Host Francois Marchand is joined by Matt Ranta—Head of Practice at Nimble Gravity—to talk about why you should trust the data over your gut for ecommerce success.
- Matt’s background [1:07]
- Nimble Gravity is a group of consultants and a collaborative team of experts that are passionate about the power of data. They believe that data is greater than opinions in a lot of instances and they try to imbue that across the areas that they work in, which are e-commerce, digital transformation strategy, data science, analytics, and engineering as well.
- They’ve been in existence for around three years.
- They’re a group of friends and former co-workers.
- They work with 10-20 organizations.
- What does a head of practice for digital transformation, e-commerce and strategy do? [2:07]
- Helping a nascent brand launch their first ever website.
- Advising an organization who’s in a large digital transformation process about the experience that they’ve had gone through in the past where they found challenges, what platforms they utilized and didn’t, and why.
- Helping organization go through selection processes.
- From a strategy perspective:
- Evaluating organizational talent and understanding how things are happening there.
- Working with Agile and coaching that into an organization.
- Management consulting and management strategy that you might see from a larger organization, like one of the typical Big Four consulting firms.
- Why is trusting data more important than trusting your gut feeling or business instincts? [3:55]
- Matt gives an example from his past company. He joined the company and decided to test display advertising in the electrical component space. Engineers didn’t like the typical adverts that were bright and eye-catching. Engineers preferred ads that were schematics, blending into the background, and didn’t have CTAs.
- You need to dig into the data because the customers are going to tell you. Your pre-determined ideas aren’t necessarily going to be correct.
- They did A/B testing, and found the more they iterated the better they got at it.
- What is a common metric ecommerce business owners tend to overlook and why does it matter so much? [7:23]
- There’s a group of three: repeat purchase rate, purchase frequency, and click through rate.
- Repeat purchase rate: you need to know how long it’ll take for a customer to repurchase. If you have that rate and notice some customers are surpassing that rate, then you need to reach out and re-engage.
- How did Matt successfully track this metric? Are there tricks or tools that make this easier? [9:40]
- Excel is a great tool for this. If you have millions of records then you’ll need to move it to a larger data tool.
- There are great tutorials on how to calculate repeat purchase rates or RFM studies.
- Amazon has published information on Amazon Science about their modeling of repeat purchasing and how they do it.
- Any data transformation tool that you’re comfortable with is good.
- How can tracking this kind of data help you grow your business? [11:47]
- This kind of data can go into your forecasting because you can estimate when a customer is going to make another purchase.
- You can look at suggested timings to email your customers to re-engage, when to update the messaging on your website, outbound campaigns, and give limited time offers. It helps you do all of this intelligently, because if you’re doing a winback campaign, you know the smaller segment of consumers who have actually forgotten about you or are looking elsewhere. As opposed to throwing away dollars to a customer who was already likely to repurchase in the near future.
- Can you build a subscription model out of that data? [14:10]
- You can but it depends on some things.
- Matt gives an example using the supplement.
- Can trusting your gut instincts over the data ever lead to success? [15:52]
- When you’re dealing with innovation there’s often a lack of data. Look at the iPhone, it’s been a big success. If you go back to when it was created there wasn’t enough market data to show that they should create an iPhone (the closest products were Palm Pilots).
- Making music—there’s AI that can assess what will be a hit song, but the artist’s gut is still important.
There’s data to inform the path that you should walk down, but there isn’t necessarily somebody who’s walked down the path that you’ve specifically gone down before that can serve as a hundred percent guide.Matt Ranta
- Will AI tools to look at the data help you be a better business? [18:33]
- Absolutely. Matt cautions people to continue to have a level of human involvement. AI is not 100% accurate—CNET had an issue with AI writing articles that weren’t factual.
- Anything else important Matt shares about his experience in using data to inform decision-making [20:53]
- It goes back to tool sets and mindset and culture of the organization. Speed is critical when you’re analyzing and looking at data. You need to set your organization up to look at data rapidly. You’re not going to derive value from the data if it’s going to take many months to analyze it.
