Unlocking the Power of AI in Retention Analytics with Ben Hindman - 87

In this episode of the D2Z Podcast, Brandon Amoroso and Ben Hindman, co-founder and CMO of Peel Insights, delve into the world of retention analytics and AI-driven insights. Together, they explore the intersection of data analysis and actionable marketing strategies, providing valuable insights for businesses looking to enhance their retention efforts.

Ben is a seasoned entrepreneur who takes us on a whirlwind tour of his career—from his roots in event planning to the inception of Splash, a trailblazing event marketing software, and his current role at Peel Insights.

The heart of the conversation lies in Peel Insights' groundbreaking creation: Magic Dash. This AI-powered marvel is designed to be a compass for businesses, particularly those in the direct-to-consumer (DTC) arena, navigating the vast sea of data. Ben expertly navigates the complexities faced by businesses generating annual revenues between $5 million and $50 million, highlighting the hurdles they face in harnessing their data effectively.

Ben and Brandon also embark on a visionary exploration of data analysis's future, with the potential to reshape the e-commerce landscape. The future? Automated recommendations and actions galore, driven by data insights. Yet, they acknowledge the yawning chasm that separates the present from this utopian vision.

As we near the end of this podcast episode, Brandon and Ben naturally gravitate toward the ever-evolving landscape of e-commerce. It wouldn't be a D2Z Podcast episode without some insights into the e-commerce landscape, right?

So, here's the bottom line: to thrive in today's cutthroat business arena, businesses need to master two key strategies—keeping customers engaged and diversifying marketing channels. It's the winning formula for profitability and long-term success, especially when investors are looking for both. Consider this episode your compass in this ever-evolving journey.

Tune in for an enriching journey through retention analytics, AI-powered revelations, and the evolving landscape of data-driven marketing. Discover the compass to navigate the labyrinth of data and emerge as a victor in the competitive arena of business.

Timestamps:

🎙️ (00:00:00) Introduction and Background of Ben Hindman

🚀 (00:01:47) Evolution of Peel Insights and Introduction to Magic Dash

📊 (00:05:57) The Gap in Analytics Tools for Mid-Market Businesses

🔍 (00:06:42) Bridging the Gap with Magic Dash

🤖 (00:10:14) The Role of AI in Data Analysis

🔍 (00:11:18) Trust and Clarity in Data Analysis

🌟 (00:11:48) The Future of Data Analysis and Marketing Integration

🔮 (00:12:26) The future of data analysis and automation

🚧 (00:12:58) Gap between current capabilities and automation vision

🧠 (00:13:27) Factors affecting progress: Consumer psychology and technology

📲 (00:13:56) Potential for reduced importance of interfaces

🌐 (00:14:08) Emerging apps automating data capture and analysis

🛍️ (00:14:28) Importance of AI-driven website personalization

🌐 (00:15:13) Challenges in website personalization compared to email

📈 (00:15:49) Discussion on e-commerce trends and retention

🔄 (00:16:12) Necessity for cross-dimensional data analysis

💼 (00:17:00) The shift towards profitability and retention

🔑 (00:17:30) The significance of retaining customers

🌱 (00:18:39) Focus on slow, profitable growth

🎯 (00:19:25) Targeting specific customer archetypes

🔊 (00:26:55) The importance of resonating deeply with the audience

Transcript

Speaker 1: 0:02

I'm Brandon Amoroso and this is the D2Z podcast Building and growing your business from a Gen Z perspective. Hey, everyone, thanks for tuning in to D2Z, a podcast about using the Gen Z mindset to grow your business. I'm Gen Z entrepreneur Brandon Amoroso, founder and president of Retention as a Service Agency, electric. Today I'm talking with Ben Hinman, co-founder and CMO of Peel Insights, which is an all-in-one retention analytics platform. Thank you so much for coming on, ben, excited to have you here.

Speaker 2: 0:37

Oh, excited to be here.

Speaker 1: 0:39

So, before we jump into everything we're going to cover today, can you give everybody just a brief background on yourself?

