January 19, 2024 • 30 mins
Unlock the secrets of AI's sweeping revolution in the retail world with Ricardo Belmar from Microsoft and Jamie Tenser of VSN Strategies. As we wrap up NRF 2024's electrifying discussions, we share ground-breaking insights about how AI is no longer just futuristic buzz but a practical powerhouse reshaping retail. Imagine store associates liberated from mundane tasks, thanks to AI's magic, and the game-changing evolution of machine learning to sophisticated generative models, all dissected in this episode.
Jamie Tenser & Ricardo Belmar, delve into whether smaller networks can stand strong against the titans of trade. We analyze the seismic shift from traditional advertising to the dynamic world of retail media and its redefining influence on the industry's future. Get ready for a strategic exploration of how retailers balance their merchandising finesse with the burgeoning demand for promotional prowess in the age of retail media networks.
RetailWire is the retail industry's premier source for news, analysis, and discussion. With a focus on the latest trends, technology, and consumer behavior, RetailWire provides a platform for industry experts and thought leaders to share their insights and perspectives. Whether you're a retailer, supplier, or service provider, RetailWire is your go-to destination for staying informed and ahead of the curve.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:05):
Welcome everyone to another Retail Wire Live.
We are here live at the finalday at NRF 2024.
I'm Ricardo Balmar.
I lead partner marketing forretail and consumer goods in the
Americas at Microsoft and I amhere with good friend Jamie
Tensor.
Speaker 2 (00:21):
Greetings all.
I'm glad to be back here.
At NRF Jamie Tensor, I run alittle consultancy called VSN
Strategies.
It's my pleasure once again tobe with Ricardo I think
sometimes as a partner in crimetrying to bring to you a
condensed summary of what thethings we thought were important
from this show.
There are many, many and we'regoing to try really hard to boil
(00:43):
it down to the richest syrup ofmeaning that we possibly can.
So bear with us.
There's a lot to say here, butI think if you haven't been at
the show, or even if you have,there's a good chance.
You didn't get to seeeverything.
I certainly didn't.
Speaker 1 (00:58):
Yeah, that's true.
We probably should start offwith the one sort of obvious
thing that everyone knows wasinevitable to be talked about at
the show, and that's all thingsrelated to AI.
It was all over the agenda.
Speaker 2 (01:11):
AI is everywhere, without a doubt.
Speaker 1 (01:13):
Without a doubt.
I think maybe some of the thingsthat I think we were talking
earlier we agreed.
I feel like, despite the hypeand there's no avoiding the fact
that there's a lot of hype likethat there always is at the
latest technology, at every NRFI came away thinking that there
was a bit of a balance or maybea counterpoint to that, that
there were plenty of examples oftangible things people have
(01:35):
already done with AI over thepast years and a willingness to
talk about it and give examples.
You know there were somesessions.
Even I saw retailers talkingabout something they did, for
example, with AI to augment thecapabilities of their store
teams, where they weren'tlooking to replace people but
they were looking to make thework easier and trying to
eliminate some of the mundanetasks, and retailers had
(01:58):
examples of that.
I think I even heard someretailers say they had KPIs that
they were targeting.
One return to session that anAI session I was at said they
were trying to save every store,associate an hour of time every
week with the use of these AItools at a minimum and they felt
that they were achieving thosetargets.
Speaker 2 (02:16):
Well, I agree with you.
It feels to me like we've gonefairly swiftly from the science
fiction stories of AI's takingover the world and jobs
disappearing in thousands to apractical conversation about
well, here's a technology thatactually is coming of age and
that we're able to start tobuild it into some of the
(02:37):
practices and solutions that weuse to run our stores every day,
make decision making better,eliminate I like to call it junk
work, but let's say tasks thatare repetitive, dreary and that
maybe we don't want our smartestpeople spending their time on,
or even our store people, forthat matter that can easily be
automated.
(02:58):
The other thing that comesacross here, as you said, in
certain I don't want to callthem point solutions, but in
specific areas of practice,there are machine intelligence
components that have been inplay for a long time, and we've
seen examples in things like,you know, inventory, forecasting
and supply chain.
Now, these are I'll call themspecial purpose machine learning
(03:20):
tools.
They are AI, if you want to usethe technical definition, but
what they are not is they arenot large language models, the
chat, gpt type of generative AIs, which I think we've crossed
the threshold on in the lastyear and a half or so.
Yeah, it's all artificialintelligence, but it's a
different nature, maybe adifferent animal.
(03:40):
Now, that's where the hypecycle seems to have come from
lately, and I'm kind of gladthat it seems like we're moving
through that, at least in ourindustry, a little bit, a little
bit briskly, and getting backto practical conversation.
Speaker 1 (03:52):
That's right, and even then, I think some of the
that, jen, you're right, that'swhere the probably the majority
of the hype has been, becauseit's the most impressive when
you see a demo of technologiesright.
It's truly creating things thatare in a manner of moments that
would otherwise take you hours,not longer, to create, and even
though, as I've seen in theexample, I think Tractor Supply
(04:13):
has been here, I was talking tofolks from there as well and
they've leveraged those toolsagain and something that they've
handed to their storeassociates where they can
leverage those language modelsto just ask natural questions
when they need to ask.
So there was another retailerwho talked, in fact,
interestingly enough, that inorder to put those tools in
front of or in the hands oftheir store associates, they
(04:33):
needed to retrain them, becauseeveryone now instinctively knows
how to search by keywords, butwhen you're working with these
models, that actually doesn'thelp you.
Speaker 2 (04:43):
It's not the same know-how.
Speaker 1 (04:45):
You need to really use a natural question.
People wanted to do a productsearch in a store because they
have a customer asking where isthis particular power tool?
You don't just search for thename of the power tool as a
keyword.
You would ask the AI where do Ifind power tool ABC in the
store?
And then you would get ananswer and that required some
(05:05):
retrain.
Speaker 2 (05:06):
Well it does.
I remember when we all startedto use search for the first time
back in the previous millennium, we had to learn how to do that
with some effect, or wecouldn't find the results.
I think today, sometimes, whenwe interact with chatbots, we
don't phrase our questions right, we get frustrated, we can't
get the right answers and as themore powerful AI is coming to
play, it's a skill, it's alearnable skill.
(05:29):
I really think that for storeassociates and people in
management, it's not going to beall that hard to learn this
once a little bit ofconsciousness is raised.
And remember, the machineslearn back, so they're going to
learn our limitations too andbecome better and better at
understanding what we're tryingto get at.
So, when it comes to answeringa question, whether it's about
(05:49):
merchandising a store, whetherit's about, perhaps, a
merchandise plan that anexecutive is trying to work out
for the next selling period ineach of those instances there
are going to be better ways toget at the answers, and that's
something to look forward to.
I think I'm a big antagonistfor anything that is junk work.
(06:15):
Right, and you can automate itand you can trust the automation
.
Can we set that aside?
