Intuit's Dave Raggio shares why SMB MediaLabs doesn’t own inventory, how it prioritizes privacy for its customers, and the reason consumer and CPG brands are turning to Intuit’s data. 

Episode Transcript

Please note, this transcript  may contain minor inconsistencies compared to the episode audio.

[00:00:00 ] Damian: I'm Damian Fowler.

[00:00:01 ] Ilyse: and I'm Ilyse Liffreing

[00:00:02 ] Damian: and welcome to this edition of the current podcast.

[00:00:05 ] Ilyse: This week, we're delighted to bring Dave Raggio to the podcast. Dave is the vice president of S& B Media Labs, a B2B media network owned by Intuit, which is of course known for business products like TurboTax, QuickBooks, Credit Karma, and MailChimp.

[00:00:22 ] Damian: Now Dave developed the idea of SMB Media Lab, which leans on the first party data from the millions of people who use QuickBooks, and it provides small businesses with the intelligence they need to reach their customers across channels like audio and CTV.

[00:00:38 ] Ilyse: We start out by asking Dave about the origins of S& D Media Labs.

[00:00:42 ] : It really came from honestly my personal frustration, in trying to reach SMBs for my, what I'm calling my day job. So, I was hired four years ago, at Intuit to lead QuickBooks acquisition marketing. And I actually still hold that position today. Um, my entire career has [00:01:00 ] been consumer brand. So I was with North Face before this.

[00:01:02 ] Um, spent a lot of time agency side, working on a variety of clients across CPG and e comm retail. And when I got to, into it, um, I tried to essentially apply the same data sources and tactics that worked very well for me in the, in the consumer world. And it was met very quickly with the reality that SMB data is very hard to find, and when you do find it, the accuracy is just not great.

[00:01:28 ] So, you know, I have a friend, um, that works in the agency that me that at the top you have enterprise level data, which is pretty high quality at the bottom. You have your consumer data, which is abundant and high quality, but between there's a big void and that's pretty much where all S and B data lives.

[00:01:49 ] Um, so it started off. Kind of, it's just a joke internally that I really wish there was a company like QuickBooks that I could partner with and [00:02:00 ] buy media through that would allow me to find not only the scale of audiences that Intuit has, but also the depth of knowledge about how those, how those businesses are operated and run.

[00:02:10 ] And then that joke kind of became a realization that it is a need for other advertisers that Intuit could very much fill and very uniquely fill as well. Just considering kind of. The breadth and depth of information that we have, um, on, on our small business owners. Um, so that was the start of it. Um, but of course, you know, we wanted to make sure that we were doing it in a way that was beneficial to our customers, um, and done in a privacy safe way.

[00:02:38 ] So that was kind of the start of the journey was just the realization that we had something that advertisers would be interested in, but we also wanted to make sure that it was something that benefited our customers as well.

[00:02:47 ] Damian: That void that you talk about in the middle between enterprise level data and consumer data is quite surprising, isn't it? That there wasn't anything there for those small businesses. I know that 99 percent of all businesses are [00:03:00 ] SMBs. So that's a huge, uh, yeah, that's a, that's a huge amount of, uh, data that's not being used.

[00:03:09 ] So was it a surprising moment when, when, when you go, when you saw that and you thought, Oh, this is an opportunity.

[00:03:15 ] Dave: Yeah, I, you know, there are small pockets of data where you can get very narrow in, it's just not scalable. So that was the sort of challenge. So you can go to a lot of individual professional sites. But the reality is the world of media is not built around the business that you run, it's built around you as a person.

[00:03:31 ] So stitching those two parameters together, because, you know, as QuickBooks growth, We're looking for specific types of business problems. And, you know, a lot of these small business owners are not active on professional networks. Um, if they have profiles there, they're not looking at them on a regular basis or updating them.

