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Hello, and welcome to another episode in Clientships Customer Experience Superheroes Podcast Series.
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My name is Christopher Brooks, and in series two, I'm going to be bringing you another episode, a special, in response to the COVID-19 crisis we're in.
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I am delighted to be joined by Dr.
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Marina Shapira.
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Marina is a specialist in consumer behavior.
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It's a topic that's fascinating at any time when you think about just what impact experiences can have on customers' behaviour and how you can change perceptions.
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Find that the reality is their actual behaviour changes.
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But even more so, it's important to understand what's going on in the middle of COVID-19 as we are now.
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How are consumers adjusting based on the information they're receiving, based on their needs and their expectations in this very challenging and unprecedented time?
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So we're absolutely delighted she's here to give us some insight and share with us some incredible research that she's been undertaking at the moment.
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As I mentioned, this is uh another special podcast, um, and we are delighted to be joined um by the head of behavioral research from Quantum Metric, and that is Marina Shapira.
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So welcome, Marina.
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Hi Christopher, thank you so much.
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I'm delighted to be here today.
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Great to have you, and uh, I mean, I think you and I probably would have uh spoken um definitely in this podcast series looking at CX superheroes because I think the the sort of work that you're doing is um is really really valuable and very insightful for for uh customer experience, but uh I guess given the current crisis um even more so.
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Now, great title, head of um behavioral research.
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Could you give uh the listeners an appreciation of what that actually means?
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Yes, of course.
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Um so I like to describe it as sort of a marriage between a few disciplines, uh psychology and behavioral science, which is kind of the theoretical framework that we base our insights and work on.
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But then we use really innovative research methods like machine learning to process digital analytics data, which is relatively new and is something um proprietary that we're doing.
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So it's it's really both worlds um enhance each other and complement each other really well.
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So there's heaps and heaps of data, um, and behavioral science lens really helps to understand what are the most important elements of the data and the insights that we're seeing that can really move the needle for companies and really make something influential for both the business and the end user who's using the digital product and really wants to get something out of it.
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And what was your journey to this position?
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What would your background include?
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Yeah, that's that's a great question.
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So I started um in pure psychology.
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Um did my PhD in cognitive developmental psychology.
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And as I was going through this process of academic research, um I really became very curious about how research is done in the sort of outside world, quote unquote.
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I was interested in venturing into the business world and bringing all that academic training and research and theory into customer experience and really helping companies, enterprises every day to touch millions of customers.
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I just felt like in this way I can influence more people faster if I'm applying my skills in the business world.
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So kind of towards the end of my PhD, I started looking at um at different research positions and actually started working at a company called Clicktail in a rather similar role.
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So it's a digital analytics company, and since then I moved a few other companies, and now I'm at uh Quantum Metric, which is um you know the industry leader in this field.
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Excellent.
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And I have to say I'm so pleased to hear that research is more and more involved in customer experience.
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I think um for quite a while the discipline has been focused from the the front line backwards, so we have a lot of great customer service people in um and marketing people and and even strategists, but uh I think there's been a lack of pure scientists and researchers in involved in customer experience, so it's it's great to hear you know of yourself um and also organizations like Quantum Metric kind of pushing the boundaries.
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So um I understand you know you're doing a lot of consumer research.
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It must be a very interesting time in sort of April 2020 to be undertaking research into consumer behaviors.
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I mean, um are you are you running research in on in the current uh crisis?
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Um yes, absolutely.
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It's a fascinating time, and there were a few hypotheses um that I had in the beginning of how customers will behave, and it's just so interesting to see it unfold um and actually matches um very basic theories in psychology, kind of how do we react in times of uncertainty, in times of change, and how does that change the way we interact with digital products and we go about our daily lives, basically.
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Okay, so at phantom metric, we um almost daily we analyze the data, we look at the trends, we keep updating the press, um, and just to give everyone the most up-to-date, fresh information to help them guide smart decisions.
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Sure.
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So so your your um your sample is it's a it's a global sample you're going out to, is it?
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Um it is um mostly based out of the US, currently, but also includes Europe.
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Okay.
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So it's a so it's a fairly good good poll then.
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And and you you say sort of um uh you're able to feed the press.
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So so you that suggests that you're actually turning this around pretty quickly if you're giving it to um organizations that then can publicize it.
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Certainly.
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I think that actually many um professionals in the data analytics field feel this pressure now of all eyes are on them, and uh data becomes this currency even more than before.
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Also, in communication between companies, it feels like any communication needs to have a good value exchange, and that value is coming from data and from user science.
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Yeah, well, I I think being in kind of the this overused word unprecedented times, um you can see uh governments being very reluctant to forecast and uh you know estimate what they think outcomes will look like because without the data there's just no certainty, and and I think we as consumers, certainly as citizens, um are valuing the importance of quality data in order to inform.
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As we see around the world certain nations who perhaps haven't submitted full data sets, you can see the di the you know the devastating impact it's having on their society when they're making changes and decisions based on half the information.
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So I completely agree with you.
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I think data's become um it's I wouldn't say it's it's fashionable.
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Data never seems to be fashionable, but it's become critical to uh to society.
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Certainly.
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Now um so you s you say you've you've got this research going going on at the moment.
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Ma may I ask, you know, what what are the sort of um the the major changes that you're seeing in consumer behaviour online then?
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What sort of things are you observing that um perhaps you you anticipated?
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You said sort of you know some of the basic human psychology and and our behaviors are just um being exaggerated.
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So what are the things that you're seeing that we'd expect to see?
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But also are there things coming out that are making you think, hey, I wasn't expecting to see that.
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Yes, definitely both are true.
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Um, so at first I was trying to look at basic theories in psychology and try to see if they can uh predict behavior um right now during this crisis.
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So one thing is that you know when we feel um greater uncertainty, our sense of control really goes down, and when we feel lack of control, our anxiety goes up.
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And one way to get back just a tiny bit of that control, for example, is to stock up on products.
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And that's why we've seen in February Hispanic shopping and um you know toilet paper disappearing uh from shelves.
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It's a way for people to mitigate and self-regulate their stress and their anxiety.
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And that might actually be a relatively harmless and not very expensive method uh of doing that, and of course, um needing to actually have those products in home if quarantine is about to start.
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And do you think with do you think with those those products actually it's almost uh it's almost irrelevant what the products are?
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It's the fact that you can exert control.
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If I feel I need eggs, if I feel I need washing powder, then I can buy washing powder.
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I'm um there's a very small thing I can control there, and therefore when the shelves are empty, it increases panic because the very small thing I thought I could control, I can't even control that.
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Yes, exactly.
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We're more likely to go towards very basic products because um when also when we are facing life's fragility and kind of almost um feeling a sense of we might have less time on earth than we think we might um before.
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It's called um a time horizon.
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So our time horizon is shorter now, uh, which leads us to really look inward and prefer things that we know.
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We don't want to broaden, we want to just you know, really optimize the present moment um and go with what we already know that makes us feel well and helps us.
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So we're not going to look for some um you know different uh product or something new and innovative that can help me.
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We're just going to double down on the basics, and that's probably why people were shopping for those essential parts.
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And does does it happen in the subconscious then, or is this something that we can actually access in our in our in our brains?
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The ability to change our our time horizon, or is it just something that happens to us that we're not aware of?
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We're typically not aware of that.
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Um people just do that intuitively, and we can see that also online when um you know, in just uh in the very early March, I released an article on this uh um phenomenon of time horizon and how can it impact online shopping.
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And I talked about this uh, you know, deep emotional connection that companies should talk to their customers in a more emotional way than ever, because this is what we favor when our time horizon is short.
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It's supported in research, and it's amazing to see that there's a flood of this type of emotional language right now, even too much.
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Um, I would say that some people are deterred from it because it might not feel as genuine.
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Right.
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So um the recommendation there might be even uh now, you know, the reverse that you need to, of course, communicate in this way that will speak to where your customers are at now from an emotional standpoint, but also don't overdo it, so it won't uh sound not genuine.
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Okay, so that's a really, really good point.
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And so the other sort of things that we experienced, what what about the things that you you you've seen come through that perhaps were less predictable?
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Um yeah, so just to add on uh some of the things that how we saw the panic shopping manifest online, there were a few very interesting metrics that that came together to support that.
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So for example, we saw that people are much more likely to discover products through search rather than navigation.
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And searching for something um means that you're goal-oriented, you know what you're looking for on an e-commerce website, and specifically we looked at websites that sell essential products.
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Yep.
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So instead of navigating where, oh, let me see what's under the linen category, you're less interested in that.
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You you know exactly what you need.
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Give me one second, Marina.
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Sorry, I've just got someone printing in the background, so I'll just get you to uh re say that bit.
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So I do apologize.
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No problem.
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Sorry, I I I I explained we were podcasting, but um it doesn't always get through.
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For some reason I've got a Henry Moore sculpture uh being printed out.
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I think I know what it is, my there's a there's a you a UK um army veteran who's walking around his garden a hundred times.
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He's a 99-year-old man.
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And um he has um he wanted to raise a thousand pounds for the National Health Service and he raised 12 million.
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Wow.
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Yeah, I know it's just um unbelievable.
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But um there's a campaign online to draw him get children to draw him pictures and say thank you.