Can we set that 80% of testaside and then free our minds,
free our hands, if necessary, todo things that really add value
and, ultimately, moresatisfying, make it a better job
?
Speaker 1 (06:31):
Yeah, I agree, and I think that's true for again.
So many examples I don't knowthat I could list them all, but,
like you mentioned earlier,some examples are related to
supply chain and forecasting,which aren't necessarily new
applications of data and seed,but I think that the difference
I see is more open conversationabout it.
For retailers, more discussionabout the benefits and what any
(06:52):
individual retailer is gaining,and that as an example to why
others should be using it andthat's being promoted a lot.
Speaker 2 (07:00):
I think it's also important to distinguish between
those large language model, thestuff that's gotten the kind of
general media hype, the openplatforms for artificial
intelligence that essentiallythat protect nothing, that scoop
up everything For a businessapplication.
That's not the place tonecessarily set up your
(07:22):
artificial intelligence tool.
There's lots of reasons to keepa walled garden, so to speak,
around your own instance, and ifyou have an AI platform that
you're using to drive whetherit's decision making or whether
it's merchandising tasks or anynumber of other applications
(07:42):
inventory, forecasting, etcetera that needs to stay in
house.
A short while ago, that wasbeyond comprehension that we
could possibly afford and enablethat within organizations.
Now it doesn't seem far-fetchedat all.
In fact, it's been happening insmall ways for a while.
Now it's happening in largerand more exciting ways.
Speaker 1 (08:04):
And I think there were a good number of maybe not
as many, but a good number ofconsumer facing examples and
applications.
There was one session wheresome from Walmart was talking
about how they added it, andagain it was sort of a search
enhancement, so adding into theWalmart app the ability to ask a
natural question aboutsomething that you were planning
, not a product-specificquestion, but the example they
(08:27):
used on stage is what if there'syour a parent trying to plan a
birthday party for your daughterand your daughter likes
unicorns?
So instead of individuallysearching for party favors that
have unicorns, like we wouldnormally do, you would just ask
the Walmart app what do I needto plan a unicorn-themed party
for my daughter?
And then it would return backsearch results to show you all
(08:49):
of those elements.
Another example was I'mplanning a Super Bowl party,
what do I need?
And so the search results cameback from anything ranging from
grocery items to a new bigscreen TV.
Speaker 2 (08:59):
Even I know you need avocados, exactly so which is?
We're going to see thisconstantly.
We're going to learn as endusers, we're going to learn to
interact with it better andthey're going to get smarter at
understanding the way weinteract with them.
So one of the applicationswhere machine intelligence has
been in play for some time hasbeen in inventory accuracy,
(09:21):
inventory forecasting.
So can I make a clever segue alittle bit into one of the other
points?
That is a conversation thatwe've heard more of from more
directions, I think, certainlyfrom the vendor side of the
question here.
I think inventory accuracy hasbeen certainly a discussion for
some time.
It's a source of loss Both overand under inventories in
(09:47):
perishable products, anythingthat's perishable or that can
expire or go out of fashion.
You don't want too much of it,but you certainly don't.
You do want to have enough thatyou can satisfy the demand, and
it's no longer good enough torely on instinct to do that.
So the fast-moving consumergoods world has been using
various forms of inventorymanagement and forecasting and
(10:10):
ordering tools for quite a whileit could be 17, 18 years, if
not longer and they've seen thebenefits from it.
They, I think, have found newways to capture information,
including the shelf status andother essential parts of the
equation, and so they can getmore and more accurate In the
(10:32):
soft lines, which, I have toconfess, because I really am a
FMCG type of guy I still find itmysterious and awe-inspiring
that bets can be made on apparelorders 18 months out, sometimes
from a factory very far away,in anticipation of a certain
amount of sell-through that willhappen during a holiday season.
(10:53):
It's a marvelous mystery.
It does look like a place maybewhere a little machine
intelligence might help narrowthose error bars and the end of
the day, if you can make themark down quantity is lower,
then that's a smashing win.
So it seems like that'sdiscussion.
It's more often in thediscussion.
A few years ago we didn't hearthat that story, inventory
(11:15):
conversation quite as much.
Now this seems to be a reallygreat emphasis on it and I think
it's connected to the interestin fulfilling store orders that
are received online as well.
So that feels like it'smaturing a little.
It's becoming part of theregular vernacular for the
(11:36):
industry and it definitelyreferences to it all over the
exhibit floor.
Speaker 1 (11:42):
I think that maybe takes us also to into
discussions that have beenhappening around returns when
returns?
are sealed in a very top themethat we're hearing more and more
of.
It kind of ties into both whatyou're pointing about the
inventory management and I thinkalso what we were saying
earlier about AI, and is therean application that makes sense
for AI?
I know there have been somesolutions I saw there where the
(12:03):
focus was on AI helping you.
I describe it as redefine howyou position the product,
because the idea then is toprevent the need for a return,
because once the items purchasedright and what do you do really
to control the consumer they'regoing to return it.
They're going to return it.
Speaker 2 (12:19):
It sets up a stream of events that you just can't
stop.
Speaker 1 (12:22):
You can control it up until that moment of purchase
and to make sure that it's theright purchase decision without
the need for doing things whereyou're doing a.
I don't know, maybe it's theright thing.
Speaker 2 (12:32):
I'll buy it anyway because I know I can return a
kind of situation which you'retrying to avoid.
Speaker 1 (12:36):
It's the retailer and maybe there's an application
that AI tools can help there.
Speaker 2 (12:40):
Well, with garments, getting the fit right is a key
element.
And there are lots of attemptsand I think some work better
than others, but they're tryingto incorporate tools that the
shopper can use to get a betteridea about how they will look in
a given purchase.
We see it for eyeglass frames,we see it for you know, there's
a company I've been looking atwhere you can put in a bunch of
(13:01):
metrics and get a custom madesuit for not that much money.
This kind of thing depends onour artificial intelligence to
drive that, and the hope, ofcourse, is that there'll be much
less likely to be returned,because each time a return is
authorized, a whole cascade ofevents has to happen that the
(13:22):
retailer would rather not haveto bother with and pay for.
It's worth noting that one ofthe major sponsors here this
year is a company called GoTRG.
Their logo is all over the show.
And what do they do?
They help retailers managetheir returns flow.
So it is a big business.
Every time you shave that downby a percentage point, money is
(13:43):
dropping to the bottom line, butit's also a reflection about
getting it right for the shopperin the first place.
So there are, I think, a hostof different places where
process and experienceimprovements.
They're trying to shave alittle bit here, improve a
little bit there, andcollectively it adds up.
(14:04):
But returns cost a lot of moneyand there's a question of what
do you do with the product whenit's received.
And there are some productswhere there's no point in even
authorizing the return.
Yeah, and I've had thatexperience I don't know if you
have where Amazon has said don'tbother sending back that part
(14:24):
you ordered by mistake.
It was an honest error.
It's cheaper for us if you justkeep it.
