Latest / The Retail Podcast / How to Start Planning for January 2024, US Retail Trends Black Friday & Cyber Monday

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How to Start Planning for January 2024, US Retail Trends Black Friday & Cyber Monday · The Retail Podcast

• 0:00
  Hello and good evening, good morning, good afternoon.
• 0:03
  Wherever you are in the world, we'll looking at the results
• 0:06
  from Black Friday and Cyber Monday specifically in the US
• 0:10
  Let me bring on Joe Shasteen from retail next who's going to
• 0:15
  be taking us through the data points.
• 0:19
  Joe, good morning. Hi, Alex.
• 0:21
  Good afternoon. And how are you doing?
• 0:24
  I'm doing great. Thank you so much for having me
• 0:26
  join you today. Yeah, My, my pleasure.
• 0:29
  Sorry, I said good morning. You said good afternoon.
• 0:31
  It is this morning for you. No, good morning.
• 0:34
  For me, but good afternoon for you, right.
• 0:36
  So, yeah. Yeah.
• 0:37
  I don't know. Good evening.
• 0:38
  Right? Depends on how you look at it.
• 0:40
  It's dark. The sun has disappeared.
• 0:43
  I don't know what time. Just just out of curiosity, what
• 0:46
  time does it get dark in San Jose?
• 0:49
  It's about, you know, well, San Jose maybe about 535 o'clock,
• 0:52
  you know, OK, yeah, not. Too bad.
• 0:54
  Yeah. Yeah, I know in the UK it's like
• 0:56
  at 3IN in mature, that's about 5:00.
• 0:59
  So. But anyway, listen Joe, I know
• 1:01
  you've had an incredibly busy week.
• 1:03
  You've been talking about the findings from your data.
• 1:07
  So if you don't mind, for those who don't know retail next and I
• 1:10
  know you guys have been around for a very long time and have an
• 1:13
  impressive list, customer base list.
• 1:16
  Can you just give us a sort of a one minute on retail next, the
• 1:20
  data set that we're going to look at in terms of Black
• 1:23
  Friday, Cyber Monday and projecting that forward and then
• 1:27
  we'll just get straight into the data?
• 1:29
  Yeah. So retail Next is a technology
• 1:32
  platform that aims to bring e-commerce style shopper
• 1:35
  analytics to brick and mortar stores.
• 1:37
  So we primarily will focus on putting a camera at the entrance
• 1:42
  to a store just to understand how many people are entering in
• 1:45
  and out of that location. And for the most part when we're
• 1:48
  discussing the data that I'm going to be showing in the in
• 1:51
  the PowerPoint that I will share, all of the data is
• 1:53
  generated from just one single camera at the front of a store,
• 1:57
  just tracking people as they enter and as they leave,
• 1:59
  generating a traffic in and a traffic out count.
• 2:02
  And that is the data that we are analyzing the metrics that we
• 2:05
  are using in this report to would require the storage to
• 2:08
  have been open for a whole year so that we can get that nice
• 2:11
  comp picture of how the store performed last year during Black
• 2:13
  Friday, how the store was performing this year and our,
• 2:16
  you know what can we see from a trend perspective.
• 2:19
  One other thing to note with the data that I'm sharing here today
• 2:22
  is that we do scale this to be more be a more representative of
• 2:28
  the overall US retail market. We however, we do not include
• 2:31
  grocers and we do not include gasoline or sort of gas station
• 2:34
  purchases in these metrics is primarily focused on specialty
• 2:38
  retail as well as maybe some of the you know, department store
• 2:41
  retailers as well. But yeah, that that's kind of
• 2:44
  the data that we have retail. Next we'll also be able to
• 2:47
  provide information around in store shopper behavior.
• 2:50
  That's not the data that I'm going to get into today, but
• 2:52
  that is another big focus of what we can do is provide those
• 2:55
  e-commerce style analytics for interior shopping.
• 2:58
  So how many people are dwelling? How long are they dwelling?
• 3:00
  You know, all of that sort of information around what people
• 3:03
  are doing when they come in the store.
• 3:05
  And I think more or less it's around 5000 data, 5000 stores
• 3:10
  roughly, right, I don't think. Yeah, In that range, yeah,
• 3:12
  there's a lot. It changes.
• 3:15
  It's changing all the time. I got you.
• 3:18
  OK, well, listen, I'm. I'm super excited.
• 3:20
  I I love data. I love.
• 3:23
  I know why I said this. You off camera.