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So I think that may be what I've got here.
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Um but oh yeah, I don't I can't see my son at the moment.
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Is it you?
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I'm on a podcast, Henry.
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So if you could just Yeah, right.
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Okay.
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Cool, sorry.
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So let's go back to uh that that that previous question about the other um things that you found.
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Um yeah, I I was about to describe um how we see online shopping manifest uh the panic shopping manifest on online.
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Mm-hmm.
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Yes, that's exactly right.
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Yeah, yeah.
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Let's go on go on that then.
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So the the the the other you were talking about in um uh goal-oriented shopping.
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Yeah, exactly.
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So we are seeing um online manifestations of panic shopping and different behaviors that coincide together and paint this picture of very goal-oriented and purchase-oriented uh behavioral patterns.
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So customers are much more likely to search um rather than use navigation on websites.
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Okay, search um is a function of a website that we use when we really know what we want, and we use navigation when we kind of want to explore and maybe see what's under a specific broad category.
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So, just like we said before, at this time we just want to get the products that we need um and make sure that uh you know we're safe, we're secure, and not explore.
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Anything that acceleration and broadening is going to decrease.
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And um similarly, we're seeing also that customers are much more faster to select the product, so they're looking um at product detail pages much less before they're hitting that add to back button.
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They're also might be fearing that inventory might go down, so they want to secure a specific product for themselves, as well as they're looking at more product pages per search that they make.
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So typically we see customers uh in a longer research phase, they're looking, they're more picky.
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Right now, they're hitting those product details pages very quickly, also because their searches are much more focused on what they need.
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Wow, okay.
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So that's yeah, also just one more metric um that that is very interesting is that the whole checkout process, both on mobile and desktop, um, is now um significantly shorter compared to in March 2020 compared to March 2019.
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So and it's the shortest on mobile, where typically checkout is more difficult and takes longer, but uh people are buying much more in the context of than here and now, and overall people are also shopping more for mobile.
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And uh that's why we're seeing those really uh speedy checkouts right now.
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Wow, so so that greater kind of um human instinct around the fact that we're our mortality is uh is at risk here and we're we're uh our life um is is is potentially shortened is actually played out on our online shopping behavior.
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You can see the correlation between the two, that's incredible.
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Yeah, precisely.
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Anyway, this is true specifically for websites that sell essential products.
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Yeah, some different trends might be seen in apparel or in cosmetics, um, where actually um people are shopping for somewhat different reasons, but uh for the panic shopping in uh online we're definitely seeing that in the essential category.
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Okay, great.
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And and are there any sort of odd things coming out that you you don't quite understand yet but are are of interest?
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Um not necessarily odd, but I personally expected that in March the panic shopping will attenuate and we're going to see more browsing from the desktop.
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We might see uh people that just want to spend some time.
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Uh so maybe exploratory patterns would go back um and restore the previous and maybe even grow.
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Right.
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And we are seeing that for apparel and for cosmetics, we're not seeing that for the essential category.
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And and so if I am a regular online shopper, I I've I've got a fairly good appreciation of what what a good experience looks like, what I should expect and and and what perhaps I shouldn't expect.
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If I give an example, when I've gone onto a hardware store, um I now get served with a message to say you can access the site in five minutes due to um exceptional levels of traffic.
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If the expectations that I had pre-COVID-19 are not being met, are consumers uh accommodating that or are they intolerant and sort of saying, right, forget it, I'm on to the next one?
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What's your what's your view or what's the observation from the research on that?
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Um yeah, so um unfortunately we're seeing um somewhat less tolerance to that.
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Um because we're seeing this, uh, like you just uh said, an influx in new customers coming, which is can be a great opportunity or a threat.
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Because if the experience is great, then customers are much more likely to remember it because our brain is wired to remember peak experiences, yeah, and we're definitely in a peak experience right now.
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So if a brand served me now, um that might contribute to my loyalty going forward because they helped me in a time of need.
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And again, that would depend on the category and how essential that is.
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But in general, we now completely depend on online to get everything that we need.
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This is our window to the world.
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So if some company blocked my window to the world or something was ambiguous about um the experience, like shipping was not clear, or I can't even access the site, then this will um you know, people are going to remember that much more than during normal times.
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And then unfortunately, we are also seeing among new customers um higher frustration rates as well as a higher error rate.
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Right.
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So some of this is stemming because um they are going through flows like account creation or first checkouts that typically have a lot of friction points and might also experience a huge influx in traffic, which might uh slow them down.
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We're seeing websites being much, much slower.
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And of course, we know that we have about two minutes for a website to load before we abandon.
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So, in this spirit of urgency um and of really goal-oriented behavior and speedy um uh checkout processes and shopping journeys overall, there is much less time to impress customers right now.
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So, um and and I think what you mentioned there about this influx of new customers, I mean, I guess there's a particular age demographic that are having to engage that previously have decided not to.
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So this this this new influx of customers, they're not coming there willingly, they're not coming there for fun and entertainment and to find a better way.
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They're coming because they have no choice.
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So I guess if when they get there, the very thing that they've resisted then doesn't work, it almost reaffirms to them that their decision to not shop online was the right one.
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So companies will who fail those customers at this time will lose them forever, I s I suggest.
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Yeah, definitely.
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I I completely agree.
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I'm doing a lot of uh work in terms of uh conceptualizing and measuring online loyalty.
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And where we know from our own research that accumulation of several errors and mistakes, um, as much as three can start to fraction and deteriorate online loyalty.
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Um so that will probably be confounded at this time.
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So as as few as as three mistakes, and that's it, I'm out.
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This is just too painful now.
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Um in certain cases, yes.
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Yeah, okay.
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Loyalty, it's it's not um, you know, they're probably um there we have this loyalty score, so they're going down on the loyalty score.
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They might abandon completely, but um, they're more likely just to uh have a lower loyalty score, which is correlated also to how much money at the end of the day they will bring into this business.
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So this is definitely a negative outcome uh from a business KPI standpoint.
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So let's let's stay on loyalty because I know this is your specialism.
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So you mentioned there about sort of peak experiences, and I kind of understand the difference between um an actual experience and the remembered experience, and the remembered experience can quite often create a very different impression than what you actually went through.
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So with with that said, it do we do we need to rethink loyalty?
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I mean, if I'm a if I'm working, if I'm a customer of a business, then that business typically will reward my loyalty based on the number of transactions that I'm giving to them rather than giving them to the competition.
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But actually, if I've been through an experience such as COVID-19 and I've been really impressed with an organization, um maybe I've not had that many transactions with them, but potentially emotionally, we're gonna get a loyalty now going on that's gonna last forever.
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So, does it mean organizations need to really r think about how they define loyalty with their customers?
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Yes, definitely.
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Uh, I think so.
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We now know uh through our research that loyalty is just like you're saying, it's more than just the transactions.
00:23:40.160 --> 00:23:53.279
And it is very much also dependent on habitual patterns of behavior and something that is quite fuzzy and might be difficult to measure, which is the emotional piece, emotional loyalty.
00:23:53.599 --> 00:24:04.720
And I think that online um traditionally were these anonymous sessions that couldn't really be tied in together into one cohesive view of a person.
00:24:04.960 --> 00:24:09.119
But now with the technological solutions, we are much beyond that point.
00:24:09.359 --> 00:24:12.000
But not all digital businesses have cut up to that.
00:24:12.400 --> 00:24:20.400
So this is why most businesses are optimizing for conversion rate because it is, of course, tied to a very clear business outcome.
00:24:20.559 --> 00:24:28.000
But in a sense, it's easier to think about um one online session and its immediate outcome, which is conversion.
00:24:28.480 --> 00:24:37.279
But over the long term, what is going to be much more profitable is measuring customer loyalty and how and even predicting it and how it unfolds over time.
00:24:37.519 --> 00:24:46.720
And what are how to sum up all those micro interactions to create a true relationship with a customer, which is going to be much more profitable.
00:24:46.880 --> 00:25:04.640
And I think everybody knows those statistics of you know how much cheaper it is to retain an existing client between five to twenty five times, and that um, you know, the top 10% of uh of our most loyal customers are bringing most of the revenue.
00:25:04.720 --> 00:25:11.759
So all of these stats are across the internet, but then how do we actually do something actionable and and measure this?
00:25:12.240 --> 00:25:26.160
What we are doing is we're combining several metrics with a predictive approach, and what we are looking at is behavioral patterns like how frequent um is a customer shopping online and what is his sentiment.
00:25:26.400 --> 00:25:38.480
Uh, for example, using voice of customer um tools in combination with uh objective behavioral measures like we see in digital analytics.
00:25:38.559 --> 00:25:47.920
So we're basically completing the picture, we're looking at um just objective browsing data in which uh you know uh we record what customers do online.
00:25:48.079 --> 00:26:01.359
So they of course it's ethical and legal, but they don't necessarily know that um their behavior is being trapped at that moment, so they're just being uh natural and this is uh almost as bias-free data as you can get.
00:26:01.920 --> 00:26:07.759
But then we combine that and weigh that against what they're actually saying because that's very important.
00:26:08.240 --> 00:26:20.319
So in in customer experience, we know that what uh people do is not exactly what they say, which is it's it's true, but we want to know what they're saying because this is their emotional experience.
