In today’s episode, my guest is Vishnu Vankayala, the CEO and Co-Founder of CustomerLabs. They are a Digital Marketing Infrastructure that helps marketers track, unify, and sync their customers’ data across websites, CRM, and other marketing tools without writing a single line of code. They help enhance customer relationships, improve ROI, and increase sales and revenue. If you are already an expert on identity and access management, but you’re keen to learn more about a customer data platform, this one’s for you.
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What You Will Learn Today:
- How CustomerLabs actually work
- What the marketers need today
- How to handle different types of site visitors
- Edge of CustomerLabs to the market
- Analyzing your customers
- Future of CustomerLabs
Links and Resources Mentioned:
Connect with CustomerLabs:
- Website: https://www.customerlabs.com/
- Facebook: https://www.facebook.com/customerlabs/
- Twitter: https://twitter.com/customerlabsco
- Instagram: https://www.instagram.com/customerlabsco/
- LinkedIn: https://www.linkedin.com/company/the-customer-labs/
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Welcome to season five of eCommerce Fastlane. This podcast helps resilient entrepreneurs, marketers, and founders to accelerate growth and thrive with Shopify. And now, on episode 248.
You're listening to eCommerce Fastlane, the podcast show, to help you build, manage, grow, and scale a successful and thriving company powered by Shopify. Listen to real conversations with partners and subject matter experts as they share proven practical strategies, platforms and the best Shopify to help you accelerate your business. The time is now for you to improve efficiencies, grow revenue, profit, and lifetime customer loyalty. Please welcome your host startup founder and strategic advisor, Steve Hutt.
Today's show is sponsored by the BeProfit app for e-commerce sellers. Need a clearer picture of your profit margins or what, an easier way to understand your ad spend or looking for a fast way to analyze all of your Shopify stores data? Then the BeProfit app does it all for you.
And like many of our listeners, I used to track a lot of my profits and expenses with all things like a spreadsheet. It worked for a while, but you know, my store started to scale up and it simply wasn't a viable method to accurately measure the profitability anymore. That's where BeProfit now changes all of that for Shopify brands. It's currently available right now in the Shopify app store.
BeProfit gathers vast amounts of data in a blink of an eye with an auto-integrations to a lot of the top ad platforms, ally expressed, and a lot more. But what BeProfit does next is to translate all of your first party, your Shopify store data into an intuitive and customizable all in one dashboard, providing you with valuable insights and it really allows you to zoom in on the metrics that matter most to your brand. You can even take full control of your data by creating and exporting your own custom reports. That's pretty exciting.
Discover your most valuable products, their top performing ads, best customer cohorts, and so much more all with the BeProfit's intuitive profit dashboard. Now you can visit BeProfit.co and you can start a seven-day free trial, kind of kick the tires and see what this platform can do.
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Well, hey there, my name is Steve Hutt. I'm senior merchant's success manager here at Shopify. And welcome back to season five of eCommerce Fastlane. Whether this is your first time listening or you're a weekly subscriber, I seriously appreciate you taking time today and listening to the show. And I know there's plenty of podcast choices out in eCommerce and direct to consumer and you know, and the fact that you're here today really does mean the world to me. And I know it's really important for our featured guests today.
Now if this is your first time listening, this is an e-commerce show where we have honest and transparent conversations about building and thriving with your store powered by Shopify or Shopify Plus. Now, if you're an ambitious lifelong learner, which you likely are since you're here today, you're definitely in the right place.
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I also highly recommend that you get the full value of today's episode that you click through from your podcast app and go to ecommercefastlane.com, where we have the show notes and there, you'll find a full show transcript, there's links, and then all the resources that we mentioned today.
Now in today's episode, my guest is Vishnu, who's the CEO and co-founder of a company called CustomerLabs and they're at customerlabs.com.
Now they're a CDP platform that stands for a customer data platform. And what they do is, they deal with first-party data. They help marketers, Shopify marketers, really, to understand their customers better and really help them to double their revenue.
