Customer Research With Zappos' Alex Genov

Our latest episode of the Question Authority podcast features Alex Genov, Head of Customer Experience Research at Zappos, talking to us about customer experience.

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Transcript

Mitch (00:00): Welcome ,to Question Authority, where the best and brightest marketers teach brands about the art and science of questions. Today we're asking about customer experience with Alex Genov of Zappos.

Mitch (00:29): Alex, how's it going?

Alex (00:29): Good. How's it going?

Mitch (00:32): Excellent. Alex, thanks so much for hopping on the show. And I look forward to you schooling us on some of the insights around how, why, when, where, Zappos, asks questions. But one of the things I find really interesting about you, even though you're head of customer experience research at Zappos, your background, and a lot of your work has been in usability. We harp on this a lot on this pod about how customer feedback and the interaction loop with customers is integral to things like product development, and just generally how you operate your business and not so much just the angle of customer support or marketing or whatever the case may be. So I'm kind of interested to hear how your UX brain thinks about customer research and how those equal more than the sum of their parts.

Alex (01:16): Sure, a great question. So my background is in experimental social psychology. So I would say that I employ my psychological brain more than UX brain. Because UX is just like a practical application of psychology, if you will, right? I bring knowledge and sensitivity about individual differences about emotions, all these things alongside with how you measure all these non tangible concepts, basically. Emotions, they're not tangible like temperature. We don't get a thermometer to measure customer experience. So it's been an evolution. So I came from academic psychology and my first few years was focused on usability, which is very important, but it was very exciting about 30 years ago. So it's still important, but it was exciting 30 years ago. Now I consider it more like plumbing. Now I'm much more interested in kind of higher level thinking about customers as people.

Alex (02:19): And recently I've been on a mission to talk about that, which is something I learned while I was still at Intuit. I met an Italian designer called Roberto Briganti then. It was an interesting story. I met him at this UX conference and then Scott Cook opened the show and he talked about the importance of understanding users and how he learned about users in the early days, he pioneered this thing called follow me home. So he would hang around the store, the physical store, and when somebody bought the box, he would approach them and say, "Can I come home with you to see how you..."

Alex (02:58): Well, that was the ethos into it. And it was interesting after all of that, Roberto Briganti got on stage and basically what he said, it's okay to understand users and to study them if you want to do incremental innovation. But if you want to do radical innovation on meaning, you need to forget about the user. And what he meant was you need to understand the person and we need this more holistic understanding. And that's something that, again, Roberto Briganti teaches, which is a bit controversial. He distinguishes between innovating on solutions and innovating on meaning. There's so many solutions now, the world is a wash with solutions. It's really, if you want to win, you have to rethink the meaning of objects, the meaning of services, the meaning of products. And then you have a better chance of winning.

Mitch (03:51): Makes sense to me that you kind of moved that stuff forward into the broader sense of customer research to say some of the stuff you've been talking about recently that I was listening to around understanding the psychology of personalization and how a lot of brands are either misunderstanding that or manipulating it, whether they mean to or not, to just get you to basically like buy more shit versus actually using it to understand the customer better, which goes back to understanding why you're building your product, where you need to expand your market, et cetera, et cetera.

Alex (04:24): Yeah. This is super important, especially because now everybody's talking about personalization, especially in retail. Before the pandemic you'd go to these huge conferences and probably 90% of the vendors were personalization. Personalization this, personalization that. And so we had this, I had a guest speaker over at Zappos because I had this little program at Zappos where I'd bring in really awesome speakers. Person who had been heading up e-commerce for Walmart for a while and he was responsible for personalization. He basically spoke about exactly that thing, which is if you want to truly personalize, you need to understand why the person is looking for, let's say a backyard grill, right? Maybe they're renovating their backyard and maybe they like to entertain people and they live in this area. And so instead of offering them 10 more grills after they buy one, you should probably think about asking them, do you have a heater for the winter and how many people are you going to entertain and you need a bigger table and so on, right? That would be understanding the customer as a person and what they want to accomplish.

