Conversions are a byproduct of great customer engagement
Prashant Kumar, VP of Products at Bluecore, a retail marketing platform that enables marketers to connect casual shoppers to the products that transform them into lifetime customers, joins us for a highly insightful conversation.
He shares how one visit to witness the day in the life of a brand front liner was an awakening that shaped the future of his career. Prashant shares insights about what marketers need for customer retention. He also talks about how data, empathy, intelligence and being flexible can feed the demands of an evolving customer. Identification of the customer demands remains the key to successful outcomes for both the brand and the consumer.
Vandana: Hey Prashant, very good morning and welcome to the FailFast podcast. How are you?
Prashant: Hey Vandana, good morning. Nice to meet you.
Vandana: Same here, same here. I can’t wait to dive into your world, Prashant, and know how the heck are you converting, you know, first-timers on your customer’s website into lifetime consumers. So that’s like super interesting for us. But before we dive into that, let us talk about you.
Let’s get a little bit of a background for our listeners today about your journey, about where you’re coming from, a little bit, five, seven minutes of your background, please.
Prashant: Sure. So I’m a career engineer and a geek. I have been trained as an engineer, grew up like pretty much taking everything apart in my house and my park was pretty much set and I couldn’t stand blood. So any biology related career was ruled out at a very young age. My career has been a mixture of serendipity and blessing, and then by design, choosing certain pathways.
I started off my career working for Apple and I was fortunate to work on some really cool projects where we helped launch like for the first 50, 60 Apple retail stores and all the point of sale systems and the training systems that went in. I was working on iTunes and then I went on to work in UK for British Telecom, where we helped take the entire country from dial-up internet, if any of my listeners are old enough and they remember the sound of the modern of KBPS going all the way to 8 Mbps of broadband. This is back in the early 2000s.
As I was doing that, that was my first brush with, I was an engineer building all of these architecting solutions and when we tried to market it and bring it to the market, because it was the first of its kind product, it was my first brush with understanding what a customer or an end consumer goes through when you build something.
As a geek, as a technologist, you have this sort of utopic view of your product of how it should be used and you have almost what I like to call an intelligent view. This is how it’s going, this is how it’s got to be done and why it’s so obvious, why aren’t you doing it this way? The moment you start seeing somebody who doesn’t know anything about it and wants to use it for its intended purpose, try to use it, you gain a serious amount of humility and empathy to understand what the customer is actually dealing with. So that was my first brush with it and I helped from engineering, I moved on more onto the product side to help the team market it, price it, bring it to market, bring the feedback loop back to the development team to actually refine the product and this was purely a backend kind of product.
What it does is it sits in every exchange in the last mile to improve your internet broadband. So it’s not something that a customer actually sees, but they experience every time they go online, sort of talk about such a product and stuff like that. And that got me hooked, so then I had the opportunity to come to the US and work with some really incredible leaders and my first job here at Sears was to work with Eddie Lamport and I was his chief of staff and it was an incredible experience where I got the opportunity to see the workings of a company from a bird’s eye view through the eyes of an investor, but also the eyes of an operator who’s actually executing products.
And over the last decade and a half, two decades, initially by serendipity and then by choice, I have pretty much grown my career to be very much about driving customer retention, enabling that through marketing technologies and driving customer engagement once they are on the platform. Now, Sears, we started doing this well before terms like ML, AI, you know, self algorithms were like the norm.
We started doing this at Sears where you’re personalizing 30 plus touch points for a customer across in-store, online, off and offline. My career took me for much further west to the west coast and I came to the Bay Area in early 2010s and I spent the bulk of my time here working for eBay and it was basically doing what we did at Sears, but at a much bigger scale, right? Because you’re operating with petabytes of data, you’re working on a much more pure e-commerce play and you have different kinds of signals.
The whole idea was how do you basically understand the shopper, how do you drive data driven nimble marketing, which pivots on certain four tenets, which I can talk about later. Today, I’m very fortunate that I’m able to take whatever I have done in the past and what I actually believe in at my core, that retention and driving quality retention is way more important than acquisition, right?