Get in there and start looking at that data and then test and iterate on top of it in order to drive true growth.Matt Ranta
Meet Our Guest
Matt Ranta is the Head of Practice for Digital Transformation, E-Commerce, and Strategy at Nimble Gravity. His 24 years of experience were earned inside of start-ups, employee-owned organizations, as well as Fortune 120 level companies. Matt has run marketplaces with 3 million SKUs and Billions in GMV, launched global sales and marketing initiatives at numerous organizations, been a part of the leadership team for a company ranked number one by Consumer Reports for buying consumer electronics online, helped introduce the iPhone to pre-paid wireless, has consulted for multi-billion-dollar ecommerce companies, has driven triple digit growth of multiple websites, and has led digital teams in both B2C and B2B.
Speed is critical when you’re analyzing and looking at data. You have to set yourself and your organization up for ingesting, manipulating, and analyzing data in a rapid fashion to truly capture its power.Matt Ranta
Resources from this episode:
- Subscribe to the newsletter to get our latest articles and podcasts
- Connect with Matt on LinkedIn
- Check out Nimble Gravity
- How to Calculate Purchase Frequency, and 3 Tips to Improve It (in 2023)
- Buy it again: Modeling repeat purchase recommendations
- Generative AI: A Journey Through Familiarity, Usage, and Concerns
Related articles and podcasts:
- How Can Picking The Right Ecommerce Subscription Management Software Impact Your Business
- Ecommerce Analytics: How To Use Data To Understand Customer Behavior And Boost Your Sales
- Nimble Gravity’s Matt Ranta on 5 Things to Know To Build A Successful Ecommerce Website
Read the Transcript:
We’re trying out transcribing our podcasts using a software program. Please forgive any typos as the bot isn’t correct 100% of the time.
Read The Transcript:
We’re trying out transcribing our podcasts using a software program. Please forgive any typos as the bot isn’t correct 100% of the time.
Francois Marchand: Data. There's so much data out there. What happens when the numbers clash with your business intuition? Are the numbers always right? How do you track and apply data findings to make better decisions? Those are good questions, right?
Welcome to The Ecomm Manager Podcast. Our mission is to help you succeed in your e-commerce journey with helpful advice from the experts who made it big. I'm your host, Francois Marchand.
Today, I'm joined by Matt Ranta. He's the head of practice for digital transformation, e-commerce and strategy at Nimble Gravity. And we'll be chatting about why you should trust the data over your gut for e-commerce success. So stay tuned to discover best practices around data gathering and analysis for e-commerce, what metrics e-commerce managers tend to overlook, and how data is key to growing your business.
We're so glad to have you on the show today, Matt. Welcome to The Ecomm Manager Podcast.
Matt Ranta: Yeah. Thanks so much for having me. Excited for the conversation. I appreciate the opportunity, first of all.
Francois Marchand: Let's talk a little bit about you and what you do with Nimble Gravity. For people that don't know you, first of all, what is Nimble Gravity? And how did you get to work with that company?
Matt Ranta: Yeah, absolutely. So Nimble Gravity is a group of consultants and collaborative team of experts that are passionate about the power of data. We believe that data is greater than opinions in a lot of instances, almost all of them. And we try to imbue that across the areas that we work in, which are e-commerce, digital transformation strategy, data science, analytics, and then engineering as well.
That's setting up teams of engineers for working on software products for companies obviously. And we've been in existence for around three years. And I got to join the organization by, it's a bunch of former friends, honestly, and former coworkers. So a lot of us work together at a past organization, Arrow Electronics, and then have found our way back together at this point in time. Yeah. It's lots of fun.
Francois Marchand: What does a head of practice for digital transformation, e-commerce and strategy do exactly?
Matt Ranta: Yeah, that's a good question. Quite a few different things. Can be anything from helping a, a nascent brand, launching their first ever website, can be coming in and advising an organization who's in a large digital transformation process about the, experience that we've had going through that in the past. Where we found challenges, what platforms we utilized and didn't, and maybe why, and helping them go through selection processes, any number of things there.
And then from a strategy perspective, this can be things like evaluating organizational talent and understanding how things are happening there, working with Agile and coaching that into an organization. And it can go all the way into management consulting and management strategy that you might see from a larger organization, like one of the typical Big Four consulting firms.
