Price, attention, delivery speed, quality, service – the parameters for brands to compete are many and to say it’s a battle out there to gain customer loyalty is an understatement; it’s pure savagery! Customers today openly scrutinize and share unforgiving opinions influencing a huge number of people, thanks to social media channels that have given a voice to the masses. No organization can now afford to ignore customer demands. Understanding them is therefore important and data takes the front seat in this scenario. Let’s look at the various options and approaches before brands to leverage data to their advantage.

Loyalty and Customer Data Platform (CDP)

There are no linear paths to purchases anymore. Customers take the curvy path of research before zeroing in on a purchase and this includes e-commerce websites and apps, physical stores, web forms, search engines, social media and so on. Brands need to keep up with this zigzagging of customers and that’s what customer data platforms facilitate ¹. They gather relevant data and present it as a unified view, highly useful in hyper-personalization.

Data Science and Loyalty

While CDPs brings a wealth of data before brands, what to do with it is a question that data science answers. The power of data lies in being able to successfully use it to understand customer behavior at every step of the marketing funnel – from product awareness to activation. Data science brings forth quantifiable metrics that allow marketers to understand at which point a customer becomes disinterested in a product and drops off. It helps bring about personalization at this very point to enable sales conversion. Of course, when personalization is successful, loyalty naturally follows.

Understanding Customers Better through AI-Based Engagement Analysis

While data science brings customers the most effective stages to intervene, artificial intelligence aids in customizing and personalizing that engagement to bring about the desired results. Here’s how they help:

• Making highly relevant purchase recommendations
• Offering insights to make digital marketing efforts effective
• Predicting the likelihood of lead conversion
• Providing direction to sales agents
• Optimizing the lifetime value of customers through predictive analytics

Personalization through Machine Learning Models

According to McKinsey Digital, organizations that successfully personalize customer experiences enjoy the optimization of marketing spends by up to 30% ².��Achieving this manually, however, is impossible and automation without intelligence can lead to ineffective personalization. Enter machine learning (ML) and the problem ceases to exist. ML algorithms allow for automatic identification of data (behavioral) patterns and suggest the best course of action without an explicit programming need for each scenario. The right mix of data and ML can help marketers build the perfect model for personalization.

Contextualization of Customer Journey

Customer lifecycle has different stages, and at each stage, the expectation is different. Moreover, the expectation differs with the nature of the business and its standing in the market. In order to be effective, the journey must be contextualized to the buyers’ preferences. It takes a dynamic combination of technologies discussed above and a practitioners’ understanding of the industry to achieve true personalization. Getting it right is only possible when you have a partner who adopts a consultative approach to offer your business a technology-led solution.

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The Use Cases

Airports are a case in point. With over half the population living in urban areas today ¹, public spaces like airports are obviously going to be crowded. This poses a challenge to offer great experiences to flyers. Enter face recognition technology – the security screening process can be simplified like never before. Put artificial intelligence into play for resource allocation and crowd management would never be an issue.

Now, let’s consider reaching out to customers in unique ways. Imagine a smart offering by an airline that leverages voice and gesture controls; mixed, virtual and augmented reality; and hologram projections to transport a customer into a virtual world where experiences are as realistic as they get. Picture being able to fly in a virtual airplane to some exotic place. The potential customer would be instantly sold to the idea of such an air travel.

First Adopters are Already Here

Steve Jobs once said, “You’ve got to start with the customer experience and work backwards to the technology. You can’t start with the technology and try to figure out where you’re going to sell it.” Amazon, with its IoT- and analytics-enabled smart stores, seems to have adopted this thought well. Amazon Go store’s system can recognize a customer entering the store. It realizes when a product has been taken off or put back in the shelf. It can move those products to a cart and charge the customer’s online wallet for all the purchases. What can be a more seamless customer experience? In essence, forward-looking companies have already begun exploring smart spaces but it’s not too late for the rest to catch up.

The Privacy Challenge

The implementation of safeguards such as General Data Protection Regulation (GDPR) in the European Union makes it is convenient for individuals to avoid tracking of their information. However, smart spaces powered by technologies such as facial recognition are highly dependent on individual data. The way forward – services that are compelling enough for people to share personal information. Of course, data security precautions must be in place.

At 91����, we see immense potential for smart spaces, as more businesses become aware of their transformational capability. Given the pace of the current market evolution, businesses must partner with established technology consultants like us to start building their smart-space strategy before it’s too late.

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“A customer walks into the store and asks for a particular product she found on the e-commerce store. She then tries the product and buys it from an e-commerce player.”

