Building a Winning Data Strategy
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The typical modern company is swimming in data. Whether in the form of inventory flows, manufacturing decisions, customer inquiries, or app and website clicks, there are vast quantities of data created and consumed every day. Yet managers continue to find it challenging to use this data to create new value for customers.
We blame this data paradox on the classic data-insight-action framework. The familiar process lulls managers into thinking that producing “valuable” data or surfacing insights for their customers is enough. This encourages passivity, and companies become much too trusting that customers will actually use and act upon the information provided. As a result, companies deploy analytics-based features and experiences that customers don’t use. And, because there is no action, there also is no value creation, and certainly no value capture, by the company.
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Consider consumer banking. When banks initially established mobile banking apps, they focused on providing customers with data (for example, transaction histories) and insights (such as spend patterns, often in the form of a pie chart broken out into categories like rent, utilities, and food). Banks proficient at delighting customers, however, went a step further. Global bank group BBVA, for example, bundled spend insights with customer stories, tutorial videos, and recommended next steps intended to motivate customers to benefit from their information. Over time, BBVA introduced features into its mobile app that integrated predicted outflows into a customer’s digital calendar, automatically saved money toward a desired savings goal, and connected the customer with a BBVA financial adviser to execute a suggested investment opportunity.
Our research (see “The Research”) indicates that analytics-based experiences and product features for customers pay off only when combined with aggressive tactics that all but guarantee that customer value materializes. Companies that do this well rely less on a sequential data-insight-action process and focus instead on interweaving insights and action activities to deliver actioned analytics to their customers.
Analytics-based experiences and product features for customers pay off only when combined with aggressive tactics that all but guarantee that customer value materializes.
Three Principles for Actioned Analytics
Fortunately, data-intensive businesses — such as data aggregators, digital natives, and progressive financial institutions — have developed an array of tactics to ensure that data offerings are activated by, or for, customers. These tactics can be organized into three key principles that can help managers produce actioned analytics and create real customer value for their company to capture.
1. Prioritize customers who are action-ready. Data-intensive businesses start by developing information offerings with or for the customers who are easiest to inspire. This means prioritizing both self-sufficient customers who are willing and able to act on insights and open-minded customers poised to respond and change.
At PepsiCo, leaders were eager to serve the company’s retail partners using Pep Worx, a suite of capabilities built to deliver information solutions such as tailored product assortment strategies, innovative marketing programs, and space-optimization suggestions for stores. But the leaders recognized that the success of Pep Worx required retailer follow-through, so they purposely worked with retail partners who had “will and skill.” According to PepsiCo’s vice president of shopper analytics and insights, “We began to model ourselves like a consulting firm, helping retailers understand how to solve their operating problems and demonstrating how we could help them do that. … It was imperative to understand the retailers who were eager and able to take action so that we could focus our efforts on them.”
At times, customers are action-ready because they have been hungering for information that helps them resolve compelling problems. Cochlear, the hearing-implant provider, discovered this after it released an external sound processor that worked with an iPhone. In 2017, the company deployed insights to a mobile app to help customers optimize their hearing and better use the physical device, which is worn behind the ear. A “find my sound processor” feature was particularly well received (and used) by parents of young patients who had long shared concerns about losing the costly physical unit.
2. Bundle insights with action-inspiring activities. Data-intensive businesses deliver insights in consumable ways that make it easy for customers to access and use them. They also might establish other customer-centered efforts, such as advisory units, automated services, and onsite support.
Healthcare IQ is a health care spend analytics company that for decades helped hospital customers lower the cost of care by comparing a hospital’s supply costs with those of peers; identifying process inefficiencies, such as off-contract orders; and finding savings opportunities, such as bulk-order discounts. Healthcare IQ leaders learned, however, that activating these insights required their customers to negotiate new pricing rates, restructure procurement contracts, and reengineer how materials were stocked and replenished — all of which are significant commitments for a hospital.
Healthcare IQ created reporting and analytics offerings that indicated to customers exactly what they should be learning from the data and how to apply new insights and lessons to generate business value. To do this, the company used data visualization, alerting and exception reporting, and hands-on support. The company established its IQ Center, a customer support unit staffed with experienced analysts and clinicians with years of hospital experience, to assist hospitals with strategic projects, special initiatives, and specialized reports. In some cases, support took the form of onsite consultants who helped the hospital’s value analysis team or negotiated with vendors.
When possible, data-intensive businesses inspire action through automation — in fact, this is the ideal state of actioned analytics. Tripbam is the leading hotel-rates shopping and compliance engine for travel managers, serving half of the Fortune 100 and a sizable proportion of Fortune 500 companies. Its core offering initially suggested rebooking opportunities as they became available as a result of rate fluctuations at the booked hotel and at nearby competitors. Ultimately, Tripbam created an automatic rebooking feature, which guaranteed that a busy traveler cashed in on the lower-cost opportunities.
As a byproduct of its continuous rate shopping, Tripbam produced insights regarding the hotels’ compliance with negotiated contract terms such as discounted-rate availability. However, only Tripbam’s largest corporate clients had travel units capable of follow-up. The company’s CEO, Steve Reynolds, explained, “In the early days, we would show reports to our customers, and they would say, ‘This is great insight, but I don’t have any staff to action it.’” In response, Tripbam created alerts that automatically generate emails to hotels with a warning to comply with specific client contract terms — or face getting kicked out of the client’s travel program.
3. Monitor action, and remediate inaction. Customer nonresponse can be astonishing. For Cochlear, product managers initially were surprised to learn that some hearing patients did not optimize their hearing settings even after receiving recommendation alerts on their mobile apps. Product managers discovered this during routine meetings with analytics colleagues to review and interpret processor usage data and while talking with customers about the feature during clinical trial processes. In response, developers designed a new technology, Scan, to analyze the sound environment and adjust the settings automatically for customers in order to deliver the best hearing for the conditions.
Duetto Research, a data-intensive hotel revenue management company, formed a customer success team that was accountable for ensuring that customers could extract the maximum value from using Duetto offerings. The customer success team lead explained, “Customer success is not customer support. The latter is reactive — customers open tickets and report bugs, and customer service representatives troubleshoot them. Customer success is proactive. It’s our job to ensure that customers see the reason to stay with the company: They make better decisions and more money.”
As these examples illustrate, data-intensive companies learn to expect customer inaction and proactively intervene with action-inspiring activities. As a result, these companies first uncover what’s going on with customers, typically by tracking usage or solicitating input from customer-facing employees. Then they jump in as needed with value-sharing incentives, gamification, education, and other methods designed to motivate customers to take action.
It’s Time to Embrace Actioned Analytics
For Tripbam, customer retention and competitive advantage are closely related. The company monitors savings in relation to monthly subscription costs and computes the ROI that each client receives from its service. Leaders aim to deliver customers value that equates to fourfold their costs. If a customer’s ROI drops below that target — an early warning of decreasing customer loyalty and possible churn — the team proactively reaches out to the customer to remediate the problem. When a customer’s ROI increases significantly above the target, leadership may evaluate a possible contract renegotiation to maintain the desired value-capture balance. As a result, the company enjoys a near-perfect customer retention rate. As Tripbam’s CEO noted, “We make sure each customer has at least a fourfold ROI. Why would they churn?”
Delivering actioned analytics is now within reach of most companies, not just seasoned, data-intensive ones. And those who commit to bridging the gap between data and action for their customers stand to gain tremendously. Such a commitment positions a company to measure, influence, and adjust customer value creation — and, in effect, establishes vertical integration with the customer’s data-insight-action process. This is an enviable competitive position to achieve, and one that ensures both customer loyalty and company value capture.