How can CPG startups tackle challenges related to leveraging data and finding insights? In this episode, host Ian Cook sits down with Jessi Freitag, an expert in CPG productivity and operations and the host of the Startup CPG Podcast. They discuss simple ways that CPG founders can start to glean insights from data to support their immediate priorities.
How can CPG startups tackle challenges related to leveraging data and finding insights? In this episode, host Ian Cook sits down with Jessi Freitag, an expert in CPG productivity and operations and the host of the Startup CPG Podcast. They discuss simple ways that CPG founders can start to glean insights from data to support their immediate priorities. Jessi shares examples of how CPG companies can access useful data for free and leverage data when building relationships with retailers.
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Key Quotes:
“I have seen where you pay for the data, but then you don't have bandwidth to dig into it and to use it. So, then you're just paying thousands of dollars per month for data, but you don't actually have anyone who has time to look at it or who knows how to manipulate it in Excel. That's a consideration as well, are you going to use it if you buy it? Just having it there might not be worth the investment.”
“Instacart has partnered with ChatGPT and artificial intelligence. And so they have an add on now on Ask Instacart where you can ask Instacart questions like, what do people buy with this? Or you can use ChatGPT to say make me a recipe for this and you can see what brands the AI recommends. I think that's really interesting data too, that you can now tap into for free and understand how other people are shopping in a category that may be similar to yours.”
“Can you plan ahead for where you think you might get chargebacks and those pieces? I think that's another critical piece that's really important to watch because it's easy to overbuy inventory or over plan and then all your cash is tied up and nobody's paying you back because it hasn't been sold in and it hasn't been invoiced.”
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Show Timestamps:
(01:50) Jessi’s background
(02:55) How did Jessi learn about the CPG space?
(04:20) Jessi’s approach to data in her early days in CPG
(06:00) What does the initial data strategy look like for CPG founders?
(07:40) When do brands start purchasing data?
(09:45) How important is access to customizable, specific data?
(11:30) Transparency with competitors
(13:27) Watching the cash cycle
(15:30) Starting simply in Excel
(18:30) Challenges understanding the impact of market spend
(20:46) Gaining an understanding of performance within a store
(27:40) Using data to get into retailers
(29:55) Leveraging community to learn about data
(33:40) Example of increasing sales through data
(35:35) Proactively using data to determine your level of success in a store
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Sponsor:
This podcast is proudly sponsored by Seek, the leader in cloud-based creation and delivery of industry-focused insights.
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Links:
Connect with Jessi Freitag on LinkedIn
Startup CPG Podcast
Connect with Host, Ian Cook, on LinkedIn
Follow Seek on LinkedIn
Ian Cook: [00:00:00] Some days, it feels like we're drowning in data, but data isn't knowledge. Data without context or the expertise to understand it is just something eating up storage space in your warehouse. That's where being insights driven comes in. Insights driven organizations focus on generating actionable insights rather than just collecting and munging data.
Insights drive better decisions. Welcome to the Insights Factory.
Welcome to the insights factory. My name's Ian Cook. I'm the CTO at Seek and your host today. Joining me is Jesse Freitag, who's actually the host of the startup CPG, as well as being a workflow and productivity consultant on her own. Thank you so much for joining me, Jesse.
Jessi Freitag: Yeah. Thanks for having me. It's really great to be here.
Excited to be on your show.
Ian Cook: Well, thanks. First, I want to start by saying congratulations. Your show Startup [00:01:00] CPG just hit 100 episodes. That's got to feel like a decent milestone in this.
Jessi Freitag: Yes, yeah, absolutely. I feel so grateful to the team at StartupCBG. I've been with StartupCBG since, I think the Slack community for StartupCBG has 14, 000 people now, and when I joined, there was around 3, 000, and that was less than two years ago.
And so, to see that kind of growth, and my piece is just the podcast, and so I feel very Proud and grateful that we've gotten the podcast to 100 episodes, but it's just a really cool community. We're supporting emerging CPG brands within food and beverage and household and all these different areas. And so to just see the interest and see that the knowledge that we're sharing is helping small brands.
Succeed and, you know, get the information they need. It's just, it's really fun. And I get to meet so many awesome people. So it's really cool.
Ian Cook: That's fantastic. I'm a member of the Slack community. I've paid attention to it. It's been terrific to also learn. So as, uh, our [00:02:00] listeners know, I repeated most episodes as I'm.
Fairly new to the CPG area. I come to it from a machine learning AI software development background, and this is a totally new industry for me. So I asked around, a lot of people said yours is the podcast to listen to, to start learning. But it sounds like you were you relatively new to CPG when you joined, or had you had time and experience in the CPG world before you started the podcast?