Speaker 2: 0:46

Oh sure, make it real quick. I am an event planner, an event marketer, by background, and I started a software called Splash SplashThatcom and built that for about a decade, making it possible for event marketers to have easy tools. They made them look awesome and made their events even better, and so we did that. It's still growing and it's a fantastic business, but I stepped down as CEO about a year ago and I've been more recently working with the team at Peel to bring their AI vision to life, and so that's where you catch me today.

Speaker 1: 1:28

Nice. I got a lot of questions about the Splash side of things. But touching on Peel, since you just brought it up, what is the AI side of things? I assume the product has changed a lot since AI has become all the rage over the last 12 months, and what does that look like for Peel now?

Speaker 2: 1:47

So actually, right after I stepped down from Splash, I took a role as the head of off-sites for Shopify and I started throwing some of their team gatherings and bringing merchants in, and it was really around that time that I started becoming obsessed with D2C. It just was the coolest thing ever. Everything about it from the cultural fabric that it creates to the habit formation and marketing prowess you need, to the creativity of the products, to just the design orientation I love D2C and as I was throwing these off-sites, I just became more and more obsessed with getting into the D2C space.

Speaker 2: 2:25

Lo and behold, I'm not a D2C operator, so my foot in the door needed to be a B2B product, and so I started looking at the App Store and came across the team at Peel, it turns out. So this team, it's just, it's a small group of really talented engineers, and the architecture that they built was it's kind of like the way an insane person would build an architecture. It's just super flat and it allows you to download all the data overnight and look for patterns and kind of read it, and it's an incredibly effective architecture for this next AI revolution. And so as I started to kick around ideas with this team, it became really clear that there was a big opportunity in AI. So you ask the question like what?

Speaker 1: 3:08

is our AI vision.

Speaker 2: 3:10

Well, this team had been building dashboards and reports and audience segmentations like deeper than anyone else in the space, but what became pretty clear to me was that they were so deep, they were so robust that it was actually kind of hard to navigate and people would often get lost in the tool. And so over the last month or so, that's what we've been building. We've been building a product that allows you to, like, infinitely easier grab whatever report, whatever metric, whatever answer you might need, and we call that product Magic Dash. And so we've been working on Magic Dash now for about four months. It just launched and it's getting better and better every single day, so I can tell you a bit about, like, what the product actually does and how it feels. Do you want me to jump in?

Speaker 1: 3:55

Yeah, are you like prompting it in the same way that I would, you know, prompt chat GPT, but instead this is going to give me, you know, insights into business performance and things that I should do from like a marketing standpoint for a Shopify business.

Speaker 2: 4:09

I think in illibrand you're hired, you know, I think the only thing I'd layer on top of that is that more often than not, when it comes to your business, there's not just one answer. There's a series of data points that will help you come to the right answer. And so when you ask it a question with natural language, we're not just reporting, you know, returning back. Here's the answer. Instead, it searches throughout the whole platform for all the different reports that you might need. It might pull up a cohort report, it might pull up an RFM report, it might pull up a market basket. It shows you those reports.

Speaker 2: 4:43

And then it goes one step further. It actually looks for insights. That helps you understand those reports. So it actually explains the numbers to you, and that actually is something brand new. To our knowledge. We haven't seen any platforms that are actually reading the data itself, identifying insights, returning it back to you in plain speak and, yeah, helping you understand the data. That simply. So we've just been kind of laser focused on figuring out how do we just make it obvious why this data is important and make that answer really easy to understand.

Speaker 1: 5:20

Yeah, I think that's a huge gap because you know there's obviously a ton of analytics, you know, apps and platforms within the Shopify ecosystem, whether it's you know, dacity or glue or lifetimeally like I could just sort of go on and on and on down the list and the biggest issue for me with any of them is actually being able to leverage them, whether it's, you know, the in-house team of the client that we're working with or it's our agency being able to utilize any of the data to make actually informed, you know decisions to progress the business forward.

Speaker 1: 5:58

And I can't even tell you how many times you know we work with like a mid-market brand who's on that, like sort of that weird cusp of you know maybe we should start getting enterprise grade tech or maybe we shouldn't, and they you know they make the leap and they're on Tableau or something and they don't even have an analyst in-house to you know actually do anything with Tableau. I'm like, okay, well, like now what, you're sort of just stuck with a very expensive, you know car that you don't actually know how to drive. So for me all of this sounds amazing because I don't actually want to, you know, have to have you know the analysts or to have to get super nitty gritty with things. I just want the insights and then to be able to actually act on them.