• 3:24
  I love the fact that you're in Milton Keynes and in Madrid, my
• 3:27
  two favorite place. It's it's no, it will go Milton
• 3:30
  Keynes. Concrete cows, roundabouts.
• 3:32
  But anyway, let's dive into the data.
• 3:35
  Great, OK, perfect. So just to kind of set the
• 3:38
  stage, we've got an initial view into you know what we've been
• 3:41
  seeing kind of trend wise going back into the summer of you know
• 3:44
  2023. So I think generally speaking
• 3:47
  what we were seeing through summer and most of you know
• 3:49
  early fall or end of summer is kind of year over year decline
• 3:53
  compared to 2022 in that you know 1 to 2% range throughout
• 3:57
  most of the summer. We didn't see a nice, you know,
• 3:58
  uptake during that 4th of July week with some comp dates.
• 4:01
  But again for the most Part 1 to 2% decline was what we were
• 4:04
  seeing leading up to the fall. Then once we started getting to
• 4:08
  fall maybe a little bit more of the back to school season, we're
• 4:11
  starting to see a little bit more of a decline in that 3 to
• 4:13
  4% range leading up to November. Now what we know leading up to
• 4:17
  that week of Black Friday and then Black Friday itself is that
• 4:20
  there is usually a positive uptick in traffic trends you
• 4:24
  know compared to maybe November Week 2 or even November Week 3
• 4:27
  in this case and that's exactly what we ended up seeing.
• 4:30
  So our overall numbers for November week four were you know
• 4:33
  as positive. They've been in you know the
• 4:35
  last four or five months that only about a decline about 0.5%
• 4:39
  for the whole week of November. But on an even more positive
• 4:43
  note what we were seeing was that we actually look drill into
• 4:45
  the individual days leading up to Black Friday as well as the
• 4:49
  weekend for Black Friday itself. We saw very positive metrics.
• 4:52
  So thinking is a very small sample size.
• 4:55
  So we can disregard that metric, but if we look at just Saturday
• 4:59
  or Black Friday itself on November 24th, we're plus 2% for
• 5:02
  traffic and then we carried on that kind of positive trend for
• 5:06
  Saturday and Sunday as well at about a + 1 year over year, so.
• 5:10
  Cynthia, just just quickly, is that are you is that a
• 5:13
  translation that from looking at the, the, the previous data set
• 5:16
  that people are actually because I keep hearing that Christmas
• 5:21
  and and and shopping is happening earlier in the year,
• 5:24
  you know, so people are. So when when you looked at the
• 5:26
  the slide it it it's sort of there was a massive downward
• 5:30
  slide leading up to. So people were like purposely
• 5:34
  holding back, holding black, holding back because in the UK
• 5:37
  there's been a lot of complaints or I've listened to some some
• 5:41
  analysis and analysis on the fact that everyone just threw
• 5:45
  their offers from like the beginning of November to try and
• 5:48
  get people to come in. But looking at your data, it's
• 5:51
  also sort of actually validates what what's happening that there
• 5:55
  is a is that right? Am I reading that right?
• 5:57
  What, Yeah. So from what I, what I had seen
• 5:59
  right when I was doing research more on the the US side of
• 6:02
  things, a lot of the expectations were, you know
• 6:04
  we've been seeing kind of softer trends leading up to Black
• 6:07
  Friday. You know, inflation was still
• 6:08
  not great for customers. A lot of concerns around 2 of
• 6:11
  are the Black Friday Deals worth it?
• 6:13
  You know, can you get those earlier, can you get them later,
• 6:16
  do you need to go out and shop on Black Friday?
• 6:17
  So a lot of questions there that I think was your tempering my
• 6:20
  expectation. And I think you know when I was
• 6:22
  asked, I was expecting Black Friday itself to be maybe flat
• 6:26
  to slightly negative. So it exceeded my expectations.
• 6:29
  When I saw that based on the perceptions, you know, kind of
• 6:31
  what we've been hearing of those deals shifting forward, I think
• 6:33
  I saw some research too that in the US there the, the discounts
• 6:38
  were at their highest rate that they've been in years for
• 6:40
  October. So the discounts were getting
• 6:42
  pushed earlier in October. But again, what it ended up
• 6:44
  seeing, what we ended up seeing from our metrics is that on
• 6:47
  Black Friday itself, you know, people still went out.
• 6:50
  It still seems like it's an event, right.
• 6:52
  So last year for Black Friday we were plus 7 compared to 2021 and
• 6:56
  then this year we're +2 compared to 2022.
