Refining customer data into valuable insights and actions
The famous phrase “Data is the new Oil” turned 10 last year, and it endures as one of our favorites.
Refining data into value. Big data in retail is oily in that it’s often idle and difficult to access. It sits just under the surface of company priorities, bubbling away in a murky unsexy form as it lies in wait for the recognition of its true potential. Upon its discovery, ecstatic shouts of excitement are not uncommon, as a whole new world of ROI rains down on the data-savvy few to appreciate it.
In this post, Simon Small, our (former) Director of Solutions, Support and Marketing, takes you through the three key challenges that are stopping companies from putting data-driven retail strategies in place.
The overwhelming potential of Big Data makes it extremely difficult to plan which activity is best to execute and how. This can paralyze teams and organizations who’re already extremely busy running, optimizing and transforming with less. It takes time to wade through the opportunity, trial things, learn and move forward. Prediction, targeting, product strategy, testing, multi-channel optimization, triggered comms, customer service, sales, brand building…. how do you mash all that together? The key is to use a retail data solution that allows you to better understand and engage your customers.
The second challenge is how to plug it together in a way that is usable by the people in the organization, can be automated, is scalable and actually works. While most platforms will persuasively convince you they can plug in, turn on and start making you a disruptive organization as easy as 1, 2, 3… they can’t. Well, they could in an ideal world, but we don’t live in an ideal world. Any retail data system is highly dependent on other platforms, quality data, seamless integration and a plan to utilize it all (see challenge 1) in a meaningful way. I’ve seen hundreds of product demos that fall flat as soon as you try to do something off sales script, or integrate in a slightly different way, or even do the thing they did in the seamless demo after they’ve gone.
Finally, it all relies on people who can efficiently access, translate, apply and action data in meaningful ways. Yes, data scientists but also designers, developers, content creators, platform managers, leaders all in cross-functional ways. Argh. The myth of completely automated and intelligent marketing platforms is mostly forgotten but many still underestimate the human effort required to turn the cogs and convert potential into value.
Lexer makes data more human
There is so much to Lexer’s customer data platform (obvs) but the standout bits for me are how easy it is for humans to use the platform (this is a big deal) to help them understand the humans that they need to service.
They bring together disparate data sources into a single location and then make the customer/user records more detailed, nuanced and human through a unique process they call enrichment. Then an organization can create groups of people based on these much more interesting data points and either understand them better or target them in much better ways.
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Read a full version of this story, including Simon’s journey to Lexer over here.