In both of the scenarios, there was little that the brand could do while these actions were being performed. What if we could track all the clothes that a customer considered, tried, rejected, shortlisted and bought online? Wouldn’t it be nice if we were able to intervene during the buying process, instead of trying to win back the customer after the action has been performed?

The customer journey is now increasingly becoming omni-channel, crisscrossing the physical and digital worlds. So, it has become imperative to develop cyber-physical systems that can address the “Phigital Customer Journeys”. We at 91���� would like to introduce our “Omni-Cart” commerce capability developed at our Innoruption Labs.

The Omni-Cart commerce capability allows retailers and e-commerce players to keep track
of customer shopping carts across physical and digital touchpoints. It provides a simple functionality with which the customer can capture an image of any product, and add it to the cart on any mobile app. This enables the customer to purchase a product, take delivery at the store, or the desired location.

Real-time Analytics and Real-time Offers

The biggest challenge of any brick-and-mortar retailer is to bring the customer into the store. So, why wait till the customer comes back? Shouldn’t we look to maximize the basket size every time the customer enters the store?

The Omni-Cart commerce capability enables a retailer to recommend matching clothes, suggest trials, and sweeten the deal with offers. It also provides a personalized real-time shopping assistant who is always ready to assist. The customer’s next-best-action is enacted in real-time while he or she is shopping, and not after. This results in higher conversions than other digital or physical marketing tactics.

Real-time Shopping Assistant

Do you wish to deploy a dedicated salesperson to assist every customer in the store, and offer
a personalized experience? Great, but are you constrained by resource cost, quality, and skills?

Omni-Cart commerce has the answer: Every customer can be provided with a personal stylist or shopping assistant on a mobile app. Powered by A.I, M.L and the entire shopping history of the customer at its disposal, the shopping assistant interacts with an unprecedented level of awareness. This enables the much sought-after personalization at a 1-to-1 ratio. This, in turn, opens up ‘Markets of One’, where every customer is a market by himself.

Experience the power of cyber-physical systems with our Omni-Cart commerce capability.

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As we trace back the association of digital, digital marketing was the flagbearer of digital business, as organizations started to move from predominantly television and print advertising to online-technology-enabled platforms, trying to follow the customer into the digital world. In essence, customer adoption of digital communication technology drove organizational approach to digital marketing. When they moved to Facebook, FB become the buzzword, and when customers started tweeting, Twitter become the platform of engagement. In essence, customers led organizations in to the digital world.

With advent of cloud technologies, access to computational power and high-tech tools increased exponentially, enabling rapid development and deployment of technology platforms to propel business forward. Advent and customer adoption of ecommerce and e-marketplaces, have brought about a paradigm change in the fundamental building blocks of business, with technology becoming the driver of business growth and business dependent on technology platform to operate.

Today, businesses have embraced digital as key business driver and technology has come to the center stage, giving rise to two kinds of digital businesses:

• Digital as Business Driver
• Digital as the Business Disruptor – Where digital is the business model

Digital as a Business Driver and Digital Transformation:

Traditional brick and mortar businesses or offline businesses are now transforming themselves into digital businesses, where critical processes are either automated or performed with the help of digital technologies to increase operational efficiencies, and reduce cost and time to market. Data created by the usage of these platforms is being analyzed and processes optimized, leading to greater operational efficiency and eventually to cost leadership, a sustainable competitive advantage.

Digital as Business Disruptor – Where digital is the Business Model

New-age businesses like aggregators and e-marketplaces have built their businesses and revenue models on digital, disrupting markets across the globe, unlocking customer value. Mobility and penetration of mobile internet have revolutionized the way organizations interact, transact and monetize customer relationships. New markets are being created at the bleeding edge of digital innovation and old ones sacrificed at the altar of digital disruption, as digital capabilities are enabling businesses to create sustainable competitive advantage.

The Next Wave of Disruption and Innovation

AI, ML, blockchain, AR/VR are few of the technologies that have the potential to completely change the way digital businesses operate.

Starting with automation of repetitive tasks, AI and ML will reduce human intervention in most digital businesses. AI will begin to augment and slowly replace tactical decisions and strategy layers of digital business structure.

