Episode 21: There’s a ‘huge gulf’ between the CX shoppers expect online – and what they get

In this episode of Retail Untangled, recorded at Shoptalk Chicago, Amie talks to Kevin Laymoun, COO at Constructor.io about how to bridge the gap between customer expectation and experience. 

Transcript

Intro:

Coming up, on this episode of Retail Untangled.

Oftentimes you see your shopper maybe if you're lucky once a month, sometimes once a year, couple times a year. And so how do you do more with less?

It's really using that data, creating a good social graph, leveraging that clickstream alongside your merchandising know-how to get much more context-aware experiences that drive that precision. 

Amie:

Welcome to Retail Untangled. My name is Amie Larter and this is the podcast where we speak to retail industry experts and find our business hacks to help you succeed. You won't find these gems anywhere else and we have some superb stories from the coal face as well as helicopter insights from retail industry leaders. This week we're bringing you insights live from Shop Talk Fall in Chicago.

A recent survey polling 900 online shoppers in the U S and UK on their search and discovery experiences revealed a significant gap between what shoppers expect and what they're currently experiencing. Four in 10 shoppers are giving product discovery experiences a C grade or less and want more tailored search results. The data also showed shoppers are experiencing poor search capabilities with seven in 10 stating the search function on retail websites needs an upgrade. 

Today I'm talking to Kevin Laymoun, CCO at e-commerce search and delivery platform Constructor.io to find out how to bridge that divide between expectation and experience. Thanks for joining me, Kevin. 

Kevin:

Thank you for having me. 

Amie:

My pleasure. As the bar for a good digital experience continues to rise, the discussion is turning to, and we've heard a lot about this on stage yesterday on the first day of Shop Talk Fall, how to enhance search and product discovery. Your team has recently released a research report into this, the State of E-commerce Search and Discovery 2024. From your team's findings, how big is the gap between what shoppers want from this journey and what they're actually being delivered? 

Kevin:

Yeah, it's a, I mean…Most people would probably assume this, but to quantify it is obviously a really cool thing about the report. But it is a big gap, right? Because I think everybody that comes online is looking for that in-store experience when you meet a greeter and they take you right to the aisle of the product that you're looking for and then after you find the product you're looking for, they maybe helpfully recommend a few other products. And that's the dream shopping experience that you almost never get online. 

And so there's just such a huge gulf between the experiences that you're used to today, even on, I would say, heavily invested in experiences like amazon.com. It's far from that experience I just described. So our goal and our hope is that everybody is pushing themselves, the technology, the UX to be able to get there. And I think we will. We'll probably talk more about that right now, but we will, the technology's think fast approaching, if not already here to get closer to that experience. 

Amie:

Okay, and to give our listeners some context, what are the biggest mistakes retailers are making right now when it comes to search and product discovery? And what's that costing businesses? 

Kevin:

Yeah, well it costs them massively, right? There's the top line of impact of lost opportunity, right? You know, the product discovery equation or should say the e-commerce equation is pretty simple. It's visitors to the site times conversion rate times average order value equals your revenue. There's things like margins and return rates, all of that good stuff. But at the end of the day, product discovery can really improve that conversion rate. It can improve the average cart value. 

And you do that by having better customer experiences. And you do that by using user clickstream, letting customers vote for the experience that they want to see, not just in aggregate, of course, but also within the session for them personally. So a lot of the emerging machine learning that really came out in 2017, but that's been pushed forward a lot by a select few companies, both in and outside of e-commerce, is making a huge difference in the precision and context that's really important. You see things like Transformers changing the game here.

Transformers is the T in chat GPT, so we all use it, we don't know it, but it's really important in determining the context for each shopper. And that's the difference maker in the experience that they end up seeing and obviously makes an impact at the bottom line and top line for the retailers. 

Amie:

Makes sense. So your research shows that shoppers are very clear about what they want in a search experience. What's at the top of the wishlist and what are the main areas brands can improve on or focus on to meet this demand? 

Kevin:

Totally. Well, I think there's two things. One, how do you promote using that user clickstream within your technology? Whether it's something that you already have or going out and finding technology that can optimise for that clickstream. And then furthermore, how do you marry it with the awesome merchandising know-how that you have? Right now, a lot of brands have a manual curation via the merchandising team. They have to go in and manually curate the stuff using some backend merchandising dashboard. 

And if they are using some machine learning, it's an either or proposition. It's either the machine learning happens or   the merchandiser is merchandising that page. So I think that the top wish list for most e-commerce companies I think I see doing this well is how do you marry both of those two things? Because oftentimes you see your shopper maybe if you're lucky once a month, sometimes once a year, couple times a year. And so how do you do more with less?

It's really using that data, creating a good social graph, leveraging that clickstream alongside your merchandising know-how to get much more context-aware experiences that drive that precision. 

Amie:

Makes sense. And you spoke about retailers that are doing this well. Who are they? And why is their strategy working? 

