Learn from Fast Growing 7-8 Figure Online Retailers and eCommerce Experts

EPISODE 338 49 mins

Building a Future-Proof Attribution Framework

About the guests

Matt Bahr

Kunle Campbell

Matt Bahr is Co-Founder & CEO of EnquireLabs, a leading zero-party data utility provider for thousands of eCommerce brands including Allbirds, Skims, and Figs. Bahr has spent the past decade consulting with DTC brands to build sustainable competitive advantages through marketing analytics and consumer insights.

In today’s episode, Kunle is joined by Matt Bahr, Co-Founder EnquireLabs, a technology company that focuses on customer insight to improve operations, products, and marketing to better serve customers.

For D2C brands, fulfilling an order should not be the end of customer transactions. In order to get returning and new customers, a brand must also focus on post-purchase. One way to do that is to ensure that your customers receive a post-purchase survey.

Knowing your customers is going to help you optimize a lot in your business, so don’t go for jumbled random questions. EnquireLabs can help you figure out the right questions by going through their Four Foolproof Categories to suit your brand needs.

In this episode, Kunle and Matt talk about the four categories you need to know about your customer. You will get to hear about how EnquireLabs integrates data to other platforms. This is a great episode for business owners and marketers who wish to know more about their customers.

Here is a summary of some of the noteworthy points made:

  • Brands cannot guess what their customers need
  • Skipping out on a well thought out survey can leave huge gaps in your growth
  • Find those secret channels that can grow your brand
  • EnquireLabs can integrate with other platforms to fit the brand’s needs

Covered Topics:

In today’s interview Kunle and Matt discuss:

  • Matt Before EnquireLabs
  • The Growth Trajectory of EnquireLabs
  • Understanding EnquireLabs
  • The Four Categories You Need to Know about Your Customers
  • The Behind the Scenes of EnquireLab
  • Integrating EquireLabs data to Shopify
  • Importance of Quizzes and Surveys
  • Critical Customer Data Points
  • EnquireLabs’ Biggest Channels
  • Evolving a Breakout Brand
  • The Inbetween of First and Last Click
  • How to Contact Matt and His Parting Words


  • 08:33 – Matt Before EnquireLabs:
    • Matt’s years in eCommerce and being a merchant
    • Starting a Headphones company
    • Being enamored with same-day-delivery
    • Transition into consulting and Caraa Sport
    • Creating a post-purchase survey and EnquireLabs
  • 12:50 – The Growth Trajectory of EnquireLabs:
    • EnquireLabs being a side hustle project
    • Scaling despite COVID
    • What is a Question Stream?
    • Seeing growth and building credibility
  • 16:01 – Understanding EnquireLabs:
    • What is EnquireLabs?
    • Known knowns and unknown unknowns
  • 18:00 – The Four Categories You Need to Know about Your Customers:
    • What are the attribution questions
    • The customer’s user persona is going to optimize a lot of things
    • The magic of CRO
    • General customer research
  • 22:54 – The Behind the Scenes of EnquireLabs:
    • Best practices with Question Bank
    • The user experience in the front end
    • How EnquireLabs trigger themselves on an order confirmation page
  • 29:23 – Integrating EquireLabs data to Shopify:
    • Capturing customer data
    • Getting data from EnquireLabs to other platforms
  • 31:05 – Importance of Quizzes and Surveys:
    • Mapping out data to correlate or integrate with what’s on the survey
    • The holy grail of capturing customers’ data
  • 33:24 – Critical Customer Data Points:
    • What is CLAF?
    • Setting up a Postgres database with Shopify data
    • Integrating with Daasity
  • 38:08 – EnquireLabs’ Biggest Channels:
    • Growing in TikTok
    • There are secret channels that drive so much volume
  • 40:33 – Evolving a Breakout Brand:
    • Reducing your risk by not jumping an agency
    • Compartmentalize a brand once it reaches $3 million
  • 43:41 – The Inbetween of First and Last Click:
    • Getting you CAC even in every channel
    • Using other tools to figure out the data streams
  • 46:13 – How to Contact Matt and His Parting Words


  • Quizzes can get you to unknown traffic that generates more traffic
  • EnquireLabs’ future is to go anywhere from pre-purchase, SMS, email, landing pages, and more.
  • A well-thought-out survey can fill in the gaps of your brand in getting more customers.

