Data is only as good as the questions that it answers.
And the actions that it drives.
Dan LeBlanc, is Co-Founder and CEO of Daasity, an analytics tool for direct to consumer brands.
Dan has the unique vantage point of working with the fastest growing brands, like MVMT and Kopari, to help pull actionable insights from their analytics.
In this conversation, we dive into the details of the most important KPI for eCommerce brands, the LTV: CAC ratio, and how to strategically approach acquisition vs. retention.
Gen Furukawa:
Daasity helps ecommerce brands understand and gather their data, but where it started was from a very large company and that’s ProvideCommerce.
And it seemed like pro flowers was one of the main early pioneers of e-commerce. That was part of the provide commerce family. Can you just share a little bit about how you actually identified the problem before Daasity started and how you started there?
Dan LeBlanc:
One of the things that made Pro Flowers really good and a really successful business is we were hyper-focused on analytics. When you think about a business that is so seasonal–there’s Valentine’s day, Mother’s Day and you have Christmas.
And those are the three holidays that really were important and it was make or break for us if we didn’t make it in one of those holidays, we’re going to struggle for the rest of the year. Nobody would need flowers on February 4th or 15th. They all need their flowers on February 14th.
And so what was really important for us is we needed to be able to make a decision. The two weeks prior around what was going to be profitable and not be profitable.
And so we had our analytics down to the point where we knew in late January whether a channel that had a Cost Per Order of $150 was actually going to be profitable by the time we got to the week of Valentine’s day.
So you’re, you’re buying flowers for 40 bucks and it costs us $150 to get you that order, then that doesn’t make sense from a revenue perspective. But we knew if that happened on January 28th, by the time you got to February 11th or 12th, then that was going to be $8 because of the volume.
We got very good at modeling it out over the years. And so that really helped us become really powerful as a company that profiles and being effective in how we spent money to acquire customers and be profitable.
In 2014, Pro Flowers was acquired by one of the main competitors, FTD. And as with any acquisition, you have people that decide to leave the organization. And I ended up with some colleagues that went to these new emerging brands that were on this platform that none of us had heard of at the time, but is a household name today, Shopify.
With colleagues at MVMT Watches, Rothy’s, Kopari–these great marketers in the direct to consumer space.
But at all of these companies, they couldn’t get the data like we had at Pro Flowers.
And so they came to me and said, “Hey, Dan, can you go help me do something?”
Gen Furukawa:
I’d love to learn a little bit about the strategy and like how analytics actually help you make the right or wrong decisions.
Dan LeBlanc:
What’s really important is thinking about it from a lifetime value perspective. Take Valentine’s Day as an example — you can buy on Valentine’s Day in February, and there’s a good chance that you will buy again in May for Mother’s Day.
And that changes the dynamics of what you’re willing to pay, to acquire a customer.
We were able to understand that this percentage of my population that are new customers, that I acquire on Valentine’s day are going to come back on Mother’s Day.
And so, and if they come back, my number one channel that, or I want to drive them through my lower cost retention channels, like email, which is significantly lower in cost thangetting them on Facebook again, or, or some other channel.
As we all think about dumping tons of money in at holiday. But have you actually ever looked at the seasonality of whether those customers are as profitable or not, and maybe you need to have a lower threshold that time period, and actually a higher threshold because of that repurchase rate.
It’s very difficult for merchants to understand that just looking at their ecommerce data. So we help them with a solution that can provide that level of insight and detail.
Gen Furukawa:
Yeah, I think analytics is, is great and it’s, it’s hard, but it really comes down to the questions that you’re asking. Right. And then like knowing what nuggets you’re trying to pull out So if we, if we say like, all right here, you can do it manually. And we all know doing it manually is a huge pain, but if you were to do that, like the theory in, you know, like the, the way that Daasity works, if I can just.
Talk this out loud and think through it, you’re basically pulling out the cohort and let’s say you’re looking at historical data. So you’re pulling out the cohort of people who purchase in Valentine’s day and then their likelihood of purchasing mother’s day, and then maybe in Christmas or Hanukkah.
And then maybe you might segment that by channel acquired and then the channel that you’re going to. Going to drive the repurchase with, and then compare that to other maybe non-customers or other customers who might’ve engaged at different points prior to that. And then their likelihood historically of converting at different points in the year
Dan LeBlanc:
There’s a couple of drivers within a business as a whole: You’re trying to acquire new customers, you’re trying to retain customers. And you’re trying to make sure you got enough product.
And so for, and so for any brand, whatever brand it may be, you need to do the data analysis. You need data to help you determine what is the right strategy for those different things.
It’s about assessing the tradeoffs, and whether to invest the time and money into different channels, what makes the most sense, in terms of acquisition?
You also need to look at it from a lifetime value perspective. You don’t just want to look at it from a snapshot. And then from a retention perspective, are you actually doing a good job of retaining your customers?