Mitch (05:40): And I think I've heard you talk about this before, as far as dark patterns and things of that nature, about the cautionary tales of using that manipulative opportunity and that power to maybe get some short-term quantifiable results at the expense of your long-term relationship with your customer, right. And maybe a good example would be something like pricing tiers or pricing something over time or pricing upsells so that you're getting maybe a big AOV upfront. But then your LTV drops or customer satisfaction and your ratings in whatever application drop over time because you've exhausted the value exchange with your customer by kind of manipulating them upfront.

Alex (06:21): Right. And manipulation is, I believe it's a very gradual scale, right? It's not a categorical thing. It's a sliding slope, if you will. I don't think it's nefarious. But you have people like Dan Ariely and others that talk about this. Dan Ariely has a great example of, I don't know if you've heard it, but they were looking at organ donor rates in different countries. You've heard this example, right? It was like Denmark and Sweden or some neighboring countries that are very similar culturally, but the donor rates were completely different.

Alex (07:03): And they try to explain it with the psychology of people and all that and the different cultural things. But it boiled down to the application process for their driver's license. And in one case it was pre-checked. And the other one you had to check it. I mean, it's as simple as that. So of course you see now all these things where it's pre-checked and you have to uncheck it or things like when you unsubscribe, some take you through the ringer. They send you an email, they know your email address and when you click unsubscribe, you go to a screen where you have to input your email address again. Like, you know, my email, right? So that becomes, goes into the realm of the nefarious.

Mitch (07:50): That's where you might have your metrics, your performance metrics on whatever platform you're using there, might say like, oh, this is working out great. We have so many fewer unsubscribes. But then if you actually talk to your customers, you might find that the sentiment and advocacy of your brand has gone way down because of that. Right?

Alex (08:09): Exactly.

Mitch (08:11): I guess on that front, curious to hear you speak to the importance of customer feedback as a data source for the company. Because it sounds nice and everyone loves the stories of Zappos in particular, where you hear things like, oh, they've had like their longest customer service call was 12 hours or how people who come in to work in different departments have to start in customer service and things like that. That all sounds really cool. But then companies that are not as visionary as Tony and you guys were kind of think, well, okay, but it's hard to quantify what the value of that is. Or it's hard to put that into some kind of operational structure, so we're just not going to do it. So I'd be curious to kind of hear like, what do you guys get operationally out of 12 hour calls and the idea of putting people who aren't customer service in customer service and just getting all of that qualified feedback from customers?

Alex (09:06): Oh, that's a great question Mitch. I think it's a matter of these two time horizons, right? And it's, the time horizon determines our philosophy as a company. It's not a matter of metrics or data. You believe as a company, as leadership, as culture, you believe in something, right? And then you invest in it. That's what makes it in a way counter intuitive and I believe that's why Zappos won. Because early on they realized, okay, we're selling shoes. I mean, first of all, they were probably one of the first ones to sell shoes online. What Tony and the team decided up front was, you know, people can go to the store and buy shoes, right? The same pair of shoes they can buy in the store. So what are we offering?

Alex (09:58): And then how can we compete with this basically immediate feedback, because you can try the shoes on. So they decided it's going to be customer service. That's what's going to set us apart. And I mean, early on when it started, you don't have data. You say, that's what we're going do and then they started getting these stories and the anecdotes of this wild email that was sent or received by a customer 21 years ago and so on. So the company was built around that and I think the end result 20 plus years now later is that that brand and that appreciation of that effort. Can you attribute the success completely to that? I don't know how we actually do that because in those cases you cannot set up an AB test. You cannot have a Zappos that's poor customer service Zappos, and good customer service Zappos.

Alex (10:51): So we're not going to be able to answer that question. But there's other examples like Steve Jobs and Apple. I mean, they based it on beliefs that we're going to have absolutely excellent products. We're going to outsource our production. We're going to control quality, highest quality, right? Beautiful design. Again, they didn't test it with crappy design and shitty products. They just said, we're going to do that. So if you, as a company, believe that that can set you apart, that's one thing. If you believe that it's a cost to be minimized, that's going to set you on a different path. But if, for example, in terms of data, it's not just data. So for Zappos, for example, it's part of the culture and part of our training. So when you start Zappos, at least when I started Zappos, it was four weeks of intense customer service training.