I guarantee you this is a hot topic right now with the cookie apocalypse that's happening right now, what's happening with iOS 14.5 update, blended ROAS and just not really knowing what to do to have, you know, tax increasing. It's a crazy market out there right now, and competition's increasing. So having a customer data platform and first-party data is a very interesting topic. So hi, Vishnu. Welcome to eCommerce Fastlane.
Hey Steve, how are you doing?
I'm doing excellent. And thank you kindly for being very flexible on the time zone difference. Me, being in the west coast in Canada, you being in India right now. I know that we're quite a few hours ahead or I'm behind, you're ahead, but I just appreciate, you know, where there's talent and where there's great platforms that are helping Shopify brands. I wanna make sure that we make the time to get together and talk about problems you're solving. So, I just, number one, I want to just publicly thank you for making some concessions to be here today.
But let's talk on a high level first, ‘cause there's gonna, people who maybe have heard the word customer data platform, or they've heard about the benefits of first party data inside Shopify, but they don't really understand maybe specifically how you can action it. So, let's talk about the problems first that your company is solving.
Sure. Thanks too. It's truly my pleasure. And thanks for accommodating us on this show. In terms of CustomerLabs, what we started doing is way back in 2013, 2014. When we were running digital agency, we wanted to make it easy for digital marketers to track the conditions. That's all it started.
But when we tracking conditions, we also started tracking the autonomous user profiles who comes and visits the website, the pages, and et cetera. But since two years ago, there was no option for anyone to activate this data, under unless you are at DMP, you cannot activate this data. And then unfortunately, this iOS 14 happened and everything started compelling eventually.
And then Facebook, what they did was they started introducing something called conversion API, and that's where this whole server-side tracking and audience activation is eventually came into picture. So eventually with CDP, people can collect the data, including a user’s data and start activating them through micro segmentations on Facebook, as well as Google analytics at the moment.
Yeah, this is lovely. And thank you so much for sharing that. Cause I think it just kind of sets the stage a bit about, you know, these specific problems. Like I know this is on the radar of a lot of brands.
So, I wanna talk a bit about the origin story, ‘cause I think it's always interesting to me. You know why people build what they build. Like it's more than just, hey, I wanna have a SaaS company. I want recurring revenue. And I believe that this is the business line building.
There's gotta be likely a deeper story around just the engineering and the data science around even wanting to solve this problem. So are able to talk about how the pieces came together for the founding team. Like, I guess I wanna understand like where the desire or the expertise come from to even want to create this platform.
That's a good point, right? So eventually when you have a serious problem, then you put all your mind to it to solve it. And when we were running additional marketing agency, the major problem was we used to run a lot of lead and action on specific eCommerce.
And we generated a lot of leads and the client when we go and ask them for the incentives, my client says, hey, you generate a lot of leads, but you don't actually give me enough conversions. We were like, what are you talking about? If we, giving you end of conditions, ideally you should be asking us to optimize it.
So, we want to get the whole insight of the customer, whether he's actually becoming a lead, whether he's purchasing on the website, whether he's becoming a customer. So, when we want to do this, obviously we want to build a whole lifecycle tracking of the customer. And we started building the whole product there, that's all it started.
But eventually with the eCommerce businesses coming in, although we have enough data, we want to build that middle layer engine where we could also own our own data. So, earlier we all pushed this data into Facebook. So, we install Facebook pixel. We hope Facebook does its magic and gives us the returns. But with the iOS update, it all started having problems. Now we have an opportunity to hold the data and whenever you want, we can activate it. So that's all it started eventually.
That's lovely. Interesting with marketers. I find a lot of conversations around RO as the return on ad spend. I also hear some conversations about the CAC. That's what we call customer acquisition costs. And then because of all these challenges and things that are happening right now, as you mentioned with iOS 14.5 and its iteration. And, you know, you hear about Google now discussing about, you know, removing cookies at a Chrome. And there's lots of stuff going on.