Links & Resources

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In this episode, we’re going to be talking about the competitive advantages you can gain by asking customers the right questions. It’s a great episode you do not want to miss, so do stay tuned.

Each week on this podcast, we interview either an eCommerce expert, a founder of a digital native consumer brand, or a representative from a best-in-class commerce SaaS platform with a tight remit to give you ideas you can test right away on your brand. So that you can improve commerce growth metrics such as conversions, average order value, repeat customers, your audience size, and ultimately, your gross merchant value or sales. We’re here to help you sell more sustainably.

On this show, it’s a long time coming because I’ve been trying behind the scenes to get this expert on board because I’ve been hearing a lot about their platform in the D2C eCommerce Twitter space. I felt, “We need to have him on.” His name is Matt Bahr. He’s the Cofounder of a SaaS solution called EnquireLabs. EnquireLabs is a leading zero-party data utility provider for thousands of eCommerce brands, including Allbirds, Skims, and Figs.

What they do is provide customer insights after they have purchased. Right off the bat of making a purchase, EnquireLabs comes in and asks critical questions like, “How did you hear about us? Who are you? Did you have any issues? Could you describe yourself?” Critical questions that give you more insights to enable you to improve all of your operations, your product, your marketing, and to know your customers better to serve them better.

They have a framework called the Customer Level Attribution Framework, which Matt explains could be a competitive advantage for eCommerce operators to view data slightly differently from customers who give you this competitive advantage to take more nimble action. Also, to be more nimble with the insights you get.

He talks a lot about having flexibility and being able to adapt to questions, the way you ask questions. Not asking everybody the same questions, but making sure that the way you ask a brand new customer is different from the way you ask a repeat customer. The way you ask a customer that’s come from Facebook is different from the questions you ask customers from Google because you know a bit more about these customers and how they probably found out about you. It’s a bit nuanced.

Making these adjustments based on channels, based on the context of the customer, where the customer is coming from could be critical. At the end of the day, this links up to knowing your customers better in order to serve them better, if there’s one takeaway, one big idea from this conversation.

He is an accomplished marketer. He’s worked with $100 million-plus companies. EnquireLabs had customers from $100 million to $200 million-plus, so they get a lot of insights. I asked him a question, what’s the number one channel customers are saying they heard about brands on EnquireLabs? They have over 2,000 Shopify stores powered by EnquireLabs. It’ll be interesting for you to find out the number one platform customers are saying they found out first about brands.

We also talked about first and last-click attribution and the importance of it, how to weigh things out. What happens beyond getting data from EnquireLabs? What do you do next in order to map out that customer journey if it’s important at all? It’s a terrific episode. He’s a technical marketer, data-driven, and he knows his stuff. Enjoy this episode. I want to give a shout-out to Recharge, our sponsor for this podcast. Thank you for your support. I shall catch you on the other side. It’s a good convo. I enjoyed it. Cheers.

Matt, welcome to the 2X eCommerce podcast. I’ve been looking forward to this conversation for forever, so welcome. A pleasure to have you.

Thanks so much for having me. I’m super excited to be here.

Before we jump into what you guys do, which is phenomenal for the D2C ecosystem, Shopify, I want you to tell me, what are you up to before EnquireLabs? What’s your backstory?

I’ve been in eCommerce for a little over a decade. I spent the first 6 or 7 years on the merchant side. Early on in my 20s, I had a small consultancy, advising online retailers at the time, which is funny, a term that’s not used too often. It’s all just D2C brands. I was doing that for about three years, and then I helped start a headphone company here in New York called Master & Dynamic. I was the first operating employee there. I led all things eCommerce from the media budget to logistics, the whole P&L on the eCommerce side.

A lot of the product decisions we’ve made with Enquire came out of my experience as a merchant. I left that company in 2016. I don’t tell this story too often but at the time, I’m enamored with same-day delivery. At Master & Dynamic, we were the first brand after Everlane in New York to integrate with Postmates’ same-day delivery API. I’m enamored with the whole idea that somebody could go to our site, MasterDynamic.com, purchase a pair of headphones, and get those headphones within an hour in all of Manhattan. We were integrated with them for about a year.

At the time, we were also in SoHo Apple Store. I was like, “Why are we selling more stores in the SoHo Apple Store than on our dot-com in New York?” That was this whole thesis I had. I left that company in 2016 to dive into the same-day delivery space. I was trying to understand those things. My current cofounder and I spent about two years in the space never finding a product-market fit. We were in the consumer marketplace and B2B SaaS.

