S&S Activewear: Improving CX without perfect data

[00:00:00] Laura Turner: AI was a really big, scary thing when it first came out, and everybody thought, Oh, only the biggest and the best companies can possibly do AI because they're the ones who have the data. They have the systems. They know how to do it. But to your point, no one is there. I don't even know if we know where “there” is. So it's like we've kind of all got to just start. Sometimes we just need to start with good.

[00:00:25] Kailin Noivo: Join us on today's episode with Laura, we're gonna talk a lot about how you can use technology to improve the end-to-end customer journey. Really insightful podcast, especially on the imperfections of data and how to actually integrate AI without having perfect data. Everyone's kinda waiting for that really, really, really good episode. Excited for you all to hear.

[00:00:46] Kailin Noivo: Joining us today, we have Laura Turner. She's actually a fellow Canadian, so not too far away, and she's the Head of Customer Experience at S&S Activewear. Welcome.

[00:00:58] Laura Turner: Thank you. Great to be here. Awesome.

[00:01:02] Kailin Noivo: I actually reached out because you did another podcast, and I really, really enjoyed some of the insights that you brought up. So I'm really excited to dive into it. And like I was mentioning before, we haven't had too many CX experts on the podcast. So I always like to start off with understanding a bit more about your career journey and how you ended up in your current role.

[00:01:20] Laura Turner: Sure. Well, how long do you have? But anyway, when you get to my age, there's a bit of history. But, anyways, I started out kinda hardcore B2C marketing with 20th Century Fox Home Entertainment way back in the day when that actually still existed and moved from there into the corporate and imprintable apparel space that I'm now in, you know, it's kind of which is business to business to cost to consumer kind of. It's a nice, long kind of chain there in marketing, and I moved from marketing into operations, which is a bit of a left turn for a marketer, but it was a really good experience. And, you know, I ran the division in our company that was responsible for putting the actual imprint on the garments, so the embroidery, the heat transfer, the screen print, that kind of thing. So really interesting journey there. And then I moved from there into customer experience, and that was fantastic. And the company decided to stand up a customer experience function, and I was like, I totally wanna do that. That sounds amazing to me. And I've seen the customer journey from, you know, demand generation and all the outreach you do in the front end, right through to actually shipping a product and having them receive it at the very end of the journey. So I thought this is it, this is the thing for me, and I started that and have loved that journey. The company's been through a couple of acquisitions, and we're now S&S Activewear and super excited to be heading up CX and kind of reestablishing a function in this even much larger organization now. So, it's been a ride.

[00:03:13] Kailin Noivo: I mean, it sounds like, obviously, you have a ton of experience. You've had long stints with your, you've been very much with the same companies, right, even though maybe they changed in former name. Talk to us a bit about forming a kinda CX business unit from scratch, like, what are some of your biggest mistakes? And what are some of the things that you kinda nailed out of the gate?

[00:03:37] Laura Turner: Wow. Well, there's a lot, the list of mistakes is on, and I don't really call them mistakes, you know, like, I don't feel like that's the, exactly. It's like things we tried that maybe didn't work as well as we thought they were going to, you know, but there was always kind of something positive that came out of them. But, yeah, I mean, standing it up, it's one thing. If you've got your senior leadership's kind of buy-in on the function and the idea, that kinda helps really pave a path, because one of the first things that I kind of feel like I got right was trying to establish this idea of transparency, and CX, customer experience doesn't happen within one team in an organization. It's not the CX team that does customer experience. The entire organization does CX. So, establishing this mantra and this idea that everyone is on the CX team, I feel like was something that I kinda got right when Alphabroder, you know, first stood up this concept. And, you know, and then, we tried things. We tried different kinds of standardized metrics and tried to figure out customer lifetime value in our industry, and a couple of these other things that, quite honestly, in our organization, with the data we had, just didn't work. So there were some of these kinds of, you know, hallmarks of CX from a metrics perspective that we kinda said, we can't really figure that one out right now, given kind of the state of our customer base and the data we had about them, because it's kind of a continually shifting customer group. So that was one thing we had kind of okay, that can go away, but we really honed and worked on some of our other metrics and developed a really good cadence with our NPS surveys and introduced CSAT and some of these other things. I've worked really closely with our customer service team to identify the kind of the key touch points within that group that were impacting the experience. And we had a lot of success working hand-in-hand with that team. And, I mean, all credit to the leadership of that group because they recognize the need to, you know, improve our training and improve our integration across the organization in a, you know, what became a remote workforce during COVID. So, there was a lot of, the real successes came from partnering and driving kind of the mindset and the idea across the organization and partnered very closely with our VP of org development, too, who really was the EX to my CX. And linking those two together early on became absolutely critical, too, in understanding that you can't have one without the other.

