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A 360-Degree Insights Engine to Drive the Customer-Centric Organization

Going on autopilot when it comes to delivering a premium customer experience can leave you behind in comparison to competitors. Learning to utilize the 5 steps of the customer journey, allows organizations to view customers more holistically.

Editor’s Note: I’ve felt for a long time that Insights departments miss an opportunity by not better connecting the different programs they run. For example, siloing the NPD process from the customer experience program makes it more difficult to drive new product opportunities from what customers are experiencing from existing products or services. Here, Doug Church describes how to take a 360-degree view of customers, and how such a view can benefit organizations.

In his 1997 book, The Innovator’s Dilemma, Professor Clay Christensen of Harvard University spelled out why entrenched technology companies can be subject to disruption by upstart rivals. He followed this with his “jobs-to-be-done” theory that espouses the notion that people use products to achieve goals or solve problems, and that disruption occurs when companies get complacent and innovative competitors offer better approaches to completing the jobs that people want to be done. While we believe this theory is crucial to successful innovation, it also remains true that enduring companies go beyond offering valued products to deliver a seamless and emotionally rewarding customer experience across touchpoints and lifecycles. There is a myriad of studies showing how poor customer experience can affect switching and the bottom line. In other words, you can make great products that solve problems, only to lose customers because they feel unappreciated, encounter unhelpful staff or have a frustrating digital experience.  

The Customer-Centric Approach

Notwithstanding an abundance of evidence demonstrating that the key to success is a customer-centric approach to innovation and experience, it remains an elusive goal for many organizations. A key reason for this is the lack of a coordinated approach to managing and utilizing the knowledge required to understand what customers want. A global study in 2015 by Kantar Vermeer found that an organization’s ability to harness insights was the most important factor in driving customer-centric growth.  Specifically, firms that overperform in terms of revenue growth are three times more likely to be skilled in linking data for insights. Yet, for most organizations, the unstructured and structured data needed to uncover customer insights is disconnected and owned by separate business functions. Moreover, there are gaps in the coverage required to paint a picture of customers across the lifecycle, from initial problem or jobs to be done, to post-sales experience and ultimate brand loyalty.

The Customer Experience

If building an insights engine is a key driver of customer-centric performance, then special care is needed to ensure the engine provides a complete picture of the customer experience. Without this 360-degree view, a company’s insights engine might miss important inflection points that impact overall performance. For example, a lack of data on product performance could miss situations where upstart competitors offer solutions that help better achieve jobs and gain market share. Lack of insights into messaging effectiveness can miss the mark in communicating the benefits of new solutions. And a lack of understanding of the desired digital channel experience could impact brand loyalty and repurchase.  

To be truly effective, the insights engine itself needs to mirror the end to end experience that each customer segment goes through for different solution categories, from initial need to repurchase. It needs to tie together disparate data sources to present a complete picture at each stage, including data from primary research sources, behavioral data, unstructured qualitative information (e.g. customer input through channels, social media). And, it needs to utilize data analytics approaches and technology to answer the right questions.

End-to-End Customer Journey

The insights engine framework shown in Figure 1 captures this end-to-end customer journey, including:

  1. Pre-product need:  Customer-centricity starts with empathy for the needs and problems encountered by different market segments.  This requires continually stepping back to understand what audiences are trying to achieve. Approaches like Jobs-To-Be-Done can be applied to understand (via qualitative research methods like ethnography) and measure (via quantitative research methods like surveys) what customers are trying to achieve, and the degree to which they are able to do so with existing products or solutions. Insights at this stage can be used to identify gaps where customers are not able to perform a job in the way that they would like to, or even a white space opportunity to address an unmet need. This is one of the most important aspects of an insights function, yet many organizations tend to direct their insights efforts at the next stage of product development.
  2. Product development:  Customer insights are needed to help shape products emerging from those identified or unmet needs.  A range of techniques and sources can be utilized to understand precise preferences, including trade-offs between cost and desired capabilities. For example, understanding utility scores for capabilities can help guide development priorities. Agile techniques can be used for iterative design testing to ensure a product looks and functions as desired, and that customers are brought to the table as stakeholders in the development process.
  3. Go-to-market:  It’s one thing to develop a valued solution to customer needs. But, in a competitive world, there is still a need to inform people of the benefits, appeal to them at an emotional level, and ensure they have access to a buying process that matches their ideal experience. Insights can be used to understand ideal customer buying journeys, identify and track problem areas. Different techniques, including data mining, can be used to understand communication preferences and the relative appeal of different messaging.
  4. In-market: Customer and markets are continually changing, shaped by environmental, societal and competitive forces.  Similar to assessing needs, JTBD approaches can be used to understand shifts in sales or financial performance, and identify emerging competitive threats and opportunities.  Behavioral and transactional data can also be used to identify important customer trends and patterns.
  5. Support: There are countless examples of organizations building great products, only to lose customers through a bad service or support experience. Again, research techniques (qualitative and quantitative) can be applied to understand journey preferences, pain points and moments of truth and track experience drivers.

Figure 1 – 360-Degree Insights Engine

While these represent individual stages relevant to the lifecycle journey, including shaping products and solutions, ultimately the insights engine needs to enable a 360-degree view of the experience a customer has with the organization, along with holistic opportunities for improvement. Through reporting and analytics capabilities, it needs to support the management of this overall experience with the customer at the center.

Developing an insights engine with a lifecycle viewpoint requires advance planning to ensure complete understanding of the customer journey across markets and solution categories, the key measures and types of data needed to inform decisions at each stage, and the gaps in data and data collection activity relative to requirements. While the technology to stitch together sources, derive meaningful insights and present them in an engaging and useful way is also important, the upfront insights strategy is an essential building block and can help inform these technology requirements.

Building a 360-degree insights engine goes beyond simply understanding requirements and capturing these through the right data and technology. It requires leadership to define a vision and a strategy and prioritize and galvanize resources. It requires collaboration across teams that own disparate data sources. And it requires an outside-in viewpoint that can represent a significant shift in organizational models, behavior, and decision-making.



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