. And with AI’s help in calculating lifetime customer value, organizations can determine the reward for their best customers.

Summary

Traditional marketing channels have considered all customers to be equal. But today, things have changed. Customers demand personalized experiences to make them feel special and build better brand affinity. For this purpose, organizations are embracing AI to make full use of their data, collected at various touchpoints of the customer’s journey. Primarily because not all metric-driven decisions make it easy for everyone to collaborate and create a customer-centric business model.

AI-driven marketing empowers teams to deliver better ROI (Return on Investment) from their marketing investment. It also helps businesses and companies make data-driven decisions and see what works for their brand and what doesn’t by forecasting sales, up-selling/cross-selling, and renewing clients’ contracts. Thereby, accelerating customers ‘ purchasing decisions and help organizations better tailor their content strategies.