[00:06:13] Kailin Noivo: Do you think that you would have done an effective job if you didn't have the operating experience from marketing, ops, and, like, different departments? Like, do you think you would have been able to kinda stitch it together from a customer journey standpoint?

[00:06:25] Laura Turner: It's an interesting question. I don't know if it was so much the experience of doing it. I mean, it certainly helped. I would say that it was absolutely an advantage to have sat in those seats and seen the business from that perspective because it just gave me insight, and I could actually speak the language better, but I think also having been with the organization through different iterations and in different spaces gave me visibility and kind of, I don't know, toot my own horn, some respect across the organization that when I was the one kind of coming to them and explaining this and having this conversation, they'd be like, okay, yeah. You kind of know what you're talking about. Okay. I'll listen to you, you know. So, it kind of gave me permission to have that conversation that, you know, I would have had to probably fight harder for if I were coming in from the outside or, you know, from a different place in the organization. So it's, yeah, kind of just, you know, the experience and the awareness and visibility I had across the organization certainly helped.

[00:07:32] Kailin Noivo: Makes sense. From some folks I've chatted with, like, some of the challenges are, if they don't have the context, some of their recommendations are, call it disconnected from reality, and then it creates a bit of a negative reinforcement loop where, like, it becomes harder to get good ideas pushed because some of your ideas don't make sense.

[00:07:53] Laura Turner: It totally does. Yeah. If you're coming forward with something that someone's gonna be like, well, I mean, we can't do that because we have this thing over here that absolutely actually stops us from doing it, you know, those kinds of scenarios. I think even if you don't have the experience from that team, if you approach it properly, you can still avoid that kind of pitfall because it's really about not making a recommendation to a part of the organization that you don't really understand. It's about taking a grain of an idea and saying, “Hey, I'm hearing this from customers. I think maybe this could be an approach. What do you think? Does this work for you?” And they would come back and go, “No, doesn't work. But if we turned it sideways and did it this way instead, that might work.” And then you go, “Uh-huh, okay.” It's about that partnership and never about assuming that you have the answers because, in all likelihood, none of us have the answers alone. We have the answers together.

[00:08:47] Kailin Noivo: No. I love that framing. And, just to kind of push this convo to a different direction, talk to me a bit about KPIs. Executives love KPIs, especially when you're standing up a new department. You'd mentioned earlier that some of the KPIs that were traditional to CX, maybe, doesn't work for every business. Maybe talk to us a bit about, like, what are some of the staple KPIs that you think every business needs to look at? And then, maybe what are some of the ones that are a bit more bespoke that could actually just be situational dependent?

[00:09:19] Laura Turner: Mhmm. I mean, I think that, obviously, if you're talking about CX, traditional CX, you know, NPS is kind of one of those kind of stalwarts that you can kind of, if you're consistently measuring that over time, you can at least understand how customers feel about their relationship with you, right? So that's a nice measurement, and I do think it's kind of important to make sure you've got that in place. You can't put all your eggs in that basket, because it is about the relationship. CSAT being your more transactional kind of, you know, touchpoint with customers is one that is, I think, really valuable. And if you can, as an organization, measure that. I think it's really important to understand in that moment that a customer had that interaction with you, you know, what was their satisfaction level? Did they actually, you know, did you deliver on what they were expecting? That's a really key metric. When you get to, you know, much more kind of, industry-specific kinds of things, I mean, in our industry, it's all about delivery to the customer, hitting our SLAs, you know, so we've got to get the order from them. We've gotta get the order into the system either, you know, via our website or via our service team. And then we've got to get it out the door to them. And it's got to arrive as they expected, when they expected, where they expected. So we also have to partner with our carriers, you know, there's a number of different kinds of stuff along that way, but, ultimately, for us, that on-time delivery metric and that accuracy and our return rates are really kind of key CX metrics even though they're not something that the CX team controls. And that was one of the things that, you know, when we first set this up at Alphabroder was I fought hard to try to get a bit of a dashboard across the organization that we could share with the more senior leadership. So everybody had visibility because when everybody can see what's going on, and you know, we have a number of different warehouses. And if you can understand that there are gonna be various issues that happen at various warehouses from time to time, and it could impact this. But if your senior sales leadership, for example, can see that and know that there was a massive snowstorm that impacted our Chicago warehouse yesterday, and guess what? We actually didn't get the goods out. They probably knew a little bit about that, but if you see it in a scorecard, they're gonna be able to share that with their team. They're gonna arm them ahead of time. This is where the EX comes in, because the sales team is gonna know, Oh, I understand what happened. Customer is calling me, I'm armed, I'm prepared to have that conversation with them. I understand. I'm not gonna feel like an idiot going, “Oh, what do you mean? That didn't happen.” Give them what they need. So, for us, a lot of those kinds of delivery-specific, any industry where you're delivering something like that is really, really important. And, I mean, when I was in the Imprintables Apparel, some of the key metrics were, you know, the accuracy of the imprint, the location of the imprint, all of those kinds of things. So it's every industry is gonna have their nuances, but it really comes out to measuring, you know, did the customer get what they wanted when they wanted it, where they expected it?

