VIDEO TRANSCRIPT:

Hello everyone, and welcome to Optimizing PCs and How the Computer Store and Academy Sports prepared earlier to protect conversion, brand sales, and margin. My name is Alyssa Miguez and I'm CDT's senior editor. We're going to get started here in just a few minutes, but while we wait for someone to join us, I'm just going to cover a few housekeeping items. First of all, the materials in the webcast have been reviewed by our editorial staff. The views of the speakers and their organizations are their own and don't necessarily reflect the opinions of CGT or its owner, Axel Nobel IQ. Though we try to make these webinars as interactive as possible, so please feel free to use the Q&A function to ask questions throughout the session. You'll find that on the left side of your screen down below the presenter headshots. We're going to answer as many questions as we can at the end of the presentations. If we don't have time to answer all of them, our speakers will follow up by email after the session concludes. You can also use the Q&A section if you have any technical questions throughout the hour, and you'll get a direct reply from our webinar producer. You can use this feature to also provide any other feedback that you might have. Finally, if you want to review the webinar later or share it with your colleagues, a replay will be available within about two hours of our conclusion today on ConsumerGoods.com. Okay, that does it for housekeeping. I'm excited to get started today. Welcome to today's webinar where we're going to be diving into how companies like the Container Store and Academy Sports successfully navigate the high stakes complexity of holiday peak commerce. You'll discover how deliberate early preparation ensures total platform stability, checkout reliability, and fulfillment accuracy. Plus what strategies these companies are implementing right now to proactively manage risk and protect their margins when it matters. when it matters most. Dominic said angel walk earlier. You've seen Chandra, chief technology officer at the container store, David Vicky, vice president of digital technology at Academy Sports and Outdoors, and our moderator today, Liz Pobistakalo, group vice president managing partner who was a CPA. Liz, I'm going to pass it off to you for intros and to kick off the conversation.

Wonderful. Thank you, Liz. All right, from one list to another. Hi, everyone. Thank you and welcome to this webinar. I'm Liz Papa-Sacalarieu. I lead our CPG vertical in North America for Publicis Sapiens and probably been in the CPG space for 20 plus years. So I'm looking forward to this discussion. I'll pass it on to David.

Hey, Vicky. VP at Academy Sports for Technology, customer-facing systems. I've been here for about 18 years. I've done just about all of it.

Mm-hmm.

I'm Hussain Chandra, previous CTO at the Container Store, and also have a lot of retail experience, about 11 and a half years at JCPenney prior to Container Store, and that's where most of my peak... recreation and activities and all these things. Nine years in a row I was with JC Penney's Peak so probably I'm going to talk a lot more about that today.

All right, we have some experts. So as Liz opened up at the beginning, holiday peak has become less of a single event and more of a sustained period of volatility. Customers expect flawless experiences regarding of traffic spikes, inventory constraints, they don't know what's happening behind the scenes, right? Or economic uncertainty. It's their product, their shopping. So today we'll explore how leading retailers. Retailers with David and Houston here are preparing their businesses, technology platforms, and operating models to deliver during these peak moments. So let's get started. David, let's start with hindsight. Looking back at previous seasons, what were the biggest friction points? Can you talk us through the specific technical or operational pain points you have faced, you and your team have faced?

Absolutely. Before we get into that, on behalf of the team and myself, I want to say thanks to everyone who joined. I think you'll find we're both very passionate about peak season and operational success. We're both a little nerdy, but I think that's going to work to work out well for us. Let's do a quick time check. I checked this morning and it's 126 days until Thanksgiving. So if you're metered to Thanksgiving and if you haven't started your peak season planning, maybe now's a good time.

Good advice.

Yes, absolutely. Let's talk about what challenges folks have had, why we've moved things forward, those kinds of questions realistically because we have to. As Liz said, delivering quality experiences in the face of sometimes 5, 10 and even 20x multiples of our sessions and our orders is something not to be underestimated. It is a big challenge. It is a big change. And we've all seen these issues, right? You know, regardless of the size of the retailer, you probably think that maybe you're the only one that has issues. I promise you, you're not. We've all seen some of these issues. We've seen hardware failures. We've seen service outages, all of those things that happen. have to be managed and have to be have to be understood and so ideally what we'd like to know is in the course of these activities how do we how do we learn where our limits are before we're actually in the moment of big season so that's how we that's that's one of the reasons we want to pull this forward these are the kinds of issues that we see from either from a process perspective or from even from a technology failure hardware hardware challenges as well

Were there any specific operational pain points that you can talk about now?

I would say we've seen more traffic than we anticipated, and you have to deal with that. Sometimes you have more success than you expect, and you have to figure that out. So you take more orders. Was the warehouse ready for all of those orders, for all of that fulfillment? Sometimes you're on the wrong side of that. Sometimes they are technology-based, and so those challenges we've seen before, and those are kind of more garden variety. But some of those operational things are what happens when you have more success than you expect.

Right. That's great. That's a good problem. Right. So Houston, what are your thoughts? Was there a particular incident or a near miss that made you and your teams realize peak planning needed to start earlier?