• 6:59
  So we're still seeing increased growth you know even compared to
• 7:02
  two years ago 2021, now 2019 and pre COVID is a bit of a
• 7:06
  different story there as we're still you know not fully
• 7:09
  recovered from where we were pre Pandemic.
• 7:10
  But I think you know some of the patterns have just completely
• 7:13
  shifted the you know shopping dynamic post Pandemic era.
• 7:16
  So we might never reach that level.
• 7:18
  But again we're seeing you know one stronger performances than
• 7:20
  we initially had expected to see, you know based on your
• 7:23
  perceptions and some of the surveys that we had been getting
• 7:25
  from customers as well. Fantastic.
• 7:28
  Brilliant. I interrupted your phone.
• 7:30
  Sorry. No problem.
• 7:32
  Yeah. So I think the main takeaways
• 7:34
  here was very positive Black Friday in the US and I think
• 7:37
  really specifically what we wanted to call out was the
• 7:39
  really strong performance in the health and beauty category.
• 7:42
  Now this might not necessarily be much of a surprise.
• 7:45
  We do tend to see health and beauty performed very well
• 7:49
  around this time of the year, you know kind of getting ready
• 7:51
  for holiday, getting ready with some of those gifting purchases,
• 7:54
  right. So that was really, really
• 7:55
  strong performance. But you know I think just to
• 7:57
  kind of see that pretty much double digit growth over the
• 8:00
  weekend year over year, you know was really, really positive to
• 8:04
  see for health and beauty. You know I think we had some
• 8:06
  perceptions that this might occur.
• 8:07
  You know, I think luxury segment is still doing great for those
• 8:11
  people who you know can afford luxury, right.
• 8:13
  They're not really changing their habits too much.
• 8:16
  But maybe those people who are on the border of maybe wanting
• 8:19
  to purchase luxury, those people maybe seem to shift a little bit
• 8:22
  lower into, you know, maybe more premium cosmetics or you know,
• 8:26
  maybe the health and beauty space as opposed to maybe, you
• 8:28
  know, the luxury apparel, the luxury accessories and those
• 8:31
  sorts of sorts of items. So that was something that that
• 8:34
  we definitely noticed was that you know that health and beauty
• 8:37
  category especially kind of the premium health and beauty was
• 8:40
  doing very well. We saw smaller growth in the
• 8:42
  luxury segment as well and we saw you know also too in the
• 8:46
  jewelry category was another category I want to call out.
• 8:48
  We saw really strong growth in jewelry.
• 8:51
  One of that some of the growth was due to luxury, but really a
• 8:55
  lot of the growth in the jewelry category was really from the low
• 8:58
  kind of costume jewelry kind of price points.
• 9:00
  That's where we're really seeing a lot of, a lot of growth in
• 9:03
  that in that segment. Understood.
• 9:08
  And then just the one final point I wanted to bring up with
• 9:11
  kind of preparing for a holiday in what we're seeing.
• 9:14
  So we got a metric from 2022. So we basically look back at our
• 9:19
  holiday trends and we look back at 2021 as well.
• 9:22
  And they're all very similar. But what we noticed is we took,
• 9:26
  we set the average traffic during this holiday time period,
• 9:29
  so basically November to December, that whole 2 month
• 9:32
  period. We're considering the holiday
• 9:33
  shopping time period and we set the average traffic to 1.
• 9:37
  So that was just your average traffic over that time period
• 9:39
  equal to 1:00. And then we looked at what is
• 9:41
  it, what are the kind of tea shopping dates, you know, Black
• 9:44
  Friday, that whole weekend, then Super Saturday, the other
• 9:47
  Saturday and then the kind of last, you know, 9-10 days
• 9:49
  leading up to Christmas. What does that traffic look like
• 9:53
  compared to the average day? And what we're seeing is that
• 9:55
  Black Friday, as you might expect, has by far the most
• 9:58
  traffic, you know, about 2.6 times the amount of traffic that
• 10:02
  you're getting on a regular kind of holiday shopping day.
• 10:05
  You're getting 2.6, that amount on Black Friday now leading up
• 10:10
  to Christmas time, right. That is where you're starting to
• 10:12
  see still really strong performance, you know, almost
• 10:14
  1.82 X the amount of average holiday traffic.
• 10:18
  But it's not quite at the same level as Black Friday.
• 10:20
  I like to say that, you know, leading up to Christmas, you get
• 10:23
  a Black Friday basically every two days.