Speaker 2: 6:42

You nailed it. I mean, that's what we found is that, right around let's call it between like $5 million and $50 million, you get into that range in terms of annual revenue. You're in that range where you don't really want to bring in a data analyst, but you need to understand the data. And so, to your point, we found that a lot of retention marketers were craving this. They want that golden nugget, they want to find that opportunity, they want to really understand, they want to go deep, but they don't want to spend all that time, they don't want to spend all the money on an additional analyst, and so we're hoping to bridge that exact gap.

Speaker 1: 7:17

How have you been sort of thinking about the go-to-market with the new product, more so from like a B2B standpoint and putting your CMO hat on? Yeah?

Speaker 2: 7:28

fun, good question.

Speaker 2: 7:30

I feel like I should just ask you what do you think I should do here? You're doing the job. No, it's been, really it's been. You know, as you mentioned, it's so, so, so, so, so. It's such a crowded space and everyone claims that they can do all of these things. So I think, first and foremost, it's been.

Speaker 2: 7:47

Our key plan is to get people in the product and let the product speak for themselves. If you can believe it, we convert about 50% of our trials, a little bit more than that. So one in two people when they try us out, they're hooked, and one of the reasons for that is that the product has these Slack notifications and email notifications that actually surface up those insights, and so, especially your founder, your CEO, might not be logging in. We find that that really does get people hooked. So that's one thing. Just get them in the product, try it before you buy it.

Speaker 2: 8:21

And so a lot of my go-to-market motion is how do I get people to just give it a shot? You know, the other piece that we've been spending a lot of time on is really just focusing on the retention marketer. I mean, I'd love to kick this back to you. I'm seeing that as a type of a role that is really underserved. You know the growth marketers and you know all the talk of ROAS. It feels like they have both a lot of products and a lot of focus on them, and I'm not seeing a lot of products really honor the important work that retention marketers are doing, and so certainly that's like my prime focus. How do we honor them, how do we make their jobs much easier? How do we highlight them? How do we spotlight the important work that they're doing? And then, obviously, how do I get them in the tool so they can understand the power of what we're delivering as well?

Speaker 1: 9:11

Have you thought about? Because there's some tools out there from a retention standpoint, like a repeat or a relo, even rebuy, doing it a little bit where they're predicting that next order date or they're passing something over to Klaviyo to trigger a series of win back or replenishment flows. But then you have tools like yours that are surfacing insights around retention, but you have, like the two that are sort of separate and are we moving towards? You know something where you'll have like an AI based Klaviyo metric that'll trigger a series of like email texts and direct mail communications, because you have this, you know this hub that's able to detect and analyze those patterns on like a one to one basis for each customer Versus it being this, you know, sort of disjointed oh, we're going to take our analytics and insights from you know, from Peele, but actually our communications to the customer are going to get triggered by something else.

Speaker 2: 10:14

It's such a fun question. I think the answer is yes, certainly within our product. Right now you can. Within a click and right within inside of Magic Dash it'll auto segment your customer base by you know who's most prime to buy as an example, and then you can pump that through to call Klaviyo, attend to PostScript, whatever that looks like right so you're right, we're doing.

Speaker 2: 10:36

We're doing a lot of the data analysis in one platform and then we're pumping it into another platform, and I think what you're alluding to is that are we not soon going to see either that kind of master app that you know you can do both inside of you know? What I've been blown away by is how, like in the Maslow's hierarchy of data needs, how far away we actually are from that. And the reason is is that people still don't trust their data. And you know, and it's not just that they don't trust their data, like, certainly like a lot of people don't trust.

Speaker 1: 11:10

you know Shopify's data and that's like most of our survey, surveys are saying that which let's just start there.

Speaker 2: 11:16

That's a problem.

Speaker 1: 11:18

Right, that should be like. The one source of truth is the Shopify.

Speaker 2: 11:21

You would think right, and so a lot of the challenges that we get from our customers are actually not necessarily do I trust my data or how do I, you know, navigate this. Instead, they're just looking for clarity on how the data was actually calculated.