00:26:20.720 --> 00:26:37.759
So by being able to distill those reactions on voice of customer tools and combining that with um you know sort of pure behavioral data, we're able to uh paint a complete picture of how loyal they are to a specific brand.
00:26:39.200 --> 00:26:54.240
So I mean I'm I'm find this topic just so fascinating because um if I'm a new company or if I'm investing in digital, one of the strengths of of digital is the ability to measure data points.
00:26:54.480 --> 00:27:02.319
Um but as you say, the emotional value of loyalty is is fuzzy and it's difficult to assess.
00:27:02.480 --> 00:27:06.720
And as you were talking, I was just thinking of an example from from Amazon, for instance.
00:27:06.880 --> 00:27:24.400
So if I take Amazon, who have during this time said, look, we're gonna prioritize from our uh uh in our marketplace some particular product lines, and these are these are back to what you said, these are the essentials, these are the ones that create anxiety, pet foods, health products, those sort of things.
00:27:24.720 --> 00:27:27.839
Everything else is going to be pushed back.
00:27:28.240 --> 00:27:38.799
Um now I know uh my my my dad, for instance, has never really been an online shopper, but has chosen to shop during this time and has done grocery shopping and Amazon shopping.
00:27:39.039 --> 00:27:43.599
But he went on to Amazon and he said it's rubbish, it takes so long to get anything.
00:27:43.920 --> 00:28:04.160
So from his perspective, it's not delivering the strength that he's understood it to deliver, but from my perspective, emotionally, I'm really, really deeply attached to Amazon because they're making the right choices, which will not go on any transactional data set.
00:28:04.400 --> 00:28:13.920
What they'll see is as you say there in the verbatim from me saying you're making the right choices, and that's why I will continue to shop with you above others.
00:28:14.240 --> 00:28:17.519
So it's a really interesting space that you're moving into.
00:28:17.759 --> 00:28:35.599
There must be one that's quite challenging when people throw data sets showing a correlation between you know retention transactions and increased share a category, whereas you're trying to use the language to explain this is a much much more complicated relationship when it comes to loyalty.
00:28:36.400 --> 00:28:39.440
Yes, definitely, but they're intercorrelated.
00:28:39.680 --> 00:28:44.400
So those emotions they're driving uh people returning to a website.
00:28:44.559 --> 00:29:08.559
So we know that the frequency of just plain visits without a purchase and how um um the the recency also of purchasing, so sort of the time that elapses between your first and last purchase, that they have also a huge correlation with ultimately how much a customer is worth to a business, which we always have to tie back to business KPIs, right?
00:29:08.640 --> 00:29:13.200
To to make digital uh organizations care about that, to improve the experience.
00:29:13.279 --> 00:29:26.400
So it's nice that when we're talking about loyalty, uh improving a business KPI is actually going hand in hand with improving someone's uh you know ability to achieve his uh goals and needs online, which are not really critical.
00:29:26.720 --> 00:29:32.240
But definitely they're intercorrelated and the emotion is driving the behavior.
00:29:32.400 --> 00:29:52.079
So I would almost say that looking at the behavioral pattern um above and beyond just purchases, but like also like visits, their duration, um, and different um metrics of the visit quality can also tell us quite a bit um about the the emotional loyalty.
00:29:52.160 --> 00:30:02.480
And of course, in a market it has competition because if there is lack of competition then and people are buying uh you know, because they have no other place to buy, then it's a it's a different dynamic there.
00:30:02.880 --> 00:30:04.880
So is there a new model for loyalty then?
00:30:04.960 --> 00:30:13.119
I mean, do you have a framework that you're working towards that will become, you know, I think uh you know, we we we crudely used to work on RFM, didn't we?
00:30:13.359 --> 00:30:15.119
Recency Frequency Manetry.
00:30:15.440 --> 00:30:18.400
I mean, what what is the new framework for loyalty?
00:30:18.880 --> 00:30:46.319
Yeah, so um my framework um that I coined and we're working on um at Quantum Metric is the acronym is CLEAR framework, um, and it stands for cognitive, a part of the cognitive loyalty, which is more of kind of the brand awareness, um just checking through metrics that customers were exposed to the main business offering, that they even know what we're um want to provide to them.
00:30:46.400 --> 00:30:52.799
And by the way, that would be a huge percentage of every digital organization um um client base.
00:30:53.279 --> 00:31:00.799
So most would be pre-transaction, uh, kind of very low loyalty for now, but a huge opportunity to move them up the ladder.
00:31:00.960 --> 00:31:11.680
And then the L would stand for um loving or liking a specific brand, which here we would measure all the sentiment data that's coming through a voice of customer.
00:31:11.920 --> 00:31:16.319
So uh the I in clear would measure the intent.
00:31:16.480 --> 00:31:24.559
It is very important to be able to predict what is the intent of the specific journey that um customers are having right now.
00:31:24.720 --> 00:31:30.640
Is it uh purchase-oriented visit for to a website, or are they still in the research phase?
00:31:30.799 --> 00:31:40.640
Because we know that before we buy something, even something small, um typically not during COVID, we want to have a few research uh visits, mainly from mobile.
00:31:40.799 --> 00:31:45.279
So a visit without a transaction on mobile is not necessarily bad, but how do we know that?
00:31:45.440 --> 00:31:51.839
So we develop um uh predictive analytics models through machine learning that can help us know that.
00:31:52.000 --> 00:32:09.279
Um, and then finally, within the clear um abbreviation, R stands for uh uh repeat purchases, and this is where we really tie it all back to the monetary, and this part we actually measure with uh a predictive customer lifetime value model.
00:32:09.759 --> 00:32:15.839
Okay, and then we take all of that together and and score that uh to create a loyalty score from one to ten.
00:32:16.400 --> 00:32:24.319
Wow, and and and how long do you mean you know how much data do you need before you start getting some kind of reliable and recognizable outcomes?
00:32:24.720 --> 00:32:26.559
Yeah, it's it's a great question.
00:32:26.720 --> 00:32:43.440
Uh it would depend on the volume of um of traffic as well as how frequently customers are coming, but typically with um the machine learning piece, we would need about between one and two months of um history to train the models.
00:32:43.759 --> 00:32:46.799
I mean, we we're going through this interesting period.
00:32:46.880 --> 00:33:06.880
I mean, we we're capturing lots of examples of great um initiatives and and organizations who are getting to grips with what the right thing means and that realizing that putting the customer's world at the heart of their business and not just the customer means they move away from transactions and move towards sort of society betterment, which which is great.
00:33:06.960 --> 00:33:19.200
And it's really reassuring to hear in your definition of loyalty how it's a much broader inclusion of different aspects of the customers' um behaviour and interactions.
00:33:19.440 --> 00:33:21.519
So, what what lessons are there?
00:33:21.599 --> 00:33:28.480
What I mean, what opportunities are there for companies in the future then to come out of COVID?
00:33:28.960 --> 00:33:33.359
How can they behave differently to uh get an advantage in in the new world?
00:33:33.680 --> 00:33:41.920
Yeah, I think that um a huge understanding that's coming to a lot of businesses right now is how fast can we do something?
00:33:42.400 --> 00:33:45.759
And how fast can we go through digital transformation?
00:33:46.000 --> 00:33:51.839
How fast can we iterate on our product uh and just provide the best experience?
00:33:52.000 --> 00:33:58.400
And projects that uh businesses thought will take six months or a year are now being done in days.
00:33:58.480 --> 00:34:05.599
We see that everywhere, and we also see this um you know spark of of innovation that's just coming out of necessity.
00:34:05.839 --> 00:34:18.480
And I think that um companies will become even more agile and we understand that they have to react um even faster, and this that black Swan events like this, they're just unavoidable.
00:34:18.559 --> 00:34:24.239
We can prepare for the future as much as we want, but some events are just unpredictable.
00:34:24.639 --> 00:34:50.159
Um so they would have to um I think uh weave this nimbleness and agility into their DNA much more because uh the only way to prepare for another unexpected black Swan event is just to make sure that you are able to adapt very quickly and change quickly and gauge uh where the market is very fast.
00:34:50.960 --> 00:35:07.280
Okay, so so that that will mean ensuring that everyone recognizes that you know you have permission to adapt and are not creating such tight restraints on the way that you do business that it prevents you from actually moving forward, I guess.
00:35:07.519 --> 00:35:25.119
Oh yeah, I spoke to um uh uh another professor last week who was talking to me about the fact that the ability to respond to unpredicted events will become part of our experience assessment.
00:35:25.360 --> 00:35:57.039
So, actually, there's a lot that I like about an organization because they manage my expectations, they fulfill um my expectations, but actually, part of what I like about them will be the fact that although I don't know what the future looks like, I'm reassured that they will adapt and adjust in that situation, which is not something we've we're necessarily worried about before, but we're becoming more and more conscious of the fact that we do not know what the future holds so much.
00:35:58.159 --> 00:36:02.880
Precisely, and uh big organizations are known for being rather risk-averse.
