In my last post, I posed five questions to retailers to help them determine whether they're ready for a customer-first mindset. Now, I'd like to challenge the retail basics that seasoned retailers were trained on, and suggest instead a new customer data science approach.
"Retail is detail" is common industry wisdom, and it means that achieving success is subtle and difficult. Success in any field demands practice and experience, and so it is little wonder that many senior retail and brand leaders and managers have vast years of involvement, and that most have grown up through the business in progressive steps.
Why What We Know About Customers Just Ain’t So<p>The old axioms are no longer factual because customers themselves have dramatically changed, in their needs, expectations and experiences. Separating fact from fiction—and business truths from myths—will change how the business sees itself and how it will make decisions. The following are some of the new truths of retailing in the 21st century:</p><ul><li>Expanding share of wallet from customers who are already "loyal" can better optimize growth.</li><li>Loyal customers need more love and investment than new customers.</li><li>Retaining loyal customers and reducing churn among "opportunity" customers can drive more growth than acquiring new customers.</li><li>Price-sensitive customers are often more profitable than other segments because their basket mix includes more private label products or higher-margin portion sizes.</li><li>Behavioral "buy-o-graphics" and intended trip missions matter much more than demographics or geographics.</li><li>Customer segments are typically distributed variably within geographic regions or zones, but all customer types exist in all stores.</li><li>Store clusters built upon customer dimensions are more useful to operations and execution than store groupings based on geographic zones or volumetrics.</li></ul>
What We Know for Sure Can Fit on a Post-It Note<p>Agility in retail can only be maintained by understanding customers and using data in all available quantitative and qualitative forms. Here's a personal story to illustrate:</p><p>A perception-based research tool measured one retailer's progress against factors that customers themselves had said are most important to them. Before the first customer perception report was published, I set out to learn how the customer ranking compared to the rankings that the senior decision-makers would assign.</p><p>The regular weekly senior team meeting brought together many of the wisest and most seasoned leaders in the business. After briefly introducing the research methodology, I asked the team to list what factors they thought customers would list as important, and in what order they thought customers would place them.</p><p>Not surprisingly, each merchant tended to rank factors in their department higher on the list than those for other parts of the store. Although little agreement was reached, a compromise ranking was eventually defined.</p><p>Comparing our list to the customers' list revealed spectacular differences; leaders had listed most of the same elements as did customers, but in completely the wrong order. That day, the team experienced a true epiphany—they realized that "we didn't know what we didn't know."</p><p>The lessons learned were:</p><ul><li>Humility gained in discovering that "we don't know what we don't know" empowers the customer-first journey.</li><li>To become more relevant to customers, we must become fact-based deciders and activators.</li><li>Using customer data well creates true consensus and inclusive action.</li></ul>
In summary, “In God We Trust” ... all others must bring data.<img lazy-loadable="true" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNDYyMjA4MS9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYyMzA2MzY0MX0.IONHl7U4GvV1SELtCU05-gSd24MuhErJw9fkohPlDJU/img.jpg?width=980" id="0a481" class="rm-shortcode" data-rm-shortcode-id="acf695ac2df738141d48aee28b7b9861" data-rm-shortcode-name="rebelmouse-image" data-width="600" data-height="988" /><p><em>David Ciancio is global customer strategist for Dunnhumby, a pioneer in customer data science, serving the world's most customer-centric brands in a number of industries, including retail. David has 48 years' experience in retail, 25 of which were in store management. He can be reached at email@example.com</em></p>
Are you looking to increase your contactable Customer base? How much money are you losing on incorrectly identified Customer communications? Throughout our 30 years of big data experience working with clients across industries around the globe, we have found that maintaining contact through relevant Customer engagement is a crucial component of putting the Customer First.
Essential to preserving contact data is ensuring that you have the most up-to-date information from your Customers; not an easy task. On average, people in the United States will move an average of 12 times in their lifetime. United States Postal Service data indicates 14% of the population change addresses annually. As email contact has grown, it's important to note that, on average, 30% of people change their email addresses each year. This is driven by ISP or job changes, or just to stop being spammed. As people move away from home phones to primarily mobile devices, phone numbers are stabilizing as consumers maintain the same numbers through physical moves.