Francois Marchand: You work with a lot of companies, like how many clients does Nimble Gravity have right now?
Matt Ranta: Yeah, so we don't share the exact number, but it's in the tens. It's not in the hundreds. And high tens I'll say that and they're very diverse. So we work with one organization that's, protecting wildlife and helping to monitor the wildlife activity and the activity on preserves and in conservation areas and things like this.
And gives software to the staff that are monitoring that facility or that area of land, whatever it might be. And helps them run that to clothing brands, to major medical distribution organizations, to all kinds of things. A huge diversity in clients. We really aren't focused on say, just FinTech or just biomedical or something like that. We have a very diverse group of clients, so pretty interesting work. Yeah.
Francois Marchand: You mentioned data, obviously, that's something that you work with very closely. It's something that Nimble Gravity is an expert at doing. Digging into the data, and I think that's what we want to talk about today. Which is why should you trust the data in e-commerce versus trusting your gut when it comes to finding success?
You know, whether that means building a brand from the ground up, or maximizing your sales or, optimizing very specific aspects of your business. So let's talk about that a little bit.
Matt Ranta: Yeah. So I can give you a really tangible example of an opportunity that I was presented with at one point in time in my career. So when I joined Arrow Electronics, we were being brought in as a group of individuals to help do a digital transformation there and accelerate their digital growth.
And a lot of us came from industries outside of electronic components. And so we didn't necessarily have an understanding of the minds of engineers who are really the consumers of electronic component products. We had an understanding maybe of typical consumers of for my background, consumer electronics, people who are buying TVs or whatever.
And for other folks it might have been, a different discipline in industry, sporting goods, something like that. And so we came in and we started to test some advertising, some display advertising across electronic component related media that we knew engineers visited, and aggregator type sites, these kinds of things.
And we used techniques and paradigms from the industries that we had been in the past, right? We had large calls to action, we had bright vivid ads, these kinds of things that we wanted to, grab the attention of these folks and then have them interact with them. Well, guess what?
They hated this. Engineers don't like that at all. And what we came to find out was they actually preferred ads that blended in the background that maybe included an electronic component schematic, like not the kind of thing that you would typically put into a traditional, maybe B2C type ad.
And they preferred these so much that if you know anything about display, click through rates, they're usually pretty low. They're tenths of percents, right? So we were getting, hundreds of percents click through rate on the ads that we thought were gonna work. And then we started getting two and three and even up to 5% click through rate on these display advertisements that had schematics that were blending into the background that didn't have a call to action at all on them, anything at all.
And so they just were completely counterintuitive to what you typically would think. And that's exactly why you need to test things. You need to go in and look at the data, and you need to understand what's really happening because your customers are gonna tell you. You aren't gonna be able to take your predetermined biases or your gut feeling all the time and necessarily have that come out to be a hundred percent positive and a big improvement on what you're currently doing.
Francois Marchand: So, did that involve a lot of A/B testing? Did you have to do a proof of concept to get to that conclusion?
Matt Ranta: Yeah, we totally did. And we worked with some both internal and external partners who understood the minds of the engineers a little bit better and did that A/B testing and got the proof back. And then continued to accelerate that and iterate on those ads that were working and continued to test those because we continued to find the more we iterated, the better we got at it.
Francois Marchand: We talked about, click through rates and other, measurements that we can use in, in e-commerce, obviously that's a big one if we're talking about landing pages, display ads and so on. But what's a common metric that e-commerce businesses or business owners tend to overlook and why does it matter so much?
Matt Ranta: Yeah, great question. So there's actually a group of three that I think of pretty frequently that get overlooked and they all play into one another in, in how you calculate 'em in their repeat purchase rate, purchase frequency and time between purchases. And so these are the kinds of things that get exposed with RFM studies and that kind of stuff.
But the reason I think that you should consider these really important and even calculate them down to the customer level because then you can create some cohorts, is that you have an understanding of the timing of purchases. Especially on say, consumables, that people are going to repeat purchase over time of what you need to be doing to message people.
