The Marketer’s Big Data Challenge: Unifying Our View of the Customer
In a recent post, we discussed what the future of big data holds, and how we can apply it to develop highly targeted and relevant campaigns for unique customer segments. Emerging opportunities for leveraging big data occur every day, and even greater opportunities are still yet on the horizon. But as we have seemed to conclude, big data is only big when it drives real, tangible results in campaign performance. When big data truly allows us to answer not only the question of, “Who is my customer?” but “Who is my best customer?” we know that it is adding real value to our programs. The ability to connect the dots between big data and analytics as it relates to a holistic customer-centric strategy is the competitive edge that every company seeks today.
How Do I Connect My Customer Data Points?
Though marketers have developed more sophisticated methods of tracking and grouping data into the appropriate segments, challenges still arise in recognizing how to actually harness every piece of information so that it drives results – so that it answers the question of who our complex customer is, how she or he behaves, and how we can deliver the most relevancy.
Where do these challenges stem from? As marketers we’re all fairly familiar with the “aspirational” customer – we’ve cultivated her into a loyal brand advocate, she engages with us in each channel seamlessly and converts when and where we expect her to. But we must ask ourselves, are we truly reaching that customer? Are we actually understanding her purchase journey by connecting her data points? Do we even know who she is, or whether she exists at all?
Surprisingly we have found more often than not that the answer to these questions is “no”. According to research conducted by technology provider, Signal, six in ten retail marketers struggle to personalize customer experiences due to fragmented data and customer profiles. The addition of big data technologies and advanced analytics has given the retail sector a unique opportunity to understand their customers. But many still feel as through their data snapshot is disjointed or incomplete. Often times, this comes from the process. Believe it or not, some of the major challenges in leveraging customer analytics begins at home, in the application of first party data.
The first step in understanding the big data environment and how it relates to optimizing customer segmentation is to disrupt the old siloed platforms of engagement. Direct mail, email marketing, search, social and display generate myriad data points about retail customers, but the key to leveraging them is by viewing them not as isolated, but as one. We can connect qualified data, but until we unify online and offline to build a single, comprehensive view of each customer, we cannot achieve scale and efficiency in our programs. Basic in house customer information – names, email addresses, sales channels through which customers engage and convert, products that he or she purchased – all represent a critical mass of data that lends us the first level of needed insight to strengthen our methods of customer segmentation.
We recently completed a customer analytics project with a brick & mortar retailer that was beginning to see slowing growth after a tremendous start. Year over year sales comps were down and this retailer didn’t have answers as to why. By connecting their store traffic customer-level sales performances, we were able to identify the source of the problem: they were not acquiring enough new customers to offset losses to their active customer base. Store visits, and ultimately sales were significantly down within this key customer segment.
With our guidance, the client opted for a multi-phased marketing strategy that would 1) increase store traffic and sales from target prospect audiences 2) improve customer loyalty through cultivation programs, including a critical first step of cleaning up their customer data and 3) enhance the ability to contact customers through direct response. Moving forward, our teams will be providing them a unified view of their customer performances to monitor and measure the success of these initiatives within and across channel.
As the retail and marketing landscape in general evolve with more complex technologies, the value of unifying customer data ever increases. Consumer expectations are amplified, and in order to ultimately build meaningful (and convertible) relationships, having the right tools and processes for implementing customer data is no longer an option.