Next wave of cyber-physical systems, which enable direct human and machine interfaces, will drive new business and revenue models to monetize digital customer experiences enabled by IoT & 5G technologies.��

Digital Imperative for Survival and Business Differentiation

In the age of the connected customer, digital is fast emerging as the only realistic capability to create cost leadership or differentiation leading to sustainable competitive advantage. Business that have adopted and transformed into digital businesses are starting to realize that digital is influencing everything about the organization. Perception of brands and their experiences are today largely dependent on digital platforms. Stakeholders, society and regulators are viewing the brand through the lens of digital experiences. Being viewed as a leader in adoption of technologies is proving to be key brand differentiator.

To summarize, the success or failure of most businesses today can be attributed to their speed of adoption of digital technologies. Transforming their businesses into digital businesses is the only way to survive the next wave of disruption and innovation, as being a brick and mortar business alone is no longer an option.

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“What’s in it for the customer?” is a question that begs to be asked when marketers are looking to snoop around every nook and corner of the web, to scoop up data to manipulate the customer journey. Taking advantage of gullible customers are marketers with nefarious designs of increasing performance KPIs like CTRs, ‘likes’ and ‘shares’, achieving them at the cost of deteriorating customer experience. The here-and-now approach weighing down long-term perspective of customer relationships.

In the age of connected customer, brands are ever so closely connected to the customer, yet have very little actionable insight about them. More the data that we have pertaining to customers, the less we actually seem to understand them. More the technology available in customer activation, lower seems the customer engagement. Why the paradox? Instead of cutting through the deluge, digital marketers are adding to the clutter by deploying me-too tactics that add little value to the customer, both in terms of experience and return on time spent with marketing content.

On the other hand, the customer has learnt to ignore these interruptions. The technology and techniques to interrupt the customer have leapfrogged the pace of adoption amongst the marketers. The result: highly inefficient marketing gimmicks that do not deliver any real-world value to the customers, poor returns on investment to the marketers with only media companies winning the game.

Where the gimmicks of technology – like creating a new filter on Instagram – fail is to create lasting bonds that bind the customer to the brand, content may be your currency, but if you cannot solve customers’ problems,, deliver real-world value, you are getting nowhere. Why should the customer engage with a brand on a sustained basis is the question that must be answered.

If you are happy posting stuff for likes and shares and offer no real value beyond that, customers are bound to lose interest as there are more practical issues and considerations that occupy their mind-space. If you need mindshare, then you better appeal to their rational side at the least – emotional is league apart, as very few can actually think in that dimension, let alone practice it.

Let us change the game, shall we? It is not about how much data pertaining to the customer we have, it is about the depth of customer insight that generates results. With increasing focus on data-driven marketing, the personal touch of the empathetic marketer has gone missing. Gone are the days where people used to wait for a specific ad on TV, watching it repeatedly, kindling the emotion it triggers. Today, customers despise the time wasted due to content that is designed to satisfy bots and not humans.

To deliver a consistent, differentiated and personalized experience each time the customer bumps into you on the web, you need a combination of human empathy and machine accuracy; a combination of human instincts and artificial intelligence to create a perfect balance – where art meets science.

Finally, if any of you marketers are wondering why you have not been able to deliver expected results in spite of having the best of the marketing technology – ask yourself, “What’s in it for the customer?”

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Knowing and Setting Customer Expectations:

Do not delight your customers – as a few marketers will tell you – because today’s delight becomes tomorrow’s expectation. The key to consistent customer experience is knowing and setting right customer expectations. A very poor experience at one touchpoint remedied by delight at another does not produce optimal customer results like increased customer lifetime value or advocacy, and only ends up exhausting valuable resources.

It is, therefore, important to communicate clearly to the customers a minimum guaranteed experience at each touchpoint that standardizes the experience. For example, a standard 15-minute response time for tweets or a maximum of 5-minute wait on customer care helpline. It is vital to constantly seek feedback pertaining to experience to gauge whether it meets their expectations. This gives a clear view as to what customers expect during brand interactions.

Standardization, Personalization and Differentiation:

We often see that brands try to implement what works for other brands. If customer experience standardization is the buzzword, we must expect every self-respecting brand in the market to take one step or the other to improve customer experience. So how do we standardize, personalize and differentiate at the same time?

• Brand Differentiation

It is imperative that brand personality, tone of interaction, language and unique value that a brand can add to each customer experience is identified, and the brand be brought to life in the interactions with the customers. Be it a twitter reply or customer care response, a unique tone of voice and character differentiating the experience is necessary. If your ads are quirky, your customer care needs to sound slick, not formal.

