Latest / The Retail Podcast / Data Unification: Retail's New Power Play

Transcript

Data Unification: Retail's New Power Play · The Retail Podcast

• 0:00
  Hello and welcome back to Parity at Rs, the retail podcast.
• 0:06
  I'm joined by the CEO of Amperity, Barry Padgett.
• 0:10
  Thank you so much for giving us the time to to talk to us.
• 0:14
  There was a group of people that need to usher out of the way, so
• 0:17
  I can imagine it's been non-stop for.
• 0:19
  You. It's been fantastic.
• 0:21
  I can't wait to go home and sleep for three days for it
• 0:25
  feels like same for you though, I'm sure.
• 0:27
  Well, yeah. Well, we started with retail
• 0:28
  safaris on Saturday and Friday, so we ran anyway.
• 0:32
  We were at CES last week in Vegas.
• 0:35
  Ohh like. In RF this week.
• 0:36
  And so it show season. Pursue.
• 0:38
  Arts. So listen, I think for those who
• 0:40
  don't know and piracy, if you don't mind just giving us a
• 0:44
  snapshot to your journey to NRF. And then my first question would
• 0:50
  be like what's been the one thing that retailers come to
• 0:53
  ask? Yeah, you know, I know ask
• 0:55
  Tamara, we were talking about retail.
• 0:57
  You've actually blown away by the number of yeah, which tells
• 1:01
  us that still running. So but anyway, yeah.
• 1:04
  So tell me, what's the birds, he How did you get here?
• 1:07
  And what's Hall? Sure.
• 1:08
  So we are in the data unification business and the
• 1:11
  easiest way to describe it I would say is you know whether
• 1:14
  you have a project that's a marketing project and ecom, so
• 1:18
  loyalty, AI, usually you can trace back whether those
• 1:23
  projects are successful or not down to the quality of your
• 1:26
  customer data and your ability to actually unify that customer
• 1:29
  data and feed it into those systems.
• 1:31
  So the easiest way to maybe describe is, I think over the
• 1:34
  last several years most people have thought about that problem
• 1:37
  as a vitamin. Hey, it would be nice to kind of
• 1:39
  Turbocharge our marketing tools or turbocharge our paid media
• 1:44
  and this does work or maybe feed our AI projects.
• 1:47
  I'd say that the pendulum has shifted a little bit to be less
• 1:49
  vitamins and more medicine given that a lot of those projects are
• 1:53
  broken now. And so there's a lot of things
• 1:55
  between security and compliance, cookies, AI, that's driving
• 1:59
  retailers to embrace their first party data, that data organised
• 2:04
  so they can go in the server. I I think having voting
• 2:08
  technology, I think people take for granted the fact that you
• 2:11
  need your data to be in some shape.
• 2:13
  Or form. Before you can get the output.
• 2:15
  Yeah, is that right? Am I right?
• 2:17
  Yeah. Or is that like?
• 2:19
  No, I think you're you're spot on.
• 2:21
  I think the difference maybe that we're experiencing right
• 2:23
  now is most folks had a fairly siloed view of like I wanna get
• 2:27
  my marketing data organised in my marketing.
• 2:30
  Yeah, I'm gonna get my loyalty data organised in my loyalty
• 2:33
  plan. I think that the overriding
• 2:36
  demand now both for us as consumers as well as with the
• 2:39
  systems we're deploying, there has to be interoperability,
• 2:43
  there has to be compatibility between those datasets.
• 2:46
  And that's I think where we're seeing everyone state to now is
• 2:49
  to unify this data, eat and hydrate all my systems with one
• 2:54
  single view of the customer, whether it's because of again
• 2:57
  control or compliance, GDPR in Europe, CDA out weren't you?
• 3:01
  Yeah. Or because I'm trying to train a
• 3:02
  large language model AI projects, I have to get the data
• 3:06
  right. But those AI projects really
• 3:09
  amplify whether you have good quality data or you.
• 3:12
  Don't. Yeah, so I'm a retailer.
• 3:14
  I've invested heavily in trying to solve this problem and it's
• 3:19
  it's going horrible. Where do I start?
• 3:21
  Yeah, because what I often see is this sort of well and Bush
• 3:24
  from imagine finance from marketing merchandising.
• 3:28
  Yeah. And pension.
• 3:29
  It feels like technology is trying to solve.
• 3:31
  Yeah, right. The tech they don't really
• 3:33
  understand merchandisers data needs are.
• 3:36
  Different from. The ERP.
• 3:38
  System that's curious. How did you help?
• 3:41
  Yeah, solving. Well, it's it's very similar to
• 3:44
  what we've been thinking about the CRM category.
• 3:47
  You know, 20 years ago it was cool to build your own CRM.
• 3:51
  That would be a tough project. Yeah, it would be hard to pitch
• 3:56
  a build it yourself CRM project. I feel like this customer data
• 4:01
  and the customer data category is also purely new in the sense
• 4:05
  that most retailers have been trying to build this unified
• 4:08
  view for a long, long time using lots of tools, ETL and the dupe
• 4:12
  data lakes. And so I feel like the
• 4:15
  overwhelming sentiment now is that there's a, there's a data
• 4:21
  supply chain count in that we can't get that data supply chain
• 4:26
  unified and built. And so a lot of companies are
• 4:28
  now looking to off the shelf providers like in Parity will
• 4:32
