August 2, 2019

Marketing, as a practice is becoming more scientific. Thanks to the increasing availability of customer data, advances in analytics, real time processing, AI, ML, etc., marketing organizations are increasingly able to do what they’ve always tried to do… deliver the right message to the right person, in the right way, at the right time, all the time. Unfortunately, most marketers are still taking an analog approach. For example, marketing organizations are creating customer data platforms, building customer analytics, integrating CRMs with marketing automation platforms, tracking campaign metrics and delivering personalized offers in real time across physical and digital channels. The analytics and automation capabilities are impressive, but marketers are perpetually missing the first step. They are still guessing about who their best customers are – an error that misguides the customer journeys at every step.

Marketers want to:

  • focus attention on key buyers and influencers
  • understand and influence buyers’ journeys
  • deliver offers that customers want
  • build a loyal customer base
  • provide superior brand experiences

To do any of these things, marketers need to understand their customer types. It’s common for sales and marketing organizations to get into tiffs about which customer group they should be targeting with which message. Sales and Marketing organizations think about, and rethink, this continually.

Here’s how it usually works. Marketing documents its understandings of the organization’s key customer personas to aid in the development customer strategies, targeting, messaging, offers, and tactics. Unlike a simple customer segment, a customer persona represents a type of person which considers many dimensions and includes insights about customer goals, needs, sentiments, affinities, attitudes, and behaviors. Persona-based marketing helps marketers organize and track strategic campaigns and more efficiently deliver personalized brand interactions at scale, as opposed to one-size-fits-all offers. They feed into many types of marketing initiatives.

For example, a marketer may determine that the most practical way to engage with their customers is to bucket customers in to one of five different customer personas that they have documented. They align offers and actions with the personas and use segmentation to build campaign lists. They then use marketing automation tools to activate and deliver the campaigns at scale. Personas are also used to model customer journeys, by setting persona-based if/then rules about actions and reactions. So if five different people all click on the same banner ad, they might each get taken to a different place and presented with a different shopping experience.

The Problem with Personas

Few marketers have a data-driven method to determine personas accurately. Unlike the impressive data platforms and marketing automation systems, building customer personas is still usually done by filling out a generic template in MS PowerPoint or Word with guesswork, gut feelings and spotty analysis of scattered data. Or they use expensive focus groups to collect questionable insights. These personas are inadequate, invalid, and stagnant. Frankly, they’re a joke. Yet it’s how nearly every marketing organization is doing it! Not only are these manual personas inaccurate, it can be difficult to determine which customers fit into which personas best. Furthermore, even if the documented personas are spot on when written, they will soon drift out of alignment with their constantly evolving customers.

Given that personas are a starting point for many marketing decisions, the damage caused by their inaccuracy compounds at each point of customer influence – costing businesses untold millions in missed selling opportunities.

It’s like the old saying “junk in, junk out”

However, there is a now an AI-driven solution to automatically look across all customer data sources to discover and reveal insights about your most highly differentiated personas. With this solution, each persona continuously evolves and customers can dynamically move into and out of personas. Before we explore this approach further, let’s break down the concepts of persona discovery and dynamic personas.

The Digital Persona Misnomer

This term digital persona is a bit misleading. You might think that a “digital persona” is a persona that is built using special technology, or one that lives online. But the word digital used here simply signifies the inclusion of customers’ online/digital behaviors, preferences, etc. in addition to their physical behaviors and preferences.

Persona Discovery

Your customer personas are out there, hiding in your data. You want to discover them – not build them. To accurately discover your most differentiated personas, you need to incorporate as much relevant information as possible and determine which combinations of customer attributes create the most differentiated groups of customers. Then you must analyze those results and glean insights that help predict future behaviors and prescribe how to influence customer journeys toward certain goals. It’s no surprise that human brains don’t stand a chance of doing this. But data science and analytics can do it.