In April of 2018, while we were winding down that business, we were in this desperate, “We don’t have product-market fit. What do we do?” We’re transitioning to consulting. We were advising this handbag company in New York called Caraa Sport. Aaron, their CEO, was having trouble with marketing attribution, high AOV, $200 to $300. Whenever he looked in Google Analytics, all of his conversions were coming from director branded search. He had no insight into what was driving sales. He was using Facebook as an ad platform, but that was only 30% of their revenue.

I suggested adding a survey for him post-purchase. He did so with the Google Form. We used a different app at the time that allowed you to drop HTML on the page. I don’t think Shopify does allow you to do that. The insight there was that the data was super valuable to him and his team. He was obsessed with looking at this Google form, but the issue was the Google Form lived in an iframe. It wasn’t connected to the order data or the customer data.

He gets all of these good responses and he’d be like, “Who submitted this response?” I’d be like, “I have no idea. If somebody left the window open for five hours, it could be any of these five orders.” That was my whole career leading up to building Enquire. We were phasing out the same-day delivery product we had. We’re comfortable with Shopify’s API and built the initial version in about two weeks. We launched on May 6th, 2018.

You’re on the essential layer in the tech stack and D2C right now. I’m not just talking about it from a Twitter standpoint because a lot of people talk about Triple Whale, EnquireLabs, and the like. What’s been the trajectory of growth since 2018?

For the first two years, Enquire was a side project. When we initially launched it, we’re like, “This would be cool if this buys us a round of beers a month or something.” In the first year, we weren’t focused on it. We spent an hour or so a week. Right before COVID, which is when we went full time, we had about 300 customers, but about 200 of them were on Shopify Plus.

It was insightful to us. Shopify has all these merchants. At the time, they had 3,000-plus merchants and 200 of them were using our product. That gave us the confidence to go full-time. We raised a little bit of Angel money from some customers. The pitch was like, “Let us focus on this for a few months.” I’m not pitching you this grandiose Qualtrics competitor. Today, we’re like, “We know the Shopify space. That’s our network. That’s our background.”

In 2020, we scaled from about 200, 300 customers to about 1,000. At that time, all of our customers were asking for multi-question. At the time, we were still single-question. It was a simple app. For the most part, we built it in a couple of days. We’re asking for multi-questions. Earlier in 2021, we built a multi-question, which we call Question Stream. It’s trademarked for a specific reason. It has a patent out. The whole idea is we want customers to start thinking about survey data in a similar way that they think about Google Analytics data.

It’s a stream of data feeding into their existing MarTech solutions, into their reporting that allows them to make better decisions in real-time. As far as the future and our whole lineage, we started with attribution, a side project. We waited for the perfect time, but the market decided to catch up with us from a privacy standpoint and is now into building something that’s way more robust that can solve a multitude of business problems beyond attribution.

You’re beneficiaries of this Apple App Tracking Transparency issue that the entire industry is having to grapple with at the moment.

We definitely saw our growth increase even before it happened, but it’s definitely helped us and given us a ton of credibility. Even before it happened, we were starting to grow a couple of months before. People saw this coming. CPMs on Facebook were starting to increase, so brands were eager to get into other channels like podcasts, for example, and influencers, and needed a way to measure this. A lot of these things are difficult to measure if you’re just looking at click data.

If you get the wrong hire that early, it could be detrimental to your business. Click to Tweet

Taking two steps back beyond question trim in terms of multiple questions in a survey, could you break down to readers who don’t understand how EnquireLabs works exactly how you work? It’s post-purchase. I’ve made a purchase on a D2C website. Prior to question trim, I will get one question, which is, “How did you hear about us?” I might have heard about you on TikTok. I say TikTok because that’s where I remember finding out about you. It’s like originating on channel question. “Where did you hear about us? Was it a friend?” Would you give a list of options initially in the survey?

We’d always recommend giving a list of options. To start if you’ve no idea where your customers come from, there’s a ton of data in the other field. We do recommend you leave this other field open. We have this framework internally called known knowns. There’s this whole idea of an unknown unknown, which is a channel that customers come from that you don’t even know exists. The only way to get it is to ask.

It could be something like word of mouth for example, like, “What percentage of your customers come from word of mouth?” It’s a question that is only answered by asking customers. You can’t rely on direct or any of that data. Getting more definitive single response data is more easily analyzed versus OpenText data if you’re doing considerable volume.