00:36:02.960 --> 00:36:56.880
And I work with a lot of Fortune 100 and 500 companies, and we're implementing for them a lot of changes uh one by one, very gradual pace and checking everything, which is not a bad methodology, but I think that many businesses are now understanding that um they have to live in the spirit of continuous product design, and they just they they have to flow and move quickly and not be too afraid to break things, but when you have the right systems in place, um to always monitor what's happening on in your online business, and when you're sure that you know if if you're going to test something and just release multiple times a day, but you know that you have the system that is there for you and letting you know if something's breaking, then you will feel much more confident to adapt quickly to user needs as they unfold so fast and just changing all the time.
00:36:57.119 --> 00:37:03.599
The idea is that all of this sits on one data platform that prov provides one source of truth.
00:37:03.760 --> 00:37:10.800
Um, and this is where we're striving towards in quantum metric and providing to a great extent for many clients.
00:37:11.119 --> 00:37:31.599
But some uh sometimes um, you know, if if the voice of customer data is not being collected, um, I think that um the objective behavioral data can still help us to understand um most of what we need to know to take the right decision quickly in the moment, uh, if that data is coming real time.
00:37:32.000 --> 00:37:39.519
I think I've uh learned an awful lot um about a topic that's fascinated me for for a while.
00:37:39.599 --> 00:38:00.079
Um, and and you you've you've explained it so brilliantly, it's been so useful to spend this time, especially at the moment, uming that there is some sense in what we're seeing, there is some logic, some of the behaviours that we're seeing are perhaps a little bit more predictable than we thought they were going to be.
00:38:00.239 --> 00:38:10.559
And and obviously also that you know organisations like Quantum Metric are out there providing organisations with quality data and individuals like yourself to sort of interpret it.
00:38:11.039 --> 00:38:11.760
It's just wonderful.
00:38:11.840 --> 00:38:12.800
So thank you, Marina.
00:38:12.880 --> 00:38:15.199
I mean, we've got um you're welcome.
00:38:15.280 --> 00:38:38.559
As part of the the CX superheroes um positioning, what what's in there are superpowers, and two that are really, really important are the analyzer, so the ability to actually read and understand the data and make something of it, but also the interpreter who's able to convey it in a way that organizations then can understand and action it.
00:38:38.639 --> 00:38:46.559
And um they're two of the six superpowers, and just in a short time talking, clearly you're world-class when it comes to both of those.
00:38:46.639 --> 00:38:48.320
So thank you so much for your time.
00:38:48.400 --> 00:38:50.880
I'm I'm sure everyone's gonna get so much from listening to this.
00:38:50.960 --> 00:39:00.000
And and I guess if people want to contact you just to pose a question or speak to you more specifically about a challenge, what's the best way to get hold of you?
00:39:00.320 --> 00:39:00.559
Sure.
00:39:00.639 --> 00:39:03.679
So, first of all, thank you so much, uh Christopher, for those kind words.
00:39:03.760 --> 00:39:05.039
I'm very humbled.
00:39:05.440 --> 00:39:12.320
And I can be found online on my website, which is bybehavior.com with hyphen.
00:39:13.280 --> 00:39:21.679
I'm on Instagram with the same name, just underscore by underscore behavior, on Twitter as um Dr.
00:39:21.760 --> 00:39:31.280
Marina Shapira, and of course on LinkedIn, which has uh another platform um that they're really like just as Marina Shapira PhD.
00:39:31.599 --> 00:39:33.599
Wonderful, and and and that's great.
00:39:33.760 --> 00:39:37.679
So uh I would be very surprised if people don't contact you.
00:39:37.840 --> 00:39:41.920
Um, and uh, you know, please do um come back a later stage.
00:39:42.000 --> 00:39:59.519
You'll be really interested, perhaps in six months' time, just to reflect on on the findings that you you've got post-COVID-19, or maybe it'll be a year's time, just to sort of understand whether some of those changes have become um permanent changes, or whether we snapped back to our pre-COVID behaviors.
00:40:00.079 --> 00:40:06.400
Yes, that's a huge question, and I I have a few hypotheses and I can't wait um to see what happens.
00:40:06.639 --> 00:40:18.239
I also want to invite listeners uh to visit quantummetric.com to learn more about this continuous product design uh paradigm approach that can be so helpful during this time.
00:40:18.639 --> 00:40:28.559
Of course, and we'll we'll be we'll be in sure we'll surely uh reference it in our social posts as well because uh things are both uh yourself and the word that's happening at Quantum Metric sounds fascinating.
00:40:28.639 --> 00:40:30.320
So uh thank you once again.
00:40:30.480 --> 00:40:31.840
We'll we'll sign off there.
00:40:32.000 --> 00:40:35.599
So um, on behalf of all the listeners, once again, um uh Dr.
00:40:35.760 --> 00:40:39.920
Marina, uh, we very much thank you for your time.
00:40:40.159 --> 00:40:48.960
Wish you well in these these times, um, continue safe uh isolating and um uh really enjoyed speaking to you.
00:40:49.039 --> 00:40:50.320
So thank you again.
00:40:50.559 --> 00:40:52.320
Likewise, thank you.
00:00:18.000 --> 00:00:24.320
Hello, and welcome to another episode in Clientships Customer Experience Superheroes Podcast Series.
00:00:24.480 --> 00:00:34.960
My name is Christopher Brooks, and in series two, I'm going to be bringing you another episode, a special, in response to the COVID-19 crisis we're in.
00:00:35.200 --> 00:00:37.600
I am delighted to be joined by Dr.
00:00:37.840 --> 00:00:39.439
Marina Shapira.
00:00:39.679 --> 00:00:42.719
Marina is a specialist in consumer behavior.
00:00:43.039 --> 00:00:53.039
It's a topic that's fascinating at any time when you think about just what impact experiences can have on customers' behaviour and how you can change perceptions.
00:00:53.679 --> 00:00:56.640
Find that the reality is their actual behaviour changes.
00:00:56.799 --> 00:01:02.960
But even more so, it's important to understand what's going on in the middle of COVID-19 as we are now.
00:01:03.280 --> 00:01:14.079
How are consumers adjusting based on the information they're receiving, based on their needs and their expectations in this very challenging and unprecedented time?
00:01:14.319 --> 00:01:21.920
So we're absolutely delighted she's here to give us some insight and share with us some incredible research that she's been undertaking at the moment.
00:01:22.319 --> 00:01:36.159
As I mentioned, this is uh another special podcast, um, and we are delighted to be joined um by the head of behavioral research from Quantum Metric, and that is Marina Shapira.
00:01:36.400 --> 00:01:37.519
So welcome, Marina.
00:01:37.920 --> 00:01:39.519
Hi Christopher, thank you so much.
00:01:39.599 --> 00:01:41.359
I'm delighted to be here today.
00:01:41.920 --> 00:02:01.519
Great to have you, and uh, I mean, I think you and I probably would have uh spoken um definitely in this podcast series looking at CX superheroes because I think the the sort of work that you're doing is um is really really valuable and very insightful for for uh customer experience, but uh I guess given the current crisis um even more so.
00:02:01.680 --> 00:02:05.519
Now, great title, head of um behavioral research.
00:02:05.680 --> 00:02:10.000
Could you give uh the listeners an appreciation of what that actually means?
00:02:10.319 --> 00:02:11.360
Yes, of course.
00:02:11.520 --> 00:02:24.879
Um so I like to describe it as sort of a marriage between a few disciplines, uh psychology and behavioral science, which is kind of the theoretical framework that we base our insights and work on.
00:02:25.120 --> 00:02:36.560
But then we use really innovative research methods like machine learning to process digital analytics data, which is relatively new and is something um proprietary that we're doing.
00:02:36.800 --> 00:02:43.280
So it's it's really both worlds um enhance each other and complement each other really well.
00:02:43.439 --> 00:03:07.520
So there's heaps and heaps of data, um, and behavioral science lens really helps to understand what are the most important elements of the data and the insights that we're seeing that can really move the needle for companies and really make something influential for both the business and the end user who's using the digital product and really wants to get something out of it.
00:03:08.000 --> 00:03:10.400
And what was your journey to this position?
00:03:10.479 --> 00:03:12.319
What would your background include?
00:03:13.759 --> 00:03:15.520
Yeah, that's that's a great question.
00:03:15.599 --> 00:03:18.960
So I started um in pure psychology.
00:03:19.120 --> 00:03:24.719
Um did my PhD in cognitive developmental psychology.
00:03:24.879 --> 00:03:34.080
And as I was going through this process of academic research, um I really became very curious about how research is done in the sort of outside world, quote unquote.
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I was interested in venturing into the business world and bringing all that academic training and research and theory into customer experience and really helping companies, enterprises every day to touch millions of customers.
00:03:51.039 --> 00:03:57.919
I just felt like in this way I can influence more people faster if I'm applying my skills in the business world.
00:03:58.240 --> 00:04:11.599
So kind of towards the end of my PhD, I started looking at um at different research positions and actually started working at a company called Clicktail in a rather similar role.
00:04:11.680 --> 00:04:23.360
So it's a digital analytics company, and since then I moved a few other companies, and now I'm at uh Quantum Metric, which is um you know the industry leader in this field.
00:04:23.759 --> 00:04:24.240
Excellent.
00:04:24.480 --> 00:04:31.519
And I have to say I'm so pleased to hear that research is more and more involved in customer experience.