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[00:12:48] Kailin Noivo: That's interesting. And you've led some pretty big teams, like 140 plus people. How do you delineate your reps, CSAT or NPS, relative to the product, right? Like, for example, I'm messaging your rep. Where's my order? I'm gonna give you a negative NPS because the answer isn't being delivered this afternoon, regardless of how courteous you were, like, is that important to parse out? Like, how do you, as an executive, think of that? And then, yeah, it sounds like there's almost like a blended KPI. Like, do you parse that apart? Do you leave it together? Talk to us a bit about that.

[00:13:24] Laura Turner: Well, we haven't got to the point where we're able to really pull that apart from a KPI standpoint yet. It's something that, yes, you know, understanding the difference between product, this comes down to how we actually, you know, use AI to tag and identify the verbatim responses as they're coming in, because somebody can give you a score. Score is a score. It's just a number. When they actually go the extra mile and give you that verbatim response, take the time. Well, that's something you really need to listen to and understand. So we use, you know, well, I mean, quite frankly, I read a lot of verbatims too, just because understanding the customer's voice and hearing what they have to say just kinda really puts you in their shoes. But, I mean, for the number that we get in, we actually run them through an AI engine to identify them, and we have specific buckets we put them in. So we separated a product issue from a delivery issue from a packaging issue, you know, so we can actually pull those all apart and understand where the issues were and what's the bigger issue at this point versus, you know, the old one. And over time, you can see, okay, well, we had a huge on-time, you know, shipping project, for example, that we really dove into and we understand, and we worked with our carriers, and guess what? That's gone way down as an identified pain point now. So, and now all of a sudden, this thing is bigger, you know, we measure on our website, obviously, that kind of the whole thing mapped out there. But from a verbatim standpoint, we can do, as a customer, talk about how they feel it was slow. Are they coming up against an error that we haven't seen? Again, that's, you know, Noibu helps out with that kind of thing for sure, but how do you measure all of that over time?

[00:15:11] Kailin Noivo: Every company that I seem to chat with on the podcast where AI comes up…

[00:15:17] Laura Turner: Mhmm.

[00:15:18] Kailin Noivo: One of the hot talking points is always data cleanliness. And that's kinda like the grass is greener. I think everyone I talk to thinks other people have it more figured out than them, and candidly, I'm starting to believe that everyone kinda doesn't have it figured out, and this is, like, a pretty big challenge that everyone shares. Maybe talk to us a bit about, like, yeah, how are you thinking about implementing AI? How, quote-unquote, clean does the data need to be? Does perfection get in the way of progress? Like, I'm very curious to hear your kinda take on that.

[00:15:51] Laura Turner: Mhmm. Yeah. That is a really big question. And the more we kind of look at it, the more we try to understand, like, what's the right starting point, and you know, and then we have tried things and kind of work through different kinds of scenarios using AI. But if you don't start, you're never gonna start, right? Like, your data is never gonna be perfect because the reality is that we're just getting more and more exponentially, more and more data available to us. So it's not like you can just stop the world and say, “Well, right now, everyone just hold it. We are just gonna fix our data right now.” That's almost an impossible statement, right? Because if you've got more coming in and it's like, oh, well, now we wanna measure this, and then now we wanna do this, and now we wanna be able to do this, and we wanna tie it to this system and that system, we need to hear, you know, so you actually have to kind of just, at some point, say, you know what? We're gonna start trying something. Maybe we're gonna use AI to help us clean up our data. There's not a you know, let's put an agentic AI on top of that to help us go find the right data as we're trying to pull things together. So that's something that I think is a conversation that's starting to happen, and I'm hearing more of that when I go to CX events and speak to other CX practitioners that people are kinda starting to think, okay, like, AI was a really big scary thing when it first came out, and everybody thought, oh, only the biggest and the best companies can possibly do AI because they're the ones who have the the data. They have the systems. They know how to do it. But to your point, no one is there. I don't even know if we know where “there” is. So it's like we've kind of all gotta just start, and yeah. So, I mean, we're starting, you know, we've tried some conversational AI in our IVR process to greater and lesser, you know, success. We're now working on, you know, using AI to input inbound orders that are coming in manually. So, not our website, but we still have customers who wanna email in orders, and that kind of thing. So those ones, we wanna just run those right through, you know, an AI platform that we're testing out right now. Have that just grab and drop right into the system. I mean, that'll be a great time savings, it'll allow our agents to, you know, till we can repurpose them for more interesting and relevant and impactful tasks as opposed to just, you know, entering orders. So, yeah, we're just kind of trying to think, okay, this task, you know, regardless of what our data is doing, this task could be automated using AI. Let's understand how we could possibly do that. And when we do that, what about the people who are currently doing that? What could we repurpose them to actually do and actually have a bigger impact on the organization that way? So that's kinda how we're looking at it and trying not to get so down in the weeds about trying to be perfect because, to your point, you know, perfect will be the enemy of good. And, sometimes we just need to start with good.