There looks to be a battle of a lot of the Googles and the Apples of the world. And so, it's very interesting how they wanna own their own data for their own advertising opportunities and they don't wanna share it.
But then you have these commerce entrepreneurs, like on Shopify that like, hey, wait a second. We still wanna advertise on these platforms, but we feel that maybe we don't necessarily have all the the best information available or the best data to be able to action it. So, like, what do you think marketers actually need today? Like, you know, because I think they still have two things, I think.
There's the top of funnel side of the business where I'm trying to, you know, get some net new visitors, just awareness and consideration for my brand and then lead them down that journey to a conversion. But then there's also the retention side of the business about, well, how do we avoid churn or how do we get a second third sale? How do we get a loyal customer?
So let's unpack that a little bit. I just would love your mindset around what you believe marketers need today. And the pain points or something.
The first and foremost angle we are asking everyone to think is when a user comes to your side, it is your data and you have the whole behavior of this user.
Let's assume the user shares email address. What ideally, we do is we push that back into email marketing platform. Either it could be (inaudible). We show that we store it. This is the data we used to collect and pretty much every single market that I've used to.
But now in terms of autonomous users, what we used to do is we start pushing this data into Facebook and Facebook is the one who is holding this whole behavior for you as well. Now, if you want to bring the customer back again, you might have to go to the Facebook and maybe 40 days or 21 days campaigns work perfectly fine. But beyond that, you are going to go and spend lot of money at the top of the funnel.
That is the actual issue. And the same Facebook came to Facebook, cannot be activated in other platforms. This is the major issue most of us are actually facing. And since the Facebook and Google were able to provide top funnel audiences pretty good two years ago, or maybe till last year, people are not worried about thinking this middle of the final campaigns.
So, if you want to reduce the CAC, if you want to increase your average order value, or if you want increase your real TV, what you need is you need to understand your customers very, very well, and you need to reach out to them the right moment.
So, for example, one of our customers who's a very big fashion brand in India. They run campaigns called multi moment campaigns. So, these multi moment campaigns are basically let's assume someone purchases top fair in last 30 days. What you can do is after 30 days or 43 days, they'll start showing offers for bottom wear and similarly the cross-selling upselling options are quite high.
Earlier, the only channel was email and email, open rates and responses. They're good. They're definitely good comparatively. But at the same time, when you can actualize the chat audiences in multiple channels, why not? And those channels are I think part now, Google and Facebook with this. So, when you combine all this wide people campaigns and customer life cycle campaigns automatically, what you're seeing your auto value going up. And your customer acquisition will also started going down in the long term. So, three months, six months, 12 months, you'll start seeing your business metrics going up and down pretty clearly.
That's lovely. And thank you for sharing that. I'm just doing a quick look right now on the internet. So, I've not really heard that term, the multi moment campaigns. And so, it seems to me that it's a very interesting touch point that is created based on that particular site visitor and in their journey in that brand. Am I correct on that?
You're right. So, in that journey, in that moment, and how do you personalize for group of users. Although, we say about inducive user, inducive user personalization is impossible. But for the group of users, you always can. And that group, that moment, that will always be a group of people in that particular stage and you can definitely start personalizing for them very, very well.
I see. Okay. So, you know, what comes up a lot too is people say, well, what if I don't get the phone number, or if I don't get an email address? So, these are the anonymous visitors and I've had other platforms different, you know, marketing people on talking about the known versus the unknown site visitor. And, you know, I think stats have floating around saying that, you know, 10% are known pretty much with a 2% conversion rate.
And so, there's like 90% of your site traffic are completely anonymous. There's no identifying information, at least given from that site, visitor being a phone number or email, or even a worst case, a push notification, some kind of opt-in of some sort. So, like how do you handle that? Both the known and the unknown. And how does that relate to your platform and how you handle each of those types of site visitors?
This is a great question, right? Because no one would've thought why should we build the database for users? No one actually thinking that line, but what I'm saying is stop thinking your autonomous audience, like an email marketing list. If you're able to have about, lets you 300, 400 out of thousand, maybe 30, 40 emails.