You shouldn't do that too oftenand there are probably people
who abuse that.
But that conversation, I meanthat's going to be going on for
a long time.
But it does connect to anotherkind of process which is a
little more sinister, and thatis what happens when somebody
(14:47):
stole the item that they'retrying to return.
And is that a good segue intothe loss prevention question?
Returns are maybe a form ofloss from the retailer, but it's
benign in its intention usually.
And there's a whole anothersinister thing that happens when
an entire store is emptied by agroup of people who next day
(15:10):
are attempting to bring thoseitems back for return elsewhere
or send them back.
That's ugly and it's gotten alot of headlines in the past
year.
So shoplifting it makes good TVimages, I'll say that.
But it's not the only form ofloss, that's the thing.
(15:33):
In fact it's not even thelargest.
Speaker 1 (15:35):
I actually think that , given the recent things that
you have to interact, there wasmaybe a lightning.
I think a bit of a tone of howsevere that is.
On the show of Florida it wasstill being discussed and still
being a real problem.
Maybe it was a littleoveremphasized in the past year
and so it's felt a little moresubdued, I think, in the
(15:56):
discussion.
Speaker 2 (15:57):
Well, more measured it ain't nothing, that's clear
about that.
It matters, stores in certainlocations are forced to take
remedial steps to reduce theft.
It actually undermines theexperience of the shopper, which
is which is pretty sad.
And I think about certain drugstores in Manhattan where
(16:18):
everything worth buying isbehind loose site doors and you
can't purchase it withoutsomebody.
If you can find them to comewith a key, that's.
That's a real Disincentive forpurchasing.
So it's not just costing thoseretailers the the cost of those
remedial Activities, it'scosting them actual sales and
(16:39):
you kind of wonder what's thearithmetic here In terms of what
we save.
But it also sends a messagethat I was discussing it through
someone today.
It makes me as a shopperwalking to that store and think
this is not a safe place.
Right, that's a terrible thingto do to the reputation of the
retailer and and, by the way,the news stories that we've seen
(17:00):
it's kind of the same thing.
You know I'm right, I don'twant to walk into a jewelry
store where any minutesomebody's gonna back in SUV
into the front and Try and steal, you know, break into the
counter.
I know that's, that's hyperbole, but it has happened.
No, so the loss preventiondiscussion is big.
We know there have beenseparate events about it.
(17:21):
One conversation I had was aboutwhether RFID tagging, which is
used principally these days forinventory management, could also
help with with that problem oftheft and what happens to
products after they're stolen,and Might even help the returns
process too.
They are interconnected, butRFID seems to be Moving faster
(17:47):
to that tipping point where it'sstarting to make sense for many
not all, but many types ofproducts.
The tags are less expensive.
There are, there are fabrictags that can be sewn into a
garment invisibly.
There are, and there are thereare Detectors that can be used
for checkout.
For a check out, what someone Iknow described the bins in
(18:09):
uniclose stores where you justthrow a bunch of garments in.
It reads the tags they get,they get pushed out the back
into a bag and you walk out thedoor.
Yeah, I, this is.
It's a nice convenience for theshopper and also they have a
very precise Set of data aboutwhat's being sold in those
instances.
Speaker 1 (18:26):
I do think there's a little bit of an RFID moment
happening.
Speaker 2 (18:30):
It is, you still can't put them on soup cans, but
but maybe, maybe that's notwhat we care about.
Okay, right, that's okay,because that's one of the ones
that need where.
Speaker 1 (18:38):
So yeah, I do.
I do think there's definitely aLittle bit more happening in
that space than there was, sohere's a long that technology.
Speaker 2 (18:46):
So here's a notion we can posit about this.
What happens if we, if wecollect that data and it's it's
shared among retailers so thatAn item, so that patterns to be
detected in theft and resale anduse that to actually help
support enforcement?
And also to decline to accept areturn for something that's
(19:07):
already known to be on a List ofitems that were stolen?
Right, I, could that be enoughdisincentive for certain
behaviors that we, we reallywould like to see Decline in the
population.
Yeah, so we will.
We'll circle back to that oneday, but I thought I thought it
was a, I thought it was athoughtful suggestion.
Speaker 1 (19:26):
Yeah, very well, I think we can't.
They can't be a retail showwithout a discussion in our next
year around Retail mediaStraight.
You can't avoid that one.
So there was a whole, there's awhole day.
For the first time, I see nrfhad a pre-day dedicated to
retail media with a number ofsessions.
I wasn't able to attend those,but they were also at least one
(19:49):
other session that I think weboth yeah, we did, we did attend
.
Speaker 2 (19:53):
I wanted to send my clone on Saturday.
I just I just couldn't, Icouldn't muster that up.
It was, it was an entire day,it was eight or nine sessions
and but there were several herethat mentioned that and one
night.
I think that stood out that weboth looked at.
Yeah, it was kind of a summaryof retail media.
They think it included themWell on analyst Andrew Lipsman,
(20:14):
representatives from bothWalmart's platform and wall
greens.
So the great walls are boththere talking about about some
of the developments and I kindof came away.
Speaker 1 (20:27):
I think there were some key things.
I mean, a lot of the themes arerecurring.
I think we can go back toprobably things we both saw and
said at the grocery shop thatwere similar.
But To me, this is one of theseareas where the the momentum is
not declining, it's stillgrowing, that's still
accumulating and although thereis, I think, a very legitimate
debate as to, you know, peoplewant to ask the question Well,
(20:48):
just how many successful retailmedia networks can there be?
Not every retailer can have amedia network and I View that,
as you know, there's somelogical the things that have to
be true, right, for a retailerthat is a specialty retailer,
where they're fully Verticallyintegrated and the only products
they sell are their own, itdoesn't really make sense, right
, and you're not going to see asmuch of a strong need, I
(21:08):
believe.
Speaker 2 (21:09):
Well, to be successful and not going to pay
themselves to advertise our ownproduct.
So who's going to?
Speaker 1 (21:12):
be to advertise them.
They would and that's one ofthe things that we we've not
seen in store for example,advertising in these networks
for Something that's notproducts sold there, right?
So you're not going to.
You know what?
Would you see?
An automotive company, forexample, pay a retail media
network for an ad placement,right?
Speaker 2 (21:31):
but I know, but I know, but I have, I have seen
potential, I have seen amanufacturer, porsche, comes to
mind, in fact where they developa, a Content network in order
to push out the most excitingcontent to their dealership
network, but but they're notpaying advertising fees to do it
(21:52):
.
They were invested mightily inthe platform itself.
So I think you're right.
If you're 100% private label,then the only justification for
having a quote unquote retailmedia network is because it's
going to drive greater sales ofyour own products.
Not a bad thing, but there areseveral ways to accomplish that.
Most of the discussion we'veseen has been about incremental
(22:13):
revenue for the retailer and forendemic products, that is,
products sold in the store thatare provided by brands.