TCS Customer Intelligence & Insights for Retail is a software product for customer analytics (with other versions for banking, and communications) that employs AI-driven digital persona discovery to power its pre-built customer experience use cases for retail, such as shopping basket analysis, targeting, segmentation, customer journey management, and next-best-offers and actions recommendations.

For marketers, automated digital persona discovery should be at the top of their list. Clarity around key customer types ensures that marketing efforts are focused on exactly the right groups with exactly the right messages for each group.

Dynamic Personas

Your customer personas are always changing, as each of your customers changes, like the way water changes the shape of a river. As customer profiles, needs, goals and more change, customers will naturally shift personas. Because markers continually utilize personas to build messaging, offers and create customer campaign lists, they need operational personas that are always based on the latest customer data.

The dynamic personas discovered by TCS Customer Intelligence & Insights for Retail are constantly based on the latest customer data, and persona-based customer campaign lists always remain current and optimized.

Putting Personas to Work

The “in person” experience has become more digital while the online experience has become more personal. This means that businesses have to incorporate more sources of data to surface insights and make smart decisions about how to engage with their customers and what to offer them.

But most marketers are not applying AI-driven analytics to really understand who their most differentiated customer groups really are. Simply documenting your best guess of your customer personas and then filing them away may check the box for some internal marketing goal, but it delivers no business value. With an AI-driven approach, persona-based marketing:

  • simplifies campaign orchestration
  • improves targeting
  • guides messaging
  • reduces waste
  • enhances customer experience

Persona discovery doesn’t work as a one-off tool or short term initiative. Personas need to be a connected component of an integrated marketing stack that harnesses those insights to surface and deliver timely recommendations for next best offers and actions to frontline customer-facing systems and apps such as PoS, websites, mobile apps, websites, etc.

TCS Customer Intelligence & Insights for Retail incorporates automated discovery of dynamic personas as a foundation to deliver superior guidance to its other capabilities for segmentation, Customer 360, shopping basket analysis, customer journey mapping and modeling, and persona-driven next best offers and actions. The solution is designed to augment and complement marketing automation with a customer analytics platform and pre-built use cases for retail.

If your marketing organization isn’t using a legitimate tool to automatically discover your customer personas, then it’s just guessing and the rest of your marketing efforts are suffering because of it.


Traditional approaches to understanding key customer types (personas) are error-prone, short sighted, and can even be a detriment to organizations that use them. B2C marketing organizations need to abandon the archaic tradition of filling out rudimentary forms and templates to capture customer personas. Instead, marketers must demand that they incorporate AI-driven persona discovery to:

  • be certain that they understand how their most highly differentiated customer types are different
  • understand the best way motivate members of each persona to take the next step toward buying
  • wisely guide their marketing automation with analytics-driven recommendations for next best offers and actions

Learn more about TCS Customer Insights & Intelligence for Retail here.

Jeff is part of the Digital Software & Solutions group of Tata Consultancy Services, as a lead evangelist for its IoT analytics platform solutions for smart cities, smart retail, smart banking, smart communications, and other areas. Jeff is part of the Digital Software & Solutions group of Tata Consultancy Services, as a lead evangelist for its IoT analytics platform solutions for smart cities, smart retail, smart banking, smart communications, and other areas. Prior to TCS, Jeff was part of EMC’s Global Services division, helping customers understand how to identify, and take advantage of opportunities in Big Data, IoT, and digital transformation. Jeff helped build and promote a cloud-based ecosystem for CA Technologies that combined an online community, cloud development platform, and e-commerce site for cloud services and spent several years within CA’s Thought Leadership group, developing and promoting content and programs around disruptive trends in IT. Prior to this, Jeff spent 3 years product marketing EMC, as well as a tenure at Citrix, and numerous hi-tech marketing firms – one of which he founded with 2 former colleagues in 1999. Jeff lives in Sudbury, MA, with his wife, 2 boys, and dog. Jeff enjoys skiing, backpacking, photography, and classic cars.