eCommerce Success Threatened by Big Tech Data Dependency

There’s a pressing need for eCommerce companies to reduce their reliance on Big Tech.

That’s according to Brady Harrison, director of customer analytics solution delivery at Kount, who told PYMNTS that online businesses need to rethink the way they use Big Tech data to drive sales.

“There’s economic uncertainty and a decrease in consumer confidence,” Harrison said, pointing to the need for retailers and merchants that are focused on growth (and mature businesses too) to be more effective in targeting consumers as they strive to grow customer lifetime value.

That’s no easy task, given that companies, fed information from the marquee Big Tech platforms, can embark on an email marketing campaign and still often see a success rate that is less than 1%. There’s no real knowledge that the emails are being sent to people that actually exist, he said, or that the targeted email marketing lists on which so many companies rely are, in fact, worth the time, effort and money.

“If you look at your costs per advertising campaign to get insight into a cohort of customers or to find out who they are, you don’t really have any access to the underlying data about that customer,” he said.

The lack of insight and cycle of dependence on Big Tech has negative ripple effects, resulting in a degradation of the online interaction as consumers engage with brands.

The Experience Killer

“Getting an ad for something that you have zero interest in is a real experience killer,” said Harrison.

The ideal way to gain top-line torque in the digital age, he said, is to pare down the customer population to the individuals who are high value and the most likely to pull the trigger and buy goods and services.

“Rather than targeting the ‘whole pie’ and getting a 1% success rate, these firms can target 10% of the pie and get a 1.5% success rate,” Harrison said. “That’s a 50% improvement.”

One way to do that, and to cut corporate costs in the meantime, is to disintermediate the Big Tech platforms from which retailers and others have “rented” access to customer level-information. The goal (and through the efforts of third-party providers such as Kount) is to get the primary data in hand that provides insight about customers, he said.

That data can offer up information about everyday habits, spending propensity and demographics that can help craft personalized campaigns that resonate with end users.

And by using third parties, it becomes easier to gather the data, store it and put it in a place where it can ultimately be useful, said Harrison — and help craft user experiences that cement loyalty.

Relying on partnerships helps solve the universal “build versus buy” debate that confronts all manner of firms as they engage with their customers online.

“Companies need to build [marketing] muscle on their own and figure out how to target their customers themselves, and it’s an extension of the direct-to-consumer model,” he said.

Rather than targeting them on a Big Tech platform, merchants can seek to target them directly through an in-app experience or a personalized approach that begins the moment they “land” on a corporate webpage, Harrison said. Thus, the consumer who’s engaging online with a grocery store could (because geolocation and weather-related info is being triangulated) be shown ads for soup that has been bought in the past and might be an especially timely purchase.

Leveraging the tech and analytics of providers including Kount, he said, can “extract” the cohorts out of the Big Tech platforms and use similar and ancillary data sources to target and customize user experiences, giving rise to a more cogent and useful experience.

“I hit your page, and you have information about me because I’ve engaged with your business before,” he said. “That cart, basket or engagement grows over the long term.”