[00:19:01] Kailin Noivo: I love that. Maybe talk to me a bit about one of the most impactful programs that you've worked on in the last decade, and what was kind of the biggest learning on the back of that? Maybe a bit more in the weeds.

[00:19:15] Laura Turner: Okay. I would say, you know, one of the things that we did when I first started in CX, when Alphabroder stood up the CX function, we knew, we were hearing a lot of friction from our customer service team at that point in time. We had just come, you know, COVID, the doors were kind of just opening back up, but we had sent our customer service team home to work remotely, and we decided to keep it that way, and then we had to hire people back. As the business started to come back, we're hiring people back, but guess what? We're hiring people into an environment that we have absolutely no infrastructure to support because we don't know what these people are doing, you know, like, we don't have, we were perfectly set up to bring a whole bunch of people into a big room and train them all how to do stuff and then sit next to each other at desks and, you know, figure out how to work you know, how to be a customer service agent for us. And in an environment where they were all working from home, it became really difficult. So we dove in. We did interviews. We you know, this was an example of where we focused on the EX side of things to really then be able to improve that CX because we were not giving them the tools and the training that they needed in this new environment. We came across a really great training platform that we introduced, and we added some gamification features. And we added a bunch of technology in our CCaaS platform to be able to kind of tie people together better, to create more of a culture, and to be able to give our supervisors better metrics and better visibility to actions and be able to coach in real time. And at the end of the day, we implemented that. And then two years later, we took a look at that, and we said, “Okay, what's happened to our training time, and what's the cost of that, you know? And what's happened to our turnover rate, and what's the cost of that?” And we figured in a two-year window, we cut our training time in half, so imagine the cost of the trainers, the speed to the floor of the new people. I mean, just the efficiency of that. We calculated that, you know, at the end of those two years, even though, you know, that was the two years from stand up to kind of, you know, start of implementation, we have already dropped an incremental $200,000 to the very bottom line, to our EBITDA. So yeah. So, I mean, super impactful. I mean, we're able to draw that line through it from execution to cost savings at the bottom, and that's what's absolutely key to any CX initiative is actually being able to prove how it drives the bottom line of the organization because none of us are here just for, you know, fun and games. It's all about helping our companies make more money.

[00:22:08] Kailin Noivo: I love it. And, Laura, as we look to wrap up, a question we usually like to ask is if you were to start a company to solve a problem that you face today, what would that company be?

[00:22:19] Laura Turner: Wow. I would start a company that, oh my God, this is a really great question. And it's a hard one to answer because there are a lot of different things that we could solve, but honestly, I think that a company that could really focus on EX, because I feel like this is something that, quite honestly, organizations know that they need to do. This is not, it's just not a lack of knowledge, but you've got your traditional HR function, and you can't take away anything from what they're doing because everything that HR does is super important. And then maybe you've got separate learning and development, and maybe, you know, they're doing a few things here and there. But tying that EX across the organization and being able to tie that in directly to CX and build culture that way, I think I would love, I would love to be able, I mean, the CX obviously is a real passion of mine, but being able to, you know, have a company that could really help that foundational EX underneath the CX would be amazing. And I think that would be something, and I mean, systemically, you could build up platforms, you could build up all kinds of things that would really be helpful and supportive in terms of, you know, how to do that and how to measure it across an organization, I think, would be absolutely fantastic. And helpful for me, I'd want to do it, but it would also be amazing if this like that existed.

[00:23:44] Kailin Noivo: Very cool, very cool. I think that's potentially a million-dollar idea. So we'll appreciate that, Laura. And yeah, thank you so much for your time. It was great chatting with you, and I really, really enjoyed this episode.

[00:23:57] Laura Turner: Fantastic. I loved being here. Thank you so much.

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