This is a way to ask, or try togarner additional spending
above and beyond the traditionalpromotional spend and allowance
support that have becometraditional in the business.
(22:34):
And there's good reason to dothis, I think, from what we can
see of the numbers, the growthand I don't know if you wrote
down Andrew's forecast, but itwas at 70 billion.
Speaker 1 (22:47):
It's for?
I think it's for this year.
What I found that were the 60billion and revenue and end
spend for retail media networks,but that is equivalent this
year to media end spend onlinear TV, which I think the
eye-opening thing that hepresented is that that means
that by next year retail mediawill overtake linear TV and that
(23:09):
by 2027, it will be more thandouble linear TV end spend.
Speaker 2 (23:14):
And this is not just because the retailers wish it to
be so.
It's also because the brandshave enough feedback from their
activity so far to believe thatthere is a payback, and so
they're steering their dollarsthere.
But they're also makinginvestment in their know-how and
personnel, because managingthat much spending is a complex
(23:37):
undertaking.
So that conversation youmentioned earlier about can more
smaller networks exist it comesdown to how much bandwidth do
the brands have because theywanna reach those audiences, if
they can possibly do it.
The issue is right now it's notyet manageable, but there are
platforms in the future.
(23:59):
I think that'll help make thosedecisions better, and maybe
it's not about buying thenetwork this is my thought but
about buying the audience andthen using a set of retail media
tools that help you optimizethat reach across a variety of
channels.
Speaker 1 (24:14):
Yeah, I do think I didn't hear it talked about here
but I haven't other places.
But I think there is thispotential that when you start to
look at these smaller networks,you know, when you move beyond
a Walgreens or a Walmart or aKroger network, what if those
smaller retail networks sort ofconnect you know, gather
together right and form theirown sort of retail media
(24:36):
aggregate network right, andfound ways to work to and
present it that way?
So then you could have 10smaller retailers in total add
up to a Kroger or a Walmart.
Speaker 2 (24:46):
Exactly right, we have in this country.
Certainly we have wonderfulregional grocers who cannot, who
have trouble competing, andthey were setting up their
networks and the distribution ofproduct through those channels
is very important to retailersin each of those geographies and
in aggregate, equal if not moreimportant than the very largest
(25:07):
retailers.
But there's still progress tobe made.
There's still process to becreated to make that efficient
and effective.
Speaker 1 (25:15):
Yeah, so it certainly worked to be done.
I think this was talked aboutagain here in measurement right
measurements, and Andrew Lipsonmade the point that measurement
makes markets that once themeasurement tools are in place
to your point, jamie right sothat the brands have an easier
time to manage all of this, thenthat kind of opens the
floodgates right it opens theability for them to invest more
because the audience is there.
(25:36):
I mean he pointed out thatWalmart's in store audience.
If you compare their foottraffic right to Walmart, that's
double the major broadcastnetworks in TC in terms of
audience size, so that has to beappealing to the brand?
Speaker 2 (25:48):
Well, it is, and they're beginning to actually
have in place the screens andthe channels to start to put
messages out there.
The brands who make thoseinvestments are going to want
not just a head count right butalso Direct, connected evidence
that their investments in eachof these messaging channels
(26:09):
Actually it results inmeasurable improvement in sales
and brand equity and certainlyin their, their total
relationship of the retailer,right, I think.
For their part, walmart, Ithink that's a pretty good
example and they're not the onlyone.
I think they're determined toprovide that evidence.
It really are.
Yeah, but you know, it's beenkind of the money first and the
(26:32):
conversation is quitecomplicated, because now we see
and hear of of meetings in whichthe merchandising team has
their hand out, asking for the,the, the allotments of, of
Promotional dollars that they'veexpected to always have.
The.
The network team is asking forinvestments in, in retail media
(26:58):
and the brand is saying well, itis a finite number I'm working
with, how about we take somefrom here and move it to there?
Well, I can assure youretailers are not investing in
retail media networks just tosee money move from one pocket
to another, but they are, Ithink, reluctantly, or maybe now
just Pragmatically acceptingwell, some of it should move to
(27:18):
places that are ultimately moreproductive in total for all of
us Better margin and I andthey're definitely hints in the
discussions today that that's,that that kind of practical
thinking is taking hold.
I mean, the payoff is so greatthat maybe people want to adjust
their minds A little bit aroundit right and I think it's also
why you know there was.
Speaker 1 (27:36):
We saw evidence of all these other partnerships
outside of the retail space thatthese networks are making right
, whether it's with trade Desk,whether it's with Pinterest or
social media networks orconnected TV platforms and
streaming TV.
When you take that, you knowwhat matters the brands at the
end of the day is the consumerdata that they're getting access
to for these ends and theability to track.
You know, did my campaign work?
(27:57):
That I have more consumers bymy product because I invested in
these ad networks?
And the more the Retailers canestablish that connective tissue
to all these other mediums,then that makes them the
preferred source.
Speaker 2 (28:09):
Well, I come.
They comes back to the data andmaybe this is a good way to
sort of Wine this down.
But retelling more and moreit's about stuff, it's about
people and it's about the data,about the stuff in the people
and the, the audienceinformation.
We've talked about advances inthat area for years and years.
It's enabled this thing wheremaybe the brands are, I think
(28:31):
they're mostly Positive about.
We can get more for ourspending this way and perhaps
also speak more Specifically anduniquely to individual shopper
segments that in ways thatreally serve them well.
So it should be a win allaround, and I'm sure they'll be
hiccups along the way, and Ialso think that this is we're
(28:52):
still kind of in the nascentstages.
Speaker 1 (28:53):
Yeah, because it is right, we ain't nothing yet.
Yeah, it's still developing andI think it's only got at this
point.
I don't think we're in a placewhere we should be talking about
is there a bubble that's gonnaburst?
It's still in that growth modeand it's still in that early,
early stage.
Speaker 2 (29:08):
Yeah, well, yeah well , so as usual, we could go on.
We could go on, but we won'tyeah, but it's to be merciful to
the audience, we're gonna tryand wrap it up and and there'll
be other opportunities thatother shows.
Ricardo, I've done this for awhile and it's always really
enjoyable.
I can't imagine being with asmarter a Smarter, a companion,
(29:33):
on this kind of, this kind oftask, and it's a privilege to
speak to all of you in theaudience.
So nrf, with its 40,000 peopleand thousand exhibits and it was
about 150, 160 presentationsyeah, it's, it's, it's
overwhelmingly big and we'vejust been able to give you a
little, a little in a littleinsight into a corner or a few
(29:53):
corners of it.
I hope that those of you arehere will Benefit from it and
those of you weren't here willat least get a sense of the
flavor of this thing.
Speaker 1 (30:03):
It is, it is, it's a phenomenon this year, as it is
every year and I think we cankind of close close here and Let
everyone know that you know ifyou did miss out on nrf, there
definitely was a sense ofexcitement in buzz.
The crowds were here, so anyonewho was wondering would, would
people attend?