Acquiring people who are right for the brand is important, retaining them for the brand is even more important because that drives the organic growth for the brand. And now what we’re doing here at Bluecore and I joined Bluecore about a year and a half ago is democratizing the work we did at Sears and eBay and bringing it to a whole suite of retailers who are trying to basically have speed to market and speed to value. So that’s sort of two plus decades of career distilled in about two minutes.
Vandana: That’s amazing and what a great journey. I mean, you touched upon some really great brands and I’m sure that, you know, the key learnings of, you know, the summary of all of that is showing up in your career today.
Can you share a story maybe of an early time, maybe with Apple or any other organization that you just mentioned where, you know, you got that sense of, oh my God, this is why I’m doing this or this is the right path for me. You know, maybe anything comes to mind where, you know, we all have those moments of realization that when we realize, yeah, this is my purpose and yeah, this is my skill and I’m matching my purpose to my skill and this brand is helping me grow.
Prashant: Yeah, certainly. There are a couple of instances, aha moments that I had in my career, which for me were very humbling, right? So I can give you maybe two experiences. So one was my time at Apple where, so after you build something, one of the tenets we had at my group at Apple was you had to go support it for six months. So you had to actually be as part of production support, do bug fixes, take on calls, customer queries, and all of those things.
And it was fascinating that when you build something, the mindset, and this is like me being very early in my career, right? Like didn’t know anything from Adam, but it was fascinating that when you build something with a certain mindset and then when you see it come to life and then even who you think is a power user, see them tackle it differently or use it for solving different problems, kind of changes perspective, right?
So initially and, you know, being like a maverick, you’re all like, you know what, build it, they will come. I know best for people kind of mindset, right? And I mean, that one step was a big pivoting point of us. You don’t have to sort of assume, right? And that kind of set my career into a different sort of mindset and trajectory of A, do not sort of assume that this is what is the use for it. This is not what is the best possible outcome.
Have an iterative approach and ask people so that you can actually build stuff that they care about. The second big sort of aha moment that I really want to share with you and the listeners is I was so at Sears when I first joined, I was responsible for building out our loyalty program. And as part of that exercise, we had like one version of it out in a few test stores and I was asked to go to a store.
And since as part of the leadership program, this is one of the things mandated that you have to actually go work in our stores to interact with customers and see a day in the life of our frontline teams, right? So I was running the, probably one of the most brutal experiences I’ve had for our cashiers and anybody who works in like front end and retail, like in the in-store experience when they are being put, a system is being put in front of them and they’re asked to ask the shopper 15 questions before they check out, the shopper is impatient.
And you as somebody who’s orchestrating like a strategy or being from the corporate office have no clue what the frontline team goes through and what the shopper is going through, right? It was literally that moment when I was standing there checking somebody out and they literally had like maybe three items.
And what was fascinating to me was it took me more time, I took more of their time asking all the questions. Do you want to sign up for a credit card? Do you want to sign up for our loyalty program? Do you want to redeem these points? Do you want these coupons? It took me more time to ask them all of these things than it took me to actually check them out for the stuff that they bought, right? And it got to the point where some of the customers are just laughing at me. They’re like, we know what you’re doing. We understand it, but this is not fun anymore, right?
So I came back from that experience with a greater sense of empathy, a great purpose, and almost a stubbornness that I will not build stuff that is going to make my, not just my, the user of my product, but also the influencer of who the product influences is not going to make their life miserable, right? I can view that in my day-to-day work. So those are the sort of very formative moments when a product manager, as an engineer, as somebody who builds stuff that impacted customers on a day-to-day basis. And that has really shaped how I think about products, how I think about experiences, and ultimately how I think about technology.
Vandana: Great. And what a great insight into that. So how would you handle it differently then? How would you handle the same scenario, knowing now what you know and what you learned?
Prashant: So I think a couple of things, right? Number one, we tend to sort of overcomplicate experiences as things that we want to do, starting with the user and simplifying what needs to be done. And that is a great virtue in actually organization of information, right? You often sort of conflate complexity with poor organization. Poor organization leads to, or like poor workflows lead to like a lot more perceived complexity than actually the amount of information or complexity that you have in the product.