However, what you can do is. You can now have your entire anonymous data. When it comes to autonomous data, what we need to have is very simple. We need to have the different IDs for them. For example, when you send the data back into Facebook, when you send the data back into Google analytics, they require few identifiers, which they call it as advanced matching parameters. And we would be able to at attach those matching parameters, along with the external ID. And we start pushing the data back into Facebook.
Now what happens is let's assume for example, the people are getting prepared for PFCF campaigns and when they start building this high intent audience over next six months, this audience can be activated even after six months, if both Facebook and Google.
And if they could put a little bit of work in terms of micro-segmentation, for example, okay. These are audiences who like black paints, these are the audiences who probably like thousand dollars gifts. These are the audiences who would purchase X, Y, Z items on my website. If they could actually put little bit work and start segmenting them properly. The kind of always, they will see for BFCM campaigns for beauty is huge.
Well, that makes sense. And I did some research kind of just before recording today, and I've had a few others on the show that are thinking about and trying to solve the first party. And we've even had people on about the zero-party data.
Zero party meaning when you ask questions through quizzes and these sorts of things where you can add on to the customer record, like maybe finding out what their likes and dislikes are, and you can ask extra questions, maybe identifiable things that maybe you could use later.
That's the zero-party data where somebody is opting in to giving you information about them as the customer or not, at least you can concatenate it on together as part of that session. And then it's, it's, it's available as, as data to be able to action against.
The first party data, which is what you're kind of handling right now. There are others that I believe are, you know, available in the Shopify app store or, you know, you just do a quick Google search and stuff like that. But I believe that you are, I guess, uniquely different.
I mean, I believe there's a blue ocean out there. I think a lot of people aren't actioning their data, their first party data that they think and know it's important, but they just don't have a workflow and a platform that they can execute on. I think that's why you're here today to say, listen, hopefully by the end of this podcast, you understand that there are benefits and understanding your first party data, and then taking action on it all with.
You know, the mindset that I want to improve my return on ad spend through the ad platforms. I want to reduce my customer acquisition costs. Like you said, a couple other, you know, I don't wanna throw out these vanity metrics, but average order value and lifetime value. These are all important KPIs for a brand to grow and scale. And I think that's where you fit into the mix.
So, let's talk about how CustomerLabs has been. I would argue maybe intentionally differentiated from others that connect to Shopify store. So, I just would love to understand your mindset around that and what the platform is doing.
Yeah. So, our entire focus has been on mid funnel audience. Just to reiterate, what we want to do is we are spending money on various platforms to create brand awareness at the top funnel. And these guys are coming to us.
Let's take for example, a small store, right? So, for example, I spend money on holding and people actually see that holding can come to my store. The moment I come to my store, I have a sense that I, who actually try to create that relationship and try to get that particular contact IDs. And the next time I go to the store, I want you to remember, okay, you have came in two months ago, three months ago, this is what you're looking for, et cetera, et cetera. Can we replicate the same kind of experience for the users through CTP?
And now the problem is the users don't come to our site once again, without extra nudge. That nudge could be a phone call, the nudge could be the retargeting campaigns. And these guys came to your site, show the intent and not coming back to the site.
Now, the question is, how far can we actually go? Can these data reading campaigns right now in all these platforms perform very very well for last 15 days or 21 days, which we call it as bottom of the funnel campaigns. But the middle funnel who had shown the high intent, cannot be activated at all. That's the area where we want to focus because we have spent money to bring them to the store. And we want to act with these audiences across the products and they activate it.
We cannot actually generic about offers, so need to identify what's their interest, what they had looked at, and what is the offer it give off. That's where the whole segmentation comes into place. We segment the users into micro segments, and then we offer the personalized offer to them on Facebook as well as on Google. And then again, bring them back into the funnel. This is the whole idea is what you're trying to bring in table at the moment.