Kevin:

Yeah. Well, I think you could see it, right? That's the cool thing with product discovery. It's client-side, its customer-facing. We're all shoppers. That's the fun thing about what I do, I think, is you work on a product that you also use and your family uses and your friends use. So companies that I think are doing this really well, would say Sephora is definitely a hallmark. I don't think that that's new for folks, but their user experience is fantastic. It's personalised, it's context aware, it changes, it's dynamic to the context. You love to see that.

Kmart Australia. Not a lot of people, maybe your listeners don't know outside of Australia that Kmart still exists, right? Certainly in the US where we're at right now, it doesn't. But Kmart Australia is really innovative in chatbots and how do you engage with the brand in a variety of ways. But having that underlying understanding of the algorithm that you're a consistent shopper and have a changing context in your shopping experiences.

I think there's some really awesome grocers out there. I think, don't know, folks in the Midwest, the United States get to use a grocer named Meyer. I think they do a fantastic job across their site in replenishment and understanding what products should be shown to a customer based off of their previous purchase history. Again, in grocery, previous purchase history is really important in future purchasing intent so they do a great job of that. 

Amie:

It's so important from a consumer standpoint, I'm telling you. Yeah, exactly. I use my previous buy list all the time. 

Kevin:

Yeah. So, you know, I think they do a fantastic job. If you go to the UK, the Very group, which is almost like the Walmart of North UK and Ireland, they do a fantastic job as well on a similar lines of personalization and optimising for the customer experience.

So those are those are the top three that I would say are easy to go and find and check out and reference 

Amie:

Makes sense So I feel I feel like this is an obvious question and I've done this a couple of times This week in the sense that we ask questions that we may have heard of before or seem obvious but how are technological advancements going to change search and discovery in the next few years and how can retailers prepare? 

Kevin:

Totally. I mean, so I'll maybe talk about this from two standpoints,  from a retailer perspective, think there's like, or an e-commerce company perspective, there's two sides of this. There's the customer experience side and then there's maybe the side of things that's not customer facing, which is more of the economics from their side. I'll maybe start there. Retail media is making a huge push into every retailer, e-commerce company's lives. It's here.

I think if you're not entering that market, you're going to be starting to see eroding at the rest of your business in terms of investment. So one of the huge advantages of a company approaching this proactively is that they can look at, how can I look at retail media and balance that against my organic revenue and experience that I'm trying to drive for my customer? If you look at them as it was done historically as two independent flows, like here's my retail media revenue and experience and then here's my customer experience and like the results I'm showing them. That's where it becomes deleterious to your business, both from a customer experience side or and or from an economic standpoint for the retailer e-commerce company. I think that's here. That's a big, big change. Yeah, that's already here. 

I think another thing that's also here, but not here, here yet, if you look at referenceable comparisons to like what Amazon reports and Walmart, et cetera, is conversational commerce. I think the technology is here. I think brands that look at this and want to invest and create really awesome custom branded experiences, there's one luxury retailer that I'm thinking of that actually has invested in recording hours of their store associates' conversations and pitches to customers and use that as the LLM, which is really, that's really kick ass stuff. 

I think that's what drives awesome customer experiences and that's already here. Now the engagement on it, right? How much revenue is driven from AI shopping assistance? That's not here yet, right? And so I think there's a lot more advancement in, again, investments in those really custom experiences that you can drive. The one I just mentioned with this electric retailer that I think will ultimately lead the the average buyer to say, this is actually how I can discover a brand and why it's more advantageous to me. And also obviously drive that incremental investment from the retailer and e-commerce company side. 

Amie:

We've heard on the ground at Shop Talk product data, it's come up as an issue. How can user clickstream be used to correct it? 

Kevin:

Yeah, classic problem. I think that's, it's always in season. Product, I've never met a retailer who said, my product data, excellent. 

Amie:

Perfect. 

Kevin:

Yeah, got that on lock. No, it's always something that can be improved on and get better.

Fundamentally, I think the ability to leverage user clickstream, what users click on, add to cart and purchase, helps inform on really what the reality of your product array is to different segments of your customer. And so really, the functional element of this is how can we go and take all of those inputs and turn those into tags for your product data so that, for instance, if you have a foundation that's really great for oily skin and your users are showing you that by their actions, what they're querying, what they're clicking on and filtering down on, we can use that back into the flow for that retailer to say, great, now this is how we can leverage this for in-store, how we're understanding supply and demand for next year's buying. This is really critical and it's available now. I think one of the things is that a lot of people don't know that.

And they say, okay, you know, I've got this, we in the search world, we call this the garbage in, garbage out problem. But they say like, I've got this bad product data. I need to go solve this manually. Or I need to go and like do continuous audits. And that's the stuff that is honestly, it was historically done and kind of still done. And so there is a way to do this programmatically. And I think one of the things that every retailer should look into, it's the foundation of all the other cool tech we're talking about.

Outro:

Thanks, Kevin, for joining us on this episode of Retail Untangled. If you have enjoyed listening, feel free to like and subscribe to Retail Untangled on your favorite podcast platform.