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I think um for quite a while the discipline has been focused from the the front line backwards, so we have a lot of great customer service people in um and marketing people and and even strategists, but uh I think there's been a lack of pure scientists and researchers in involved in customer experience, so it's it's great to hear you know of yourself um and also organizations like Quantum Metric kind of pushing the boundaries.
00:04:57.120 --> 00:05:00.319
So um I understand you know you're doing a lot of consumer research.
00:05:00.480 --> 00:05:08.160
It must be a very interesting time in sort of April 2020 to be undertaking research into consumer behaviors.
00:05:08.560 --> 00:05:13.120
I mean, um are you are you running research in on in the current uh crisis?
00:05:13.759 --> 00:05:14.879
Um yes, absolutely.
00:05:14.959 --> 00:05:40.480
It's a fascinating time, and there were a few hypotheses um that I had in the beginning of how customers will behave, and it's just so interesting to see it unfold um and actually matches um very basic theories in psychology, kind of how do we react in times of uncertainty, in times of change, and how does that change the way we interact with digital products and we go about our daily lives, basically.
00:05:40.800 --> 00:05:54.800
Okay, so at phantom metric, we um almost daily we analyze the data, we look at the trends, we keep updating the press, um, and just to give everyone the most up-to-date, fresh information to help them guide smart decisions.
00:05:55.120 --> 00:05:55.519
Sure.
00:05:55.600 --> 00:06:01.040
So so your your um your sample is it's a it's a global sample you're going out to, is it?
00:06:01.519 --> 00:06:06.959
Um it is um mostly based out of the US, currently, but also includes Europe.
00:06:07.199 --> 00:06:07.360
Okay.
00:06:08.319 --> 00:06:10.480
So it's a so it's a fairly good good poll then.
00:06:10.560 --> 00:06:14.560
And and you you say sort of um uh you're able to feed the press.
00:06:14.720 --> 00:06:22.560
So so you that suggests that you're actually turning this around pretty quickly if you're giving it to um organizations that then can publicize it.
00:06:23.279 --> 00:06:23.920
Certainly.
00:06:24.079 --> 00:06:37.439
I think that actually many um professionals in the data analytics field feel this pressure now of all eyes are on them, and uh data becomes this currency even more than before.
00:06:37.680 --> 00:06:49.040
Also, in communication between companies, it feels like any communication needs to have a good value exchange, and that value is coming from data and from user science.
00:06:49.360 --> 00:07:17.040
Yeah, well, I I think being in kind of the this overused word unprecedented times, um you can see uh governments being very reluctant to forecast and uh you know estimate what they think outcomes will look like because without the data there's just no certainty, and and I think we as consumers, certainly as citizens, um are valuing the importance of quality data in order to inform.
00:07:17.199 --> 00:07:33.279
As we see around the world certain nations who perhaps haven't submitted full data sets, you can see the di the you know the devastating impact it's having on their society when they're making changes and decisions based on half the information.
00:07:33.439 --> 00:07:34.560
So I completely agree with you.
00:07:34.720 --> 00:07:39.040
I think data's become um it's I wouldn't say it's it's fashionable.
00:07:39.199 --> 00:07:44.079
Data never seems to be fashionable, but it's become critical to uh to society.
00:07:45.680 --> 00:07:46.399
Certainly.
00:07:47.199 --> 00:07:51.199
Now um so you s you say you've you've got this research going going on at the moment.
00:07:51.360 --> 00:07:59.920
Ma may I ask, you know, what what are the sort of um the the major changes that you're seeing in consumer behaviour online then?
00:08:00.000 --> 00:08:04.319
What sort of things are you observing that um perhaps you you anticipated?
00:08:04.399 --> 00:08:11.279
You said sort of you know some of the basic human psychology and and our behaviors are just um being exaggerated.
00:08:11.439 --> 00:08:13.920
So what are the things that you're seeing that we'd expect to see?
00:08:14.000 --> 00:08:18.879
But also are there things coming out that are making you think, hey, I wasn't expecting to see that.
00:08:20.319 --> 00:08:22.800
Yes, definitely both are true.
00:08:23.040 --> 00:08:33.919
Um, so at first I was trying to look at basic theories in psychology and try to see if they can uh predict behavior um right now during this crisis.
00:08:34.159 --> 00:08:45.519
So one thing is that you know when we feel um greater uncertainty, our sense of control really goes down, and when we feel lack of control, our anxiety goes up.
00:08:46.399 --> 00:08:53.840
And one way to get back just a tiny bit of that control, for example, is to stock up on products.
00:08:54.240 --> 00:09:01.840
And that's why we've seen in February Hispanic shopping and um you know toilet paper disappearing uh from shelves.
00:09:01.919 --> 00:09:07.039
It's a way for people to mitigate and self-regulate their stress and their anxiety.
00:09:07.200 --> 00:09:19.759
And that might actually be a relatively harmless and not very expensive method uh of doing that, and of course, um needing to actually have those products in home if quarantine is about to start.
00:09:20.080 --> 00:09:27.519
And do you think with do you think with those those products actually it's almost uh it's almost irrelevant what the products are?
00:09:27.679 --> 00:09:29.600
It's the fact that you can exert control.
00:09:30.000 --> 00:09:35.360
If I feel I need eggs, if I feel I need washing powder, then I can buy washing powder.
00:09:35.440 --> 00:09:46.320
I'm um there's a very small thing I can control there, and therefore when the shelves are empty, it increases panic because the very small thing I thought I could control, I can't even control that.
00:09:47.279 --> 00:09:48.399
Yes, exactly.
00:09:48.559 --> 00:10:04.879
We're more likely to go towards very basic products because um when also when we are facing life's fragility and kind of almost um feeling a sense of we might have less time on earth than we think we might um before.
00:10:05.200 --> 00:10:07.279
It's called um a time horizon.
00:10:07.360 --> 00:10:13.759
So our time horizon is shorter now, uh, which leads us to really look inward and prefer things that we know.
00:10:13.919 --> 00:10:23.679
We don't want to broaden, we want to just you know, really optimize the present moment um and go with what we already know that makes us feel well and helps us.
00:10:23.759 --> 00:10:31.200
So we're not going to look for some um you know different uh product or something new and innovative that can help me.
00:10:31.279 --> 00:10:36.720
We're just going to double down on the basics, and that's probably why people were shopping for those essential parts.
00:10:37.279 --> 00:10:44.799
And does does it happen in the subconscious then, or is this something that we can actually access in our in our in our brains?
00:10:46.159 --> 00:10:52.960
The ability to change our our time horizon, or is it just something that happens to us that we're not aware of?
00:10:54.080 --> 00:10:56.080
We're typically not aware of that.
00:10:56.399 --> 00:11:11.759
Um people just do that intuitively, and we can see that also online when um you know, in just uh in the very early March, I released an article on this uh um phenomenon of time horizon and how can it impact online shopping.
00:11:11.919 --> 00:11:23.360
And I talked about this uh, you know, deep emotional connection that companies should talk to their customers in a more emotional way than ever, because this is what we favor when our time horizon is short.
00:11:23.440 --> 00:11:33.039
It's supported in research, and it's amazing to see that there's a flood of this type of emotional language right now, even too much.
00:11:33.120 --> 00:11:37.679
Um, I would say that some people are deterred from it because it might not feel as genuine.
00:11:38.000 --> 00:11:38.159
Right.
00:11:38.559 --> 00:11:54.000
So um the recommendation there might be even uh now, you know, the reverse that you need to, of course, communicate in this way that will speak to where your customers are at now from an emotional standpoint, but also don't overdo it, so it won't uh sound not genuine.
00:11:54.639 --> 00:11:56.320
Okay, so that's a really, really good point.
00:11:56.559 --> 00:12:04.000
And so the other sort of things that we experienced, what what about the things that you you you've seen come through that perhaps were less predictable?
00:12:04.960 --> 00:12:15.440
Um yeah, so just to add on uh some of the things that how we saw the panic shopping manifest online, there were a few very interesting metrics that that came together to support that.
00:12:15.519 --> 00:12:22.159
So for example, we saw that people are much more likely to discover products through search rather than navigation.
00:12:22.559 --> 00:12:34.240
And searching for something um means that you're goal-oriented, you know what you're looking for on an e-commerce website, and specifically we looked at websites that sell essential products.
00:12:34.480 --> 00:12:34.799
Yep.
00:12:35.360 --> 00:12:40.960
So instead of navigating where, oh, let me see what's under the linen category, you're less interested in that.
00:12:41.200 --> 00:12:42.320
You you know exactly what you need.
00:12:42.799 --> 00:12:44.240
Give me one second, Marina.
00:12:44.320 --> 00:12:49.519
Sorry, I've just got someone printing in the background, so I'll just get you to uh re say that bit.
00:12:49.600 --> 00:12:50.720
So I do apologize.
00:12:51.200 --> 00:12:51.679
No problem.
00:12:52.240 --> 00:12:56.879
Sorry, I I I I explained we were podcasting, but um it doesn't always get through.
00:13:03.840 --> 00:13:09.120
For some reason I've got a Henry Moore sculpture uh being printed out.