And I knew in past roles that like it was 121 days on average before 85% of my buying population had made a second purchase. So they made a purchase on day one, and then on day one, a hundred twenty one, they came back for it, their second purchase. And I knew then that, okay, if I've got a cohort of people that have made it to say a hundred days and they haven't made their second purchase, I should be talking to them.
I should be sending them an offer. I should be, messaging them when they come on site. They should be getting an email from me, whatever it is, all of those, in order to pull that purchase behavior forward. And then if they've gone to that 121 day period or beyond it, then I need a retention tactic, a reactivation tactic, right?
I need to start putting them into a different email sequence, whatever it might be. I need to be making sure that I'm utilizing RLSA kind of Google Ads to go back and retarget them so that they're seeing me when they're, shopping for that same thing if they happen to forgotten where they got it, whatever it might be.
So those kinds of things really help you in growing through data in kind of the, secondary set of metrics that a lot of people aren't paying attention to, I think. Yeah.
Francois Marchand: So this is the kind of stuff that you would measure using, certain tools. You can do that through, your CRM, your dashboards, and so on. What kind of tools do you use to successfully track metrics such as your repeat rate, your frequency of purchase, and so on? And are there some that actually make this job easier for e-commerce managers?
Matt Ranta: Yeah this is gonna sound crazy, but excel's a great one for this kind of study, honestly. If you have a, a relatively manageable set of purchase history for clients, if you're gonna be on a million records, right? Then you have to move that into probably a big data environment, something that can ingest and transform records beyond, a million if you're talking, if you have 5 million purchase records across your customers, if you have 10, 20 million.
And then you just gonna want to set up some dashboarding and reporting through whatever your preferred platform is, whether that's a Tableau or a Looker or something like that, where you go in and you work with your data science team in order to figure out those calculations and then have them in, in, regularly refreshed reporting.
And you can go find these kinds of things, I can give you some links that we can share with your audience, but there's great tutorials on how to calculate purchase frequency that are out there, or how to do RFM studies, both of which will get you to the point that you need to be.
And then companies like Amazon have even, published information on Amazon Science about their modeling of repeat purchasing and how they do it. And so you can go look those up and learn from people that have been doing it before, how you might want to do that, and what the benchmarks are that they got and that you can look for.
So lots of great things out there, but any data transformation tool that you're comfortable with is a great place to start.
Francois Marchand: Yeah. So if you're like a small, medium type business and not like at a enterprise level, Excel probably works. Doing Google Sheets probably works. But if you are going to scale and move into volume selling, this is probably where you'd want to invest into those subscription based tools or SaaS tools that could maybe take you to the next level. Correct?
Matt Ranta: Yep. Yeah, absolutely.
Francois Marchand: How can tracking this data help you grow that business, cuz we talked about scaling. So if you wanna scale, how do you do that?
Matt Ranta: Yeah, so this kind of data is gonna give you all kinds of great information, right? It can go into your forecasting because you'll understand when a cohort of customers who, you know, made their first purchase is likely to make their second purchase.
You can bake that into your future forecasting as well as what you're doing to augment that in the meantime, right? Cuz you're also at that same time bringing in new first, first time acquired customers. And so you've got a base that you understand of when they're gonna be repurchasing again potentially.
And then to go to the kind of marketing side of things, you can start to look at suggesting timings for emailing to particular cohorts, potential messaging on your website or for outbound messaging of any kind. You can do, even direct mail still works great. And you can send out postcards that are automated and based upon the data of your systems.
And puts an offer in a, in an actual mailbox and, give somebody a special limited time offer on your website. You can pull in revenue sooner if you need to, right? By incentivizing this kind of stuff. And it allows you the opportunity to create winback emails, so you're going after the reactivation after, and giving people particular offers.
And it also gives you the ability to do that intelligently, right? Rather than just giving your entire cohort who haven't made a second purchase a winback email, you know the smaller subset of people who should get it and when they should get it. So you maybe don't send a 10% offer to a consumer who was probably gonna rebuy already.
You send a 10% off offer to a consumer who maybe forgot about you, started looking somewhere else, whatever it is, and then you're not giving away dollars that you didn't have to. So there's a lot of smart ways that you can do this and that it can impact your business in total and the total profitability. So it's a fantastic set of metrics to look at.