I like that, known knowns. With EnquireLabs getting a bit more sophisticated or more sophisticated beyond that, “Where did you hear about us?” What other questions are you having to ask customers who’ve jumped across the chasm? They’re no longer shoppers, they’re now customers. What else do you want to know about customers?

We group this into four categories. We have attribution. Attribution-related questions are like, “How did you hear about us? How long have you known about us?” To understand the consideration window. There’s a different way to phrase these for returning customers as well if you’re trying to understand attribution for returning customers. Attribution is the first one.

The second one is general personalization. Think of what other data points would you like in your ESP that would allow you to send better emails. One of our favorite questions is, “How would you classify yourself?” The example I’ve given is we work with this company that sells this piece of hardware to educators, hobbyists, and professionals. It’s clear user personas that allow them to then send personalized content follow-ups, etc.

That’s definitely something we recommend to all our customers, like, “What are your user personas?” It’s funny how often we hear like, “We know them.” You haven’t needed to know them because you traditionally invested in Facebook and Facebook found the different personas. Knowing them is going to help you optimize creative and a ton of other things.

The third one is CRO, conversion rate optimization. Surveys are an incredible tool for getting started with CRO. Questions like, “How was your shopping experience?” I typically recommend starting that one with a single response like, “Good,” or, “Bad,” or, “Great,” with follow-ups on each of them. It’s like, “What can you tell us about it?” Or use emojis, however you want to talk with your brand voice, and then have the user follow up. “It was great.” “What was so great about it?”

This is an easy way to learn like, “It was good,” and then you’ll hear customers be like, “I spent ten minutes looking for your return policy.” You should probably take your return policy and start to link to it near the add to cart button. Make it more accessible so these customers don’t have to dig deep and find these data points.

Just to run through them, attribution, personalization, CRO, and fourth one is general customer research. This is where all survey platforms historically have sat, in the research corner. We always talk about operational or operationalizing this data. It’s like, “How do we put this data to use in real-time?” Historically, survey data has always been for research. The research questions that are super valuable are questions like age and gender, like, “Why did you buy today?” That crosses the customer research and CRO side of things. Start to understand more about your customers.

The holy grail of all this is combining all this data. Now you have a customer who has answered maybe 5 or 6 questions like what channel are they coming from. Now we know like, “People who purchase for this reason are this age and gender from TikTok, are different from people who purchase for this reason are this age and gender who came from TikTok.” There are these two TikTok audiences that you are always grouping into one. We see that all the time.

As far as utility, you’ll see us move beyond post-purchase this 2022. We’ll start to look a little bit more like some of these legacy survey players. We talk about our Question Stream, not surveys. We don’t use the word surveys anywhere on our product because we want people to think about this linear conversation with customers like, “What can you learn?” You’ll see things like NPS and other more traditional survey things coming out of us later this 2022.

At the core of it, EnquireLabs is a customer insights platform.

Exactly. The difference between us and survey platforms is this continuous conversation. Every customer has a customer ID versus most survey platforms today. You create a survey and then you add questions to that survey, and then you say, “Who do you want this question to target?” For us, it’s like, “What do I want to learn?” You create a question and each question could have its own targeting. Hypothetically, you and I could purchase somewhere, maybe via email in the future, and get completely different surveys based on our algorithm or the way that a customer has set up our platform.

How much guidance does the platform give users to set all of this up? You talked about attribution, personalization, CRO, customer research, insights. At the point of setup, is it intuitive? Do I just figure it out and tinker with it? What does it look like behind the scenes?

It’s definitely intuitive. We have a Question Bank, which is a link out to a table, which is for inspiration. As far as attribution surveys go, we’ve done a good job of getting a ton of brands on them. Most, if not all customers who want to implement an attribution survey have already seen one and have a good idea of how they want it to be set up.

We do have best practices in content in our docs in this Question Bank, but it is self-service. Our team is always there to help. One of our internal goals is to get customers to ask more questions. If you’re only asking one question, how do we get you to ask two? Part of that, you’ll see UI changes this 2022, but we’re definitely leaning on the Question Bank as far as giving inspiration there.

In terms of user experience, is it similar to a type form experience or is it a pop-under Qualtrics type experience? How would you describe the EnquireLabs user experience on the front end?

