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Research Methodologies
August 7, 2019
Better understand the customer lifecycle journey with a 360 approach.
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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.
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.
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.
The insights engine framework shown in Figure 1 captures this end-to-end customer journey, including:
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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The views, opinions, data, and methodologies expressed above are those of the contributor(s) and do not necessarily reflect or represent the official policies, positions, or beliefs of Greenbook.
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