Jessi Freitag: Yeah, first of all, that's so kind that people referred you to the show. I love that. That's really amazing to hear. So I, this is, I think my fifth year within CPG and my background has been in operations across a lot of different industries. So I entered CPG, I was actually working in sportswear at Adidas and I got the opportunity to be the first hire at a CPG company that had just received some funding and was going through a restructure and getting ready for some national launches.
And so I was with that brand and energy bar brand [00:03:00] from, you know, being employee kind of toothed. There was two of us hired at the same time, two or three. through up until about 30 employees and we did our own manufacturing. So over, you know, two and a half years, we essentially went from 10 stores to 2000.
We built out our own manufacturing facility. Um, we onboarded with Kehi and UNFI nationally and all these different experiences. So it was a really, it was a crash course in CPG over a really short period of time and it was really fun. I was going
Ian Cook: to ask, did you learn simply trial by fire or is there somewhere that you turned to learn the CPG world?
Maybe just the people around you.
Jessi Freitag: It was a lot of trial by fire for sure. And then finding Startup CPG was actually, you know, before I came to the podcast host that I was in the community asking questions saying, Hey, where are people getting sunflower seeds right now? Or how are people navigating this current challenge and the podcast.[00:04:00]
So yeah, I was, I was in the community connecting with people. I'm also someone that I had another podcast first for fun. I'm someone that's always reaching out to people and saying, Hey, can we chat? Can we talk? And so I essentially just started recording those conversations during the pandemic. So that's a lot of how I navigated CPG early on was just, you know, Calling other people, even other energy bar companies and competitors and saying, Hey, I know we're technically competitors, but can I ask how you navigated this?
And almost always people are like, Oh yeah, there's room for all of us. We're all trying to make better food and make a better food space. So let's talk. And I love how collaborative it is. That's
Ian Cook: fantastic. You don't normally hear that from a lot of competitors, especially in the world I came from, which was software development is you don't want anybody.
Like peeking over your shoulder or looking over the fence to see what's in your area. Obviously our show is a great deal about data. Was data a really big part of your early days as the CPG?
Jessi Freitag: Yes. Yeah, there was a lot. So my focus was operations and marketing and my focus today. Now I [00:05:00] work with brands on operations.
So I'll essentially act as their outsourced operations department for CPG companies. So handling everything from co manufacturing to sourcing to warehousing and those kind of pieces. So I still deal with these things today. And in when I was Actually, you know, running the startup departments myself, a lot of the data came down to, you know, forecasting of what are we, how much ingredients do you order, especially when you're not an established brand and you don't know which retailers are going to pick you up.
You may have submitted to five different retailers and they all may say yes at the same time, or they all may say no at the same time, and you needed to have purchased raw materials before you had any of those decisions. So a lot of it came down to trying to do the best with the data that you have from.
Small independent stores and trying to turn that into, you know, to make some longer term projections using really rough numbers and estimates for raw materials of, okay, this is what I think we're going to use, you know, maybe I'll contract buy enough of that so we don't [00:06:00] run out of this ingredient, but I'm going to really hedge against it and then also go, you know, starting to use, uh, we did a lot of in store demos.
So, tracking demo, uh, data from demos on our own, and then eventually pairing that with, you know, purchase data from distributors and from reports like SPINs and trying to figure out how to actionably use that data.
Ian Cook: Well, you've already anticipated the next sort of question I've got, which is you're working with various sized retailers, tons of different places to, um, Place your product.
Gathering all that data must be a considerable effort, but you've mentioned you can purchase some data, some data you collect when you do demos. Is a good portion of that early days as a CPG company figuring out how to collect that data or is it just a side part of everything else that has to go on and suddenly you realize, well, this is the data I have, so I have to make the best of it.
Jessi Freitag: Yeah, it's, it's tough, and it depends on the business. Sometimes I see, sometimes, you know, you're digging into the data in a reactive way, like a [00:07:00] store drops you, and then you're like, wait, why? What happened? And then you're looking, you're trying to ask them for sell through reports, and then they're like, look, here's your units per store per week, and you were too low compared to everybody else.
So that's a, not a great scenario where you're looking at the data a little bit too late. But a lot of it is trying to find out and build into because you've sold such a limited budget and such limited resources, you want to make sure your dollars are going to the right place. So if you do a demo, making sure that that person tracked how many units there were before, how many after, and then logging that somewhere, even if it's in a basic spreadsheet, a lot of this is so.
not fancy. It's just so basic, but it is data and being able to track that and understand like, okay, this demo rep is performing really well, or this store seems to respond really well to demos and having that kind of information is super helpful. It can be hard to track though, because when you're, you know, one or five people, there's just not enough time in the day.