• Standardization

Does your brand talk in the same tone of voice in both twitter and customer care? Do customers from your retail stores and eCommerce go back thinking the same thing about your brand? Standardization helps to deliver consistent quality of customer experiences repeatedly at each touchpoint. Customer feedback improving the qualitative aspects, persistent measurement and optimization will lead to higher consistency and quality.

• Personalization & Privacy

Does your communication make the customers feel they are just a record in your database? The true test of the personalization is making the customers feel that they have a privileged relationship with a brand. An illusion of one-on-one relationship must be created using personalization. Customers want personalization but it is definitely not limited to addressing them by their full names in emails & text messages, it about communication being personalized to the customer’s preferences, need, context, issues and expectations. Cold calling customers at random or sending offers on products that customers hate will surely earn trolls & memes on Twitter.��

The challenge is to personalize without creeping out the customer and sparking privacy concerns. It is all about building trust to motivate customers to share more about themselves and letting the brand gain a deeper insight in to customer behavior. There is a fine line between staying connected with customers and stalking them.

Standardization, personalization and differentiation of customer experiences at scale is the challenge that confronts us today. A finely crafted and unique customer experience strategy is the need of the hour and not gimmicks or me-too tactics, which will only increase the clutter.

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The above statistics lead to one undeniable conclusion. There is a lot of room for improvement in the user experience domain of healthcare. One of the most important levers to improve member experience is working on member engagement.

Organizations face 2 fold problems in member engagement today. Firstly, there is insufficient engagement on the part of the payers and providers i.e. the frequency and volume of communication are greatly lacking. Further on, most healthcare organizations follow a one-size-fits -all strategy. This means they engage with all members in the same fashion, regardless of differences in members’ attitudes, economic conditions, social conditions, etc. This reduces the efficacy of most member outreach activities.

The global customer engagement solutions market size is expected to reach $ 26.4 billion by 2024 and is expected to expand at a CAGR of 11.5% over the forecast period¹.

Advancements in Big data processing tools, data organizations, and data mining along with the shift in member attitude demanding retail-like experience in healthcare are prompting healthcare organizations to leverage advanced analytics algorithms to drive member engagement.

The Opportunity for Data-Driven Member Engagement

In healthcare, large amounts of heterogeneous data have become available to various healthcare stakeholders (payers, providers, pharmaceuticals). This data could become the enabling resource for extracting insights to improve care delivery, maximize ROI, boost member engagement, cut down costs and so on.

With the onset of social media, wearables, and member portals, healthcare organizations now have access to much more personal data pertaining to members. This includes their preferences, their likes, and dislikes, their motivations as well as barriers in achieving health goals as well as influencers that they follow. Analyzing this data using the right tools and technologies can help deliver care and experiences that way more effective and relevant for the member.

Proactive Member Participation using Personalization

It is a well-known fact, that only 20% of a member’s health depends on clinical factors or in other words on the treatment delivered by the provider. The rest of the portion is in the hands of the member himself. Thus, it is in the interest of members to start taking care of their own health. For doing the same, members need to be made aware of the best health practices they should follow according to their lifestyle and health conditions.

This makes a strong case for healthcare organizations to try and understand the psychographics and lifestyles of members. Providers and payers alike need to take into account their social determinants of health (including literacy rate, housing, transportation patterns, etc.), economic conditions, motivations as well as obstacles in life, attitudes towards health and so on. Apart from this, family history, their existing fitness regime, their influencers and so on also provide very powerful and relevant information pertaining to the individuals. Only then can we create and deploy effective care strategies that will ensure higher compliance rates among members. E.g. A 30-year old member who works in an office 5 days a week can be sent a notification on an app (assumed he might prefer to ingest information using apps) to go for his annual wellness visit on a Saturday(weekend).

NLP to improve member clinical literacy

Doctor’s prescriptions and clinical notes contain important information that cannot be leveraged easily due to its unstructured format (paper based or digital) which makes it difficult to analyze. Using advanced analytical algorithms, Natural Language Processing can be used to absorb information from all this unstructured data and deliver useful information to members (since payers have access to clinical records in form of CCDA documents) at the right time.��

Incentives to entice members for wellness

Apart from sharing regular and relevant information with members, running a personalized rewards programs can be another way of motivating members to participate in improving their own health. By analyzing each individual’s tastes, likes and dislikes, analytical algorithms like clustering can be used to create personas which are representations of individuals who share similar characteristics. These personas along with claims and EHR data can be combined to recommend member specific health goals and relevant incentives that motivate the members to achieve these goals. Health goals can be anything from physical activity to calorie intake or even closure of existing care gaps. This will lead to healthier members, lower claims and increased profitability.