Alex (11:52): We're on the phone. And then later on, everybody had to do 10 hours at least around holidays on the phones. And so data is one thing, but empathy is a completely different thing. You build empathy. You hear the customer and it becomes part of the culture. Of course you can get tactical data. And I mean, we do have a very rigorous voice of the customer program. But then we also supplement it with our CLT, customer loyalty team members, here. And then we kind of put it together as sort of a validation, triangulation sort of thing.

Mitch (12:29): Right. Yeah. So is a lot of that then really just reading qualified responses and as a team kind of assessing that in a qualified way? Or do you guys end up trying to kind of boil it down where possible the keywords or some kind of time-based interaction or anything like that, without giving anything away, obviously.

Alex (12:50): No, I think the secret really is to put all customer data in one place. I think that's the, if say we collect customer service data here and we collect click stream data here, and we collect this somewhere else, you don't understand the customer because you understand the caller here and clicker here and the purchaser there, and you might not understand it's the same person. It's the same person that may be having difficulty searching for a product. And then the same person who received the wrong product and then called your customer service and they were not happy with the answer and then they left, right? If it's all piecemeal, you're not going to get that, like why this person left or is not coming back.

Mitch (13:38): Yeah. The lack of integration exactly has been, I think even for people who want to pursue things like surveys, longitudinal studies, stuff like that, a lot of the hesitancy is like, I don't know where this integrates and therefore I'm going to have difficulty using it as a data source.

Alex (13:54): That's essential. If you cannot, and that's one of the issues with using third-party data is, especially for Zappos, we're part of Amazon, privacy and data security is of utmost importance. It trumps everything. So then like we cannot collect sensitive information using third party tools. That's why we developed our own tool behind the firewall. But that enables you to then connect the clicks to what they said. And if you don't do that, it's going to be very piecemeal. And then the other thing is when I collect open-ended data, unstructured data, text data, without a good text analytics tool, you're done for, basically. It's hard to read a hundred comments and make sense of them, let alone a thousand or a hundred thousand comments because comments, especially longer ones, are within a comment you can have both positive and negative sentiment then you can have different reasons why it's positive or negative. So imagine the complexity of coding that and tagging it to [inaudible 00:15:04] these things manually. It's just impossible.

Mitch (15:07): This remains one of the big problems in natural language processing. In AI, any decent application can tell you that the word happy is in this body of text, but it can't tell you that the person is saying "I'm absolutely not happy and will never buy from you again".

Alex (15:26): Yeah, exactly. Or it can say, I love Zappos, I've always loved Zappos, but blah, blah, blah, blah recently. We've been on a long journey of finding a good provider, but recently we've had luck with a startup out of England that they're doing really for us, a pretty awesome job, but it's not easy.

Mitch (15:47): Yeah. And as you were pointing out, it's sometimes with whatever tools you have, you're trying some rudimentary approach to solving that problem around usability of the data. I thought one of the interesting takes, Matt, you mentioned once you have a customer who sorts based on like length of a response or something like that? Is that what it was?

Matt (16:06): Yeah. It's length of open-ended response. And there's this whole practice, I forget the name of the person who invented it, but you essentially ask open-ended questions and then you sort by length of response. And that starts to tell you the customers who are essentially the most passionate.

Alex (16:24): For sure. Well, I mean, when I have to share internally, then I have like a thousand or 2000 responses. Sometimes I sort by the length of the response, which of course a lengthy response gives you more. But that doesn't mean that, again, that's completely orthogonal to having good software to figure out why.

Mitch (16:51): Right. And I always forget the name of this company, but the one who has the, they're very popular, just the three buttons in brick and mortar as you walk out.

Alex (17:00): Oh yeah.

Mitch (17:03): And that basically that was the bare minimum of customer feedback. And obviously you're getting no real context around why someone hit the red angry face, but they used it purely from a volume standpoint to say, hey, look, it's not going to be very valuable if one person hits this. If 20% of your customers hit it over the span of an hour and your baseline is 5%, then you know that something is going on and maybe you need to check out what's going on at that store or something to that effect. Which I found super interesting giving that the data was on its own as a data point, arguably useless. But you use scale and all of a sudden it's really interesting.