00:13:11.039 --> 00:13:18.720
I think I know what it is, my there's a there's a you a UK um army veteran who's walking around his garden a hundred times.
00:13:18.960 --> 00:13:21.039
He's a 99-year-old man.
00:13:21.440 --> 00:13:30.799
And um he has um he wanted to raise a thousand pounds for the National Health Service and he raised 12 million.
00:13:31.679 --> 00:13:32.080
Wow.
00:13:32.320 --> 00:13:34.399
Yeah, I know it's just um unbelievable.
00:13:34.720 --> 00:13:42.159
But um there's a campaign online to draw him get children to draw him pictures and say thank you.
00:13:43.120 --> 00:13:45.440
So I think that may be what I've got here.
00:13:45.600 --> 00:13:49.919
Um but oh yeah, I don't I can't see my son at the moment.
00:13:50.480 --> 00:13:51.120
Is it you?
00:13:51.279 --> 00:13:52.720
I'm on a podcast, Henry.
00:13:52.799 --> 00:13:55.039
So if you could just Yeah, right.
00:13:55.600 --> 00:13:55.919
Okay.
00:13:56.720 --> 00:13:57.519
Cool, sorry.
00:13:57.600 --> 00:14:04.559
So let's go back to uh that that that previous question about the other um things that you found.
00:14:05.279 --> 00:14:11.279
Um yeah, I I was about to describe um how we see online shopping manifest uh the panic shopping manifest on online.
00:14:11.679 --> 00:14:12.080
Mm-hmm.
00:14:12.480 --> 00:14:13.519
Yes, that's exactly right.
00:14:13.600 --> 00:14:14.159
Yeah, yeah.
00:14:14.240 --> 00:14:15.519
Let's go on go on that then.
00:14:15.600 --> 00:14:22.320
So the the the the other you were talking about in um uh goal-oriented shopping.
00:14:22.720 --> 00:14:24.240
Yeah, exactly.
00:14:24.559 --> 00:14:37.519
So we are seeing um online manifestations of panic shopping and different behaviors that coincide together and paint this picture of very goal-oriented and purchase-oriented uh behavioral patterns.
00:14:38.000 --> 00:14:44.559
So customers are much more likely to search um rather than use navigation on websites.
00:14:44.879 --> 00:14:56.240
Okay, search um is a function of a website that we use when we really know what we want, and we use navigation when we kind of want to explore and maybe see what's under a specific broad category.
00:14:56.480 --> 00:15:05.200
So, just like we said before, at this time we just want to get the products that we need um and make sure that uh you know we're safe, we're secure, and not explore.
00:15:05.919 --> 00:15:10.399
Anything that acceleration and broadening is going to decrease.
00:15:10.720 --> 00:15:24.879
And um similarly, we're seeing also that customers are much more faster to select the product, so they're looking um at product detail pages much less before they're hitting that add to back button.
00:15:24.960 --> 00:15:36.240
They're also might be fearing that inventory might go down, so they want to secure a specific product for themselves, as well as they're looking at more product pages per search that they make.
00:15:36.399 --> 00:15:41.759
So typically we see customers uh in a longer research phase, they're looking, they're more picky.
00:15:41.919 --> 00:15:50.240
Right now, they're hitting those product details pages very quickly, also because their searches are much more focused on what they need.
00:15:50.480 --> 00:15:51.120
Wow, okay.
00:15:51.279 --> 00:16:09.120
So that's yeah, also just one more metric um that that is very interesting is that the whole checkout process, both on mobile and desktop, um, is now um significantly shorter compared to in March 2020 compared to March 2019.
00:16:09.440 --> 00:16:23.360
So and it's the shortest on mobile, where typically checkout is more difficult and takes longer, but uh people are buying much more in the context of than here and now, and overall people are also shopping more for mobile.
00:16:23.840 --> 00:16:28.159
And uh that's why we're seeing those really uh speedy checkouts right now.
00:16:28.480 --> 00:16:46.879
Wow, so so that greater kind of um human instinct around the fact that we're our mortality is uh is at risk here and we're we're uh our life um is is is potentially shortened is actually played out on our online shopping behavior.
00:16:47.039 --> 00:16:50.080
You can see the correlation between the two, that's incredible.
00:16:50.720 --> 00:16:51.759
Yeah, precisely.
00:16:52.000 --> 00:16:55.919
Anyway, this is true specifically for websites that sell essential products.
00:16:56.159 --> 00:17:12.880
Yeah, some different trends might be seen in apparel or in cosmetics, um, where actually um people are shopping for somewhat different reasons, but uh for the panic shopping in uh online we're definitely seeing that in the essential category.
00:17:13.200 --> 00:17:13.920
Okay, great.
00:17:14.160 --> 00:17:21.039
And and are there any sort of odd things coming out that you you don't quite understand yet but are are of interest?
00:17:22.079 --> 00:17:32.400
Um not necessarily odd, but I personally expected that in March the panic shopping will attenuate and we're going to see more browsing from the desktop.
00:17:32.480 --> 00:17:36.640
We might see uh people that just want to spend some time.
00:17:36.720 --> 00:17:43.279
Uh so maybe exploratory patterns would go back um and restore the previous and maybe even grow.
00:17:43.519 --> 00:17:43.680
Right.
00:17:43.920 --> 00:17:50.319
And we are seeing that for apparel and for cosmetics, we're not seeing that for the essential category.
00:17:51.119 --> 00:18:05.119
And and so if I am a regular online shopper, I I've I've got a fairly good appreciation of what what a good experience looks like, what I should expect and and and what perhaps I shouldn't expect.
00:18:05.279 --> 00:18:17.279
If I give an example, when I've gone onto a hardware store, um I now get served with a message to say you can access the site in five minutes due to um exceptional levels of traffic.
00:18:17.599 --> 00:18:31.519
If the expectations that I had pre-COVID-19 are not being met, are consumers uh accommodating that or are they intolerant and sort of saying, right, forget it, I'm on to the next one?
00:18:31.599 --> 00:18:35.200
What's your what's your view or what's the observation from the research on that?
00:18:36.079 --> 00:18:43.200
Um yeah, so um unfortunately we're seeing um somewhat less tolerance to that.
00:18:43.359 --> 00:18:52.799
Um because we're seeing this, uh, like you just uh said, an influx in new customers coming, which is can be a great opportunity or a threat.
00:18:53.119 --> 00:19:03.839
Because if the experience is great, then customers are much more likely to remember it because our brain is wired to remember peak experiences, yeah, and we're definitely in a peak experience right now.
00:19:04.079 --> 00:19:11.920
So if a brand served me now, um that might contribute to my loyalty going forward because they helped me in a time of need.
00:19:12.319 --> 00:19:17.200
And again, that would depend on the category and how essential that is.
00:19:17.440 --> 00:19:22.400
But in general, we now completely depend on online to get everything that we need.
00:19:22.640 --> 00:19:24.319
This is our window to the world.
00:19:24.640 --> 00:19:42.000
So if some company blocked my window to the world or something was ambiguous about um the experience, like shipping was not clear, or I can't even access the site, then this will um you know, people are going to remember that much more than during normal times.
00:19:42.480 --> 00:19:51.039
And then unfortunately, we are also seeing among new customers um higher frustration rates as well as a higher error rate.
00:19:51.279 --> 00:19:51.440
Right.
00:19:51.680 --> 00:20:06.720
So some of this is stemming because um they are going through flows like account creation or first checkouts that typically have a lot of friction points and might also experience a huge influx in traffic, which might uh slow them down.
00:20:06.880 --> 00:20:09.440
We're seeing websites being much, much slower.
00:20:09.680 --> 00:20:15.759
And of course, we know that we have about two minutes for a website to load before we abandon.
00:20:16.240 --> 00:20:30.640
So, in this spirit of urgency um and of really goal-oriented behavior and speedy um uh checkout processes and shopping journeys overall, there is much less time to impress customers right now.
00:20:31.039 --> 00:20:42.480
So, um and and I think what you mentioned there about this influx of new customers, I mean, I guess there's a particular age demographic that are having to engage that previously have decided not to.
00:20:42.720 --> 00:20:52.799
So this this this new influx of customers, they're not coming there willingly, they're not coming there for fun and entertainment and to find a better way.
00:20:53.039 --> 00:20:54.799
They're coming because they have no choice.
00:20:54.960 --> 00:21:06.880
So I guess if when they get there, the very thing that they've resisted then doesn't work, it almost reaffirms to them that their decision to not shop online was the right one.
00:21:07.039 --> 00:21:15.279
So companies will who fail those customers at this time will lose them forever, I s I suggest.
00:21:15.920 --> 00:21:16.960
Yeah, definitely.
00:21:17.039 --> 00:21:18.160
I I completely agree.
00:21:18.240 --> 00:21:24.319
I'm doing a lot of uh work in terms of uh conceptualizing and measuring online loyalty.
00:21:24.960 --> 00:21:37.759
And where we know from our own research that accumulation of several errors and mistakes, um, as much as three can start to fraction and deteriorate online loyalty.
00:21:38.000 --> 00:21:41.359
Um so that will probably be confounded at this time.
00:21:42.160 --> 00:21:45.680
So as as few as as three mistakes, and that's it, I'm out.
00:21:45.759 --> 00:21:47.599
This is just too painful now.