A good case in point is take any of the well-designed sites that you have, or take a well-designed product like say Apple, what they provide, right? It’s a pretty complex product. The way it’s organized, the way the workflows will operate, the consistency of experiences, and having cognizance of certain fundamental things that cannot be slow. For example, when you’re browsing on Safari, okay? The way your mouse moves and moves the screen, you never experience hiccups or hangups, right?
That’s something that very early on, I’m talking back in the early 2000s when I was working at Apple, the teams understood that those are sort of core fundamental experiences that you don’t want to frustrate a user.
When you want to close an application and it’s not responsive, you don’t want to sort of struggle with it. So yeah, you might have the spinning beach ball, or you can force quit an application. To me, these are all like fundamental experiences that you want to make sure that you’re simplifying and having a core experience that doesn’t deviate from the principles.
And then you have layers of complexity, you can do a whole bunch of things, but they’re organized properly. I hope I’m articulating this well, but that’s one major way I see solving the problem. The second thing that I’ve kind of brought back in terms of understanding is, what is the incentives? Understanding incentives is actually really important.
So I’ll give you an example from my day-to-day life today, right? Today, the marketing technology platforms that we build, okay, they’re sold to senior business leaders on the marketing organization or the technology organization. The people who use it on a day-to-day basis are actually very different. So having user personas and building different aspects of the products for these user personas makes a difference, right? And not being cognizant of that invariably results in frustrations.
Vandana: So then how would you change that approach to asking the right questions? What did you do in that scenario where you were asking the questions and it was taking more time than the actual transaction that the customer was there for? How would you then look at that scenario?
Prashant: See, I think for me, right, let’s start with core tenets. It starts with data, but then it’s on flexibility. So for me, when I say it starts with data, right, whether it’s the experience that you’re driving in store or online, what is the ultimate goal or metric that you’re trying to move? Let’s start with that question first, right, and then make it pithy to address those questions and the workflow sort of works well back. I want to pivot and talk a little bit about like, for example, what we do today, and that will probably give you the connection on how we address some of these things.
It starts with data, which means in today’s case, when you’re building a marketing technology platform, you have to understand your shopper very well, okay? A lot of marketing technologies, for example, want to focus only on conversion, but conversion is a byproduct, right? They really focus on the full funnel of the shopper’s experience and thereby demonstrate that you understand the shopper, right? So the way this manifests is you don’t ask 15 questions if you understand shopper upfront and all you do is ask them one question or no questions because you already know that they are a loyalty member or you already know that they have purchased these items, so there’s no point asking them about some other item, right?
Connecting experience with data and bringing the data to life in a format that really makes your sort of communication personalized can manifest in many ways, right? Whether it’s actually a call center person talking to somebody on the phone, whether it’s a cashier actually interacting with somebody at the till or your website actually showing some information or your email actually coming up to you, right? So understanding the shopper, understanding like pivoting on the starting with data is very, very important.
Focusing on the full funnel rather than just the last mile, very important, right? Now, when you start thinking about all of these things, it’s also like when I think about my primary consumer of my product today, it’s also important that we not only start with data but we pivot on flexibility. So things like your marketing solutions being extensible so that they can actually connect with other systems so that they’re not buying redundant systems, giving control to the marketers on automation and AI so that they are not like working off of a black box, right?
So bringing speed to communications and value by identifying signals and then building a platform such that you’re able to convert a signal to an action immediately is another example of where you are able to empathize and understand your primary consumer needs and your secondary consumer needs and you reduce friction by integrating that, sort of absorbing that complexity into the platform and not having the end user bear the burden of it.
Vandana: Very well understood and what a great way to kind of touch upon different multiple facets of how this whole thing comes together and then the delivery of it. So let’s say I know about Prashant and who’s checking out of the Sears till right now and I am standing at the register and knowing what I know about you and your behavior and your shopping behavior.