Alex (17:40): Well, it's admirable that they have it there. Although what, they're usually in those bathrooms, right?

Matt (17:47): They're always in airport bathrooms.

Alex (17:50): Are you going to stop using the airport bathroom?The loyalty there is not...

Mitch (17:55): Yeah. What's your favorite question to ask whether it's whatever's in that voice of the customer survey or just one that you'd like to ask that you guys don't ask? But what is kind of your favorite question to ask a customer if you had them sitting in front of you?

Alex (18:10): Well, that's a tough one. I don't know if I have a favorite. It's really important to figure out what you care about as a company. So we talked about personalization before. If you care about personalization, have you asked your customers, do you feel like our product is personalized to you? And then even more importantly, do you want personalization?

Mitch (18:30): Do you want it?

Alex (18:32): Do you want it? And do you want to give us your data in exchange for personalization. Then you'll know, I mean, I really like a question, it's more of a statement, but it was developed by Fred Reichheld, the creator of the net promoter score. I think it's brilliant. I heard him talk about it years ago and then now I'm using it in our surveys, which is retailers always have my best interest as a customer in mind. Or you can say whatever business you're in. And then agree, disagree, on a scale.

Alex (19:04): And I think that is very important. Because then you get to how do people feel about your design practices and about your checkboxes and about your unsubscribing. When they send you emails, are they taking, or are they giving? I'm conflicted in a way, in terms of collecting all this feedback, because it's basically customers are giving us a gift. That feedback is a gift, what are we giving back? And I think that's the next level of when you ask those questions, what are we giving back?

Alex (19:36): I'm a big fan of this concept of product centricity versus customer centricity. And I learned that from a free online course. I can't believe it was free, but it was the Wharton business school classroom. And it was on Coursera. And it was taught by a few professors, Barbara Kahn, but also Peter Feder was probably the godfather of customer centricity in the United States.

Alex (20:02): And then he distinguishes product centric companies and customer centric companies. He has a very specific definition of customer centricity, which is then all the same. And then you need to understand the value to the company and what you can provide to them and what they provide to you and your segment. You do segmentation, and then you basically provide a level of excellence for everybody, but you only go above and beyond for certain customer groups, because those are the ones that are going to spread the word for you and so on and provide you with long-term value, lifetime value. And he gives examples of really excellent product centric companies like Starbucks and Apple and even Nordstrom, in his view is they provide absolute excellence and in terms of operational excellence and all that stuff.

Alex (20:56): And in his view, most of the business is done that way, but he is saying, he has a great book, and in that book he's saying a lot of things have changed since the days of Henry Ford. And I mean, that was the only option you could get. And now customers have a lot of options. Everything is globalized. We have a lot of information. Switching products is easy, right? So now more and more customer centricity and loyalty are going to, the way he puts it, it's much harder to win if you're just product centric.

Mitch (21:31): That's interesting to kind of think of it as like going from the industrial age to the information age that it lines up with product centricity versus customer centricity. I hadn't thought about that, but that makes sense. I like that. That's interesting. I'm sure all the DTC brands listening are feverishly taking notes, but I want to give you a minute to plug anything you want to plug, whether you're hiring people or if you just have an organization or even an idea that you want to just put out there for folks to know about.

Alex (21:59): Well, actually a lot of those thoughts we're putting together in a book, a couple of friends and I are writing a book on that topic. So hopefully we'll get it ready soon.

Mitch (22:13): Did you decide to start that book at the beginning of the pandemic or just now, squandering that whole opportunity in your house by yourself?

Alex (22:21): At the beginning of this podcast actually.

Mitch (22:23): That'll do it for today. Thank you for listening, subscribing and rating the show. Keep an eye out for Alex's upcoming book. And in the meantime, check out all his talks on customer experience. Question Authority is made possible by Fairing, the leading post-purchase survey provider for over 1,500 DTC brands. Learn more and to try a 14 day free trial, check out Fairing.co. See you next time.