• 10:25
  So Black Friday traffic every two days during the Christmas
• 10:29
  ramp up period, that last 10 day period is equivalent to the
• 10:31
  traffic that you're getting in the black right here.
• 10:33
  So you know just something to keep in mind that you know we're
• 10:36
  still going to have our most valuable days for retailers are
• 10:39
  coming up that last you know 10 days before Christmas.
• 10:42
  Really strong drivers for traffic, really strong drivers
• 10:45
  for sales. So it's really important just to
• 10:47
  kind of you know, take some learnings from you know,
• 10:49
  whatever we're seeing from traffic on Thanksgiving, you
• 10:51
  know, in what were your trends looking like from an hourly
• 10:53
  perspective. And you know, and just making
• 10:55
  sure that we're ready during the holiday time period from a labor
• 10:58
  perspective, from coaching up the labor to understand where
• 11:01
  those associates are going, where they can interact with
• 11:04
  customers on the floor plan to really try to drive that
• 11:06
  conversion as we're going to start to get that more valuable
• 11:09
  traffic in the store, you know, when there's much more urgency
• 11:12
  to make those purchases. So how does that breakdown in
• 11:16
  terms of from your experience as you move because obviously the
• 11:20
  the next big shopping event are the sales that in the UK
• 11:24
  literally start the day after Christmas, Boxing Day they call
• 11:28
  it. In Europe they have the King's
• 11:30
  Day or it's like the 7th or 8th of January in the US When, when,
• 11:36
  when is that sales? And I guess that's what you're
• 11:38
  saying here as we come out of Christmas into that festive
• 11:42
  sales period, there's you're expecting the traffic to solve,
• 11:46
  keep going and retailers should be briefing their store
• 11:50
  associates in that way. Yeah, so.
• 11:51
  From my, my perspective, I think you know we're going to see a
• 11:54
  downturn, you know, over the net, not a downturn, but
• 11:56
  traffic's going to slow. It's still going to be strong,
• 11:59
  but it's not going to be what you're going to see in those
• 12:01
  last, you know, two weeks leading or last week or two
• 12:04
  leading up to Christmas. That's where you're going to get
• 12:07
  your high traffic and you're really high valuable or you
• 12:10
  know, highly valued customers in there because there's going to
• 12:12
  be a lot more urgency to make that purchase.
• 12:15
  You know what? We literally.
• 12:15
  In the next two weeks? Really.
• 12:18
  Yes. Yeah.
• 12:19
  So I would say probably starting around, you know this about two
• 12:22
  Saturdays out from Christmas and then we've got a little bit of a
• 12:24
  kind of a on Christmas this year and that you know I think
• 12:27
  Christmas last year was on a Sunday, this year I think it's
• 12:29
  going to be on on a Monday. So it's going to be about two
• 12:31
  Saturdays out from Christmas is really when you start to see
• 12:34
  that stronger growth. And you know in this case we had
• 12:36
  a 1.8 times traffic day on that two Saturdays out and then right
• 12:41
  before, you know the 12:23 on that Friday, we had about a 2.0
• 12:46
  X traffic. So a little bit lower because
• 12:48
  you had Christmas Eve kind of driving down that Saturday
• 12:51
  trend. But this year, I think it'll be
• 12:52
  interesting with that Christmas Eve on Sunday, how is that
• 12:55
  driving? And you'll have the full and
• 12:57
  you'll have a full Saturday for for shopping right before
• 13:01
  Christmas that. Day Understood.
• 13:03
  OK, that's fantastic. I mean so much to unpack and I
• 13:09
  guess that the other thing that retailers or folks that work in
• 13:12
  retail or sell to retailers are thinking about our our NRF you
• 13:16
  know looking at what, what, what, what's that all about,
• 13:21
  what are they, what should they be focused on?
• 13:24
  You you you're going to be there, you're going to be
• 13:26
  talking what what do you, what's your focus this year on NRF?
• 13:30
  Yeah. So I'll be doing a few few
• 13:32
  things that are up. So one of them will be talking
• 13:33
  about our traffic data. I think we are also kind of in
• 13:36
  the early stages but we are planning to expand our our kind
• 13:39
  of benchmarking data. So this data is based on the US
• 13:42
  but we are in the process of expanding, providing
• 13:44
  benchmarking data on more of the the UK, the EU and the Middle
• 13:48
  East as well. So you know hopefully during
• 13:51
  that time, I don't, I don't want to promise yet, but we are you
• 13:53
  know planning to kind of discuss some of the traffic trends that
• 13:55
  we're seeing in those regions, do a little bit more with the US
• 13:58
  as well with what we've been seeing kind of a post you know
• 14:00
  holiday recap will be in January at that time be able to recap
• 14:03
  the Christmas confested period, you know provide some details
• 14:07
  there and then I'll also be providing some more information
• 14:10
  kind of around the work that I do with our retail lab.