Can I get that info, like is everybody who’s interacting with Prashant aware of what his needs are or how do you like kind of distribute? So this is one way of like understanding the data and ingesting it but then also communicating how that gets to the delivery or who is actually, whoever is interacting with Prashant throughout the brand experience, how does that get relayed to the whole team?
Prashant: So it’s actually a very cool product that I’m actually working on right now, right? So I’m going to sort of take a slight detour and then come back to answer your question. So when I was working at Sears and eBay, whatever solutions we were building was for one company, right? Like one consumer, which was the teams inside eBay or Sears and for the customers or the consumers of that brand. What we’re doing now is actually democratizing all of the technology, right?
So first and foremost, you need to start thinking about when you’re building these experiences, how can you sort of build both those common denominators so that it serves multiple people and then a highest common factor for each individual brand, that’s number one, right? Number two is how do you think about facets of information that manifest for different reasons? So example, glucose core sort of strength, if you will, is its ability to understand people, the shoppers, products, inventory information and events that is behaviors of people interacting with these charts at a very, very granular level.
Now all of this information in its most rawest form is sort of, you can slice and dice it however you want. But for a marketer who wants to communicate with the customers, there are two forms of that information, the way it manifests, the form of models. So I can tell you what is the next best action or the next best purchase, or I can tell you that I have a signal that this person has abandoned a cart.
So you set up an abandoned cart trigger and the moment you see the customer across any touchpoint, whether it’s a synchronous touchpoint like a website or a mobile app, or whether it’s an asynchronous touchpoint like an email, SMS, or a social channel, I basically surface the communication to the customer. So that’s basically your triggers and your models and intelligence.
But as a marketer, you also want to do strategy, right? How do I actually focus the customer stories, the customer migration patterns, and the customer lifetime value and the collection points of the customer lifetime value to in a manner that you understand these are the set of customers that you acquired last year and customers were profitable. These are the ones who are not profitable.
The profitable customers, how do you sort of move them across the value chain or the lifecycle of engagement with your brand through different steps? And what kind of communications, promotions, inflection points you need to observe, right? And what are the strategies you want to put in place to make those changes happen? That’s a strategy and an aggregated point of view that a marketer could use. We’ve got data that I said, like in the form of data science models, but we have all of this data that can be skinned differently for a front-end person, like a call center person.
I’ve done in my career before, where if somebody calls you, let’s say Vandana calls XYZ brand, the moment your phone number comes in, and this happens to some extent in many companies, like in insurance, for example, right? From a phone number, they already know that it’s you, and they have a full profile of who you call.
So we have an example of shopper data manifesting in a format where it will have scores. For example, this person is an Uber loyal customer. You won’t see them. So if they’re calling up with a frustration, make sure it’s addressed. You will have numbers that will be populated for you that tell you that it won’t tell you the shopper profitability, but it will tell you how much money you can sort of get more and still be okay with it.
And for example, say five, $6,000 with a brand, and let’s say the brand makes, I don’t know, five, $6,000 with a brand in a year, and the brand makes about, let’s say, 30% margin of all the things I purchase. You’re talking about $150, $200 that the brand makes off of me. And if of some bad experience, I call up the call center, I’m ready to sort of churn as a customer. You should be willing to spend not just $150, $200, but the sort of next two, three years worth of value to save you.
That’s the kind of insight and information that data can be presented to you in different formats, right? Whether it’s in the form of a coupon that you market to me, or whether it’s when I call up somebody, or when I’m actually at the store, and with the frustration, you want to basically make sure that I don’t end up turning to them. That’s one more form where data gets presented.
The third form, or the fourth form, where data is really useful for presentation is to be able to tell the shopper a story back with their own information. When you go to eBay, okay, and you sort of bid on an item, it tells you how many people are bidding on that item. When you are watching an item, it tells you how many people are watching.
At Bluecore, we have a product called Social Proof, which basically exactly does that, right? But it does that and more by bringing inventory information, like there is only five of these items left. Today, in the last 24 hours, so many people are interested in this particular item. What you’re basically doing is playing back selective stories to the user, and then they’re decisioning that much better.
So these are all examples where you can use data, cuts of data, to actually tell the story of the customer without making it overwhelming or overbearing, but making it incredibly useful.