So, when somebody onboards with CustomerLabs and then the mid funnel, it's important. So that you're onboarded, you ingest all the data, then am I right to assume that there's going to be some recommendation engine or something going on inside the platform and saying, hey, just so you know, all this traffic we've analyzed it all. And we believe that the next sort of tasks that you probably want to implement and then. Is there a workflow?
‘Cause I think that's the key. If someone's gonna get involved with a new platform to help them understand their data first, ingesting it and then giving them some kind of recommendations to execute on it. So, I just would love your feedback about how you kind of maybe not white glove, but how do you hold a marketer's hand maybe in their early stages with your platform. So, they're getting maximum value out of it.
As a matter of fact, we do the white glove service at the moment.
There you go. All right. That's awesome. I love it.
The reason is when we speak to the marketers, they know what to do, right? The only problem is they don't know how to do it, and this is more like you're giving a tool to someone who as is not thinking in those slack. So, what we literally do is we sit with them entirely till they get their campaigns right?
So, we have created multiple templates. So, we started with something called tracking guide. People come there, especially for Shopify. It's like 10 minutes, couple of codes, their live. And then we asked them to wait for a couple of weeks to gather the data. And then we sent them something called segmentation template, which will have various examples of how they can start thinking about using these mid funnel audiences.
And then from there we would start focusing on, okay. How do you do the offers and how do you position the mid funnel audiences and what kind of audiences we should use? What kind of audiences we should not use. All this data, we will, till that particular moment, we actually have all the one guide. This is what we do with every single flight, by the way.
So, this is what you're calling the audience builder. So basically, you're understanding the known and the unknown site visitor, and then we're making decisions on segmenting them. And then coming up with a marketing plan about is it an SMS plan? Is it an email plan? Is it an ad networks plan? You know, you still create your own creative, but at least, you know, whom you're going to be marketing to.
And so, the known customer who in mid funnel where you've paid money to show some, at least some buyer intent, but the conversion was not there yet. I can see how that would be an interesting way of trying to recoup your initial investment to get ‘them to come to the site to begin with. I get that part. Especially if they're known now with either phone number or email.
Does the platform work in the same kind of anonymous format? Obviously, I can't SMS or email them, but is there ways of still anonymously through a segment to be able to market, to site visitors shown some intent, not sure who they are, but I think Facebook knows or Google knows, but I don't know. Am I able to still market to those people the 90% of the unknowns with intent, I don't know who they are, but is there ways of having that data sent back over through these session IDs and things that you talked about so that we can market to them?
What happens in the background is we collect these IDs of this user, the moment, they segment it, where the first the segment backed into Facebook and Google every single day or three days or seven days, whichever the way they want, we would be able to do that. And the Facebook keeps this data fresh. We were able to match almost 75 to 80% of the audiences, in any given point of time.
So that's excellent. So, then you get direct access to, you know, that's a pretty high percentage of the 90% of the unknowns. I'm sure there's case studies and we'll probably put them in the show notes and stuff like that, but, well, what happens based on the unknown and then the campaigns, they ran against that.
And all of a sudden, the unknowns became, because, you know, if they were known that would be in the platform and that would be part of the journey getting the second sale or loyalty or the initial. But you know, there was some kind of an opt-in, which is another whole conversation about how to effectively get opt-ins another whole conversation at another time.
But if you don't have the opt-in through your email service provider, or just UNO or Privy, or, you know, Optimenga, or whatever you're using to try and get an incentive to the site visitor in exchange for an Instagram handle, that's like Gatsby or getting an email or phone as a really good starting point.
If you don't get that, which is typical, 90% are probably not giving you that, that sort of thing. And if that's the case, your platform really sounds very interesting to me. The fact we understand the unknown site visitor, maybe not specifically to a name, but it's synced back into Facebook and then there could be some continued, almost retargeting campaigns around the fact that you showed up, not sure who you are, but I understand the buyer intent.
So, it's not just a generic retargeting campaign. This could be very specifically targeted to this one individual person. But as the vendor, as the merchant, I don't know who that person is. Facebook does. Google does. But I wanna market to them. Am I on the right angle here?