• 14:12
  So that was where I kind of mentioned at the beginning of
• 14:14
  the call. We do also do and the majority
• 14:16
  of the work that I do is actually in retail lab.
• 14:18
  We'll put multiple sensors kind of all throughout the store to
• 14:22
  provide those e-commerce style analytics, not just at the door,
• 14:26
  you know entry point to the store, but as users are
• 14:28
  shopping, as they're moving throughout something you can
• 14:30
  really understand more about the shopper path.
• 14:32
  So you know, one of the sessions that I'll be talking about will
• 14:35
  be highlighting some of the work that I've been doing with one of
• 14:37
  our customers on that side of things as well.
• 14:40
  Making the invisible visible, right?
• 14:43
  Exactly. Yeah, exactly.
• 14:45
  I. Agree.
• 14:46
  That's an interesting thing because that's like something
• 14:47
  I've been, you know, my whole career has been in creating or
• 14:52
  transparency in the path to purchase and understanding
• 14:55
  people shopping missions. I'm just curious, is there, are
• 14:58
  there any snippets that you can share with us in terms of things
• 15:02
  that surprised you by that? Because obviously I always get
• 15:05
  surprised myself when predict, but I was just wondering is
• 15:07
  there anything that surprised you when you were doing that?
• 15:10
  Yeah. I mean, well, I mean, there's
• 15:11
  been so many projects. I think for the most part, what
• 15:13
  I would say is I'm sometimes surprised by the unique nature
• 15:16
  of a lot of the retail stores, right?
• 15:18
  Like you think there might be something, there's definitely
• 15:21
  takeaways that you can make. But typically every product that
• 15:24
  we work on, the store, the layout being very different and
• 15:27
  unique, there's always different kinds of findings and different
• 15:29
  trends and different ways that you can drive shopper movement
• 15:33
  through the way that the store is laid out, right.
• 15:35
  So some of that can be bad, right?
• 15:36
  If it's too blocked or there's too much congestion, there's not
• 15:39
  enough flow to get to certain parts of the store.
• 15:41
  So, you know, we can provide metrics to customers letting
• 15:44
  them know, you know, what does abandonment rate look like?
• 15:46
  How many people are coming in the store and leaving you know
• 15:48
  before actually engaging with the product.
• 15:50
  You know we can have different methodologies for doing that.
• 15:53
  But you know we can also provide details on you know what
• 15:55
  proportion of customers make it to certain areas of the store.
• 15:58
  So let you know where they kind of peeling off on that funnel
• 16:01
  where you potentially losing that conversion rate.
• 16:03
  And I would say you know for the most part that's that's kind of
• 16:06
  what I find is you know all these retailers are very unique,
• 16:10
  very different kind of paths to purchase, very different shopper
• 16:12
  journey. And I think that's what makes it
• 16:14
  so exciting to really kind of dive in and try to you know find
• 16:17
  those different tests that we can run those EB tests.
• 16:19
  I mean that's really the, the key factor of our platform is it
• 16:23
  really for those test and learn labs, right, where you're
• 16:26
  testing out a new fixture, you know, maybe one style of you
• 16:29
  know, putting the product folded versus one style maybe hanging
• 16:32
  it on the rack, testing out, how is that driving, you know, dwell
• 16:35
  behavior or traffic behavior or people just not seeing it,
• 16:38
  right. And then you can tie that to
• 16:40
  your sales metrics and understand, you know, not only
• 16:43
  that kind of lagging indicator did someone buy, but where did
• 16:46
  we maybe lose them on the funnel, right?
• 16:48
  Did we, did they even get them for the product?
• 16:50
  Do they even know that it exists, right.
• 16:52
  And if not, then maybe you need to move it to a place where
• 16:54
  there's more traffic, where people will see it or maybe
• 16:57
  there is in a great spot for traffic, but it's in an area of
• 17:00
  like a major thoroughfare and people don't want to stop and
• 17:02
  shop that. So you need to provide to give
• 17:04
  them you know a little bit more ability to kind of you know
• 17:08
  interact with the product and not be getting bumped into by
• 17:11
  customers that are moving through.