Vandana: Great. What a great way to use data, and I love that fact, and also helping the customers decide, right? That decisioning that you said, helping them, and I’m seeing myself in these experiences right now. And you talked about the evolution of a shopper. So what are some of the things that you’re seeing for the last five years, and where do you see the evolution of the shopper going in the next five years?
Prashant: Yeah. That’s actually going to talk about something else, which is also connected to the evolution of the shop, right? But see, we were talking about like lower funnel conversion, right? But if you think about your own purchase journeys, it’s never a linear purchase journey that today morning you wake up and you decide, I want to buy a phone.
So I’m going to start searching for phones. I’m going to then matter it on a phone, and then I’m going to actually compare prices, and then I’m going to convert on a purchase, right? A shopper’s journey is sparked by different moments. It’s very nonlinear, and it follows a different path for different product, depending upon interest, depending upon proclivities, depending upon mean states, and depending upon whether it’s a necessary or a discretionary purchase.
The BlueCore CMO, Jason, recently did a podcast, and he actually made a very interesting point about making sure that like conversion is always going to look good whenever you do like investment scenarios, but making sure that you don’t forget to invest in acquisition, or more importantly, upper funnel investments, like engagement, right? I’m a big believer that conversion is a byproduct, having engagement is critical, right? Over the last five years, if you look at customer trends and patterns, right, comfort with buying stuff online has gone up through the roof.
D2C brands have really found their space and are actually doing pretty well in certain scenarios, like Nike, for example, is a great example of a D2C brand that’s also got a hybrid business model of working through other retailers, but of their core products, and the kind of new business models or new launch patterns that they’re testing out is insane of how much demand it gets, right? And customers are also responding with a lot of engagement. Ultimately, the product is king, right?
What you’re selling should have value, marketing can only enhance that value. So customer behavior over the last five years, A, has, like I said, has sort of, there’s been more comfort, more migration towards e-com purchases, direct-to-consumer has definitely grown quite a bit. And I believe that over the next few years, we’re going to see more and more what I’d like to call as headless commerce emerge. So social like Instagram or TikTok will allow you to purchase from the experience directly. Social channels are already hugely influential in influencing the decision of your purchase. It’s only a logical extension that they should become the purchase point.
So it enables both brands and marketers to think about how do you enable customers with those experiences. Mobile, obviously, and one of the topics that we didn’t talk about as much because the segway didn’t happen is identification, right? Identification is a very, very important tenet for not just marketing, but in general, all forms of commerce.
And mobile offers you a huge advantage if you have an app experience in terms of identification, you know who you’re talking to, and they’re able to be that much more personal. And I’d be remiss if I didn’t mention all the changes that we’re seeing in the market in terms of large language models and Gen AI, which will basically reshape the industry for a lot of the stuff that we do manually or we execute with brute force today.
You’re probably going to see a lot of changes in both customer shopping patterns. Trust in what is actually being sold is going to be required to be that much more higher. Businesses are probably going to have a lot more outsized presence where people can not only have the ability to buy items first hand, but second hand also, and also people who are able to get in on early experiences are able to sort of share that with other customers.
Vandana: Awesome. Awesome. And what are some of the challenges that you see as we are all proceeding into these kind of experiential buying journeys? What are some of the things that are going to be lagging behind the things that companies have to be cognizant of?
Prashant: See, I think, and this is again, like my POV, right? You’re going to have, so I keep coming back to the marketer because if you think about the day in the life of a marketer, they have 7 million things that are hitting them at the same time. Even before getting into like, what are the challenges that we are going to see as an industry, if I think about challenges as somebody who’s building marketing technology solutions that we should be aware of is you have to empathize with both the marketer and the shopper.
When my primary job is to give them either tools to communicate to their shoppers or actually send communications to shoppers. And the more we are able to give them flexibility and build workflows, build experiences that allow them to save time and be fungible with any other things that they have in their tech stack. It makes life that much more easier for a marketer lens.