Simple. That’s on purpose. We like to have all of the complexity hidden from the user. We have some design challenges ahead of us. It’s how we continue to do that. For us, it’s intuitive to create a list of questions within your Question Stream, add new questions, reorder them, turn them on, turn them off. It’s going to get more complex. That’s a fun challenge for us as we add more functionality. For the most part, it’s been intuitive and easy for our customers to get set up, add a question, and turn it on probably all within five minutes.

When shoppers are converted to customers, once they’ve gotten to the thank you page or the order confirmation page, what happens? Does the screen change like a type from experience? How does EnquireLabs trigger itself on the order confirmation page?

We inject a form directly into the page. We don’t load in an iframe. There are security reasons and also styling issues with that. We inject the form and grab all the existing styles from the page. On Shopify, it’s one click, you install us, turn us on. You usually don’t have to do anything unless you want to get fancy or customize something a lot.

We’re going to be publishing some snippets of code that allow you to do full-page takeovers, fully customize this. If you wanted something that looked more like a type form, you could easily do that. The options are definitely limitless. We’ve had companies like Vouri and Maiden totally surprise us with, “That’s us powering.” It looks nothing like our default question. They’ve styled it like crazy. It’s like, “This is incredible.” We’re taking some inspiration from them and going to publish some stuff to allow customers to see all the options.

It’s great to have brand-first customers driving innovation there. You take inspiration to further improve your product. In terms of pushing data from EnquireLabs to critical channels or platforms, am I right in saying that in your Shopify customer section or customer list, new fields are added from EnquireLabs? Do I log into my EnquireLabs app to see customer data? Do you append the data to customer data?

We don’t by default. We are capturing customer email, customer ID, order ID. That’s how our platform needs to work to know which questions to serve. We leave it up to the user as far as where they want and how they want the data. We have a Shopify flow integration, which is one of our most popular integrations. More than half of our customers are in Plus. At least our roadmap was focused on them.

If you wanted to tag orders, tag customers. We have customers using Shopify as new meta fields functionality to get the data to live on the order and customer record as well. It’s still not exportable. It’s not the most ideal place to live but it is key-value pairs, which is easier to understand while you’re looking at the page. That’s what we’ve relied on and Alloy as well, which is similar to Flow. If you want to get the data anywhere out of our platform, that’s how customers have done it.

Let’s talk about surveys in general and quizzes. Quizzes get you to know unknown traffic. Rather than having unknown traffic, you start to get some more insights and more traffic. How do you not just compare to quizzes but how do you map out that ecosystem so the data I’m getting from quizzes correlates or is integrated with data we’re getting from surveys? Do you see yourselves playing pre-purchase at some point so it’s one, singular customer data center?

Yeah, for sure. We’re investing the majority of our resources into our question engine. We want to be the application that serves the right question at the right time. We are somewhat agnostic to what that future looks like. It might be a quiz to utilize our API and us powering the questions that are asked on the front end. It might be us building a front-end functionality with forms. We’re open to that.

The biggest advantage that we could build for our customers is getting them to ask better questions at the right time. That’s our focus in training our algorithms to be able to do that. We’re already at a volume level where we could start being somewhat smart with that. As far as the future goes, we want to live everywhere, pre-purchase, SMS, email, landing pages, etc. The first step in getting there is understanding which questions to ask where.

Our Holy Grail is, Matt enters a site and he has never filled out a quiz before on the other 500 sites that EnquireLabs powers quizzes. We’re not even going to show him a quiz because the likelihood of him completing it is zero. We’re going to capture this data from Matt on a different surface, maybe it’s via SMS after he purchases. That’s how we’re thinking about capturing this data programmatically long term.

Speaking of which, customer data points, data is becoming hugely critical. We’re in the age of zero-party data. This is party data post-purchase, essentially. First, party data, behavioral data. From what you guys are seeing, what are critical customer data points, eCommerce directors, and operators who are readers of this show should pay attention to?

The whole idea is that competitive advantages are built around proprietary frameworks, tools, or analytics. Click to Tweet

Thinking about first-party data and zero-party data. Zero-party data, I’m not going to not pitch that. Let’s go back to CLAF, the Customer Level Attribution Framework that we’re working on.

What is CLAF?

It’s a framework. We’re still up in the air of like, “Will we publish a template? Will we publish things?” The whole idea is competitive advantages are built around proprietary frameworks, tools, or analytics. The whole idea of CLAF is to get marketers to start thinking from a bottoms-up approach to, “What could I possibly want to learn about my customer?” It’s the products they purchase, their survey questions. If we then analyze that data thereafter, what is the narrative that data tells us?