• 17:12
  There's so much kind of data that you can get through
• 17:14
  understanding customer flow and overall dwell and you know
• 17:17
  traffic to different areas of the store and you know working
• 17:20
  with the advanced analytics team of retail.
• 17:22
  Next, we can provide all other sort of custom metrics around,
• 17:25
  you know, how shoppers are are, you know, behaving in store and
• 17:28
  what they're engaging with and what they're not engaging.
• 17:31
  With, yeah, I mean it always surprises me how much retailers
• 17:35
  leave on the table in the failure of conversion upsell and
• 17:39
  cross sell because it's just like left to a a a dark art
• 17:43
  based on some POS data that they've got historically that
• 17:46
  says if they buy this, they'll buy that as opposed to physical
• 17:50
  data from what's happening in in the path to purchase or in that
• 17:55
  so, so. That's a great point.
• 17:57
  Just to jump on that. I mean that's a great point and
• 17:59
  that's kind of what we can also provide you know, with like
• 18:02
  adjacencies, right. So we can understand, you know
• 18:05
  this in the online space, right. If someone clicks on one link
• 18:08
  for one product and they click on another one for you know that
• 18:10
  they, you know, there's overlap there.
• 18:12
  Well, we can get to that with our data, right.
• 18:15
  We know that someone shop picture A and then we know that,
• 18:17
  OK, they skip picture B and picture C and like the fixture D
• 18:21
  So we can provide details on maybe what are some of those
• 18:24
  overlaps where maybe you don't see that in the sales data
• 18:27
  because maybe for some reason they're not converting.
• 18:29
  So you're not seeing that in their basket, but we're able to
• 18:31
  provide a little bit more of a perspective again on that kind
• 18:34
  of higher level of the funnel of where were those opportunities
• 18:37
  that might have been lost. And you know it even goes back
• 18:40
  to you know higher level data for for traffic and you know
• 18:43
  just conversion at the store is you can use this, this kind of
• 18:46
  data to compare your different stores if you just have sales
• 18:49
  data. And this kind of going back to
• 18:50
  your point about what surprises me most.
• 18:52
  I think one thing that I've seen is that really kind of drilled
• 18:54
  into like looking with some of our customers for segmenting out
• 18:57
  their stores and kind of clustering them because it
• 18:59
  oftentimes you'll think stores before are very similar because
• 19:02
  they have very similar, you know daily average sales or you know
• 19:05
  whatever sort of sales metrics you're looking at.
• 19:07
  But when you look at the traffic level, it's very different and
• 19:11
  that shows what the true opportunity of a location is,
• 19:15
  right. And that can really help you
• 19:16
  understand, you know, is this, is this store actually
• 19:19
  performing well? Do I need to maybe consolidate
• 19:22
  locations? You know, do I need to expand
• 19:24
  locations, right. It can really just let you know.
• 19:26
  Overall, what is that opportunity that you really
• 19:28
  don't have insight into unless you understand how many people
• 19:31
  are actually coming into the door or, you know, coming into
• 19:34
  the store through your door? Oh, absolutely.
• 19:37
  I mean look, there's been so many probably they're probably
• 19:40
  off record conversations where retailers admit that they've got
• 19:44
  this flagship store that already converts of the 10,000 people
• 19:48
  that have walked through the door something like 1% whereas
• 19:51
  their High Street branch that is under invested in, under you
• 19:55
  know utilized is converting a higher percentage of of traffic.
• 20:01
  So listen, Joe, as you can tell, I can carry on.
• 20:04
  It's a subject that I love in terms of dissecting why people
• 20:10
  do what and and what is happening.
• 20:13
  If people want to find out more about your research or what
• 20:16
  retail next they're up to, where should they go?
• 20:20
  Yes. So you can go to our website
• 20:21
  Retail Next, just Google for Retail Next will pop up.
• 20:25
  We also have some dashboards that are made available to us
• 20:28
  that include the data that I've shown here.
• 20:31
  So for our customers, we make them available.
• 20:33
  We do also make that available for some media as well.
• 20:36
  So you know that would be the best way.
• 20:37
  Just research retail next and then you know reach out to
• 20:41
  myself, you know my e-mail is justjoe.chastinaretailnext.net.
• 20:44
  Happy to address any other questions or forward those along
• 20:47
  to anybody else at the at our organization that can help with
• 20:50
  that. That's fantastic, Gerald.
• 20:52
  Look forward to seeing you at NRF, hopefully in a bar some
• 20:55
  way. Have a wonderful rest of your
• 20:58
  day. Thank you.
• 21:00
  Cheers. Bye.