NCSolutions, leader of the old guard of shopper marketing data suppliers, has revamped its go-to market model. It culminated this year with a new clean room data product, Insights Stream, which takes the company’s in-store shopping receipts data to where advertisers are using data nowadays.
Which is to say, the cloud.
Jeff Doherty, chief operating and product enrichment officer, has been with NCS since its 2010 launch as a joint venture by Nielsen and Catalina Marketing – which, if you don’t know, is a large seller of receipt printing machines to US stores. The “product enrichment” element is an internal term referencing data partnerships and other ways NCS strengthens its data set, he told AdExchanger.
NCS is a standalone entity, but it accesses Nielsen’s consumer panel and census-based data modeling on one side and the Catalina stream of receipts info on the other.
The company, which Doherty said has processed more than 1 trillion sales across 100 million households, puts that data through its own machine learning models. “We’re projecting and predicting, based off that, how to fill in the rest of the US.”
AdExchanger spoke with him.
AdExchanger: Historically, going back to Nielsen and Catalina Solutions, the data came from stores with Catalina receipt printers. Is that still the case, and where else does the data come from?
JEFF DOHERTY: The same sources, but expanded over the years.
We’ve expanded our channels, from typical grocers to convenience and drug stores, which feed us receipt data. We have a consumer panel now, too. And we now have two providers of receipt capture data as well.
What we’ve been looking for to add to our data is not “more data is better,” but specifically expanding our channel coverage of true offline purchase data.
There are retailers out there that simply won’t share their data. I can’t name their names. But, overall, what a CPG gets with us is a wide breadth of transactions through receipt captures.
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If a retailer launches its own retail media ad business, is that a typical reason why they would not share their data?
We haven’t seen that with the rise of retail media networks. And we’ve been through several rounds of negotiations with these retailers over the years. I think the reason why it works is we primarily focus on the national advertising side of the house.
Most of the retailers that we work with, we’re not conflicting. For one, they do campaigns within their shopper network. they might look for a bit of reach extension, but most of the time on the retailer media networks, they’re doing deterministic targeting versus reach extension.
It feels like different swim lanes, when we’re doing measurement and targeting modeled out for national campaigns, while they’re targeting within their network.
With the data clean room trend, do you think of it more as a buzzword, or are these really new capabilities?
I think it is net new capabilities and a different kind of hands-on-keyboards way of doing things for the brand.
It’s an inexact analogy, but I compare it to whether to have a contractor come to your house and remodel, or do you say, “I think I’m pretty handy. I’m going to go to Home Depot to buy all these things and do it myself.”
I would call a clean room the Home Depot approach. The things we offer around our targeting and measurement service is, basically, like we’re going to come in and be that general contractor for you. But with clean rooms, I do think that advertisers and brands are looking for ways to empower themselves and get more detailed analysis outside of managed services.
Is there one particular – or a number of – clean room vendors that underpin your technology?
Snowflake, Habu and LiveRamp we work with and are big players in the space. But there are more coming every day. There also are different terminologies – data lakes, clean rooms, privacy-enhancing or data-sharing technology – but the tech is really useful.
I like to say “privacy friendly.” What it does is it keeps aboveboard how the data intersects. It creates an audit trail of intersecting data. It’s aggregated, so you can’t get to the roots of what an individual has done or see that row of individuals or the households from within a clean room. You only see where data – or ad impressions – intersected.
LiveRamp and others are talking about the next step for the technology, which is federated data. What they’re trying to figure out are ways to share data between clean rooms.
Isn’t the point, from a privacy tech perspective, that data can’t be shared across clean rooms?
CPG advertisers are a bit different here. It’s difficult for them to know who’s buying their products because the purchases are through stores and channels they don’t own.
What they’re trying to do in clean rooms are types of measurements for themselves – like CRM suppression, frequency capping, incremental lift – linked to their households. But CRM enrichment, for instance, is different. A lot of CPGs have CRMs, but don’t know their purchasing activity.
Our Insights Stream [the NCSolutions data clean room product] is projected nationwide based on Census levels. So they can see where their ad impressions intersected with households in their CRM and do high-level measurement.
It’s not as robust the measurement you’d get with our managed service and our own data models, but it means you can do reach extension or audience suppression based on your CRM, and they only see the outputs, not the model. And the output is the modeled data that you intersect with.
Hopefully that makes sense.
This interview has been edited and condensed.