Speaker 2: 11:39

So, if you ask me like the lowest hanging fruit towards the vision that you're describing is getting people just to have a better sense of how this data is calculated. When you know certainly if you have a bigger organization you just walk up to a data analyst and say, hey, like, did you include this month? Did you include that skew? You know, did you exclude that? You know, more often than not that's actually where people are getting tripped up. Okay, but let's just presume that, like you're right, like in the next call, a year or so, people start to trust that a more people start using magic dash and the explanations become super apparent. I think your question is do we not start to see like an actual molding or melding of the data analysis and the actual actions that can be taken from them?

Speaker 1: 12:23

Is that was that kind of what you're alluding to. Yeah, yeah, exactly yeah, I think you nailed it.

Speaker 2: 12:29

I think that that's an inevitability. People so badly want to take actions from the insights, from the data. Right, they want to run a deep analysis, get so deep, double click, triple click, understand it and then take an action that it does seem obvious to me that, like pretty soon we're going to see products that you do just that you take actions from the data and then eventually those actions will be kind of just be recommended and then just done for you. I'll tell you right now I'm surprised at how far away we actually are from that. There still seems to be a need for these deep analytical products that you can go as deep as you can with Peele and magic dash. I think we're still pretty far away from that big vision of kind of that super app.

Speaker 1: 13:17

Do you think it's primarily on the sort of the consumer psychology side of things where people aren't going to be comfortable with it, or is it a technology limitation right now as well, too?

Speaker 2: 13:28

I think the answer is yes. I think that the interface layer and the ability to understand the data is actually what is in the way of it being incredibly useful, but I do believe that in the next call it five years, we're actually going to see an era where UX and interface won't be as important, because the data will be making decisions for you. So we are starting to see apps that are just really beginning to automate the capture, analysis and action taking of that data.

Speaker 1: 14:08

Yeah.

Speaker 2: 14:08

I mean.

Speaker 1: 14:10

I'd rather have a platform make all the decisions for me, because so much of what we're doing is still very manual. And you know, the whole campaign ideation process for brand is outdated and, I think, in the wrong direction, where you think about oh, how many times do we want to send an email this month? And then, okay, well, what are the ideas for the email? And then from there it's like, all right, well, what segments do we want to target with it? At no point is a piece of software telling us, hey, this cohort needs this type of communication at this point because they purchased X months ago or whatever insert prompt here, and so it just feels like it's being done backwards, given the enormous amount of data that any app that's plugged into Shopify storefronts, you know, gets access to. And especially once you start to look at the fact that, let's say, you know Peel and I talk about this a lot with you know the rebuy guys as well.

Speaker 1: 15:09

Let's say, peel is installed on five stores that I've made a purchase from, but then you know, on the sixth store that I go to, peel is installed, peel knows it's me, and so why are my interactions with those five other stores like, not, you know, informing my interaction with that sixth store, we're very far away from that. But that would be like. My preference is that the tools just tell me hey, you know, go make this creative and drop it in here or Peel, maybe they'll start making the creative for us and then we literally don't have to do anything. But that would be an ideal state, because so much of what we're doing now is still batch and blasting to, you know, a one size fits all segment.

Speaker 1: 15:49

You know I agree with you and I don't think we're that far away from what you're describing.

Speaker 2: 15:52

My expectation is that that type of kind of cross store analysis will become more and more possible on the Shopify platform and then with products like ours, kind of helping connect those dots. And I take your point that to be able to have automated actions would make a big difference in certain segments. But what I've also been seeing a lot with some of our operators is that some of the biggest decisions that they're making aren't able to be automated.

Speaker 1: 16:22

Certainly won't be for a long time and those kind of decisions are how do you position a product?

Speaker 2: 16:28

What is the right product to present? On a second order, what is, you know, the correct bundle to present to which audience? And certainly there's ways to trigger that in an automated way. But when you start to combine that with actual product development, actual fulfillment, it does get a few steps removed from that kind of automation.

Speaker 1: 16:49

So I think we're both saying the same thing.

Speaker 2: 16:51

I think we're in agreement that there is there will be, supreme automation very soon for some of those lower level tasks like deploying an email, some of the highest leverage tasks. I still think you will need to crack open your reports and really dive in. What do you think?