100 percentage, right? So, opt-ins, yes, it activates one more channel for the user. But like you mentioned, 90% of them don't adopt them. We can still nudge them going back to the Facebook. And if you look at the whole data, Facebook holds your data for 28 or 30 days, but now we have capacity to hold your data literally forever. That's the difference.
All right. I wanna pivot a bit to a story right now. Cause I think we're all very motivated. You know, we're founders and entrepreneurs. I mean, I think a story really can educate and really inspire people to take action. And I just, it would be awesome. You know, most people listening today, there's 20 some thousand people listening to this podcast now and they want to learn about well, okay, interesting. First party data. I get it. Your platform sounds interesting and sounds like you have some great white glove kind of handholding and that's awesome.
Let's talk about someone else in the Shopify ecosystem. Another brand that has made the choice to use your solution. Hopefully, I don't put you on the spot here, but it would be nice to be able to hear. And I did see a few case studies on your website, but is there anyone notable that you can talk about? Maybe they didn't have first-party data. They knew it was important.
They found you somehow implementing your solution, you know, with your white glove handhold and some recommendations I just was curious on maybe, I dunno, dish their journey and then kind of what happened in the other end with the end of the campaign, or did they continue on as a customer and kind of how things have played out.
Absolutely. So, we have a customer from Europe and the (inaudible) and we reached out to their agency and the agency is the one who started pitching this solution for the brand. So ideally the problem they had was none of the campaigns were actually performing very very well. Right after this iOS issue, they started having a lot of issues. They had to rethink their whole strategies.
So, when we pitched this solution, the first idea was okay. What about first party? Can you actually prove by (inaudible) can we actually sustain it? And obviously that's the basic. So, the moment you send better data to back to Facebook automatically the Facebook would be able to match it. So, we said, don't worry about it, but takes care of it by default, but then why don't we start focusing more on your bottom funnel and withfunnel audiences.
The bottom funnel audiences, especially when I say bottom funnel. Add to cart, did not purchase in last 14 days. And initiate checkout did not purchase in 14 days. These 14 days audience and 21 days audience is the maximum. They were able to go. But then like, as you, if thousand people are actually doing view, content are visit the PDP pages. Facebook are actually matching only 20 percentage of them or maybe 25% of them.
So out of thousand people, Facebook were saying, hey, you can actually target only 200 people out of this thousand people that was actually creating lot of issues because the reach is minimal. The moment the reach is minimal, Facebook either don't show the ads to the correct people, or you tend to spend more on the CPM. This is what happening with them.
After installing CustomerLabs, the first thing we did was to increase this audience out of thousand, we were able to push that up to 700 to 750, that's the first step we did. So, India started seeing (inaudible). And then they started focusing on beyond these 14 days. 14 days, they do dynamic product ads using catalog. After 14 days, they don't do the catalogs anymore, but they eventually start focusing more on different offers by doing micro segments. This is where eventually they started seeing the whole advantage.
Apart from it, when we sent the data back to Facebook, Facebook needs to identify that user to the maximum, with the maximum probability. So, for that, we have our own technology, which actually says, tell the Facebook, if Facebook, you can be a hundred percent sure that this is the guy using the identifiers and automatically Facebook would be able to match that particular event to that particular customer.
So, when you personalize the whole stuff, Facebook would be able to personalize that, to add to that particular tool very very well. So that's how the whole book has be covered.
That's lovely. I was thinking about the CRO, this conversionary rate optimization. You brought up a good point about the bottom of the funnel with this case, with this Hermes Labs. And I get the exact same feedback from brands too. They're saying, hey, you know, why is it that my add to cart and probably on the unknown customer at this point, the new site visitor could be second, third visit, but still unknown. Their add to cart in the flow shows maybe 10% add to cart of total traffic.