Relevance is everything. And I sincerely believe that shoppers actually care about marketing communications. It is not like blasting them with information that is irrelevant or untimely, right? Or insensitive for that matter. So relevance in communications is important.
So in order to address that, you need to have, now nobody sort of gets up in the morning and has sort of this utopic answer for everything, right? So giving marketers tools like experimentation, ability to experiment and see what works and scales and really do it quickly without depend upon technology or analytics teams is important. Being able to establish a relationship and articulate the value of that relationship with the shopper is important.
So that’s going to be one of the always sort of ongoing challenges, right? It’s something that we have to keep evolving on. The other piece is going to be, again, I’m talking from a marketing standpoint is where do you sort of draw the slider scale of customization versus configuration? How much do you build solutions that are customized for an individual or a specific brand versus when I’m trying to build a platform that is more configurable so that more and more people can use it?
With the big customers of the world, everybody wants certain customization or last mile specificity that you need to their brand. With that versus have it configurable, but it sort of reduces the specificity and reduces the level of sophistication that a platform can offer for them. Those are like the, I’m talking very specific, like more tech stack, some of the challenges that I would love to deal and solve on an immediate basis or a long-term basis. I think the more we can build trust in communications and the more we can solve for knowing who you’re talking to, and by that I mean identification, right?
The more you become relevant and the more you become sort of intelligent in speaking to someone, right? And that to us is always going to be the challenge because it’s this balance of how much do you want to know about a person, but how much are you not, you don’t want to be infringing on their privacy or be creepy about it.
So you want to always have that sort of respectful line of adhering to all the rules around privacy, adhering to all the sort of social mores about how do you want to sort of know, how much you want to know a person and communicate with them with intelligence, but not stepping over the line. Right. That’s going to be a big challenge.
Vandana: Very well said. Yes. Yes. Very true. Yeah. Because there’s a very fine line, you know, when it gets to be.
Prashant: I remember this incident that happened back in, I want to say 2014 or 13, where I think Target was sent out to communication, again, data-driven communication where they’re able to identify, they sent maternity products to somebody and I think the daughter’s pregnancy was known through the data before I think even it was communicated internally. And to me, what is fascinating is that was actually, obviously like data really won out then, right? Data was able to predict all the right things, but where do you draw the line on being, are you being creepy or are you being actually like intelligent in communicating with the customer? Right.
That was an example where it stuck with me for a long time. Like, okay, this is where you could, the argument would have gone either ways, right? It was actually a win for data and it was, the story was told that way, but it could have gone either ways. Right. Yeah. Yeah. That is also reflective of how society has evolved in appreciating and understanding semi-artificial intelligence in our lives, right? We kind of expect that when you see products, they are recommended with relevance to you, right? At what degree of relevance and what degree of specificity is what that will decide.
Vandana: Yeah. Very well said. Well, that’s amazing. So Prashant, this was such an insightful conversation and I think I can, I feel like I can keep talking to you, but I know we have to kind of wrap it up. Is there, is there like one great golden nugget that we can, that you can share with our listeners where they need to be cognizant and maybe it is coming from that again, branding, customer engagement, kind of a perspective that we need to keep in mind as folks who are trying to kind of serve, coming from a place of service, but also keeping in mind what we need to be aware of.
Prashant: So shameless plug, but actually not even a plug. In order to be able to talk to someone, I mean, take your day-to-day life, for example, right? If you want to talk to someone intelligently, you need to know who they are. Did you know that last year during Black Friday, Cyber Monday, retail and e-commerce was the biggest time of the year. Retailers were unable to identify 74% of their visitors.
Think about it. X amount of traffic, three quarters of it, you have no idea who they are. And which means that you cannot talk back to them. You cannot actually engage with them. And all that billions of dollars that you spend on acquisition or like any kind of search engine or any kind of social marketing goes down the tube. If you want to sort of really be effective in marketing as a brand, just try to improve your identification.
Vandana: Hmm. Well said. Okay. Well, thank you so much for coming on the show. This was very, very insightful and I wish you all the good lessons and learnings in all that you’re about to do in your career.
Prashant: Thank you very much, Vandana. This was a lot of fun.