Francois Marchand: Yeah. Obviously you'll probably get a better ROI if you're not wasting money into these marketing efforts, especially if you're doing physical marketing where you know there's costs involved in mailing stuff out. Saving money is a big deal.
Matt Ranta: Totally. For a new, young business that's small or whatever and trying to grow, it's a huge deal. Yeah.
Francois Marchand: Is it a good way to build subscription models? I mean, obviously we talk about these knowing the repeat rate and how long it takes before someone is going to repurchase. Can you build a subscription model out of that data?
Matt Ranta: You sure can and it depends on kind of some things, right? So obviously if you have a pre-packaged supplement or something that you want people to subscribe to, right? And you've got 120 pills in the bottle and it's designed that you take three a day or whatever, right? You've got a set finite period where somebody's gonna need one already.
But if you start talking about consumables that people might not use the same amount of, let's say like a facial cream or something like that, right? And somebody might be, very vigorous with the amount that they're pumping out of the container and somebody else might be a little bit more sparing.
And you can start to find that data of gosh, we should be sending this every 45 days, or it should be every 60 days based upon the great number of our population. And then there might be things where it's, food that people consume differently, these kinds of things that, that you're selling that can be fantastic for figuring out the timing of that and suggesting that to consumers and then giving them the opportunity and the pricing for that. So yeah, that's a great point.
Francois Marchand: Thanks for that. I appreciate the input on that cuz we get a lot of questions about, subscription models and if they work well. Obviously, Amazon does it quite a bit. But if you're a smaller business that wants to start offering that type of model, you don't wanna waste your time in offering a product that people don't need to repurchase right away. So that's a good way to track it.
Matt Ranta: Totally.
Francois Marchand: Can you ever trust your gut instincts over the data to lead to success?
Matt Ranta: Yeah, I love this question. So one, there's actually data that says yes. So it'd be foolish of me to ignore that and say no. And what I'd point to is innovation and creative disciplines, right? I think we'll probably start to see a lot more data around those two areas as we continue this journey with, AI, machine learning and getting deeper and deeper into that and all disciplines of life.
But when you're dealing with innovation, there's frequently a lack of data, and an unknown and, take a look at the iPhone. iPhone has been unbelievable, massive success in, in all aspects. And if you go back in time to win that project originated with Apple and the people that were involved, sure there was some interest in like palm pilots and things like these.
But there isn't necessarily enough market data that is gonna show you, yeah, you should totally go after making an iPhone. If you said to somebody, Hey, would you like it if we combined a calculator and a camcorder?
They're gonna go, no, not really. It's I see no reason for you to do that. Right? And, and so there's no data that's gonna prove that out a hundred percent. And instead that's a gut instinct. That's intuition. It's kind an understanding of the total market and the total psychology within the market that those people who are really driving innovation and doing creative disciplines, making music, right?
Like some people just know what a hit song is and there's now, granted, there's AI and stuff that is capable of analyzing those and rewriting hit songs as well. But I think there's still gonna be, creative involvement in those kinds of things, and that those people in that discipline must continue to trust the gut. Yeah.
Francois Marchand: Yeah. I mean, if you're going to create a brand new product or, build a new category, we talk about category creation, which is a big deal in, in tech and new new product. There's no data there to help you figure that out, or is there? Can you look at other companies or brands that have successfully invented something new and see what the data is through their progress?
Matt Ranta: Yeah, I think you can, to some degree, you can definitely see their process. You can see the trial and error that they went through. You can see, how they might have ideated and been tested and these kinds of things. So there's data to inform the path that you should walk down. But there isn't necessarily somebody who's walked down the path that you've specifically gone down before that can serve as a hundred percent guide, right?
Yeah, I think there's a little bit of both.
Francois Marchand: Do you think that with the event of AI and it being such a hot topic, that it'll make data analytics more predictive? Will it make you a better business if you start using AI tools to look at the data?
Matt Ranta: Yeah, a hundred percent. I think that AI will get us there and that you'll be a better business if you utilize AI in that kind of framework in data analytics and these kinds of things.