And then they see that the preceded checkout in Shopify is 5%. It's like, wow. Half of the customers dropped off. That's interesting. So, they added to cart and didn't proceed other things that we can work on or how do we market to those people. And then in the end, it turns out that they have a 2% conversion rate. I'm just using some generic numbers, but it seems to be in that kind of way, where you have a high add to cart and then half or less is the proceeded checkout. And then, a significantly less is the, is an actual final conversion.
So are you suggesting that maybe CustomerLabs, I mean, this was a great case study, but CustomerLabs in general could kind of understand that checkout flow and going, hey, how do we market to those people where they're strictly just a browse and left.
So, they are a.) An add to cart and then left, or they proceeded to check out when, you know, especially on plus side where we have access to checkout dot liquids so we actually see the fact that they went to the next step and started entering in their information and then got confused or busy or wasn't enough trust signals or whatever it was. And poof, they're gone.
I just wanna make sure that we understand, is there a way of marketing to the browse people, the add to cart people and the proceed to check out people.
Exactly. So, with our segmentation engine, we could do all these segments, different segments. And these are all typical bottom funnel. And bottom funnel can be influenced not only 14 or 21 days, although let's assume if they are at the apparel fashion, it is impulse buy, but not all the eCommerce merchants are impulse-buying, right? So, we will still have a capacity to go back to them and tell them, hey, why don't you do this?
The simple example, if I'm buying tuxedo. In India, we don't buy blazers or suits quite often because it's a tropical country. So, when I'm going to make the decision, but I'll be definitely buying a suit or blazer every three months or every six months, but the vision making it won't be like impulse buy, right? So, I have to see it. I have to understand it. I have to under see whether seat, but then they actually suits. So, it might take three, four weeks. And in those three, four weeks, definitely you can come back to me and start showing video ads about new blazers, about the design updates of the blazers and what kind of occasion I could be using, whatever it is. You could start doing that.
So impulse buying is one thing actually, but at the same time, not all the customers, maybe 40% of the customers won't be doing impulse buying and you can start focusing the long term or couple of weeks campaigns which can actually give them better updates about the products why they should buy. That's how you can actually increase the line of the customers as well.
So, let's talk a bit about the future of CustomerLabs. I know your Shopify app is in the works right now. I know that there is a really nice tight connection you have, that's part of your white glove service, where, you know, you're adding your tracking pixels and some details. So, we just would love to understand the future.
Like what's the north star looking like for you, I guess for the remainder of '22. I'm just trying to set people up for success. If they're listening to the show right now and they agree that they're not segmenting and actioning their first party data. How do you believe that the CustomerLabs product today is perfect for them? And then what could they reasonably expect, you know, over the next, you know, six months to a year with your platform?
It's a big response for us, Steve.
I bet. I bet it is.
No. Seriously. The reason is, just to add on a little bit of context, the way we think we've come from a very small background, I actually threw up open a village where having a bed was a luxury. And when we want to compete with the highly talented people or with people with lot of money, what happens is we need a lot of tools, lot of guidance. That's exactly what we want to provide to medium sized brands. That knowledge, not only the tool, but all of also the knowledge. How they could actually start winning this networks game or customer acquisition game or marketing game. This is what we want to do.
And number two, with the moment they start having this data with them, the next, the machine learning models and the few other products we are lined up, which will automate most of the stuff, how Facebook was automatic for them now. The good chance is it was only Facebook they were focusing on with this data with them, and the mission early models, which you're gonna bring can automate the mid funnel campaign as well as audience segmentation into multi ad network options.
This is where we'd be going. But for that, they definitely need to have the data. If they start relaying on an ad networks to hold the data, they won't have it. When we introduce these things, the brands will not start from the day one.
You know, it's interesting you mentioned that because one of the things that I mentioned to brands right away that are maybe a lot of them are building their email list that's kind of like table stakes for most people. I would argue that maybe SMS as powerful as the automation is for browse and cart recovery and a browse recovery sort of things necessary pieces of technology either built into Clavio or getting attentive or postscript or whatever you're using as a tool for the SMS. So, I think that is growing in notoriety and the open rate is fantastic and its money left on the table by not having SMS.