As far as what data I would look at, it might not be click data for every time somebody visits a site because that might be hard for us to analyze and put on the customer record. If you’re large and you could process and analyze all of that, for sure. Getting started in a more simplistic way, what can help you make better decisions and analyze that? This framework comes from our experience setting up databases.

Our second most trafficked blog post on the Enquire site is on how to set up a Postgres database with your Shopify data. It takes two minutes. You don’t have to be technical. A lot of these frameworks are ways that we think start with a database thinking versus a top-down tool or SaaS platform thinking. If we can get more customers to think in that manner, like, “What are the tables that make up my customers in my business?” You’re going to be able to build a lot better internal or what call proprietary competitive advantage. That’s what we’re pushing our customers to start thinking about doing.

It’s the way you view data and the way you act, which create a moat around your insights and then allow you to make progressive changes. That feedback loop is important.

I’ve always had this hypothesis. This isn’t tried and tested many times over. For me, it’s like, “At what stage does a brand bring in an analyst, someone whose sole job is to analyze the data?” If you think about a brand doing $3 million or $4 million online with a 65% or 70% margin, when does this employee start to pay for themselves?

Think of it like a lever or an angle. It’s like, “Can this entry-level person with a year or two experience, $80,000 to $100,000, generate that in bottom-line revenue by allowing you to understand your customers better and make better decisions?” I would argue yes but having this background, it’s a little jaded. That’s the story that I push people to start thinking about versus relying on all of these third parties to make all their decisions.

Are you saying EquireLabs is looking to be the data plug prior to when you get to an actual analyst when you’re ready for a natural analyst to crunch the data from a data perspective?

At least from a zero-party data and survey data perspective. We integrate with Daasity, for example. They’re a good partner of ours. We don’t want to compete with Daasity. To my point before, we want to get good at serving questions. You already use Daasity for your entire BI reporting. It’s like, “Here’s your inquiry data in Daasity. There’s no reason for you to log into both platforms.”

You have over 1,000 brands, half of which is Shopify. What’s been the biggest channel thus far? The Northstar question, “How did you hear about us?” If you were to consolidate all answers, what’s been the number 1, 2, and 3 channels?

It’s Facebook. There are over 2,000 customers on the platform. We have a large data set. It’s about 15 million to 20 million. In Q4, it was double that. It’s a lot of data as far from a monthly standpoint. The biggest platforms are Facebook and Instagram by far.

How does TikTok compare?

It’s growing exponentially. In the first month, maybe there were ten on our platform. There’s got to be at least 200,000 to 300,000 responses a month from TikTok. It’s growing exponentially. We have gone back and forth a lot around, do we publish this type of data? We don’t yet, mainly because a brand that’s doing $10 million to $20 million, their channel makeup is different than a brand that’s doing $1 million to $2 million.

If I start shouting from the rooftops that TikTok is a great channel, everyone’s going to start investing in TikTok. The people that discovered it first using EnquireLabs are going to have to eventually pay a higher CPM. We’ve gone back and forth as far as how much benchmarking do we do. We’ll start to do it once the channel gets critical mass like Facebook and Instagram. Word of mouth is a great one we could start to do. I don’t want to call them secret channels but there are some channels that most people would never think of that drive so much volume. A certain brand has figured out a channel.

Like what?

I’m not going to say it because we want the customers to be able to trust us with all this data.

We’ll ask questions. Super interesting insights here. This has nothing to do with EnquireLabs but more insights from the merchants who use your site. What’s the team structure for a breakout brand under $5 million, $10 million, $50 million, and then $50 million-plus? If you were to operate a breakout brand in that transition going through those milestones, how does the team evolve up that value chain?

The smaller is called sub $5 million. I would lean heavily into agencies and consultants as much as possible on the smaller brand. Maybe not for the reason that many people think about but an agency and a consultant are 1,000 times easier to fire than an employee. If you get the wrong hire that early, it could be detrimental to your business. If you have the wrong agency, most agencies have a 24-hour out clause. It’s not great to jump agencies because there’s some knowledge that they learn working with your brand.