Oh, yeah. The first peak preparation that we did, first peak that I, when I was at JCPenney, was back in 2012. That's when I was involved in and then I was the lead architect for digital platform back then. So that was a year when we launched the new ADG Commerce. We just did a transformation and migrated from the 10-year-old legacy .NET to ADG Commerce back then. So 2012 was when we launched and also that was the first peak for the platform. And we did a lot of preparation months before that, right? We started in August, September, like we launched in July and then sometime in September is when we started doing a lot of load testing and a lot of hard work and late nights because we were literally doing it on the production system, right? We did all the load testing. And biggest lessons learned that year. So we did a lot of load testing because it's a new brand new e-commerce platform. So we did a lot of put a lot of focus there. And then And during Thanksgiving Day when the day comes, it's like, you know, when the work, when you, it's like the World Cup, right? You go to the tournament at least months before preparation for that tournament.

And it's time to perform.

And it's time to perform. And what happens was the e-commerce platform did really well. But what was not doing well was the back end, which is the inventory where we didn't really put a lot of focus that year.

Hmm

in performance testing that so what happened was there's a bottleneck in the inventory calls and stuff and then we see a lot of inventory calls getting timed out because our OMS system was was pounded by traffic and so what happened was we when we saw like majority of the inventory calls like timed out we have to make a call so there was like VPs in the room they had to make a call so one of the suggestion was let's just instead of like hurting our brand and like put put up the waiting room or spark page or site is down let's just turn off the call there's a flag that you can just turn off from the e-commerce side to the to the back end inventory right service

Oh, interesting.

So we decided to do that because at least the customer can still place orders. But guess what? The consequence is order

Over

cancellation.

promise.

Yeah, over promising. So over promising an order cancellation was a big deal that year. So a lot of customers getting disappointed and stuff. So that's a big lesson learned for us, actually.

Yes, definitely. That definitely that is a trend, right? One of the one of the myths people think is that, you know, traffic is the biggest high traffic is the biggest risk, right? But to your point, it's do you have the right inventory, the right order management, the right checkout process? So absolutely a lesson learned. Absolutely. So this naturally leads to the question of how technology teams are becoming more proactive rather than reactive. Absolutely thinking about the full end to end. So now let's explore. probably one of the most important things revenue right so how do you protect revenue through your technology so starting with houston during peak season an unstable website or crashing checkout means immediate loss of revenue and lost customers to your point right like those are the kind of things that you were like how do you turn on what do you turn off from a pure it architecture standpoint what are you doing right now to support and de-risk you the broader business of what did well you know what did you do coming out of that year for the following year

Yeah, so right after that incident that in 2012 that peak, so one thing that we did was definitely we kind of like pull forward the peak preparation so that we can have time to test the end-to-end ecosystem, the pre-purchase, right? uh which is the dot com site and then also the post purchase the oms and downstream so that's something that um we started doing right it's the end-to-end it's not just the e-commerce site it's just you have to test oms and all those things and you have to create test orders that actually goes into the messaging system and also goes into the downstream distributed order management system and stuff so so that's the the thing that we we learned from and we started doing it like every single year whenever we do the test we'll do all all channels all omni channels plus also the downstream all the way down to OMS and we have to create test orders to make sure that the downstream system are not taking that as real orders right so basically systems has to change to basically understand those those test orders and it doesn't go into the BI analytics downstream as well and

That's right.

all those things getting filtered so

That's right.

that's that's one of the lessons learned and in terms of like brand or damage and all those things so that year we had a choice of whether we want to put up a site and stop the customers from from ordering or we just let them order and then we of course we pick the letter right we just pick the one that okay that's not we made this point a customer but let let the order comes in so that's something that we don't want to do back then from the leadership team as a company.

You have a question on that because, you know, it's a tough decision to make, but then also you want to retain customer loyalty, right? So we're going to get into that a little bit as we continue the conversation. So David, you know, adding on to this question on top of that, how do you decide where to invest? Is it in scaling infrastructure, improving observability, automation or incident response? Like, you know, how do you make sure that you're not losing? that revenue or losing customers.

Yeah, I think I think it's, you know, we'll talk about this several times today.

Mm

I

-hmm.

think you have to have a good understanding of what your business plan is, what the forecast is, what the business expects. And you have to have, you know, this customer talked about the fact that they were doing performance testing. I don't think we were having the same issue in 2012. So you can kind of relate. But in practical terms, we were seeing some of the same issues. You know, we have to understand. what the business needs from technology and then we have to do the performance testing the spike testing the endurance testing all these things and if you can't support the business you have to invest in those areas so for me it still comes back to what is the business need from technology and how do we support that

Yeah, it's interesting to see how you would gather those requirements from the business, right? And you said 2012, but I'm imagining from 2012, even to today, the evolution of those business needs, like what have been some of those evolved needs from the brands that you've seen?

