The Monday Stack: Adventures with Customer Data

Where does the time go? It’s almost a year ago I spoke with Dave Dague, EVP of Marketing at Infutor, learning how the Chicago-based data solutions vendor supports the marketing tech eco-system with its expansive, daily updated, consumer identity graph. Back then, Dague agreed that Infutor was primarily an “enabler” of personalized marketing: It’s become more than that, but its foundational position puts it in a good position to identify marketing tech trends — “A few trends we kind of thought were going to happen, but a couple which were a surprise. Which keeps things interesting,” he said when we caught up last week.

One trend which was surprising “from a demand perspective” was chatbots. They came on faster than expected. During 2017, Infutor launched ID Ver, an API-based solution which identifies —  and provides supplementary information about —  inbound leads, essentially in real-time. For example, visitors to an online mortgage site can be guided to the best product for them, within seconds, as Infutor’s data converts them from an anonymous prospect into “a real live person.”

The solution works for call centers too: The surprise was the demand from customers for ID Ver to support chatbot services. The principle is clear: “The chatbot needs to know who the person is,” said Dague, in order to personalize the interaction. ID Ver can provide that information, based on the email address the visitor inputs to begin the chat, or even just based on cookie history. The approach is clear enough: “We didn’t foresee it taking off at the level it has,” said Dague.

Another area coming on strong is predictive modeling. Infutor’s identity graphs capture “a snapshot of the most complete and accurate information and intelligence possible on a consumer.” That can mean a 30 to 50 year history of purchases, and property and automobile ownership. The graphs are essentially “life ID graphs,” Dague explained. “We know when someone gets married. We understand where they are in their life journey, and that’s highly predictive of needs.”

It’s also valuable for clients who have infrequent interactions with customers, who come to them for periodic big ticket purchases, from travel and hospitality, to automobiles or even solar energy for home installation. If brands are dealing with those — valuable — customers only rarely, data will get “pretty stale,” said Dague. Infutor now offers ID monitoring, telling clients on a query basis, or through regular reports, where their customers are in their lives. 

Infutor is positioned already to supply raw intelligence on consumers, which clients can use to feed their own predictive models. But also: “We’re beginning to move into this area ourselves, very judiciously.” An in-house team of data scientists (“Three, so far”) are starting to develop proprietary models, combining raw identity data with behavioral data like browsing history. “We’re not getting into the big segmentation game any time soon,” Dague cautioned, but “we’re starting to build some very strong models.”


It’s cold in New York City. It’s a holiday. And yet life rages on, in the shape “retail’s big show,” the National Retail Federation’s vast expo under the chilly and echoing ceilings of the Javits Center. We’ll be there tomorrow, despite the wind blowing off the Hudson River, but mean-time here are some highlights of what Salesforce is announcing. Gordon Evans, VP of product marketing, gave me a preview.

  • An integration between the Commerce Cloud (which we’re learning to stop calling Demandware) and the Marketing Cloud which will allow eCommerce behavior to trigger email campaigns. Despite a 60% abandonment rate for online shopping carts, only a third of retailers are set up to send recovery emails, Evans said. “That’s a missed opportunity,” and that’s without even looking at abandoned browsing sessions and abandoned searches. Salesforce clients leveraging both clouds can now trigger automatic email follow-ups.
  • Einstein-powered intelligent customer service. The rise of IM in retail, said Evans, “speaks to the end of ‘please hold.'” Using Salesforce LiveMessage, representatives are provided with a holistic view of the customer’s history from the Commerce and Marketing clouds. What’s more, about one third of customer message inquiries fall into the category of common questions or use cases — appointment bookings, order confirmations, shipping inquiries. Einstein bots can deal with these kinds of engagements automatically, or seamlessly escalate to a live agent, Evans explained.
  • “Instagram,” said Evans, “is the new first screen for retail.” Integrating with Commerce Cloud, retailers can now project product categories and shopping opportunities into Instagram posts. And of interest to AI geeks, Salesforce is also offering an Instagram use case for Einstein Vision, the deep learning solution which can identify images, deploying it to show visual references to brands and products where the names aren’t mentioned. This capability integrates with Social Studio, allowing brands to respond online when appropriate.
  • Salesforce will also be discussing the applicability of “distributed marketing,” which we reported on from Dreamforce, to retail brands with local stores or franchises. 

And where would we be without some latest data? According to Evans, 81% of shopper journeys now span multiple channels; 75% of shoppers want more personalization; and 65% are willing to exchange data for a better customer experience.

Javits Center, here we come.

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