Is there still you know whatdesire to come to a show like
(30:24):
this?
I think the answer is aresounding yes.
We're back to thosepre-pandemic levels where the
world is moving on and we'reeveryone's ready for it.
Speaker 2 (30:31):
Surely the energy is great, yeah, so so thank you for
listening to us.
I hope that we enlightened youa little bit.
Thank you, ricardo, for makingme look good, and and and.
Speaker 1 (30:41):
I can't wait to do it again.
That's right.
So we'll sign up here and wehope that everyone Remember to
join us for online discussionsat retail wirecom.
Thanks for joining us,everybody today.
Welcome everyone to another Retail Wire Live.
We are here live at the finalday at NRF 2024.
I'm Ricardo Balmar.
I lead partner marketing forretail and consumer goods in the
Americas at Microsoft and I amhere with good friend Jamie
Tensor.
Speaker 2 (00:21):
Greetings all.
I'm glad to be back here.
At NRF Jamie Tensor, I run alittle consultancy called VSN
Strategies.
It's my pleasure once again tobe with Ricardo I think
sometimes as a partner in crimetrying to bring to you a
condensed summary of what thethings we thought were important
from this show.
There are many, many and we'regoing to try really hard to boil
(00:43):
it down to the richest syrup ofmeaning that we possibly can.
So bear with us.
There's a lot to say here, butI think if you haven't been at
the show, or even if you have,there's a good chance.
You didn't get to seeeverything.
I certainly didn't.
Speaker 1 (00:58):
Yeah, that's true.
We probably should start offwith the one sort of obvious
thing that everyone knows wasinevitable to be talked about at
the show, and that's all thingsrelated to AI.
It was all over the agenda.
Speaker 2 (01:11):
AI is everywhere, without a doubt.
Speaker 1 (01:13):
Without a doubt.
I think maybe some of the thingsthat I think we were talking
earlier we agreed.
I feel like, despite the hypeand there's no avoiding the fact
that there's a lot of hype likethat there always is at the
latest technology, at every NRFI came away thinking that there
was a bit of a balance or maybea counterpoint to that, that
there were plenty of examples oftangible things people have
(01:35):
already done with AI over thepast years and a willingness to
talk about it and give examples.
You know there were somesessions.
Even I saw retailers talkingabout something they did, for
example, with AI to augment thecapabilities of their store
teams, where they weren'tlooking to replace people but
they were looking to make thework easier and trying to
eliminate some of the mundanetasks, and retailers had
(01:58):
examples of that.
I think I even heard someretailers say they had KPIs that
they were targeting.
One return to session that anAI session I was at said they
were trying to save every store,associate an hour of time every
week with the use of these AItools at a minimum and they felt
that they were achieving thosetargets.
Speaker 2 (02:16):
Well, I agree with you.
It feels to me like we've gonefairly swiftly from the science
fiction stories of AI's takingover the world and jobs
disappearing in thousands to apractical conversation about
well, here's a technology thatactually is coming of age and
that we're able to start tobuild it into some of the
(02:37):
practices and solutions that weuse to run our stores every day,
make decision making better,eliminate I like to call it junk
work, but let's say tasks thatare repetitive, dreary and that
maybe we don't want our smartestpeople spending their time on,
or even our store people, forthat matter that can easily be
automated.
(02:58):
The other thing that comesacross here, as you said, in
certain I don't want to callthem point solutions, but in
specific areas of practice,there are machine intelligence
components that have been inplay for a long time, and we've
seen examples in things like,you know, inventory, forecasting
and supply chain.
Now, these are I'll call themspecial purpose machine learning
(03:20):
tools.
They are AI, if you want to usethe technical definition, but
what they are not is they arenot large language models, the
chat, gpt type of generative AIs, which I think we've crossed
the threshold on in the lastyear and a half or so.
Yeah, it's all artificialintelligence, but it's a
different nature, maybe adifferent animal.
(03:40):
Now, that's where the hypecycle seems to have come from
lately, and I'm kind of gladthat it seems like we're moving
through that, at least in ourindustry, a little bit, a little
bit briskly, and getting backto practical conversation.
Speaker 1 (03:52):
That's right, and even then, I think some of the
that, jen, you're right, that'swhere the probably the majority
of the hype has been, becauseit's the most impressive when
you see a demo of technologiesright.
It's truly creating things thatare in a manner of moments that
would otherwise take you hours,not longer, to create, and even
though, as I've seen in theexample, I think Tractor Supply
(04:13):
has been here, I was talking tofolks from there as well and
they've leveraged those toolsagain and something that they've
handed to their storeassociates where they can
leverage those language modelsto just ask natural questions
when they need to ask.
So there was another retailerwho talked, in fact,
interestingly enough, that inorder to put those tools in
front of or in the hands oftheir store associates, they
(04:33):
needed to retrain them, becauseeveryone now instinctively knows
how to search by keywords, butwhen you're working with these
models, that actually doesn'thelp you.
Speaker 2 (04:43):
It's not the same know-how.
Speaker 1 (04:45):
You need to really use a natural question.
People wanted to do a productsearch in a store because they
have a customer asking where isthis particular power tool?
You don't just search for thename of the power tool as a
keyword.
You would ask the AI where do Ifind power tool ABC in the
store?
And then you would get ananswer and that required some
(05:05):
retrain.
Speaker 2 (05:06):
Well it does.
I remember when we all startedto use search for the first time
back in the previous millennium, we had to learn how to do that
with some effect, or wecouldn't find the results.
I think today, sometimes, whenwe interact with chatbots, we
don't phrase our questions right, we get frustrated, we can't
get the right answers and as themore powerful AI is coming to
play, it's a skill, it's alearnable skill.
(05:29):
I really think that for storeassociates and people in
management, it's not going to beall that hard to learn this
once a little bit ofconsciousness is raised.
And remember, the machineslearn back, so they're going to
learn our limitations too andbecome better and better at
understanding what we're tryingto get at.
So, when it comes to answeringa question, whether it's about
(05:49):
merchandising a store, whetherit's about, perhaps, a
merchandise plan that anexecutive is trying to work out
for the next selling period ineach of those instances there
are going to be better ways toget at the answers, and that's
something to look forward to.
I think I'm a big antagonistfor anything that is junk work.
(06:15):
Right, and you can automate itand you can trust the automation
.
Can we set that aside?
Can we set that 80% of testaside and then free our minds,
free our hands, if necessary, todo things that really add value
and, ultimately, moresatisfying, make it a better job
?
Speaker 1 (06:31):
Yeah, I agree, and I think that's true for again.
So many examples I don't knowthat I could list them all, but,
like you mentioned earlier,some examples are related to
supply chain and forecasting,which aren't necessarily new
applications of data and seed,but I think that the difference
I see is more open conversationabout it.
For retailers, more discussionabout the benefits and what any
(06:52):
individual retailer is gaining,and that as an example to why
others should be using it andthat's being promoted a lot.