Speaker 1: 17:08

Yeah, I mean there's a gap right now even between email and SMS segmentation and personalization, and, like website segmentation and personalization, we have almost no clients that do any sort of you know, I would say, real website personalization in the way that they do email and SMS personalization, and there's sort of like a missing gap there. Maybe there's eight different variations of the email going out, but there's just one variation of the website, and so everybody's going to the same product page, or everybody's going to the same homepage. You know, obviously not Ecom, but HubSpot, with their CMS, allows you to basically have a completely dynamic you know front end website based off of all the CRM data that you have. So, hypothetically, you know somebody who's a prospect of electric could go to the website and interact with an entirely different experience, all the way down to the content and the CTAs that are being shown, versus, you know, a client who comes back to the website. So we could have, you know, 50 different variations of a homepage because of the fact that we're leveraging CRM data to push through personalization onsite.

Speaker 1: 18:19

Just because it's possible, though, doesn't mean we actually do it. It's like it's a pain in the ass to set up and who's going to actually manage it and it's the juice really worth the squeeze there too. But I feel like there's a gap right there in the e-commerce sort of industry right now with website personalization, and I think that might be a little bit further out. But I just you know?

Speaker 2: 18:41

I think you're right and just have you heard? Seen these guys burner page. Just a little vendor plug here.

Speaker 1: 18:48

Burner page yeah.

Speaker 2: 18:50

I just got hip to them and I'm just obsessed. Look, it's not doing what you're describing in terms of connecting the CRM data to website personalization, but it is using AI to update your site on a element level. You know every, you know button, every you know header. So our, our, our peel home site, homepage peelinsightscom, as well as magic dashcom. If you refresh your screens, you'll see a bunch of iterations that I'm testing and it's actually testing it for me.

Speaker 1: 19:22

So I do think look.

Speaker 2: 19:23

I think we're pretty darn close to what you're describing here just connecting that data to a CRM. We're certainly seeing that across larger clouds like Adobe and things like that, but I do wonder I mean it's a fun question to ask at which point does data analysis become just useless and just let the machines handle it? I don't know. As I sit in these quarterly business reviews with our operators, I'm finding that less and less are they focused on what's that next email I can send? And they're really thinking about some of those higher level decisions. What's the next product to launch?

Speaker 2: 20:07

What is going to drive a subscription versus not. What is going to actually increase LTV? Those are the types of questions we're seeing being asked. I do think there's going to be a place for data analysis, but nevertheless, it should be easier.

Speaker 1: 20:21

So, if it's speaking to the e-commerce business owners out there I think both agencies and also brands as well what should they be thinking about in 2024 when it comes to data analysis? I guess, from an agency standpoint, how to leverage something like a magic dash to be able to provide better insights. But if you're a brand, why is now the time that they should be acting on this? What's the risk of sitting on the sidelines in nine months here? They'll not being super intentional with the way that you're doing your analytics.

Speaker 2: 20:59

Well, look, I'd say it's more than ever. We're seeing that if you can't drive a repeat purchase, you're dead. So we're seeing subscriptions and bundles and just driving retention. It's just the most important part of the business right now. So the data that you're working with it has to be cross-dimensional. You have to start looking across not just what is your cohort, for instance, but you have to look across combined cohorts. You have to be looking across your market basket by user type or by customer type. It's these cross-sections that we're finding the most interesting data up here.

Speaker 2: 21:46

So to answer your question, I guess. Why should people be looking at this data? Well, because your ROAS is not going down.

Speaker 1: 21:57

I should say that their ROAS is not going up.

Speaker 2: 21:59

Let me try it again. Why should they be looking at this data? Because your ROAS is not going up, but your LTV can, and you can actually build a profitable business based off of the customers you already have. I mean, look at some of the decisions that we've already seen happen on our platform, just since we've launched Magic Dash, or staggering, I mean right now, it appears to me just the economics do not work for growth-oriented businesses only and that if you cannot drive a repurchase you're just dead in the water.

Speaker 2: 22:35

I mean, what are you seeing on the retention side? Is that in line with what you're finding?