You know, from my perspective, I would say every year, you know, you've got delivery teams, pretendance, we had features on the website, on the mobile app, on the various places on the order management system, all throughout those 10 months. And then you go into peak season and you're using all these new features, but you have to have stress test all of that, you know, those three or four or five or six months before. So in our world, we kind of start right about June where we're kicking off today in this case. case for for the our peak season planning and we're going to run that all the way through basically October but but at the end of the day you have to take all those new features make sure that they all work under load throughout the course of obviously peak season

Yeah.

Yeah, and I'm sure you're testing out different features through other seasons that are not specifically holiday, like other big events, I would imagine.

And in our case, we literally for every release we do a we'll call it, you know, we can get into some detail here, but like a 2X load test for each regular release. And then we have a slightly different model for peak season because those levels are even much higher.

Absolutely.

Yeah.

She's in your essay.

Yeah, to add to that, I think if you think about the requirements, like every single year, we always collaborate and work with business to understand what is the sales goals volume, what is the traffic volume, and what is the order rate. We normally use order rate per hour, like those type of things to help us assess like how much capacity that we need, right? Sometimes we need to buy more. uh to basically expand more if you're not in a club if you're on brand maybe you have to buy more hardware maybe so those those are the things that um like uh that we have to consider uh in terms of investments and stuff

Absolutely.

Okay.

So, David, how has the IT, so speaking of like preparing, you're in June, you start getting ready June through October, and you even talk about other requirements throughout the year, like how has the IT strategy evolved to ensure you can accurately predict and handle the seasonal inventory trends? How can technology help position inventory for high demand items closer to consumers before peak demand? hits, I would say.

You know, I think the short answer is the data, right? One of the things that we've evolved over time is, you know, we were probably pretty immature in that 2012 period, even how we thought about a load model, you know, what percentage of traffic is going to the homepage, what percentage of the traffic is going to the PDP and obviously down the funnel and into post purchase. And so I would say at that point we were pretty immature, but then over time we said, hey, we need to. understand this data better we need to know where the inventory is you have to understand in this case what the business wants to sell that year you have to understand your customer you want to know what they want to buy and then based on that you have inventory levels and then realistically you execute peak season throughout that period and you're monitoring okay how are inventory levels you know sitting at the level that people are buying and are we going to run out of that inventory before ultimately we get through the end of peak season. And so you're taking certain steps to do that. Sometimes you adjust margins, sometimes you adjust other things to manage sort of that incoming revenue, that incoming business flow to help make sure, and you're putting things like, we'll talk about focus, for example. For customers, we want to replace Bobo's orders, but sometimes those Bobo's orders sit in the store for a week or more, and you have to decide, do you let that inventory still sit there, or do you make a kind of a tough business call to say, hey, we're going to let these orders cancel so that inventory can go back to other customers, and so you have business decisions to make really throughout this process.

How often are you bringing the business along with you or are you making these choices on your own?

It's absolutely business technology partnership. We meet in our case, we meet every morning from we'll call it 1126 November 26 almost to December 20th or something like that, right up to the point of shipping cutoff. We're having daily meetings. How much revenue is at risk from a bogus perspective? You know, where are these SKUs, the top performing SKUs? When are those about to run out? Those kinds of things. So very active.

Absolutely. That's how I see in our experiences. From a public safety saving perspective, sometimes we're in the middle and we make sure that the business and technology are working together because you underestimate how important that is. So that's how I see it. And using like adding on to what David said, are you relying more on we have to talk about AI? Have to come to this conversation. Are you relying more on AI, predictive analytics or real-time signals than you were a few years ago and how?

So I think AI, I mean, the evolution or revolution of AI in recent years definitely helped a lot, right? um even prior to that uh prior to ai when if you move to if you did a digital transformation from on-prem to the cloud and make it uh cloud native uh you know api first those type of things like the mac alliance right um

Right.

once you if you the more modern architecture allows you to like you have self-healing you have uh you know auto scaling and all those things features right if you use the serverless features that all those hyperscaler uh cloud providers have so so that's that's the biggest um uh benefit and and kind of like a that i see for improvements but ai definitely helped a lot in terms of understanding um try to proactively figure out and alert you like what is you know is do you need do you need more capacity you know is something wrong and all those things even without ai before we can we can still fire the alert but with ai i think we can be more more accurate more advanced although we haven't tried yet right so when i was at a container store we didn't have the you know five to ten times five to ten x that capacity But the AI operationally, the one that we normally kind of like use is more from kind of like the engineering side, like code delivery, code assistance, right? It makes the entire...

velocity for time to market for a new feature and enhancement a lot faster because uh the engineers don't write code from scratch anymore right

That's right.

even automation code like all this python whatever script for all this automation you can just buy code books and then use ai to do it so that's that's the biggest benefit that i see even from a product management side If you have cloud kind of like integrated with Jira, all the ethics and the storage creation, all this mundane work can be shifted to AI and then the human, the product managers and product owners can start using those brain space to come up with new ideas to solve business problems. So that's the biggest benefit that I see with AI.

And that takes absolutely that brainpower to like think about innovation, think about like what's ahead. How do you think about, you

Absolutely.

know, facing any kind of new product that is in high demand and how do we make sure that our customers are happy? David, how are you thinking about AI in your space?