Speaker 2 (07:00):
I think it's also important to distinguish between
those large language model, thestuff that's gotten the kind of
general media hype, the openplatforms for artificial
intelligence that essentiallythat protect nothing, that scoop
up everything For a businessapplication.
That's not the place tonecessarily set up your
(07:22):
artificial intelligence tool.
There's lots of reasons to keepa walled garden, so to speak,
around your own instance, and ifyou have an AI platform that
you're using to drive whetherit's decision making or whether
it's merchandising tasks or anynumber of other applications
(07:42):
inventory, forecasting, etcetera that needs to stay in
house.
A short while ago, that wasbeyond comprehension that we
could possibly afford and enablethat within organizations.
Now it doesn't seem far-fetchedat all.
In fact, it's been happening insmall ways for a while.
Now it's happening in largerand more exciting ways.
Speaker 1 (08:04):
And I think there were a good number of maybe not
as many, but a good number ofconsumer facing examples and
applications.
There was one session wheresome from Walmart was talking
about how they added it, andagain it was sort of a search
enhancement, so adding into theWalmart app the ability to ask a
natural question aboutsomething that you were planning
, not a product-specificquestion, but the example they
(08:27):
used on stage is what if there'syour a parent trying to plan a
birthday party for your daughterand your daughter likes
unicorns?
So instead of individuallysearching for party favors that
have unicorns, like we wouldnormally do, you would just ask
the Walmart app what do I needto plan a unicorn-themed party
for my daughter?
And then it would return backsearch results to show you all
(08:49):
of those elements.
Another example was I'mplanning a Super Bowl party,
what do I need?
And so the search results cameback from anything ranging from
grocery items to a new bigscreen TV.
Speaker 2 (08:59):
Even I know you need avocados, exactly so which is?
We're going to see thisconstantly.
We're going to learn as endusers, we're going to learn to
interact with it better andthey're going to get smarter at
understanding the way weinteract with them.
So one of the applicationswhere machine intelligence has
been in play for some time hasbeen in inventory accuracy,
(09:21):
inventory forecasting.
So can I make a clever segue alittle bit into one of the other
points?
That is a conversation thatwe've heard more of from more
directions, I think, certainlyfrom the vendor side of the
question here.
I think inventory accuracy hasbeen certainly a discussion for
some time.
It's a source of loss Both overand under inventories in
(09:47):
perishable products, anythingthat's perishable or that can
expire or go out of fashion.
You don't want too much of it,but you certainly don't.
You do want to have enough thatyou can satisfy the demand, and
it's no longer good enough torely on instinct to do that.
So the fast-moving consumergoods world has been using
various forms of inventorymanagement and forecasting and
(10:10):
ordering tools for quite a whileit could be 17, 18 years, if
not longer and they've seen thebenefits from it.
They, I think, have found newways to capture information,
including the shelf status andother essential parts of the
equation, and so they can getmore and more accurate In the
(10:32):
soft lines, which, I have toconfess, because I really am a
FMCG type of guy I still find itmysterious and awe-inspiring
that bets can be made on apparelorders 18 months out, sometimes
from a factory very far away,in anticipation of a certain
amount of sell-through that willhappen during a holiday season.
(10:53):
It's a marvelous mystery.
It does look like a place maybewhere a little machine
intelligence might help narrowthose error bars and the end of
the day, if you can make themark down quantity is lower,
then that's a smashing win.
So it seems like that'sdiscussion.
It's more often in thediscussion.
A few years ago we didn't hearthat that story, inventory
(11:15):
conversation quite as much.
Now this seems to be a reallygreat emphasis on it and I think
it's connected to the interestin fulfilling store orders that
are received online as well.
So that feels like it'smaturing a little.
It's becoming part of theregular vernacular for the
(11:36):
industry and it definitelyreferences to it all over the
exhibit floor.
Speaker 1 (11:42):
I think that maybe takes us also to into
discussions that have beenhappening around returns when
returns?
are sealed in a very top themethat we're hearing more and more
of.
It kind of ties into both whatyou're pointing about the
inventory management and I thinkalso what we were saying
earlier about AI, and is therean application that makes sense
for AI?
I know there have been somesolutions I saw there where the
(12:03):
focus was on AI helping you.
I describe it as redefine howyou position the product,
because the idea then is toprevent the need for a return,
because once the items purchasedright and what do you do really
to control the consumer they'regoing to return it.
They're going to return it.
Speaker 2 (12:19):
It sets up a stream of events that you just can't
stop.
Speaker 1 (12:22):
You can control it up until that moment of purchase
and to make sure that it's theright purchase decision without
the need for doing things whereyou're doing a.
I don't know, maybe it's theright thing.
Speaker 2 (12:32):
I'll buy it anyway because I know I can return a
kind of situation which you'retrying to avoid.
Speaker 1 (12:36):
It's the retailer and maybe there's an application
that AI tools can help there.
Speaker 2 (12:40):
Well, with garments, getting the fit right is a key
element.
And there are lots of attemptsand I think some work better
than others, but they're tryingto incorporate tools that the
shopper can use to get a betteridea about how they will look in
a given purchase.
We see it for eyeglass frames,we see it for you know, there's
a company I've been looking atwhere you can put in a bunch of
(13:01):
metrics and get a custom madesuit for not that much money.
This kind of thing depends onour artificial intelligence to
drive that, and the hope, ofcourse, is that there'll be much
less likely to be returned,because each time a return is
authorized, a whole cascade ofevents has to happen that the
(13:22):
retailer would rather not haveto bother with and pay for.
It's worth noting that one ofthe major sponsors here this
year is a company called GoTRG.
Their logo is all over the show.
And what do they do?
They help retailers managetheir returns flow.
So it is a big business.
Every time you shave that downby a percentage point, money is
(13:43):
dropping to the bottom line, butit's also a reflection about
getting it right for the shopperin the first place.
So there are, I think, a hostof different places where
process and experienceimprovements.
They're trying to shave alittle bit here, improve a
little bit there, andcollectively it adds up.
(14:04):
But returns cost a lot of moneyand there's a question of what
do you do with the product whenit's received.
And there are some productswhere there's no point in even
authorizing the return.
Yeah, and I've had thatexperience I don't know if you
have where Amazon has said don'tbother sending back that part
(14:24):
you ordered by mistake.
It was an honest error.
It's cheaper for us if you justkeep it.
You shouldn't do that too oftenand there are probably people
who abuse that.
But that conversation, I meanthat's going to be going on for
a long time.
But it does connect to anotherkind of process which is a
little more sinister, and thatis what happens when somebody
(14:47):
stole the item that they'retrying to return.
And is that a good segue intothe loss prevention question?
Returns are maybe a form ofloss from the retailer, but it's
benign in its intention usually.
And there's a whole anothersinister thing that happens when
an entire store is emptied by agroup of people who next day
(15:10):
are attempting to bring thoseitems back for return elsewhere
or send them back.