And there's already tools popping up that do this and that, that help folks specifically with exactly what you, you're asking about. What I would caution people about is there still has to be a level of human involvement. I don't think AI has reached a point where it's a hundred percent error free. In fact, if you look back at CNET is a big example of this, right?
Like they've been writing articles with AI, they had a whole bunch of factual errors in those articles. They got called out, they had to go back and rewrite them and correct them and notate them differently. And I think that continues to be an area where human involvement is gonna be necessary.
Like you're gonna have to go and check, did everything happen correctly? And get that validity and that trust in a particular system and tool. And does that mean that you thereby 100% of the time afterwards can leave out the human intervention? Maybe, not necessarily. Like I would still encourage people to go back and check those processes.
Are you writing good code using, AI? Possibly. Is it filled with errors because the bias of the data that it went out and looked at is also filled with errors? Yeah, it probably is. Right? And so you probably need somebody to go and proofread that because if something like a ChatGPT is trained on the entirety of the internet, right?
Like you and I both know that there's some great functional production code out there and that there's also some bloated, not very good code out there. And there's no way, unless you have removed the bias of that from your dataset and from your training, that you're gonna be able to authentically say, this is a hundred percent always going to produce 100% valuable, viable code that we should publish without anybody ever looking at. Right?
Francois Marchand: Yeah, that's right. The internet is filled with everybody else's gut instincts, so. It takes us back to the beginning. Is there anything else that you think is important that you'd like to share about your experience in using data to inform decision making for all the e-commerce managers and business owners that might be listening out there?
Matt Ranta: Yeah, that's a great question. And I think it maybe even goes back to tool sets and mindset and culture of the organization as well. The other thing that I would point to around that is speed is critical when you're analyzing and looking at data. And so I, I feel like you have to set yourself and you're organization up for ingesting, manipulating, and analyzing data in a rapid fashion to really, truly capture its power.
If you're gonna use a tool set and assign individuals to do these studies and it's gonna take them, 12 months or whatever, which is probably a ridiculous amount of time for some of the things we were talking about. But yeah, you're not gonna derive the value from that, that you really need to, and you need to consider how can we make that a heck of a lot faster?
Is that hiring more expertise? Is that getting different tools? Is that just flat out using a tool set that we're more familiar with, whatever it might be, set yourself up for speed and combine that with a, the data is better than opinions kind of viewpoint, and you'll be on a good path.
Francois Marchand: What's your number one piece of advice to be a successful e-commerce manager? I think you've mentioned that already, but if you can give us a quick nugget your number one piece of advice.
Matt Ranta: Yeah. My number one piece of advice to be a great e-com manager and to help grow your business is really to look at the data to dive into all your analytics. Don't be afraid. Get in there and start looking at that data and then testing and iterating on top of it in order to drive true growth, because that is something that is shown to you by the actions of your customers through all your analytics, whether they're qualitative or quantitative, and number one thing you should go do right now.
Francois Marchand: Speaking of tools and recommendations, we'll have all of these in the show notes. If you're looking for Matt's recommendations, Matt will send us some links. We also have links to other articles from the e-commerce manager website. As well, I'd like to mention that Matt and I had a great interview where we discussed how to build a successful e-commerce website. So you can check that out on the e-commerce manager, and that will also be in the show notes.
Matt, where can people follow your work, keep track of everything that you're doing with Nimble Gravity and outside of Nimble Gravity?
Matt Ranta: Yeah, so the two best places are really the Nimble Gravity website, which is nimblegravity.com. And the other one would just be connect with me on LinkedIn or follow me on LinkedIn and you get all that that information.
Francois Marchand: Matt, thank you so much for joining us today. It's been a real treat to talk data with you. And now we know gut instincts are good when it comes to creating, when it comes to inventing, when it comes to conceptualizing the products that you want to put out in the world.
But really, once you get to the next step, you want to scale, you want to grow, look at the data. Look at what your performance is on things like repeat rate, frequency of purchase, and click through rates on your ads. These are the metrics that matter. And I think, Matt, you've confirmed that today.
So again, thank you for being here on The Ecomm Manager Podcast.
Matt Ranta: Yeah, thanks so much for having me. First of all, I really appreciate it. Great convo.
Francois Marchand: Thank you very much. We'll see you next time.