If you can outsource that and keep them accountable, it will reduce your risk early on. Once a brand starts to hit the $3 million to $5 million mark, that’s when they’ve scaled a little bit beyond that co-founder or founder growth of someone who maybe had some previous direct-to-consumer knowledge. You should start to look ahead of growth or someone who comes from a more quantitative background. Hopefully, the brand is already built so you’re not looking for someone with a brand background. You’re looking for someone more who dive deep into the spreadsheets and hopefully knows some sequel or analyzing data who could start to look at the business from that point of view.

I’m not going to mention anything on the supply chain side because that depends on the vertical and what the product is. From $5 million to $10 million, your team is growing so you’re starting to compartmentalize everything. This head of growth might then have a head of email, head of retention, or the different channels reporting up to them. That’s what it looks like until about $50 million. It starts to get more compartmentalized. A lot of these brands can grow efficiently from an employee headcount perspective.

After $50 million is where things get a little bit more exciting, at least from what we see from the data side of things. That’s when we start to get more data-literate people we interact with who might not even have any direct-to-consumer or eCommerce experience. They have a tonne of data analytics or analysis experience. That’s the path that we see as far as companies scale. To my point earlier, how quickly should you hire that data analyst? It’s a question that I’d love to get answered. Quicker than most people think. At least that’s what we see as far as how companies should think about team size as they scale.

Thank you for that. The final question is from the first to last click attribution data. Your last click is Google Analytics. Your first click is the answers you get from tools like EnquireLabs. Should brands care about what happens in between? I find out about a brand on Facebook. I’ve watched your YouTube channel, seen a billboard, and then eventually I google them and purchase. Should you care about what’s in the middle or is it just the first and last?

I would say yes if you’re starting to think about marginal CAC. On the margin, you want your CAC to be even across all channels. You want to get your next customer the cheapest you possibly can. If you’re at that level of optimization, it could start at $5 million or $15 million. In total, you’re going to want to think about all the past purchases. Honestly, I’d probably go use Rockerbox. Triple Whale has been doing a ton of great stuff to go solve those problems. That’s if you’re trying to optimize at the margin.

If you’re not yet, let’s say you’re advertising on a few channels, I would not increase the complexity of the data you’re looking at because it’s going to get difficult to action on. A lot of what I’ll preach is how easy is data to understand and be confident to move forward with it directionally. A lot of it is MTA Solutions. Rockerbox uses a fancy ML algorithm to measure and weight channels. The long and short of it is it’s hard to understand. Their platform will report what channel did what during a path to purchase, which is what you want. That’s what you want to action on. As far as understanding the underlying principles, which does that, it gets complicated.

There’s a time and place for it. If I was a brand doing $10 million, I would 100% have an MTA Solution integrated along with a lot of my proprietary attribution modeling that I would be doing. It would be my bottoms-up approach combined with top-down to create, hopefully, an awesome competitive advantage.

Thank you for that. Those are all the questions I have. This has been a terrific conversation, Matt. Thank you for sharing your knowledge. Any parting words to eCommerce operators reading this episode? Do you want to have any last words? A word of advice, please.

I keep preaching this CLAF framework or methodology of the way of thinking. If anyone wants to reach out to me, I’m on Twitter, @MattRBahr. Email me at Matt@EnquireLabs.com. I’m happy to have open conversations with customers or merchants about this and how we think about it. We’re going to start publishing more on this as well so we’ll have some content to reference. That’s my parting words.

I’m not going to say it doesn’t fit nicely with survey data because it does well. It’s like, “What do I want to know about my customer that I could then model up for?” Our parting words is to start thinking about solving and building a brand and a business from bottoms-up. It’s like, “Who are my customers? What could I possibly know about them?” Versus the traditional, “I spend X on Facebook and this is my return,” which is more or less your top-down approach.

It’s a timely episode. In the episode before this, we had Rich Page on. He’s a CRO guy and he was talking about customer research being the goldmine for eCommerce. This is timely. Customer Level Attribution Framework or CLAF is your core. Thank you. For those of you who want to find out more about Matt and EnquireLabs, go to EnquireLabs.com. Matt, are you a LinkedIn person or a Twitter person?

Either, to be honest. Choose your desired channel.

Thank you so much for coming to the 2X eCommerce podcast.

Thanks so much for having me on. Hopefully, we’ll connect soon.


About the host:

Kunle Campbell

An ecommerce advisor to ambitious, agile online retailers and funded ecommerce startups seeking exponentially sales growth through scalable customer acquisition, retention, conversion optimisation, product/market fit optimisation and customer referrals.

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