Speaker 1: 22:41

Yeah, I mean the appetite from investors for businesses that are growing at all costs is significantly lower. I also just think people are investing a little bit more wisely into the e-com space. So the attention isn't solely on top line revenue and new customer acquisition growth. When you have only 15 to 20% of those customers actually coming back and reordering again, there's a lot more scrutiny, at least from my friends who are raising right now, who own brands. The diligence process has been a lot more painful than the first time around when it comes to digging into what does it look like after that first purchase is made and a lot of questions both from a data standpoint that they have to dig into with the potential investors around repeat purchase rate, around the LTV, but also just philosophically how do they think about bringing in new customers and retaining them versus just bringing them in? So it's extremely important because the ROAS is only going to get worse and worse on these advertising platforms.

Speaker 1: 23:49

I feel like I mean there was a little bit of a correction as some businesses have gone out of business, so competition has been waning a little bit, because it was sort of like a triple whammy during COVID where you had everybody and their brother creating a website and then going to spend money on Facebook ads. You had a bunch of free money flowing around and then you had people start to return to shopping in person and that sort of happened all under the guise of the the advertising policy changes or privacy policy changes, so it was really like four things all at once. That just caused it to be a total shit show. So competition has pulled back a little bit and we've seen some clients get better performance, but it's stabilized and now it's only gonna start to, I think, get worse and worse over time.

Speaker 2: 24:37

I could agree with you more. I mean, I recently saw a stat that said e-commerce investment had gone down 97% since last year. I think it was something like it went down 80% from the year before. It's minuscule what people are investing. So we know that. We know that it's gonna be tough to attract investors. We also know I mean, if you look at most certainly our clients they're doing a lot of diversification when it comes to the channels that they're hitting. We're seeing a resurgence in B2B or resurgence in retail. We're even seeing like four walls come up.

Speaker 2: 25:17

A lot of people are refocusing their efforts on Amazon as well as Shopify, and so, look, now is the time to calibrate as you go.

Speaker 2: 25:26

Certainly, that's how I feel, and the good news is, as I look back at my last business, we were able to get our net retention rates and, of course, this is a SaaS business, but we were able to get our net retention rates at certain points in the business above 120, 130% on a customer every year, and it just saved us In the tough times. It was those customers that actually stuck around and expanded and really, more than anything, it reminded us to double down on our core. It was, at the end of the day, the best businesses are great at doing one thing and doing it extremely well, and, especially as I look around the e-commerce space, I find that there's a lot of businesses that actually have a harder time doing their second act. And yeah, I wonder if this kind of relook towards retention metrics isn't actually incredibly good for many of the businesses. Maybe we grow a little slower, but ultimately I think it'll provide a lot more staying power.

Speaker 1: 26:28

Yeah, I think there's an article I was reading about how, in times like this, some of the best businesses are actually started, because it's a little bit more challenging and there isn't the best environment necessarily to be able to get away with certain mistakes or overlooking certain things.

Speaker 1: 26:47

But also, I think better actions are being incentivized now, like slower growth, profitable growth.

Speaker 1: 26:54

Versus four years ago you'd be hard pressed to not just focus on growing top line revenue when that's when you were going to get rewarded or that's what you were going to get rewarded for, but doing one thing only and focusing on that for a certain group. I started a new business with my brother after selling the agency that launches in a few weeks here and we had that initial sort of back and forth discussion about that exact topic, because the product we've built can service anyone technically. But my whole spiel was hey, we're only going to target Shopify businesses and we're only going to target these certain types of Shopify businesses, and then also on the website, in the one pager within everything, we're going to be talking to that particular customer because if we just launched a super broad, it does everything for everyone. Even if it did, which I don't believe in to begin with. But even if it did, then you're not able to resonate with anybody. You're going to lose them versus being able to actually go super deep with that one particular customer archetype.

Speaker 1: 28:07

Yeah and where did you land? Where Only Shopify, only Shopify. And the talk track there is we'll look at vertical expansion in the future. So maybe after that it's restaurants, or maybe after that it's a certain type of industry, it's an HR product. So taking a verticalized approach to growth, I think, makes the most sense, and you also see this even at Shopify, where five years ago they bucketed mostly everything into just GMV. They didn't really care is it food and Bev, is it skincare, is it fashion?

Speaker 1: 28:46

But as they've gone more up market and they're starting to run into certain types of verticals that require a verticalization approach alcohol being one of them that we're on the front lines with them on withdrinkscom.