00:21:48.480 --> 00:21:50.000
Um in certain cases, yes.
00:21:50.160 --> 00:21:50.559
Yeah, okay.
00:22:00.160 --> 00:22:08.240
Loyalty, it's it's not um, you know, they're probably um there we have this loyalty score, so they're going down on the loyalty score.
00:22:08.400 --> 00:22:19.920
They might abandon completely, but um, they're more likely just to uh have a lower loyalty score, which is correlated also to how much money at the end of the day they will bring into this business.
00:22:20.079 --> 00:22:24.559
So this is definitely a negative outcome uh from a business KPI standpoint.
00:22:24.880 --> 00:22:27.759
So let's let's stay on loyalty because I know this is your specialism.
00:22:27.920 --> 00:22:43.039
So you mentioned there about sort of peak experiences, and I kind of understand the difference between um an actual experience and the remembered experience, and the remembered experience can quite often create a very different impression than what you actually went through.
00:22:43.359 --> 00:22:48.240
So with with that said, it do we do we need to rethink loyalty?
00:22:48.400 --> 00:23:03.599
I mean, if I'm a if I'm working, if I'm a customer of a business, then that business typically will reward my loyalty based on the number of transactions that I'm giving to them rather than giving them to the competition.
00:23:03.839 --> 00:23:20.799
But actually, if I've been through an experience such as COVID-19 and I've been really impressed with an organization, um maybe I've not had that many transactions with them, but potentially emotionally, we're gonna get a loyalty now going on that's gonna last forever.
00:23:21.039 --> 00:23:28.480
So, does it mean organizations need to really r think about how they define loyalty with their customers?
00:23:29.759 --> 00:23:30.960
Yes, definitely.
00:23:31.039 --> 00:23:32.240
Uh, I think so.
00:23:32.559 --> 00:23:39.839
We now know uh through our research that loyalty is just like you're saying, it's more than just the transactions.
00:23:40.160 --> 00:23:53.279
And it is very much also dependent on habitual patterns of behavior and something that is quite fuzzy and might be difficult to measure, which is the emotional piece, emotional loyalty.
00:23:53.599 --> 00:24:04.720
And I think that online um traditionally were these anonymous sessions that couldn't really be tied in together into one cohesive view of a person.
00:24:04.960 --> 00:24:09.119
But now with the technological solutions, we are much beyond that point.
00:24:09.359 --> 00:24:12.000
But not all digital businesses have cut up to that.
00:24:12.400 --> 00:24:20.400
So this is why most businesses are optimizing for conversion rate because it is, of course, tied to a very clear business outcome.
00:24:20.559 --> 00:24:28.000
But in a sense, it's easier to think about um one online session and its immediate outcome, which is conversion.
00:24:28.480 --> 00:24:37.279
But over the long term, what is going to be much more profitable is measuring customer loyalty and how and even predicting it and how it unfolds over time.
00:24:37.519 --> 00:24:46.720
And what are how to sum up all those micro interactions to create a true relationship with a customer, which is going to be much more profitable.
00:24:46.880 --> 00:25:04.640
And I think everybody knows those statistics of you know how much cheaper it is to retain an existing client between five to twenty five times, and that um, you know, the top 10% of uh of our most loyal customers are bringing most of the revenue.
00:25:04.720 --> 00:25:11.759
So all of these stats are across the internet, but then how do we actually do something actionable and and measure this?
00:25:12.240 --> 00:25:26.160
What we are doing is we're combining several metrics with a predictive approach, and what we are looking at is behavioral patterns like how frequent um is a customer shopping online and what is his sentiment.
00:25:26.400 --> 00:25:38.480
Uh, for example, using voice of customer um tools in combination with uh objective behavioral measures like we see in digital analytics.
00:25:38.559 --> 00:25:47.920
So we're basically completing the picture, we're looking at um just objective browsing data in which uh you know uh we record what customers do online.
00:25:48.079 --> 00:26:01.359
So they of course it's ethical and legal, but they don't necessarily know that um their behavior is being trapped at that moment, so they're just being uh natural and this is uh almost as bias-free data as you can get.
00:26:01.920 --> 00:26:07.759
But then we combine that and weigh that against what they're actually saying because that's very important.
00:26:08.240 --> 00:26:20.319
So in in customer experience, we know that what uh people do is not exactly what they say, which is it's it's true, but we want to know what they're saying because this is their emotional experience.
00:26:20.720 --> 00:26:37.759
So by being able to distill those reactions on voice of customer tools and combining that with um you know sort of pure behavioral data, we're able to uh paint a complete picture of how loyal they are to a specific brand.
00:26:39.200 --> 00:26:54.240
So I mean I'm I'm find this topic just so fascinating because um if I'm a new company or if I'm investing in digital, one of the strengths of of digital is the ability to measure data points.
00:26:54.480 --> 00:27:02.319
Um but as you say, the emotional value of loyalty is is fuzzy and it's difficult to assess.
00:27:02.480 --> 00:27:06.720
And as you were talking, I was just thinking of an example from from Amazon, for instance.
00:27:06.880 --> 00:27:24.400
So if I take Amazon, who have during this time said, look, we're gonna prioritize from our uh uh in our marketplace some particular product lines, and these are these are back to what you said, these are the essentials, these are the ones that create anxiety, pet foods, health products, those sort of things.
00:27:24.720 --> 00:27:27.839
Everything else is going to be pushed back.
00:27:28.240 --> 00:27:38.799
Um now I know uh my my my dad, for instance, has never really been an online shopper, but has chosen to shop during this time and has done grocery shopping and Amazon shopping.
00:27:39.039 --> 00:27:43.599
But he went on to Amazon and he said it's rubbish, it takes so long to get anything.
00:27:43.920 --> 00:28:04.160
So from his perspective, it's not delivering the strength that he's understood it to deliver, but from my perspective, emotionally, I'm really, really deeply attached to Amazon because they're making the right choices, which will not go on any transactional data set.
00:28:04.400 --> 00:28:13.920
What they'll see is as you say there in the verbatim from me saying you're making the right choices, and that's why I will continue to shop with you above others.
00:28:14.240 --> 00:28:17.519
So it's a really interesting space that you're moving into.
00:28:17.759 --> 00:28:35.599
There must be one that's quite challenging when people throw data sets showing a correlation between you know retention transactions and increased share a category, whereas you're trying to use the language to explain this is a much much more complicated relationship when it comes to loyalty.
00:28:36.400 --> 00:28:39.440
Yes, definitely, but they're intercorrelated.
00:28:39.680 --> 00:28:44.400
So those emotions they're driving uh people returning to a website.
00:28:44.559 --> 00:29:08.559
So we know that the frequency of just plain visits without a purchase and how um um the the recency also of purchasing, so sort of the time that elapses between your first and last purchase, that they have also a huge correlation with ultimately how much a customer is worth to a business, which we always have to tie back to business KPIs, right?
00:29:08.640 --> 00:29:13.200
To to make digital uh organizations care about that, to improve the experience.
00:29:13.279 --> 00:29:26.400
So it's nice that when we're talking about loyalty, uh improving a business KPI is actually going hand in hand with improving someone's uh you know ability to achieve his uh goals and needs online, which are not really critical.
00:29:26.720 --> 00:29:32.240
But definitely they're intercorrelated and the emotion is driving the behavior.
00:29:32.400 --> 00:29:52.079
So I would almost say that looking at the behavioral pattern um above and beyond just purchases, but like also like visits, their duration, um, and different um metrics of the visit quality can also tell us quite a bit um about the the emotional loyalty.
00:29:52.160 --> 00:30:02.480
And of course, in a market it has competition because if there is lack of competition then and people are buying uh you know, because they have no other place to buy, then it's a it's a different dynamic there.
00:30:02.880 --> 00:30:04.880
So is there a new model for loyalty then?
00:30:04.960 --> 00:30:13.119
I mean, do you have a framework that you're working towards that will become, you know, I think uh you know, we we we crudely used to work on RFM, didn't we?
00:30:13.359 --> 00:30:15.119
Recency Frequency Manetry.
00:30:15.440 --> 00:30:18.400
I mean, what what is the new framework for loyalty?
00:30:18.880 --> 00:30:46.319
Yeah, so um my framework um that I coined and we're working on um at Quantum Metric is the acronym is CLEAR framework, um, and it stands for cognitive, a part of the cognitive loyalty, which is more of kind of the brand awareness, um just checking through metrics that customers were exposed to the main business offering, that they even know what we're um want to provide to them.
00:30:46.400 --> 00:30:52.799
And by the way, that would be a huge percentage of every digital organization um um client base.
00:30:53.279 --> 00:31:00.799
So most would be pre-transaction, uh, kind of very low loyalty for now, but a huge opportunity to move them up the ladder.
00:31:00.960 --> 00:31:11.680
And then the L would stand for um loving or liking a specific brand, which here we would measure all the sentiment data that's coming through a voice of customer.
00:31:11.920 --> 00:31:16.319
So uh the I in clear would measure the intent.
00:31:16.480 --> 00:31:24.559
It is very important to be able to predict what is the intent of the specific journey that um customers are having right now.
00:31:24.720 --> 00:31:30.640
Is it uh purchase-oriented visit for to a website, or are they still in the research phase?
