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In-store heat mapping can help retailers create more offline to online connectivity as well as optimize store performance Photo Credit: Retail Store Analytics

Operationalizing Customer Data: Examples From Nike and Zara

Now is the moment for brands to prioritize listening to their consumers above all else. Instead of driving consumers to your platforms, sites and events, businesses should meet them where they are. There are two important behaviors that can help companies to reinforce both their value proposition and license to communicate to consumers.  First, brands should be using customer data to cultivate a relationship instead of a transaction. Second, firms should be developing solutions to turn channel engagement into quantitative insights. Adopting these two systems will create an authentic reason to engage with the fans of your brand and perhaps more importantly, contribute to a company cultural shift towards a customer-centric approach.

Nike’s Nike Training Club (an exercise community platform) is a great example of prioritizing a consumer relationship over a transaction. After watching yoga class attendance rise during COVID-19, Nike has added to the number of yoga courses offered and prioritized cultivating a community on the platform over product messaging. Decisions like this have led to a 100% increase in active weekly NTC users[i]. The consumer engagement through these efforts will yield meaningful information that can inform future product launches and brand activations, increasing Customer Lifetime Value as well as related switching costs.

As consumers return to stores post lock down, measuring in-store engagement has never been more important.  In-store engagement, a challenging metric for most retailers, can be effectively measured by leveraging heat mapping technology to turn qualitative interaction with your store into a quantitative output. Two consumers visit the Zara flagship store and neither makes a purchase. However, one spends 40 minutes trying on accessories and talking to store ambassadors, while the other spends 1 minute in the store as he or she waits for a friend.  Those two experiences should be valued accordingly. Data scientists can analyze these interactions and group them based on the behavior. The data collected from these journeys can be inputted into multiple KPIs like “time spent talking to store ambassadors” or “products tried on”. The result would be a robust attribution thread between offline activity and offline + online transactions as well as a tool to optimize store experience and offerings.

A thoughtful and meaningful omnichannel approach is predicated upon being nimble enough as a company to recognize where a consumer wants to meet you rather than drive them to where you are. Agility to adapt to new growth-oriented KPIs and metrics will be a characteristic of best practice retailers.  The above two recommendations can be the building block that ensures that data is leveraged to understand where the consumer wants you as a brand to be.





Oliver Embry

Oliver is a guest contributor and McMillanDoolittle affiliate partner. He has worked in online and offline retail strategy for adidas and is passionate about helping brands create omnichannel approaches to commerce solutions. He currently is an independent consultant advising companies on how to drive better online or offline engagement, depending on the priority.

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