  come in. We have a great sort of set of
• 4:34
  models that are all machine learning and AI based and it
• 4:37
  takes the pressure off of the retailer through to those teams
• 4:41
  and building a foundation. So they can use that foundation
• 4:43
  to go do all the cool things they want to do like they'll
• 4:45
  propensity models, density, sure, customer lifetime are you
• 4:49
  eat all their downstream tools serve their internal customers.
• 4:52
  And so I feel like no shame on companies trying to build this
• 4:56
  themselves. We're just now reaching the way
• 4:58
  where there's actually tooling out there to go help.
• 5:00
  Whether you want to do that directly with a company like
• 5:02
  Impurity, yeah, or use amperity tech within a lake house
• 5:06
  architecture like Databricks or Snowflake, these are the kinds
• 5:09
  of things that are are now available to tech teams,
• 5:12
  retailers for the very first time.
• 5:15
  Those two questions, yeah, is something that surprised you as
• 5:18
  an outcome from one of your customers that has sort of gone
• 5:22
  on the journey with. Yeah, and then?
• 5:25
  Yeah, and. Then the second one.
• 5:27
  I'd love your vision of future. Where do you think?
• 5:29
  With AI and everything? What do you think we're going?
• 5:31
  Yeah. So on the first question, say a
• 5:34
  surprise for me, Brooks running, who's here at the show
• 5:37
  somewhere. They're a great customer of Ann
• 5:39
  Parity. They're based in Seattle.
• 5:40
  We happen to be based in Seattle too.
• 5:42
  We have a lot of great Seattle brands, Alaska Airlines, sports
• 5:45
  from T-Mobile, Brooks running. One of the things I love most
• 5:48
  about that story was they did the data unification project
• 5:52
  they to sort of retention programme for existing customers
• 5:55
  new acquisition eating all their downstream tools, my favourites
• 5:59
  that bit was we got a blurb back from Melanie Allen who's the CMO
• 6:03
  there and I wanted to share this with you which is well customer
• 6:06
  service reps. So people that are calling
• 6:08
  support for some reason are return or refund.
• 6:11
  And the customer service quote was with with what's going on
• 6:15
  with our data now and able to close pieces or the customer can
• 6:19
  fully explain what their problem.
• 6:22
  And the reason is when someone's calling customer service.
• 6:25
  Now that customer service reps like Ohh Alex is calling and it
• 6:28
  looks like he bought 2 things. You returned one on Monday,
• 6:32
  Wednesday is probably calling to see where the refund is.
• 6:34
  Yeah. So when you call us, yes.
• 6:35
  Thanks for being a customer. It looks like you bought 2 pairs
• 6:37
  of shoes, your return one. Do you have a question on size
• 6:40
  or you asking about the refund and you're like, yeah, that's
• 6:42
  why I'm falling and so unintended, unintended to get
• 6:45
  that customer service quote. But the fact that you can drive
• 6:48
  internal employee experience is given that our employees want to
• 6:52
  serve the customer, they desperately want to make great
• 6:54
  customer impression and giving them the data and the tools you
• 6:58
  don't do that is fantastic, so. For so long.
• 7:01
  Totally. And then your second question in
• 7:02
  terms of where we're going. I think what you're going to
• 7:05
  find at least in our perspective in the customer data space,
• 7:08
  you're going to find most companies have really nicely to
• 7:12
  large language model that's bespoke to their customers,
• 7:16
  their customer tooling ecosystem of technology they use, their
• 7:19
  semantics and preferences. And you'll find that you'll be
• 7:22
  able to plug in all these off the shelf Pi tools you know into
• 7:26
  your large language model and really drive personalization.
• 7:29
  I know it's been a a a goal for so long personalization at
• 7:34
  scale. Now listen like putting
• 7:35
  someone's correct person name in an outbound e-mail is not
• 7:38
  personalization. Understanding that you're the
• 7:41
  head of a household and you buy for your kids and you they for a
• 7:43
  spouse and you buy for yourself. And really understanding what
• 7:46
  that sentiment is and your goal and purpose for the next
• 7:49
  engagement is, that's where AI is going to be.
• 7:51
  Great. Takes a large language model.
• 7:53
  Tune to your data and you have that customer data built that
• 7:56
  foundation unified before you can trade it.
• 7:58
  It was actually one of the talks.
• 7:59
  When someone signs up to your loyalty programme and makes
• 8:02
  themselves digitally pressed for you, they want more.
• 8:06
  That's right, I've already agreed all the GDPR things
• 8:09
  you've been. Anyway, I carry on soldier,
• 8:12
  here, Thank you so much for giving me your time.
• 8:14
  And of course you are because and I look forward to seeing you
• 8:18
  guys. Great.
• 8:19
  How are you internationally? Like are you?
• 8:21
  Officially. US based their new.
• 8:23
  Offices in Melbourne, Australia and get served by these and in
• 8:26
  each pack regions from there opposite in London that serves
• 8:29
  how you're. OK, yes.
• 8:31
  Yeah. Yeah.
• 8:32
  Thanks, Alex.