00:31:30.799 --> 00:31:40.640
Because we know that before we buy something, even something small, um typically not during COVID, we want to have a few research uh visits, mainly from mobile.
00:31:40.799 --> 00:31:45.279
So a visit without a transaction on mobile is not necessarily bad, but how do we know that?
00:31:45.440 --> 00:31:51.839
So we develop um uh predictive analytics models through machine learning that can help us know that.
00:31:52.000 --> 00:32:09.279
Um, and then finally, within the clear um abbreviation, R stands for uh uh repeat purchases, and this is where we really tie it all back to the monetary, and this part we actually measure with uh a predictive customer lifetime value model.
00:32:09.759 --> 00:32:15.839
Okay, and then we take all of that together and and score that uh to create a loyalty score from one to ten.
00:32:16.400 --> 00:32:24.319
Wow, and and and how long do you mean you know how much data do you need before you start getting some kind of reliable and recognizable outcomes?
00:32:24.720 --> 00:32:26.559
Yeah, it's it's a great question.
00:32:26.720 --> 00:32:43.440
Uh it would depend on the volume of um of traffic as well as how frequently customers are coming, but typically with um the machine learning piece, we would need about between one and two months of um history to train the models.
00:32:43.759 --> 00:32:46.799
I mean, we we're going through this interesting period.
00:32:46.880 --> 00:33:06.880
I mean, we we're capturing lots of examples of great um initiatives and and organizations who are getting to grips with what the right thing means and that realizing that putting the customer's world at the heart of their business and not just the customer means they move away from transactions and move towards sort of society betterment, which which is great.
00:33:06.960 --> 00:33:19.200
And it's really reassuring to hear in your definition of loyalty how it's a much broader inclusion of different aspects of the customers' um behaviour and interactions.
00:33:19.440 --> 00:33:21.519
So, what what lessons are there?
00:33:21.599 --> 00:33:28.480
What I mean, what opportunities are there for companies in the future then to come out of COVID?
00:33:28.960 --> 00:33:33.359
How can they behave differently to uh get an advantage in in the new world?
00:33:33.680 --> 00:33:41.920
Yeah, I think that um a huge understanding that's coming to a lot of businesses right now is how fast can we do something?
00:33:42.400 --> 00:33:45.759
And how fast can we go through digital transformation?
00:33:46.000 --> 00:33:51.839
How fast can we iterate on our product uh and just provide the best experience?
00:33:52.000 --> 00:33:58.400
And projects that uh businesses thought will take six months or a year are now being done in days.
00:33:58.480 --> 00:34:05.599
We see that everywhere, and we also see this um you know spark of of innovation that's just coming out of necessity.
00:34:05.839 --> 00:34:18.480
And I think that um companies will become even more agile and we understand that they have to react um even faster, and this that black Swan events like this, they're just unavoidable.
00:34:18.559 --> 00:34:24.239
We can prepare for the future as much as we want, but some events are just unpredictable.
00:34:24.639 --> 00:34:50.159
Um so they would have to um I think uh weave this nimbleness and agility into their DNA much more because uh the only way to prepare for another unexpected black Swan event is just to make sure that you are able to adapt very quickly and change quickly and gauge uh where the market is very fast.
00:34:50.960 --> 00:35:07.280
Okay, so so that that will mean ensuring that everyone recognizes that you know you have permission to adapt and are not creating such tight restraints on the way that you do business that it prevents you from actually moving forward, I guess.
00:35:07.519 --> 00:35:25.119
Oh yeah, I spoke to um uh uh another professor last week who was talking to me about the fact that the ability to respond to unpredicted events will become part of our experience assessment.
00:35:25.360 --> 00:35:57.039
So, actually, there's a lot that I like about an organization because they manage my expectations, they fulfill um my expectations, but actually, part of what I like about them will be the fact that although I don't know what the future looks like, I'm reassured that they will adapt and adjust in that situation, which is not something we've we're necessarily worried about before, but we're becoming more and more conscious of the fact that we do not know what the future holds so much.
00:35:58.159 --> 00:36:02.880
Precisely, and uh big organizations are known for being rather risk-averse.
00:36:02.960 --> 00:36:56.880
And I work with a lot of Fortune 100 and 500 companies, and we're implementing for them a lot of changes uh one by one, very gradual pace and checking everything, which is not a bad methodology, but I think that many businesses are now understanding that um they have to live in the spirit of continuous product design, and they just they they have to flow and move quickly and not be too afraid to break things, but when you have the right systems in place, um to always monitor what's happening on in your online business, and when you're sure that you know if if you're going to test something and just release multiple times a day, but you know that you have the system that is there for you and letting you know if something's breaking, then you will feel much more confident to adapt quickly to user needs as they unfold so fast and just changing all the time.
00:36:57.119 --> 00:37:03.599
The idea is that all of this sits on one data platform that prov provides one source of truth.
00:37:03.760 --> 00:37:10.800
Um, and this is where we're striving towards in quantum metric and providing to a great extent for many clients.
00:37:11.119 --> 00:37:31.599
But some uh sometimes um, you know, if if the voice of customer data is not being collected, um, I think that um the objective behavioral data can still help us to understand um most of what we need to know to take the right decision quickly in the moment, uh, if that data is coming real time.
00:37:32.000 --> 00:37:39.519
I think I've uh learned an awful lot um about a topic that's fascinated me for for a while.
00:37:39.599 --> 00:38:00.079
Um, and and you you've you've explained it so brilliantly, it's been so useful to spend this time, especially at the moment, uming that there is some sense in what we're seeing, there is some logic, some of the behaviours that we're seeing are perhaps a little bit more predictable than we thought they were going to be.
00:38:00.239 --> 00:38:10.559
And and obviously also that you know organisations like Quantum Metric are out there providing organisations with quality data and individuals like yourself to sort of interpret it.
00:38:11.039 --> 00:38:11.760
It's just wonderful.
00:38:11.840 --> 00:38:12.800
So thank you, Marina.
00:38:12.880 --> 00:38:15.199
I mean, we've got um you're welcome.
00:38:15.280 --> 00:38:38.559
As part of the the CX superheroes um positioning, what what's in there are superpowers, and two that are really, really important are the analyzer, so the ability to actually read and understand the data and make something of it, but also the interpreter who's able to convey it in a way that organizations then can understand and action it.
00:38:38.639 --> 00:38:46.559
And um they're two of the six superpowers, and just in a short time talking, clearly you're world-class when it comes to both of those.
00:38:46.639 --> 00:38:48.320
So thank you so much for your time.
00:38:48.400 --> 00:38:50.880
I'm I'm sure everyone's gonna get so much from listening to this.
00:38:50.960 --> 00:39:00.000
And and I guess if people want to contact you just to pose a question or speak to you more specifically about a challenge, what's the best way to get hold of you?
00:39:00.320 --> 00:39:00.559
Sure.
00:39:00.639 --> 00:39:03.679
So, first of all, thank you so much, uh Christopher, for those kind words.
00:39:03.760 --> 00:39:05.039
I'm very humbled.
00:39:05.440 --> 00:39:12.320
And I can be found online on my website, which is bybehavior.com with hyphen.
00:39:13.280 --> 00:39:21.679
I'm on Instagram with the same name, just underscore by underscore behavior, on Twitter as um Dr.
00:39:21.760 --> 00:39:31.280
Marina Shapira, and of course on LinkedIn, which has uh another platform um that they're really like just as Marina Shapira PhD.
00:39:31.599 --> 00:39:33.599
Wonderful, and and and that's great.
00:39:33.760 --> 00:39:37.679
So uh I would be very surprised if people don't contact you.
00:39:37.840 --> 00:39:41.920
Um, and uh, you know, please do um come back a later stage.
00:39:42.000 --> 00:39:59.519
You'll be really interested, perhaps in six months' time, just to reflect on on the findings that you you've got post-COVID-19, or maybe it'll be a year's time, just to sort of understand whether some of those changes have become um permanent changes, or whether we snapped back to our pre-COVID behaviors.
00:40:00.079 --> 00:40:06.400
Yes, that's a huge question, and I I have a few hypotheses and I can't wait um to see what happens.
00:40:06.639 --> 00:40:18.239
I also want to invite listeners uh to visit quantummetric.com to learn more about this continuous product design uh paradigm approach that can be so helpful during this time.
00:40:18.639 --> 00:40:28.559
Of course, and we'll we'll be we'll be in sure we'll surely uh reference it in our social posts as well because uh things are both uh yourself and the word that's happening at Quantum Metric sounds fascinating.
00:40:28.639 --> 00:40:30.320
So uh thank you once again.
00:40:30.480 --> 00:40:31.840
We'll we'll sign off there.
00:40:32.000 --> 00:40:35.599
So um, on behalf of all the listeners, once again, um uh Dr.
00:40:35.760 --> 00:40:39.920
Marina, uh, we very much thank you for your time.
00:40:40.159 --> 00:40:48.960
Wish you well in these these times, um, continue safe uh isolating and um uh really enjoyed speaking to you.
00:40:49.039 --> 00:40:50.320
So thank you again.
00:40:50.559 --> 00:40:52.320
Likewise, thank you.