A lot of the same. I don't know that the... The full potential of AI has been proven. There's such potential and everybody knows it, right? We're using it a lot more diagnostically. So even as you have an issue figuring out whatever analysis needs to be done, that is absolutely happening. The codicist use cases, we're obviously doing that. Everybody's, I think, doing that to some degree. But is it helping peak season yet? I don't think we're quite there yet. You know, we have data to. To who since point, we hadn't predicted sort of analytic before in a more traditional ML type model. And we had some of that and we know how many orders we get per year and we know how many sessions we're getting and how many mobile app downloads and those kinds of things. But but I think the AI story is still being told still being written.

Yeah, maybe not somewhere you want to experiment during holiday season. Maybe not.

I

Not

think you do use

yet.

it. You still use it. You still use it. I think you have to be careful when you put it right in front of the customer.

Exactly. All right. So even with AI and great forecasting tools and the data. It's really about your customer experience and their expectations because, you know, even though it's a high inflation environment, consumers are less forgiving of any kind of mistake. So, Houston, from your perspective, how much margin or brand equity is actually lost when the site lags or delivery promise is missed during the holidays? So, to your point, that time you decided to keep orders going. But you may not have been able to fulfill. So like, what were the consequences and how were you able to recuperate?

Yeah, brand equity wise is very difficult to measure, right? Because whether or not you're putting up a, we used to call it a spa page or the waiting room page or maintenance page saying that the site is down. Would you see a lot of retailer like Best Buy, Target and even Lowe's had it before in the past, right? I think if you see that sometimes whether it's because to me it's more opportunity cost because if your site is down during Black Friday, then during that time. Your customer may go somewhere else to buy the same thing.

I was going to say you've lost them.

That

They're not coming back.

unfortunately causes more apparent and easier to measure than brand equity or margin. Because at the end of the day, it's like let's say in that hour you can make like $4 or $5 million. So in that hour if you're down.

Yep.

And that's $4,500,000 cost.

And that's

That's how it is. The entire data is $450 million. That's your opportunity. Yeah, exactly. So, yeah.

not only the tech, right? That's not only the web traffic, it's. That's obviously the revenue that you've lost, but then all the other efforts that have that, you know, investments that the company have made to drive traffic there, you know, that's a waste. That's a waste.

all those marketings are wasted like you said because now your site is down to go to your site you can't even purchase anything that's the reason why we pick the you know turning off the inventory call because we still want people to come to the to the site but their order may get canceled so they will get disappointed but they'll get a gift card so that's something that we kind of like how to remediate from the customer loyalty perspective and all those things

That's actually a really nice, I was going to ask if you have any kind of incentives. So that's

Yeah, there is incentive like gift cards that

good.

we give the customers for cancel order so that or we have proactively ask the customer service to call them and all those things that say sorry and stuff right so that's that's definitely there

Yeah, I mean, from a consumer perspective, at least, you know, makes me happy to know that you have seen me in any kind of way, right? So David, how about you? What do you guys do to kind of help, you know, retain margin or brand equity? Do you think customers remember a bad holiday experience longer than a good one?

I think it depends on how bad it is, right? If a website's down for an hour, I don't think they're quite so punishing. If you told them they're going to get their order in two days and you cancel it two days later or that takes three days or five days, particularly during December and when Jimmy's waiting for his trampoline and it doesn't come and you ruin Christmas, they will remember that forever. But an individual outage, even if it's a little bit longer. They're probably a little more forgiving than those things where if you've made a promise, you have to you have to commit to that promise. You have to be able to deliver to the degree that you can on that promise.

Yeah, I mean, it's hard. What do you do when it's like a third party shipping fulfillment and it's really out of your hands? It's left your warehouse. And I'm maybe speaking a little bit selfishly because that was one of my experiences. Hey, Taylor, they're like in two days, give it to your point three days and I'm waiting and it was a holiday period and I'm waiting and they're like, well, now it's with third party. It's out of our hands. What do you do for your consumers?

You do the same thing that Houston said, you give them money, you give them a gift card, you apologize, you hope they come back. But ultimately, it's a terrible, terrible brand experience. It's a terrible customer experience. You know, we try to do, we do all the things that we do architecturally, right? We have multiple systems, we have redundancy, we have secondary, you know, partners that can do this. And so you send the, you know, the Siebes of the world or the other white glove carriers of the world or whatever the case may

be.

the case may be, but ultimately you try to have all of that redundancy almost everywhere you can, but sometimes you cannot.

