This article sets out the Insights2020 findings and the role of insights and analytics in the customer-centric organization. The study included 337 vision interviews with business, marketing and insights leaders and an online survey of 10,495 practitioners in 60 countries.
Its purpose is practical: to give brands a roadmap to customer-centric revenue growth and to decode the role of insights and analytics in driving it. The work builds on Marketing2020, which focused on aligning marketing strategy, structure and capability with business growth.
Key findings
- The authors argue that traditional value drivers no longer confer advantage. Anyone can produce quality products, manufacturing no longer provides sustainable advantage, and distribution access is widely available both online and off.
- Customer centricity is routinely confused with customer service. The authors separate them by objective: customer centricity focuses on making profit and maximizing it over as long a period as possible, while customer service aims at satisfaction regardless of cost and profit.
- The study found the answer was not where the authors expected. They anticipated findings about data science, software and technology, and instead found a much higher emphasis on the human element, organizational connectedness, leadership qualities and orchestration skills.
- Self-reported growth was validated against actual revenue figures obtained from Bloomberg, and the two correlated highly, with the clearest patterns at the top and bottom boxes.
- From the survey rent authors analyzed the contribution of 66 potential drivers to customer-centric growth, which let them quantify the impact of each on revenue growth.
What leaders said helps and hinders
Among external opportunities, the ability to translate insights into actions was ranked most important by just over half of respondents, at 50.3 percent, followed by the increasing importance of brand purpose at 35.9 percent, personalization at 35.7 percent and availability of behavioral data at 34.1 percent.
The internal challenges are organizational rather than technical. Internal barriers were named by 54 percent, legacy of structure by 43 percent, making sense of all the available data by 37.5 percent, and recruiting and training whole-brain people by 33.3 percent.
Four consumer demands frame the problem: speed, where patience is described as becoming a rare commodity and KLM promises a response within an hour on social media around the clock. Integrity about why and how you do business and about data privacy. Convenience. And relevance, where a hotel may ask for personal data as long as it uses it, remembering an intolerance to feather pillows.
Dimension one: total experience
Customers expect a seamless, consistent brand experience built on a clear purpose. 80 percent of over-performing companies invest in making all activities purpose-led, against 32 percent of under-performers.
Great brand purpose mixes inside-out factors such as brand DNA, credibility, heritage and the founder’s passion with outside-in factors such as customer needs, white spaces and societal shifts. The hard part is not defining it but living it consistently across the whole organization.
Whiskas is the worked example. Mass qualitative research found that people are fascinated by the big-cat characteristics they see in every little cat, which lifted the positioning from care to nurturing the cat’s true nature. The purpose reached the product itself, changing the shape of the pellets and the nutritional profile toward what cats needed rather than what The authors learned that there are thought looked nice.
The second driver is customization: 73 percent of over-performers use data-driven insights to customize their offer, against 31 percent of under-performers, ranging from the product itself to service, pricing and distribution. Telematics in car insurance is cited as an example of personalization reshaping an industry.
The third is touchpoint consistency, at 64 percent against 29 percent. The recommended approach is to start with a few select touchpoints and expand into more moments of truth along the journey, eventually extending consistency beyond a company’s own touchpoints. Burberry is the example, as the first brand to launch an Apple Music channel in 2015.
Dimension two: customer obsession
Taking the voice of the customer into every business decision was observed at 87 percent of over-performers against 22 percent of under-performers, and the strategy being embraced by all functions at 79 percent against 13 percent. This driver showed the largest link with revenue growth in the study.
The base level of maturity, outsourcing customer centricity to the insights and analytics team, is dismissed by the authors as hardly a strategy at all. The highest level is seamless alignment with external partners.
Leadership priority separates the groups sharply: the strategy is a priority for top leadership at 91 percent of over-performers against 48 percent of under-performers, and 45 percent base incentives on customer-related KPIs against 25 percent.
Culture at over-performers leans toward risk and experimentation, climbing a ladder from a risk management mindset through occasional experimentation to allocated budget and full empowerment of employees. The authors quote LinkedIn’s phrase, take intelligent risks.
GoPro illustrates collaboration taken to the customer. Rather than paying agencies and professional photographers, it rewards users for sharing the best real-life material, which becomes its marketing.
Dimension three: the insights engine
The authors argue this dimension is the most important of the three, and that customer centricity should start with the insights engine, because it makes building a customer-obsessed mindset and delivering a total experience easier.
51 percent of over-performers say the insights and analytics function is used to its full potential, four times the score among under-performers, which indicates the function influences all parts of the business planning cycle.
The role is shifting from support function to business partner with a seat at the leadership table, driving strategy and real-time execution with marketing, IT and finance. Unilever’s consumer and market insights function is given as an example, moving toward a mission to inspire and provoke to enable transformational action.
Reporting lines follow. Insights and analytics leaders report directly to the executive chamber almost three times as often in over-performing organizations, with TATA Sons cited, where the head of insights and analytics reported directly to the chairman from 2014.
No participating company complained about a lack of data. The authors describe the increase in availability as infobesity, and locate the opportunity in moving from data and information provider to full partner and part of the solution.
The practical obstacle is disparate datasets owned by different teams or companies, which the authors expect to persist for years. Over-performers respond by centralizing ownership into a single source of the truth and organizing expert communities that turn data into actionable insight.
The capability gap is whole-brain. Over-performers’ employees show more business context mindset, find creative ways to answer complex questions, and tell better stories, combining the science of what the data says with the art of creative recommendation. The authors quote Brené Brown: stories are data with a soul.
What the authors ask readers to do
The conclusion is that customer centricity and revenue growth go hand in hand, and that leaders should improve all three dimensions together: total experience externally, true customer obsession internally, and full exploitation of the insights engine.
Companies wanting to apply the findings are pointed to a benchmarking tool that requires a minimum of 50 internal participants and identifies opportunity areas and challenges.
The next phase of the study shifts from the what to the how, asking how to drive customer centricity through the organization, which metrics to use to measure and reward progress, and how to distil insights from multiple internal and external data sources.
Scope and limitations
The quantitative data comes from a single data pull in September 2015, with interviews conducted between May and September 2015 and survey completes between July and September. Growth comparisons rest partly on self-reported figures, validated against actual revenue on a subsample.
Source
This page summarises Driving Customer-Centric Growth: A Practical Roadmap, by Mario Simon, Frank van den Driest, Tom Wilms, June 2016.