But I'd also argue that, you know, maybe quicker adding this solution, like if it was push notifications, turning it on and getting those opt-ins now and getting this data to start getting into the engine. And then you get to use the data when the time is right. I mean, I'm like, I don't wanna think about the fall and BFCM [Black Friday Cyber Monday]. But as marketers, we have to be pretty crafty right now. And thinking about what's the future gonna look like? And part of it is getting these opt-ins in.
If it's getting push notifications, getting email, getting SMS and then having a customer data platform exactly what CustomerLabs is offering by at least ingesting this data known or unknown site visitor. And then over time being able to figure out, well, how do we action this pool of data? Because you know, poof it's gone outta Facebook and Google. They're not gonna give you access to it.
And we know that I don't know what the attribution numbers are like the seven day on Facebook now. It's like, it's just insane where you just proof gone. So, I think that's one of the advantages. Am I on the right track here?
You are. You are eventually right. So even in adaptation, now they can analyze the data over last six months or even a year, or even couple of years, the moment they have this data.
I see. Okay. That's awesome. So, we are near the end of the show. Where would you like people to go today to learn more about CustomerLabs? Do you have obviously the website, but is there just, maybe you can just share some details and where you'd like to, I guess, a call to action and kind of next steps for those listening today.
Well, a website. We host all our case studies, blogs, and strategies, eCommerce strategies on our website. They can actually get into a blog CustomerLabs/blog that they will see tons of resources and our work, everything there, especially for the e-commerce clients at the moment.
Okay. Perfect. All right, Vishnu, well, thank you so much for that. So CustomerLabs.com, I'll make sure I update all the show notes and some of the details. Cause I know that there is quite a bit of data there actually. I'm gonna, I think I'm gonna start syndicating some of your content on Fastlane, because I think you have some really good playbooks and some very specific use cases, especially for commerce about just kind of going over some of the things that we talked about.
I see some partners near like Saint and Sophia and a few others that you have some case studies. So, I'll make sure I put links to all of this stuff. There's a dedicated landing page to talking about eCommerce first-party data and what it's all about. So, all these details are going to be over at the show notes.
And thanks again for coming on the show. I know that we kind of briefly chatted just before recording and understand like, you know, we have a 14-day free trial right now for those that want to kick the tires and just let the platform ingest the data and then let you know those listening. They can actually see what the platform actually can reveal to them and kind of the next steps about how to action that data known or unknown. So that's the 14-day free trial. And then after this kind of white-glove onboarding, is there any offer for those that want to continue using the platform?
Absolutely. So, we are happy to offer all the eCommerce customers, 15% discount for the first six months. Definitely special onboarding assistance to help them understand how to use the first-party data strategy.
Okay. Beautiful. All right. Well, I'll make sure I have all those details again in the show notes. So whatever app you're listening to or on YouTube, you can just click through either there, go to the show notes, have a peak. They'll give all the details.
I think your growth plans is quite affordable, I guess really depends on, on number events and stuff, but really a hundred dollars a month seems quite reasonable as a decent starting point. So, I think that's lovely. And then it just obviously goes up from there just depending on number of sessions and the size of database, but wow, it's a really good starting point.
Thanks so much for, you know, once again, being flexible on your time, because I know it's late for you. I just really appreciate you kind of giving back the Shopify ecosystem. I'm excited for the next steps in your platform. I'm excited for more Shopify brands to be educated about first-party data, why it's important. And I appreciate you building this platform then just helping Shopify brands to grow and scale.
So once again, Vishnu, thank you so much for coming on the show.
Thank you. See you. Thank you very much.
All right. Have yourself a great evening.
Thank you. Bye.
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Well, that's it for today's episode. I'd like to thank you. A loyal listener of eCommerce Fastlane. It's my hope that this podcast is offering you a ton of value through growth strategies, tactics, and exclusive insider tips on the best Shopify apps and marketing platforms. All with my personal goal, to help you build launch, grow and scale with Shopify.
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