Right. I know. You do the best you can. All right. So Houston, let's talk about data. You've mentioned a little bit looking at the data, David, you as well. How are you using data to move away from panic discounting, which is another key topic that's happening, right? So instead of using targeted promotions to protect and instead of using targeted promotions to protect your year-end margin. So like, what do you do if things aren't. moving the way they should be and all of a sudden you're like should we be discounting should we not what what are some of the tips that you have for us

Sure. Of course, that's more of a business decision, right? So the business, whether it's any retailer, I'm sure academics boards do the same thing. They have this. price elasticity model and research and make sure that whatever price that they are targeted discount for certain holidays especially for peak between Thanksgiving and Cyber Monday uh that week i'm sure they they did a lot of uh research and model to a point where they will try to you know margin of course is going to be very thin during that time but at the end of the day is the margin dollar that's coming in right it's not really that margin percentage so in retail i'm sure that's that's the the fundamental and i'm sure that's going to be you looked at right so that we don't have like all this last-minute discount but sometimes business do that because let's say if they

Well,

were

you have to, right? If another,

there's

right.

a lot of regulatory is whatever that they discounted did not did not sell some of the potentially hot skews did not did not become the hot skews so those will will be kind of like marked down right even further and all this thing so sometimes they have to pull that lever but most of the time I see the business are doing a good job in terms of using whatever previous data that they have from previous years and use those predictive models and come up with the right pricing for for the holidays or for whatever events

Yeah. Awesome. So David, adding on to that, on top of that, how much more confidence do better forecasts and customer insights give you when making pricing decisions? I know it's you and the business, but what's that confidence level?

No, I think a good merchandising plan.

Yeah.

Yeah, I think good merchandising plan and understanding of the things that are going to drive volume in your plan versus the things that are going to drive margin in your plan. A good understanding of that is really helpful, I think, from the perspective of let's assume that in one of those, you know, scenarios, a particular set of SKUs doesn't pop as much as we thought. But you know that over the course of the rest of peak season, you can make that back. You have. And in this case, if it's a Black Friday retailer throughout the course of December, you have a reasonable expectation to get to those numbers. You have other products. You have a sort of a rich and a robust merchandising plan to get through peak season. If you don't have that foundational data knowing where the margin is, where the top line is and have an understanding, OK, we're hitting it up here, but we're not hitting it down here. You obviously want to make those tactical decisions, but you don't have to get into that scenario. of sort of panic discounting.

Yeah. And hopefully you've placed the right bets on those hard items on your list, I would say.

Wind hurt,

Exactly.

wind hurt.

That would be the magic, the crystal ball, right? All right. So David, so you have a lot of experience each year is a new year, I would say, and there's a new lesson learned. How do you formalize those lessons learned? To begin the cycle for the following year. So like you're you started you said you started in June already How do you start to formalize that process

You know, I think it's a culture thing, right? I think you get an organization aligned with the fact one customer always comes first to you talk about the fact that. what this means for the business, you know, peak season, a lot of companies talk about this number, you've seen this 40% number, Amazon quotes numbers that on Black Friday, they make 30% of their annual revenue, those kinds of things, some of the obviously the prime day similar things, but in practical terms, you have to have an alignment with your business of how important this is. And then you start doing the tactics, right? You have you have a business retro where they take a look at what they're doing and say, hey, These are all the things that we could have done better. These are the things that we did well. They're doing their retrospective. IT obviously is doing their retrospective. How well did we execute? Did the systems perform? Did they hold up? Did they handle the volume? And even at executive level, you have lookbacks and similar things like that to say, hey, this was my tactic. This was my plan. How well did I execute this from a business perspective? And then ultimately you do that. But I think the most important piece of that is just that alignment with. business and tech of how important this period is for the retailer.

Yeah, I love that you say culture, right? It does seem that you guys have a really nice culture between business and IT and it's a great lesson, I would say. And so the holiday has passed Houston. How quickly after peak do those writing conversations begin?

The planning conversation after peak?

after people yeah what what's next like okay

yeah

I'm not gonna let you breathe how do you start to plan for the next

first of all i think you do the retrospect and you look at what what what went wrong during you want to look at what went wrong and learn from it right like a 2012 uh uh incident that i i talked about at jt penny And every year there's going to be a different incident and you're going to see something that you can improve on and stuff. And then one of the things that we always plan ahead, once the rest of the spec is there, then you try to figure out like if you want to test all the systems within the ecosystem, how much time do you need and stuff, then you start planning. And a lot of times... sometimes it's not the peak season that is captured by space some some marketing campaign which

Hmm.

originally does really well and there's a spike in traffic and you suddenly don't have that capacity you don't have enough capacity to handle that so that's that's the that's some of the surprises and stuff right so that like like David said that collaboration that close collaboration with businesses to understand not just the peak but also every single marketing campaign and have technology team understand the marketing calendar throughout the year that that is important for for planning throughout the year because you just don't want to do it for the five days during thanksgiving and cyber monday right so you want to do it throughout the year and as a matter of fact if um container stores peak is not really the those five days between thanksgiving theirs is actually the alpha sales after peak is their is their peak right um which starts in december till february and like their largest biggest marketing campaign i was there back in 2022 it was february 22nd 2022 it's 2222 and then that was one of the best marketing campaign that i've ever seen uh even better than some of the one that nike nike used to have right and and it's about um show me your drawers and then they have this celebrity her name is um and i forgot the name her her her oh drew barrymore drew barrymore yeah her her birthday falls on february 22nd and it was a year of 2022 and guess what our discount was 22 all of the time so basically 22 everything and it was on tiktok it was so viral and it almost crashed our site and then what then happens on 222 so i remember that day very well because that was the biggest dot-com digital sales day for the continuous war and the history of continuous war right the largest one so it almost brought down the site but almost

Almost.

