Think Tank: When It Comes to Data, Use It or Lose It
In an increasingly digital world, the way you shop and engage with brands is changing rapidly — mostly because it’s in the palm of your hand. The jeans you bought on the web instead of an old brick-and-mortar say so much about you as a result of the data those purchases produced.
Widespread store closures aren’t expected to stop anytime soon, (an estimated 4,000 big-box locations closed shop last year alone), but it’s premature to say this signals the death of retail.
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Actually, it seems we’re in the midst of a retail renaissance. Much of that growth is attributed not only to the dawn of customer data but what brands are doing to capitalize on it. If retailers want to take advantage of these growth opportunities, they must consider what they can do in the short term that will warrant long-lasting impacts.
Step one is reckoning with how brands use key customer relationship management data sets to build customer-centric relationships. To become truly customer-obsessed, retailers should create a complete customer picture by bringing together external data sources (demographics, location and market data) and match that with internal data sources (transaction histories, e-mail and newsletter status, or loyalty program memberships).
Quality Is Key
The endgame is a single-customer view to inform manual and automated decisions in intelligence-based marketing, expansion strategies and cross-channel campaigns. But before heading down that route, retailers need to ensure data is high-quality and reputable. When it comes to data, more doesn’t necessarily mean better.
Gaining quality data involves establishing high standards from the get-go. For example, when integrating data sources for customers, companies could run transaction data through a series of steps to spot and remove outliers, delete bad transactions and ensure product attributes are properly encoded to drive the most insight. This removes any question about the veracity of the information, which is significant in a brand’s plans to put data to use.
On top of validating your data, removing extraneous or duplicate data will help you avoid potentially misleading results. Having these checks in place means the data that comes out of the process isn’t arbitrary.
Nobody wants superfluous or — even worse — inaccurate results. Increasing the accuracy of your data increases the quality of your analytics, which means that the actions you take on those insights will have a greater ROI.
Holistic and Realistic
After establishing data standards, the next step is to integrate it all into one place. Not only do consumers engage with brands more than ever, but they’re doing it across more channels and devices. There are an incredible amount of ways to inject your brand into every step of the customer journey. Brands want to create perpetual customer loyalty, improve return shopping, boost margins and develop the best experience all around.
All of these interactions produce an enormous amount of data, but to gain value from these mountains of customer information you need to organize. Processes often spit out data in siloed systems that produce disparate effects. Targeted data is a flashlight in the dark for retailers who must build and integrate meaningful relationships with their customers by being able to access a comprehensive view of those customers.
Take a customer who makes half of her purchases in-store and the other half online or on mobile. This hypothetical half-and-half customer will engage with messaging tied to brick-and-mortar locations just as much as she’d be responsive to digital messaging about her purchases. But if the retailer favors one over the other, such as e-mails talking up big sales at its nearby storefront, there’s a huge gap in potential engagement with this particular customer. That’s one big missed opportunity for significant brand interaction.
To deliver unified brand experiences to customers, retailers must unify and optimize all channels across the board.
A Personal Touch
The relationship between customer and retailer is mutually beneficial. All this marketing has the ultimate goal of serving the customer better, with enterprise and store-level strategies pointing to personalization.
It isn’t just a gimmick, either. McKinsey & Co. found that personalization reduces acquisition costs by up to 50 percent, lifts revenues by 5 to 15 percent and increases the efficiency of marketing spend by 10 to 30 percent.
Luckily, the rise and virtual takeover of mobile retail e-commerce has made personalization — and data collection — easier for brands to improve customer relationships outside of physical stores. Brands can create personalized online commerce experiences with immersive, curated online destinations with purchase history, wish lists and access to sales that foster loyalty to in-store trips.
With most retailers still relatively clueless about the big-data picture, there’s plenty of room to learn how to actually put the customer-specific data they collect to potent use. To effectively use customer data, retailers must gain confidence in their sources and know how to attain and leverage a complete view of each customer. The only thing left for retailers to do after that is use it.
Corey Pierson is the cofounder of Custora, a cloud-based customer analytics software.
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