[00:03:51 ] Um, so they, they kind of become. In the shadows, like the S and B part of the data and the targeting capabilities and the need state from the business that they [00:04:00 ] run sits behind their sort of consumer profiles. So I think it was a surprise when I first joined, but. Logically, after a little while, I was like, okay, that makes sense of why we're not able to find the business traits and qualities that we are able to.

[00:04:18 ] Damian: Yeah, that makes sense. The

[00:04:20 ] Ilyse: Now, how would you go about like describing the value of these small businesses and the data that their advertisers are trying to use to reach this audience?

[00:04:31 ] Dave: Yeah, um, so great question. And there's, there's a couple of different layers of sort of knowledge that we have on our, on our customer base, and we're not unlocking all of those just yet. So we want to, again, going back to the want to do what's right by our customers, we want to make sure that. All the information that we're collecting is something that they would expect us to collect, that they have full control over their ability to participate in this, and that we're only partnering with advertisers that, um, you know, have the best [00:05:00 ] intent for, for our customers.

[00:05:02 ] With that, uh, we are layering on top of ad buys, data that seems to already exist in the market, but is much more accurate. So that was one of the sort of uphill battles that we've had in the early stages of this. So things like industry, age, revenue, employee count, these are things that on the surface appear to exist in other third party data sources, but You know, again, being on the other side of the buying of this one, I see how wildly off some of those data sources can be and the assumptions that they have about a small business.

[00:05:34 ] So what we're adding on to that is just a very, very, um, deterministic one to one knowledge and accuracy that didn't exist. So we eliminate a lot of waste that comes with using some of the other data providers or even just kind of doing broad market advertising. So that's kind of the main value prop.

[00:05:54 ] That said, we are working with our legal and privacy team. And our [00:06:00 ] executive sponsor is actually the head of privacy. So that should tell everyone a little bit about how serious we're taking this. But we're also thinking about with our customers, what value can we add to them if we continue to go into what we're calling transactional type data, if we're able to go the next step deeper.

[00:06:16 ] And the reason for that is every business. on the surface may look the same in an industry size employee count, but how they run their business could be very different. So if you're a construction company, that's in the same region as another construction company, roughly same revenue, roughly same employee count doesn't mean that you invest completely different in marketing.

[00:06:37 ] And you may be, Think about your supply chain very differently. What that allows us to do is actually find need states for our customers and be able to pair them with the advertisers that might be able to serve, um, solutions for them in those needs states. And so that's kind of the next wave that we're working on.

[00:06:52 ] It's something that we haven't done yet, but we're hoping to unlock for our advertisers.

[00:06:57 ] Ilyse: Yeah, that's definitely a good example. [00:07:00 ] Um, I feel like, In a, such a new kind of company like this, and I know you refer to you guys as like a retail media network, although you're not exactly a retail media, um, so it's, it's, it's definitely hard to kind of describe, I would assume, to other B2B businesses exactly what to do and how your like first party data And you essentially use QuickBooks, um, primarily, right?

[00:07:27 ] Um, how they can use that data to their advantage. Is there, like, another example that you can give how, um, advertiser would use your, your media network in order to, like, reach their audience? Heh

[00:07:43 ] Dave: you mentioned that, that, you know, we've, we've been using the term retail media network, but we're, we're very much not a retail media network. So we do not have owned and operated inventory and that's by design. Um, you don't start a business because you're passionate about bookkeeping in most cases.

[00:07:55 ] Um, so we're leaning into as a company, AI and, and, [00:08:00 ] um, automation to make sure that we're trying to reduce the amount of time that That a customer has to spend in our platforms in order to, um, to get their work done. So throwing ads in there will slow that down. It's not something that, you know, someone that's already paying for subscription would, would want to have that said, there are potentially ways that we've been looking at that. Provide additional value to that. That said by not having owned and operated, I think that we accidentally fell into what I'm calling kind of the next wave of retail media network. So we are more of an audience network that can be layered on to any part of your ad buy that's programmatic. So we have partnerships with the trade desk