Yeah. And to your point, though, like from from from a container store perspective. Yes, it's holiday, but it's then the, you know, January, February, it's the New Year's resolution, clean out the house, start new. So even your season definitely continues even, you know, like and David, for example, your side, you're starting back to school. Your school probably is just as hectic, which is happening like now, soon. I see it already on the site. It's just as hectic as, you know. holiday time period,

Yeah,

I would say.

for us, there's a couple of mini peaks. There's Father's Day, there's Back to School, and there's obviously the traditional peak season.

Absolutely.

Yeah, the other thing I would add to what Susie said, you come out of your retro, and then ideally those things feed into that year's roadmap. And so what you learn during peak season goes into the product team's roadmap, and that makes it into features that ultimately help you execute next year's peak season better.

Yeah. You know, you guys talking about culture and how it informs trends. you know, you can get caught off guard, obviously, but how do you prepare for like massive volume spikes? I think you've met, you've both talked about it very lightly, but you know, maybe let's get a little bit more into the details and like, how do you ensure that the platform remains stable across the different audiences and channels? Because, you know, if some influencer all of a sudden starts talking about their water bottle, David, you know, you're going to get inundated with that. for that water bottle. So, and you don't know when it's going to happen. It can happen this morning. So how do you guys prepare for that high volume?

You know, I think if I was going to say the same thing I'm going to say here, you know, one is the architecture itself. So scalable architecture, there's going to be some references to cloud native technology ultimately. We want to be able to scale to the level that our business needs. We build, you know, we're sort of religious here about performance testing. And so we do a thing where we say, okay, this is what the business says they need. We don't really think that's the right number. So we add a little bit to that number. And then we run that as like a 1x multiple. And then we run a 2x of that and a 3x. And it's very sort of expensive. It's a lot of infrastructure, whether cloud or physical, but ultimately you're sort of. planning for the unforecastable, right? So something

Right.

that like beyond the, you know, so beyond the expectation so that you can eliminate the variable of where we might have gotten this wrong, where there's one service can't really handle it. How do you handle that? You handle that with some of this additional infrastructure and ultimately the form of testing around it.

That's awesome. Houston?

Yeah, I 100% agree with David. I think the... Whether or not it's on-prem or the cloud, right? Cloud gives you that flexibility where, well, if it is on-prem, you need to have that five to ten X system capacity compute in

Mm-hmm.

the data center, even though it's not being used, only being used by those five days during the cyber week. So. what cyber holiday right so in that's why we moved to the cloud uh for jcpending back in um 20 from 2016 to 2018 is when we started the migration to the cloud so that we can get that elastic compute now that elastic computer is very important because you like during the um regular month in a year we the jcpending only do like a two x of the capacity there deploying three available zones within AWS right only up to 2x like if your average is about you know 5,000 orders order rate then you have the capacity to handle like 10,000 order rate that's that's pretty but the peak is like 60 like their their highest peak that I've seen was 60,000 order per per hour rate so you have to basically do a 5x um like in a month of uh you know between november and december right so that's that's the thing so so you basically just have to basically assess that's why you need all this um rigorous testing to understand how much capacity do you really need but if you're in the cloud it's a lot it's a lot more flexible because you have that elastic compute you can just first the capacity and then just shrink it back when you don't need it right

Yeah, absolutely. All right.

Makes sense.

So I think it's great. I have a couple of things.

So at the end here, which is going to be exciting. But so David, as we look to the future, now let's think about the future. How do you scale these peak season strategies across, right? Are you moving towards a more scientific data-driven framework for planning and demand anticipation? What are you thinking about for the future? What would you hope for for the future?

You know, I would say. You know, I don't want to lead with AI, but I will, you know, more from that side. And I think we will see that we're starting to see, you know, the hope we say we have the hope we're starting to see the fulfillment over time, you know, continue that that good relationship with the business, understanding what their needs are, what our needs are using data to make our decisions, not instinct and not emotion and not, you know, those kinds of things. You know, I think in the question you talked about how do you how do you. You partner, you know, how do you work with your partners? Right. In our case, we have a model where we literally look at every third party integration. We sort of assess them from a risk perspective. How important are they? How critical are they from the experience? And so check out and payment providers are super important. Other things maybe not quite so important. And then we have meetings with those folks. Some of them we meet weekly. Some of them we meet quarterly. Some of them we meet a couple of times a year. And so ultimately, you're making sure that they know what we're doing, they know when we're doing it so that they can make the same plans that we're making, that they're doing the degree to the degree that they can, they're also doing their own performance testing. And so you're just partnering with those folks, but all of it using data, data of what order level, what volume level we saw last year, what are we seeing over the course of this year, what features did we add to drive even more volume. And so making sure all of that comes into this comprehensive plan.

Absolutely. Hussein, how about you? What's the future look like for you?