That's ugly and it's gotten alot of headlines in the past
year.
So shoplifting it makes good TVimages, I'll say that.
But it's not the only form ofloss, that's the thing.
(15:33):
In fact it's not even thelargest.
Speaker 1 (15:35):
I actually think that , given the recent things that
you have to interact, there wasmaybe a lightning.
I think a bit of a tone of howsevere that is.
On the show of Florida it wasstill being discussed and still
being a real problem.
Maybe it was a littleoveremphasized in the past year
and so it's felt a little moresubdued, I think, in the
(15:56):
discussion.
Speaker 2 (15:57):
Well, more measured it ain't nothing, that's clear
about that.
It matters, stores in certainlocations are forced to take
remedial steps to reduce theft.
It actually undermines theexperience of the shopper, which
is which is pretty sad.
And I think about certain drugstores in Manhattan where
(16:18):
everything worth buying isbehind loose site doors and you
can't purchase it withoutsomebody.
If you can find them to comewith a key, that's.
That's a real Disincentive forpurchasing.
So it's not just costing thoseretailers the the cost of those
remedial Activities, it'scosting them actual sales and
(16:39):
you kind of wonder what's thearithmetic here In terms of what
we save.
But it also sends a messagethat I was discussing it through
someone today.
It makes me as a shopperwalking to that store and think
this is not a safe place.
Right, that's a terrible thingto do to the reputation of the
retailer and and, by the way,the news stories that we've seen
(17:00):
it's kind of the same thing.
You know I'm right, I don'twant to walk into a jewelry
store where any minutesomebody's gonna back in SUV
into the front and Try and steal, you know, break into the
counter.
I know that's, that's hyperbole, but it has happened.
No, so the loss preventiondiscussion is big.
We know there have beenseparate events about it.
(17:21):
One conversation I had was aboutwhether RFID tagging, which is
used principally these days forinventory management, could also
help with with that problem oftheft and what happens to
products after they're stolen,and Might even help the returns
process too.
They are interconnected, butRFID seems to be Moving faster
(17:47):
to that tipping point where it'sstarting to make sense for many
not all, but many types ofproducts.
The tags are less expensive.
There are, there are fabrictags that can be sewn into a
garment invisibly.
There are, and there are thereare Detectors that can be used
for checkout.
For a check out, what someone Iknow described the bins in
(18:09):
uniclose stores where you justthrow a bunch of garments in.
It reads the tags they get,they get pushed out the back
into a bag and you walk out thedoor.
Yeah, I, this is.
It's a nice convenience for theshopper and also they have a
very precise Set of data aboutwhat's being sold in those
instances.
Speaker 1 (18:26):
I do think there's a little bit of an RFID moment
happening.
Speaker 2 (18:30):
It is, you still can't put them on soup cans, but
but maybe, maybe that's notwhat we care about.
Okay, right, that's okay,because that's one of the ones
that need where.
Speaker 1 (18:38):
So yeah, I do.
I do think there's definitely aLittle bit more happening in
that space than there was, sohere's a long that technology.
Speaker 2 (18:46):
So here's a notion we can posit about this.
What happens if we, if wecollect that data and it's it's
shared among retailers so thatAn item, so that patterns to be
detected in theft and resale anduse that to actually help
support enforcement?
And also to decline to accept areturn for something that's
(19:07):
already known to be on a List ofitems that were stolen?
Right, I, could that be enoughdisincentive for certain
behaviors that we, we reallywould like to see Decline in the
population.
Yeah, so we will.
We'll circle back to that oneday, but I thought I thought it
was a, I thought it was athoughtful suggestion.
Speaker 1 (19:26):
Yeah, very well, I think we can't.
They can't be a retail showwithout a discussion in our next
year around Retail mediaStraight.
You can't avoid that one.
So there was a whole, there's awhole day.
For the first time, I see nrfhad a pre-day dedicated to
retail media with a number ofsessions.
I wasn't able to attend those,but they were also at least one
(19:49):
other session that I think weboth yeah, we did, we did attend
.
Speaker 2 (19:53):
I wanted to send my clone on Saturday.
I just I just couldn't, Icouldn't muster that up.
It was, it was an entire day,it was eight or nine sessions
and but there were several herethat mentioned that and one
night.
I think that stood out that weboth looked at.
Yeah, it was kind of a summaryof retail media.
They think it included themWell on analyst Andrew Lipsman,
(20:14):
representatives from bothWalmart's platform and wall
greens.
So the great walls are boththere talking about about some
of the developments and I kindof came away.
Speaker 1 (20:27):
I think there were some key things.
I mean, a lot of the themes arerecurring.
I think we can go back toprobably things we both saw and
said at the grocery shop thatwere similar.
But To me, this is one of theseareas where the the momentum is
not declining, it's stillgrowing, that's still
accumulating and although thereis, I think, a very legitimate
debate as to, you know, peoplewant to ask the question Well,
(20:48):
just how many successful retailmedia networks can there be?
Not every retailer can have amedia network and I View that,
as you know, there's somelogical the things that have to
be true, right, for a retailerthat is a specialty retailer,
where they're fully Verticallyintegrated and the only products
they sell are their own, itdoesn't really make sense, right
, and you're not going to see asmuch of a strong need, I
(21:08):
believe.
Speaker 2 (21:09):
Well, to be successful and not going to pay
themselves to advertise our ownproduct.
So who's going to?
Speaker 1 (21:12):
be to advertise them.
They would and that's one ofthe things that we we've not
seen in store for example,advertising in these networks
for Something that's notproducts sold there, right?
So you're not going to.
You know what?
Would you see?
An automotive company, forexample, pay a retail media
network for an ad placement,right?
Speaker 2 (21:31):
but I know, but I know, but I have, I have seen
potential, I have seen amanufacturer, porsche, comes to
mind, in fact where they developa, a Content network in order
to push out the most excitingcontent to their dealership
network, but but they're notpaying advertising fees to do it
(21:52):
.
They were invested mightily inthe platform itself.
So I think you're right.
If you're 100% private label,then the only justification for
having a quote unquote retailmedia network is because it's
going to drive greater sales ofyour own products.
Not a bad thing, but there areseveral ways to accomplish that.
Most of the discussion we'veseen has been about incremental
(22:13):
revenue for the retailer and forendemic products, that is,
products sold in the store thatare provided by brands.
This is a way to ask, or try togarner additional spending
above and beyond the traditionalpromotional spend and allowance
support that have becometraditional in the business.
(22:34):
And there's good reason to dothis, I think, from what we can
see of the numbers, the growthand I don't know if you wrote
down Andrew's forecast, but itwas at 70 billion.
Speaker 1 (22:47):
It's for?
I think it's for this year.
What I found that were the 60billion and revenue and end
spend for retail media networks,but that is equivalent this
year to media end spend onlinear TV, which I think the
eye-opening thing that hepresented is that that means
that by next year retail mediawill overtake linear TV and that
(23:09):
by 2027, it will be more thandouble linear TV end spend.