Speaker 1: 29:00

But then automotive is another one there's certain industries where they're just wildly different and they have totally different pain points and totally different networks and also let's just call them influencers or thought leaders in that space, and so it requires a sales team that is solely focused on alcohol, or sales team that is solely focused on automotive, because if you just roll out somebody who's in that 25 to 125 GMV category, for example, they're gonna get run over by the automotive exec who's been in the business for 30 years and you don't understand how skews work within the automobile industry or something.

Speaker 1: 29:40

Personally, I'm a big believer in just the verticalization approach to building a business, but also scaling it as well. It's cool. But so, taking a step back though, one last question I had for you, which doesn't necessarily relate to appeal per se, but what has it been like stepping into a role where it isn't like sort of your brainchild, because obviously with Splash that was accepted by you, conceived by you, and you were building that for 10 years. And now you're stepping in and helping. I don't know if there's a founder or multiple founders appeal, but you're helping a team sort of realize what originally was their vision. What has that evolution been like for you?

Speaker 2: 30:28

Yeah, it's been hard and it's been fun, but it's been hard. I have to constantly remind myself that I am assisting and I'm kind of helping the founder play out his vision while simultaneously holding that rope that I'm here to bring value. And it's been a while. Yeah, to your point. When I was at Splash, I was Splash. Anyone who stepped into the Splash office would be like oh man, this is just Ben's brain. I always felt a lot of pride in that.

Speaker 2: 31:06

But I'll tell you what I'm feeling a lot of pride in the relationship that I've built with our founder, a guy named Nico. He's an incredible dude. He's an engineer by background. He also does all the designs for this product and he happens to be like a data statistician it's a wild human. So the guy is bringing just a tremendous amount of value and just understands the market and I really appreciate the way he has pushed me. He's called me out several times in areas where I felt like he's felt like I hadn't stepped up. And I'll tell you what.

Speaker 2: 31:46

Like man, as a former CEO, I feel I eat some humble pie. You know, I can't tell you how many times I was upset at someone who wasn't ramping fast enough or, you know, yelled at a product manager for, you know, not totally understanding my vision right and being on the other end of this gosh, it's hard. It's hard to get hip to someone else's vision and get ramped and get smart and make good decisions. It's hard. Simultaneously, though, yeah, he's he's also really trusted me in areas where he's felt like I had broad expertise, and so I can't, I just love the relationship. I'm feeling a lot of that we're seeing each other and that we're, you know, helping each other grow.

Speaker 1: 32:31

Yeah.

Speaker 2: 32:32

And look just to be real, it's not an easy business that we're in. You mentioned it. This is a really competitive space. We've got a super differentiated product for those who know like it seemed and I've just entered the business but anybody who knows about Peele is like, oh you guys do it right, and anyone who uses Peele just loves it. It's a higher retention product. But because of all the noise, because of what I'll call like commoditization of, you know, data, and because I think of just general aversion to being data driven, it makes it into a pretty challenging business to grow in, but hopefully not for long. I think a lot of the way that we're approaching the product, the way we're revamping the go to market, I gotta believe it's going to hit and people are going to really see how we're different. And so you know, being in the trenches with someone else is a lot more fun, and so I'm happy that I have him as a partner here and I'm appreciative of his trust.

Speaker 1: 33:31

Yeah, I am empathize with the brands that have to make decisions around analytics platform because, you know, unless you're really in the nitty gritty of like the business intelligence world or a data analyst, it's hard to understand. You know the differences between these platforms when everybody is saying the same thing at a surface level and that's like actually digging in or, you know, getting within the tool and testing them out, trying it out. But you know, more often than not you don't know until you know. And we tried a you know product that shall not be mentioned, about a year and a half ago to do basically centralization of like all of our agency reporting into dashboards that we could easily clone to be able to have at scale, you know, 60 clients all with the same dashboards, same metrics for our team, no manual pulling or reporting from disparate tools or anything like that.

Speaker 1: 34:26

And you know just, unfortunately, reality was not what was sold per se. So we ended up with, you know, an expensive tool set that didn't actually free up our team to spend more time on insights and we still had to do a lot of that. You know, reporting, pulling and stuff like that. So it's until you get going, it's, it's, it's very difficult, you know, even for somebody who's supposed to know. You know what's going on within the Shopify ecosystem.

