Hello and welcome back to Parity at Rs, the retail podcast. I'm joined by the CEO of Amperity, Barry Padgett. Thank you so much for giving us the time to to talk to us. There was a group of people that need to usher out of the way, so I can imagine it's been non-stop for. You. It's been fantastic. I can't wait to go home and sleep for three days for it feels like same for you though, I'm sure. Well, yeah. Well, we started with retail safaris on Saturday and Friday, so we ran anyway.
We were at CES last week in Vegas. Ohh like. In RF this week. And so it show season. Pursue. Arts. So listen, I think for those who don't know and piracy, if you don't mind just giving us a snapshot to your journey to NRF. And then my first question would be like what's been the one thing that retailers come to ask? Yeah, you know, I know ask Tamara, we were talking about retail. You've actually blown away by the number of yeah, which tells us that still running. So but anyway, yeah.
So tell me, what's the birds, he How did you get here? And what's Hall? Sure. So we are in the data unification business and the easiest way to describe it I would say is you know whether you have a project that's a marketing project and ecom, so loyalty, AI, usually you can trace back whether those projects are successful or not down to the quality of your customer data and your ability to actually unify that customer data and feed it into those systems.
So the easiest way to maybe describe is, I think over the last several years most people have thought about that problem as a vitamin. Hey, it would be nice to kind of Turbocharge our marketing tools or turbocharge our paid media and this does work or maybe feed our AI projects. I'd say that the pendulum has shifted a little bit to be less vitamins and more medicine given that a lot of those projects are
broken now. And so there's a lot of things between security and compliance, cookies, AI, that's driving retailers to embrace their first party data, that data organised so they can go in the server. I I think having voting technology, I think people take for granted the fact that you need your data to be in some shape. Or form. Before you can get the output. Yeah, is that right? Am I right? Yeah. Or is that like? No, I think you're you're spot on.
I think the difference maybe that we're experiencing right now is most folks had a fairly siloed view of like I wanna get my marketing data organised in my marketing. Yeah, I'm gonna get my loyalty data organised in my loyalty plan. I think that the overriding demand now both for us as consumers as well as with the systems we're deploying, there has to be interoperability, there has to be compatibility between those datasets.
And that's I think where we're seeing everyone state to now is to unify this data, eat and hydrate all my systems with one single view of the customer, whether it's because of again control or compliance, GDPR in Europe, CDA out weren't you? Yeah. Or because I'm trying to train a large language model AI projects, I have to get the data right. But those AI projects really amplify whether you have good quality data or you. Don't. Yeah, so I'm a retailer.
I've invested heavily in trying to solve this problem and it's it's going horrible. Where do I start? Yeah, because what I often see is this sort of well and Bush from imagine finance from marketing merchandising. Yeah. And pension. It feels like technology is trying to solve. Yeah, right. The tech they don't really understand merchandisers data needs are. Different from. The ERP. System that's curious. How did you help?
Yeah, solving. Well, it's it's very similar to what we've been thinking about the CRM category. You know, 20 years ago it was cool to build your own CRM. That would be a tough project. Yeah, it would be hard to pitch a build it yourself CRM project. I feel like this customer data and the customer data category is also purely new in the sense that most retailers have been trying to build this unified view for a long, long time using lots of tools, ETL and the dupe
data lakes. And so I feel like the overwhelming sentiment now is that there's a, there's a data supply chain count in that we can't get that data supply chain unified and built. And so a lot of companies are now looking to off the shelf providers like in Parity will come in. We have a great sort of set of models that are all machine learning and AI based and it takes the pressure off of the retailer through to those teams
and building a foundation. So they can use that foundation to go do all the cool things they want to do like they'll propensity models, density, sure, customer lifetime are you eat all their downstream tools serve their internal customers. And so I feel like no shame on companies trying to build this themselves. We're just now reaching the way where there's actually tooling out there to go help.
Whether you want to do that directly with a company like Impurity, yeah, or use amperity tech within a lake house architecture like Databricks or Snowflake, these are the kinds of things that are are now available to tech teams, retailers for the very first time. Those two questions, yeah, is something that surprised you as an outcome from one of your customers that has sort of gone on the journey with. Yeah, and then? Yeah, and. Then the second one.
I'd love your vision of future. Where do you think? With AI and everything? What do you think we're going? Yeah. So on the first question, say a surprise for me, Brooks running, who's here at the show somewhere. They're a great customer of Ann Parity. They're based in Seattle. We happen to be based in Seattle too. We have a lot of great Seattle brands, Alaska Airlines, sports
from T-Mobile, Brooks running. One of the things I love most about that story was they did the data unification project they to sort of retention programme for existing customers new acquisition eating all their downstream tools, my favourites that bit was we got a blurb back from Melanie Allen who's the CMO there and I wanted to share this with you which is well customer service reps. So people that are calling support for some reason are return or refund.
And the customer service quote was with with what's going on with our data now and able to close pieces or the customer can fully explain what their problem. And the reason is when someone's calling customer service. Now that customer service reps like Ohh Alex is calling and it looks like he bought 2 things. You returned one on Monday, Wednesday is probably calling to see where the refund is. Yeah. So when you call us, yes. Thanks for being a customer. It looks like you bought 2 pairs
of shoes, your return one. Do you have a question on size or you asking about the refund and you're like, yeah, that's why I'm falling and so unintended, unintended to get that customer service quote. But the fact that you can drive internal employee experience is given that our employees want to serve the customer, they desperately want to make great customer impression and giving them the data and the tools you don't do that is fantastic, so. For so long.
Totally. And then your second question in terms of where we're going. I think what you're going to find at least in our perspective in the customer data space, you're going to find most companies have really nicely to large language model that's bespoke to their customers, their customer tooling ecosystem of technology they use, their
semantics and preferences. And you'll find that you'll be able to plug in all these off the shelf Pi tools you know into your large language model and really drive personalization. I know it's been a a a goal for so long personalization at scale. Now listen like putting someone's correct person name in an outbound e-mail is not personalization. Understanding that you're the head of a household and you buy for your kids and you they for a
spouse and you buy for yourself. And really understanding what that sentiment is and your goal and purpose for the next engagement is, that's where AI is going to be. Great. Takes a large language model. Tune to your data and you have that customer data built that foundation unified before you can trade it. It was actually one of the talks. When someone signs up to your loyalty programme and makes themselves digitally pressed for you, they want more.
That's right, I've already agreed all the GDPR things you've been. Anyway, I carry on soldier, here, Thank you so much for giving me your time. And of course you are because and I look forward to seeing you guys. Great. How are you internationally? Like are you? Officially. US based their new. Offices in Melbourne, Australia and get served by these and in each pack regions from there opposite in London that serves how you're. OK, yes. Yeah. Yeah. Thanks, Alex.