The 91���� Advantage

Using the Healthy Me solution developed by 91����, payers and providers can engage with their members effectively while improving member satisfaction, brand image as well as lowering the cost of care delivered to improve profitability. The solution is developed on a big data platform and runs on a core analytics engine.

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Insight generation. Automated and accelerated.

What’s the use of presenting an awe-inspiring bar chart to a user who struggles to extract the required informationfrom it?

The traditional static reports and dashboards may no longer be able to provide the insights needed to take informed decisions. Augmented analytics uses machine learning and natural language processing to automate and simplify the process of insight generation. In other words, it’s like data interpretation on steroids! Truly a disruption, it’s expected to change the way data analysts create, interpret and share data with a diverse group of users. But the good news is that it’s the new way to add artificial intelligence to existing business intelligence tools. The result: work gets done faster and the results become more meaningful.

Deeper analysis of data

Augmented analytics detects latent signals, patterns and outliers traditional analytics tools may not be able to view clearly.
It also analyses different formats and combinations of data to arrive at more accurate results. The solution streamlines data collation, governance and assimilation, while offering a single view of the customer (SVC). The analysis will also be aimed at extracting information that makes business sense to stakeholders. Nobody wants metrics and graphics that camouflage the reality!

Faster and smarter sharing

In this era of Siri and Alexa, the voice command is becoming commonplace. Augmented analytics leverages this trend, so even business decision makers can draw insights easily�� – just by asking simple questions! A case in point – A sales manager wants to compare the server sales figures of two previous quarters. He has two options: Count on the data analyst who is busy running repetitive reports, or chat with a bot to elicit the desired answers in jiffy. The latter is what augmented analytics can do.

Simplified analysis

Stakeholders across departments stand to gain immensely by this disruptive technology. Augmented analytics tools help eliminate time-consuming and error-prone manual processes. The users get to focus more on strategic tasks rather than discovery and interpretation.�� Business decision makers (read non-technical folks) can also draw insights easily without much assistance from data analysts. Instead of spending time on reports, they can focus on applying the insights to explore profitable business opportunities.

According to , the company that coined the term augmented analytics, more than 40% of data science tasks will be automated by 2020, thereby resulting in increased productivity and broader usage of��.�� Stated simply, augmented analytics is not a fad. It is here to stay and transform the world of data and analytics.

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Creating an Evolving Customer Engagement Ecosystem

As the customer journey evolves continually, marketers are counting on ways to provide enriched experiences through meaningful engagements. Invariably, most businesses deploy a loyalty program irrespective of its impact on business growth. Many choose to add a new lease of life to their existing programs, while others resolve to reimagine and reinvent their customer engagement strategy.

Cost-conscious businesses might maintain that loyalty programs are losing their relevance in today’s cluttered marketplace. But that’s nowhere close to the truth. The workaround is to upgrade the legacy loyalty platforms, but the effect may not meet expectations. This is ascribed to the fact that these obsolete solutions are usually loaded with a clutch of limitations – clunky architecture, complexity in customization, high level of maintenance, legacy data structures and more. So, the solution lies in total, but gradual, transformation. A next gen loyalty solution addresses most of the issues and paves a path to better customer engagement and understanding.

Next Gen Loyalty Solution – the New Way to Create Winning Experiences

The need for creating consistency of CX, personalized experiences and constant excitement can be addressed by an enterprise-class, cloud-based loyalty solution. This makes it easier to recognize loyal customers, so they go on to become ambassadors of the product they use.

Bundled with features, these solutions usually have options for gamification aside from a slew of CX connectors. Optionally, they offer industry-specific templates, a member portal and mobile app to offer customers a seamless experience on the go and across devices.

A core loyalty decision engine comprises multiple components (essential and optional) for management, measurement and engagement. Featured below are just a few.

Managing with ease – Multiple programs, loyalty currencies, promotions, partner ecosystem, rewards catalog and games.

Measuring & optimizing – Referral incentives, real-time redemptions and pool points.

Engaging & exciting – Custom dashboards, transactional reports, member reports and program effectiveness.

Popular across verticals including retail, hospitality, travel, the loyalty program has now become a business imperative. Technology can help a business cash in on its potential, so the business can maximize its customer lifetime value to the hilt. Though the task of raising the customer experience bar is not as easy as it sounds, the implementation of a smart loyalty program can go a long way in making it real. This can be accomplished by partnering with an experienced technology provider who can ensure end-to-end support – from customer engagement to acquisition and advocacy.

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