I see brands from the data where a lot of their repeat purchasers are coming in through high cost channels, like Facebook where you’ve already paid a bunch of money to get that customer the first time. But you’ve just paid again for a paid channel to acquire a customer who is already in your CRM.
it’s data can help you in all those different areas in terms of figuring out how to make the right decisions and in turn either grow your business or be more profitable.
Gen Furukawa: What do you think are the most important metrics or KPI that every brand owner or CEO has to look at in order to understand the health of their e-commerce business?
Dan LeBlanc:
There are basically six KPIs that everybody in a company should look at every day.
And that is your traffic, your conversion, your orders, your AOV, your sales and then you choose either your Cost Per Order or Return on Ad Spend. But essentially the marketing efficiency.
Look at those six on a daily basis.And then depending upon what sort of function you provide within the organization, you’ll probably add a couple to there and that’s going to depend on, are you an acquisition marketing? Are you in retention? Are you a merchandiser planner?
These six KPI will give you a pulse in your business and help you determine if something is wrong. Because over time you develop a sense of what the right range is for the business.
It should take you about two minutes. How did we do? Are we on track? OK, now move on to go do something else. That’s going to go help grow your business.
Those six KPIs that we’re talking about is you said exactly. It’s like, it gives you that initial set and then you go dig in deeper.
Gen Furukawa:
How are you actually calculating the lifetime value for those kinds of brands? Particularly for products that are often one-time purchases, like watches?
Dan LeBlanc:
So you use a lot of historical data to help you in terms of your analysis. You’ve acquired a certain customer that bought a certain product from a certain channel.
And so you could go back to somebody that exhibited similar behavior a year or two years ago. And you’re going to basically make the assumption that that customer is going to behave very similarly, from a kind of cohort or what we say sort of group perspective.
So the concept of a cohort being a number of people that fit a similar profile, and then you can do that based upon what’s the channel of acquisition or what time period did they come in. And that’s how you essentially model lifetime value.
It gets more challenging when you are more seasonal, or there are a lot of new products where you don’t have historical context over time. Then you need to look for similar groups, who may have similar behavior patterns, and then you’re tracking that and making assumptions.
Gen Furukawa:
Are there certain benchmarks you see in terms of lifetime value and Customer Acquisition Cost?
And of course it depends on niche and, and average order value for e-commerce in terms of lifetime value to CAC ratio.
Dan LeBlanc: Yeah, strangely enough, it’s actually a bit the same 3:1 LTV:CAC ratio.
It’s just about profitability.
So you generally want to be in the same, at least at that same range, you have to think about that lifetime value.
For most businesses, the gross margin is hopefully around 60%.
your general administrative, it is about 15% to 20%.
10-15% for marketing expenses, no more than 20%.
And so ultimately you’re hopefully making about somewhere between 10 and 20% profit on each order.
That’s kind of your longterm goal.
And so if you think about that from a. From a LTV perspective, you’re going to say, Oh, I want my sales to be about 3x, my acquisition cost.
And so it’s funny that that’s the benchmark that you have for a lot of Software as a Service companies is actually very much in line with many direct to consumer brands.
And so that sort of really determines your product cost or what your average order value is on that first order and how your product costs can really drive what are you able to spend in terms of acquisition cost.
And so it is really interesting, like how similar those two are.
Gen Furukawa:
Yeah, we’ll, we’ll sell X more to this person. How does the LTV: CAC ratio change for lower cost items?
Dan LeBlanc:
Fow lower cost items, you’re just assuming a higher repurchase rate to get you to profitability, because you almost have to lose money on that first order. And so then your repurchase rate becomes really, really important. It’s a very different game, ultimately you have to try to get the same profit per customer, but it’s just if you are a mattress brand like Casper you have to do it in one order, as opposed to soaps or razors, where it has to be done over 10, 12, or 15 orders.
Gen Furukawa:
But what do you think is most important that a merchant can do to unlock data-driven growth by looking at their analytics today?
Dan LeBlanc:
I think the biggest different between successful growth companies and those that struggle is understanding retention.
And it’s interesting, like we all go hire marketing people and then tell them to focus on getting new customers.
And then we don’t focus on the percentage of customers who are your repeat customers. Successful companies have really good retention. And that comes down to repurchase rate — what percentage of a cohort has repurchased? And tracking that over time is really great way to understand how you’re improving.
So you get a new customer.
Do you have a welcome series?
Are you doing something special to introduce that customer to your brand?
Now they’ve come and bought a second time. If are you doing anything different after that person got the welcome series?
Like we all have these sort of daily, weekly campaigns, right?
If somebody behaves differently, are you actually doing anything differently or are you just sending them the same old thing is everybody else. And that’s one of the areas where I think a lot of brands have a lot of opportunity because you’ve already spent so much money to get these customers.
So use the data that you have to go and think about that customer experience and how you can make that consumer feel special.
We talk to the brands that we love are the ones that make us feel special. So if there’s anything that I can tell merchants to do, it’s not just about using data to drive analytics, it’s using data to drive your customer experience.