Speaker 2: 34:54

I mean, I think he nailed it it's it's the reason I'm so adamant about kind of getting people into trials and can't.

Speaker 1: 35:01

It can't only expanding trials.

Speaker 2: 35:02

I mean, one of our new moves is just especially if you're bringing an agency, extending the trial for really as long as it takes, you know, upwards of months if necessary just making sure that people actually get the value because, as you pointed out, it's, it's really annoying when you get in a product and it doesn't do what you need, especially if you spend time on it, and it's really hard to figure that out in advance, and not for nothing you can't it's not like you can bring in demo data.

Speaker 2: 35:31

You got to do with the real stuff. You know demo data is not very interesting at all and more often than not the way that you've organized your data is different than others. But I will say you know, obviously I'm biased I've been blown away at how effective these trials are because of the way they've architected the software. It's just as such a simple architecture that is so powerful and allows you to figure out very fast if it's the right data or the wrong data.

Speaker 2: 35:58

So that's been, that's, that's worked to our advantage. Yeah, man, I I hear you, it is. It is not easy figuring out your data system as a operator.

Speaker 1: 36:09

No, maybe one day we'll offer that as a service.

Speaker 2: 36:13

Truly Well. What do you? What do you think? What's what it's just? It's just going to turn the microphone around on you. What do you think is missing as a retention marketer, the retention marketing agency? What are the three, or even just one, killer features that you would say if that product is delivering on buying?

Speaker 1: 36:34

So I still think there is a lot of like. You know, everybody wants to talk about one to one personalization. I don't. I don't think that like exists at all yet and there's still so much gray area around that first to second order. How do you maximize the percentage of customers that are coming back and placing that second order? But that's the most important, because if you get that second order you know it's beginning to become habit forming you always have the most drop off from first to second order. So if you can, you know, reduce that drop off, then it's going to just trickle out into the rest of your, you know, your second to third order, your third to fourth order, and so on.

Speaker 1: 37:18

So for me, let's just focus on one thing in particular, and that's how do we bump up that first to second order rate? I don't think there's a great way to test into that cohort like in any sort of way. That's strategic, where let's say, hypothetically, you know we're offering a free gift to everyone on their second order. Well, how do we, you know, split that off so that we're only communicating it to half of the customer group and then actually see the results? And does that improve retention and increase LTV.

Speaker 1: 37:51

So I don't know what the actual end product would be, but any solution that actually helps with that that first to second order and is able to, you know, separate out between the one shot customers and the subscription customers, because there's there's a gap right now where you have analytics tools, that'll be like oh you know, on average, people will come back and place an order, their second order in in 24.3 days or whatever. It's like okay, great. But you know what if the person in place their first order spent $500? Or maybe they have like a family of six that they're feeding and you have no idea? So, like, how do you take into account all these different variables versus having a one size fits all? You know, first to second order, please come back and buy from us. That's the. That's the biggest thing in focus for us, just as an agency as a whole.

Speaker 2: 38:38

Beautiful. Yeah, it couldn't be more. It's really. It's that leap from one time purchaser to repeat. That's just like the holy grail.

Speaker 1: 38:50

Yeah.

Speaker 2: 38:50

And yeah, we're. It's what we're sickening our AI's on. You get it. We're highly focused on how do you get them from OTP to many TP.

Speaker 1: 39:03

Yeah, and if you, if you crack that, then I mean you'll be set. So oh, thank you so much for joining us. Before we hop off here, though, can you let everybody know where they can find you online?

Speaker 2: 39:18

Yeah, go check out magic dashcom. That's our new product, it's live, it's pretty darn good and, as I mentioned on this podcast, we'd be happy to extend your trial so you can really get in there and feel it out. And yeah, I'm on LinkedIn. So if you have any questions or you want that hookup, just hit me up on LinkedIn. I'm Ben Hindman. H-i-n-d-m-a-n.

Speaker 1: 39:41

Awesome. Well, thank you for joining us. As always, for everybody listening, this is Brandon Amoroso. You can find me at BrandonAmorosocom and electricmarketingcom, and we will see you next time.