The future looks like, I think in retail and especially in digital for.com, I think that DNA of your site has to be highly available, highly performant, highly scalable. I think that has to be there in the DNA, right? Meaning that. You don't just try to, you know, last minute do your homework within the last two months before the peak happens. So because like I said earlier, there will be some marketing campaign, which is surprisingly good with your business. It will bring down your sales.

Your sales.

So those are the things I think the DNA has to be there. And I agree with David that like with. maturity of AI I think you probably already see that right now that even for those hyper scalers they're like all those auto healing and auto scaling capabilities it's a lot more accurate and more predictable with with the new AI technology right although that that technology has been there for at least you know 10 years now but I think they just replace it with a more mature model to make it more predictable and more accurate in terms of whether you want to scale this to x through x whatever right so that that automation is going to be there and then for alerting as well for you know people who jumped on on the on the bridge call to make sure that they handle all this critical incidents and stuff I think those those will will be there as well right so I think most of the operations, especially in DevOps, where if you have a DevOps culture or SRE, site reliability engineering, most

Yep.

of those automation will improve with AI, whether it's LLM, whatever, but it will definitely improve. And operational excellence is going to be very high, I think, in the future. and it's just that human is always more creative right we'll come up with something to figure out how to make the

still more creative still all right so what i heard about from you said on you know how that uh elasticity of volumes helps you get prepared so david finally if our product suddenly goes viral tomorrow Or this afternoon, how confident are you that your technology platform can respond in real time? And what are those capabilities that give you that confidence? Like give us a couple more nuggets there.

Yeah, well, I'll say fairly high confidence. A single product, I think, shouldn't affect either of our platforms, right? You know, we're sitting on 70,000, 80,000, 100,000 products on a given store or on a given region. any one product shouldn't be able to do that. He said auto-scaling. I'm going to say the same thing. All of those technologies, you've got multiple stacks, you've got multiple providers, you've got enough redundancy really, even if this one tips, that the other one can pick it up. And so you've done a lot of good work there. Auto-scaling is going to be a big piece of it. The only thing I'll add, auto-scaling, you know, we talked about it like it's sort of a silver bullet. While these systems are scaling, there is a little bit of an experience. It's impact. And so we have to be very close to that to make sure that even while it's scaling up, is it slowing down? Is that affecting customers? Are you losing, you know, losing brand, as you say? So these are things that we have to be close. We can't just rely on the fact that there's this tech and the tech is going to solve the problem.

That's

We think

right.

that way a lot of times and we're not always right.

Yeah.

All right. So as we're wrapping up, right, if you could give one piece of advice to our audience today as you get in or as you are in 2026 peak season, what would that be for both of you? Houston, I'll call on you first.

Well, like to me, just make sure that. For the peak season and stuff, just have peak as part of the DNA. Every day is to

It

me is. really a peak. So that's something that I think I would just give the best piece of advice is like I've seen a lot of people even when I was at Nike that there was a global event. It wasn't really it was a global 10k running event and that one because there's a lot of spike on the Nike plus like back then. A lot of times it's some marketing event that drives those traffic. So you just have to be always prepared. And now with the newer technology, with automation, you can prepare that if

Awesome.

you use it right. Technology

Technology. David, one

Yeah,

piece of advice.

that's sort of the point I'll start with. There's a quote, how you do one thing is how you do everything. So I don't know if every day is peak season, but every day should be able to be handling a volume or load like peak season. So like we talk about it in sports, right? How you practice is how you play some of those kinds of things, right? I would say. The one guiding says, you know, understand your customer, understand the plan with your business, partner with your business, you know, very closely, very interactively. And I think the rest of it sort of works itself out.

Yeah, absolutely. So this is awesome. Thank you very much. A few learnings that I was capturing along the way is those daily meetings between IT and technology. super valuable also make sure that you have customer satisfaction so gift cards are always welcome to make the customer feel like they're being listened to and appreciated then have a good merchandise plan is what I heard also heard volume is better than margin sometimes so that's something to think about definitely

You get to pretend like.

customer first is what I heard from you. I also learned about scalable architecture and auto scaling. I heard about having a good relationship not only with your business, but also with your partners, which I think is key, and use AI to allow for innovation. And what I love about, you know, working with my clients in this in this space and this conversation that I have is at the end of the day I do really think that you guys are the heroes this this work is the hero of making a business successful so you're really hats off to the hard work that you know these teams do and and when I you know at the end of the day every day's peak would be my my headline of today so I'm gonna open it up to Liz D as so we can take can take on some additional questions from the audience.

Thank you, Assistant David. So we're going to move into Q&A. We do have a few audience submitted questions. The first one, David, why don't you kick us off here? How do you stress test your external vendor APIs?

usually over their objection I'll start there two two things happen you know it's kind of funny one is they say we're so big you can never tip us over and invariably sometimes that happens and so that's why we're so religious about the performance testing but ultimately we build a load model and we talked talked about earlier everything from home page all the way to the checkout page the order confirmation page and you call those all those APIs is uh we've seen uh mentioned this um and i think we probably work with the same guy on this but but we built a framework in production that you can run test orders through production they have a special email address so they don't get shipped to customers and they have some special things and they don't get analytics and they don't get conversion but that you can hit their apis you can hit your apis and it's the closest you can get you know i'm at my opinion to a true test of what What the experience will be in production for your customers.