Speaker 2 (23:14):
And this is not just because the retailers wish it to
be so.
It's also because the brandshave enough feedback from their
activity so far to believe thatthere is a payback, and so
they're steering their dollarsthere.
But they're also makinginvestment in their know-how and
personnel, because managingthat much spending is a complex
(23:37):
undertaking.
So that conversation youmentioned earlier about can more
smaller networks exist it comesdown to how much bandwidth do
the brands have because theywanna reach those audiences, if
they can possibly do it.
The issue is right now it's notyet manageable, but there are
platforms in the future.
(23:59):
I think that'll help make thosedecisions better, and maybe
it's not about buying thenetwork this is my thought but
about buying the audience andthen using a set of retail media
tools that help you optimizethat reach across a variety of
channels.
Speaker 1 (24:14):
Yeah, I do think I didn't hear it talked about here
but I haven't other places.
But I think there is thispotential that when you start to
look at these smaller networks,you know, when you move beyond
a Walgreens or a Walmart or aKroger network, what if those
smaller retail networks sort ofconnect you know, gather
together right and form theirown sort of retail media
(24:36):
aggregate network right, andfound ways to work to and
present it that way?
So then you could have 10smaller retailers in total add
up to a Kroger or a Walmart.
Speaker 2 (24:46):
Exactly right, we have in this country.
Certainly we have wonderfulregional grocers who cannot, who
have trouble competing, andthey were setting up their
networks and the distribution ofproduct through those channels
is very important to retailersin each of those geographies and
in aggregate, equal if not moreimportant than the very largest
(25:07):
retailers.
But there's still progress tobe made.
There's still process to becreated to make that efficient
and effective.
Speaker 1 (25:15):
Yeah, so it certainly worked to be done.
I think this was talked aboutagain here in measurement right
measurements, and Andrew Lipsonmade the point that measurement
makes markets that once themeasurement tools are in place
to your point, jamie right sothat the brands have an easier
time to manage all of this, thenthat kind of opens the
floodgates right it opens theability for them to invest more
because the audience is there.
(25:36):
I mean he pointed out thatWalmart's in store audience.
If you compare their foottraffic right to Walmart, that's
double the major broadcastnetworks in TC in terms of
audience size, so that has to beappealing to the brand?
Speaker 2 (25:48):
Well, it is, and they're beginning to actually
have in place the screens andthe channels to start to put
messages out there.
The brands who make thoseinvestments are going to want
not just a head count right butalso Direct, connected evidence
that their investments in eachof these messaging channels
(26:09):
Actually it results inmeasurable improvement in sales
and brand equity and certainlyin their, their total
relationship of the retailer,right, I think.
For their part, walmart, Ithink that's a pretty good
example and they're not the onlyone.
I think they're determined toprovide that evidence.
It really are.
Yeah, but you know, it's beenkind of the money first and the
(26:32):
conversation is quitecomplicated, because now we see
and hear of of meetings in whichthe merchandising team has
their hand out, asking for the,the, the allotments of, of
Promotional dollars that they'veexpected to always have.
The.
The network team is asking forinvestments in, in retail media
(26:58):
and the brand is saying well, itis a finite number I'm working
with, how about we take somefrom here and move it to there?
Well, I can assure youretailers are not investing in
retail media networks just tosee money move from one pocket
to another, but they are, Ithink, reluctantly, or maybe now
just Pragmatically acceptingwell, some of it should move to
(27:18):
places that are ultimately moreproductive in total for all of
us Better margin and I andthey're definitely hints in the
discussions today that that's,that that kind of practical
thinking is taking hold.
I mean, the payoff is so greatthat maybe people want to adjust
their minds A little bit aroundit right and I think it's also
why you know there was.
Speaker 1 (27:36):
We saw evidence of all these other partnerships
outside of the retail space thatthese networks are making right
, whether it's with trade Desk,whether it's with Pinterest or
social media networks orconnected TV platforms and
streaming TV.
When you take that, you knowwhat matters the brands at the
end of the day is the consumerdata that they're getting access
to for these ends and theability to track.
You know, did my campaign work?
(27:57):
That I have more consumers bymy product because I invested in
these ad networks?
And the more the Retailers canestablish that connective tissue
to all these other mediums,then that makes them the
preferred source.
Speaker 2 (28:09):
Well, I come.
They comes back to the data andmaybe this is a good way to
sort of Wine this down.
But retelling more and moreit's about stuff, it's about
people and it's about the data,about the stuff in the people
and the, the audienceinformation.
We've talked about advances inthat area for years and years.
It's enabled this thing wheremaybe the brands are, I think
(28:31):
they're mostly Positive about.
We can get more for ourspending this way and perhaps
also speak more Specifically anduniquely to individual shopper
segments that in ways thatreally serve them well.
So it should be a win allaround, and I'm sure they'll be
hiccups along the way, and Ialso think that this is we're
(28:52):
still kind of in the nascentstages.
Speaker 1 (28:53):
Yeah, because it is right, we ain't nothing yet.
Yeah, it's still developing andI think it's only got at this
point.
I don't think we're in a placewhere we should be talking about
is there a bubble that's gonnaburst?
It's still in that growth modeand it's still in that early,
early stage.
Speaker 2 (29:08):
Yeah, well, yeah well , so as usual, we could go on.
We could go on, but we won'tyeah, but it's to be merciful to
the audience, we're gonna tryand wrap it up and and there'll
be other opportunities thatother shows.
Ricardo, I've done this for awhile and it's always really
enjoyable.
I can't imagine being with asmarter a Smarter, a companion,
(29:33):
on this kind of, this kind oftask, and it's a privilege to
speak to all of you in theaudience.
So nrf, with its 40,000 peopleand thousand exhibits and it was
about 150, 160 presentationsyeah, it's, it's, it's
overwhelmingly big and we'vejust been able to give you a
little, a little in a littleinsight into a corner or a few
(29:53):
corners of it.
I hope that those of you arehere will Benefit from it and
those of you weren't here willat least get a sense of the
flavor of this thing.
Speaker 1 (30:03):
It is, it is, it's a phenomenon this year, as it is
every year and I think we cankind of close close here and Let
everyone know that you know ifyou did miss out on nrf, there
definitely was a sense ofexcitement in buzz.
The crowds were here, so anyonewho was wondering would, would
people attend?
Is there still you know whatdesire to come to a show like
(30:24):
this?
I think the answer is aresounding yes.
We're back to thosepre-pandemic levels where the
world is moving on and we'reeveryone's ready for it.
Speaker 2 (30:31):
Surely the energy is great, yeah, so so thank you for
listening to us.
I hope that we enlightened youa little bit.
Thank you, ricardo, for makingme look good, and and and.
Speaker 1 (30:41):
I can't wait to do it again.
That's right.
So we'll sign up here and wehope that everyone Remember to
join us for online discussionsat retail wirecom.
Thanks for joining us,everybody today.
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