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.