Great. Do you have anything to add to that?

No, I think, yeah, of course you have to. So after that, it's just you have to give the vendor like at least, you know, 30 to 60 days of lead time, you know, before you start doing the load tests on their systems. And you want it to be to be production, right? Even for the CDN, you have to also actually inform that, hey, we're going to push this much load on the CDN side. So we just contact with the CDN. That's the only thing that I'm stressing

really

about.

great uh we have another question here she's seen uh you've talked a lot about readiness but how do you actually define success quantitatively aside from the obvious metric of like site didn't crash what are the two or three technical ppi dashboards that you watch closest during a major traffic surge

Yeah, of course, I think I mentioned earlier, one of the things that we used to... uh size the capacity we need for peak season is the the order rate right from business or the sales goal sales goals and order rate and from there then we look at the you know the pps and all those things for for each systems the transactions per seconds and all the things how much each one can do so those are the metrics that we we normally gauge but also the sales is the one that is actually like From the people and the culture side is the sales that actually makes more and the order like when you hit or exceed that order rate that the business projected so I think there's like a huge you know gratification in the room right you usually have a war room just for the peak season and that that culture I miss that actually after after the COVID I think that That kind of like a ceremonies or that type of a rigor is actually I didn't see it after the COVID happened. So I told you I've got a lot of people work remotely. yes when people are in the room of the water you

Because

see a lot

of remote?

yeah

You think it changed because people are remote?

Absolutely.

Does that make it a

Absolutely.

better sense of like satisfaction of meeting your sales goals?

the sales goal is the one that is actually excites the entire room whether it's a business uh world there's a room for business there's a room for it technology right both sides actually look at order rate and the sales there's a big big screen that is just order rate and the sales and then each you know each team will have their own like metrics for their own systems and but most people are looking at that like oh man we reach you know 60 60 uh you know we catered 60,000 orders order rate per hour that's that's a that's that's a big deal and um and that that is the the culture that I think um I miss a lot I miss that a lot so during those nine years uh I was every single Thanksgiving I was I was in the world I didn't really have a Thanksgiving with my family but but uh but I'm not uh you're

You're a marine,

right

you know.

because I'm a retailer but nine years in a row but it was fun it was it was hectic it was a lot of tough and hard work a lot of late nights but it was fun that that culture that you build is something that is not easily replaceable in my opinion

Yeah. I think always when we do like a post holiday review. Obviously, we first look at the revenue. OK, what did the sites achieve? Did we achieve the revenue that the business wanted?

Right.

And once we can have a good time with that, hopefully, right? Absolutely, you know, a lot of my clients are like, OK, so now let's get into the nitty gritty of the checkout, time on site, the experience. And that's how you start to think about what are those best practices. practices that you can put forward for the next planning session but definitely that number that revenue number is first but can't forget under the hood so

Yep

All right, I think we have time for one more question here. David, how did you approach the cultural change of moving the calendar forward and what kind of benefits did you see as a result?

You know, I think we had some of those issues that a lot of retailers have, you know, we sort of stubbed our toe and I'm going to say this is probably more like 10 years ago and we realized it was so obvious we needed to we need to do more in terms of prep, in terms of planning. We needed more time to do that. And so it was almost one of those decisions that made itself. We talked to our business partners, to your point, was P, we we have really good active dialogue with the business and said, hey, we're going to kick off in June or we're going to kick off in. in July, even if their kickoff doesn't start until August, but we felt from a technology perspective, we needed more time to work through the ultimately the load model and what their forecasts were and put all of those things together into a plan and there are operational tasks like flipping flags at different times on different days and content changes and all the various things and so it wasn't really that much of a fight. It was kind of one of those fait accompli things where it just it sort of happened because everybody knew we needed to do it.

Yeah. You know, and going a little bit back to that, that time during holiday when you're all together, I do see a lot of my clients going in that direction again. I mean, you know, we try to all be in the even in the same city together or definitely like these like team collaborative moments together. One of the clients we support is America's Zone. So we try to bring people that are in Canada and in LATAM in one. and room together as well during that holiday because you know we we talk a lot about our consumer our customer that is bringing in the revenue but we also have to make sure that we're taking care of our teams and they're kind of like in it to win as well so that's

Yeah.

part of that David to your point building that culture of of of a good team that will deliver on the holiday

Yeah, and I would say they're equally invested. When we hit a new record, they're as high as we are. They're as excited as we are. People are fully on board and they want to see those wins. They want to see the next best Black Friday in the history of Academy or whatever the case may be.

All the hard work pays off.

That's correct.

Well, thank you all so much. I'm afraid that's all the time that we have today. So big thank you to today's speakers and for people's safety if you're sponsoring. I will see everyone on the next webinar.

Have a great day.

Thank you very much.

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