So even the most. Basic notes can go a [00:08:00] long way for just trying to understand what's going on. So a lot of it's just kind of trying to cobble together whatever you can and then use that to make the next best decision.
Ian Cook: Is that the majority of the data you have at an early stage? Is there? a point at which you are big enough now that you want to go out and start purchasing data.
Is that sort of a, uh, a knowable milestone or are you from day one, like you mentioned, a couple of companies where you might buy data also saying, look, I've got to set aside some money because I need to start having that data feed come in.
Jessi Freitag: Yeah, that's, it depends on the company where I see this kind of inflection point happened for.
The brand that I was at, we eventually purchased Spins data when we reached, when we launched nationally with Sprouts. And when we were nationally distributed with UNFI and Kahey, it was like, okay, it makes sense to purchase this Spins data. But there's also some, you know, that, that might not be the right inflection point for some brands.
It is really expensive and it depends on what expenses you can afford. There are opportunities like within Startup [00:09:00] CPG, so once a week, we have our data genius, Candice, will post, she'll choose a category, and she'll break down like, okay, here's the units per store per week for this category, here's some of the biggest competitors, and she'll do a little overview.
And then also there, you know, we'll work with partners like Nielsen, who will provide like three, like, visor reports, which will just kind of give you a, a small breakdown of your category. And sometimes that's enough to go on without having to purchase the big amount of data. So for those that are in the Slack community, that can be a good way to get some access to that data without having to pay for it yet.
And also understand, I also have seen where you pay for the data, but then you don't have bandwidth to dig into it and to use it. So then you're just paying. You know, thousands of dollars per month for data, but you don't actually have anyone who has time to look at it or who knows how to manipulate it in Excel.
And so that's a consideration as well as do you, are you going to use it? If you buy it, just having it, you know, there might not be worth the
Ian Cook: investment. That is a huge part of what [00:10:00] we at Seek are challenging and working on is precisely that as data becomes very expensive. Once it's there, it could be rich.
It could be fantastic, but you've got to spend time figuring that out. It was interesting. You mentioned that, um, some places like, uh, I think you said Nielsen will provide some reports. Is it more common to try to get those reports because that already has the prebaked kind of information, or do you find that it's still, even with that, you still need more customized.
Reporting and you need more specific data.
Jessi Freitag: Well, and it depends on what you're trying to accomplish. If you're trying to understand, like, if you've sold into a big retailer and you're trying to track your own performance and understand which stores are performing well so that you know where to demo or where to pull different levers, then you're trying to look at really specific information as far as like, where, what am I selling?
What are my units per store for a week? But if you're trying to understand generally, like, okay, I'm ready to pitch to this retailer. How, you know, what is their expectations of units per store per week, [00:11:00] then maybe you don't need as, you know, as specific of information, maybe then getting some category information will help you build your pitch to say, okay, here's how at this independent retailer, I've achieved this Many units per store per week.
It looks like that's what your, you know, my competitors are doing at your store. Here's how we can fit in. So some, it depends on what you're trying to accomplish. And sometimes more general data can kind of get you where you're needing to go. That's
Ian Cook: something I find just really fascinating about this industry is, is places I have been before.
You don't see data about your competitors. You don't see how things are going in general. You've got your data and you have a little bit of leak and you're trying to. Poke at other companies to figure out exactly. All right. How many users do you have? How many monthly active users do you have? How many minutes do they spend with your tool?
But in this case, you're saying I can get some data and I can see that there's some competitor to, um, I believe you said you had a, uh, a bar of some kind in your early one. You can see how others are doing because you can see across the category, but that means everybody can then see how you're doing that just seems like a [00:12:00] really hard position to be in when you're talking with the retailers.
Is it, or am I over complicating things? Yeah,
Jessi Freitag: well, I think it's, I mean, I actually think the transparency can kind of be helpful just so you kind of understand where you're at. And also it can help you position of understanding, like, you know, if you're selling cookies, for example, your, your, your units per store per week, you're, you're not going to want to position yourself as being the competitor to Oreo.
Like, you know, the Mondelēz has, has that down and has a different marketing budget than, than you're going to have. So, You know, you can, you can help determine like, okay, here, here are the people that are closer in my category that I'm actually want to position myself against and where I think I can provide value.
And so that can be helpful because it all comes, there are 40, 000 items at the average grocery store. And so the grocery store can then determine, you know, That way everyone kind of knows where they sit and it all comes down to the basic, you know, the unit economics of how the store is going to make money on your [00:13:00] product.
So I think it's helpful that it's so transparent, but it is, it is also intimidating because a lot of industries, you're not seeing that kind of data. And if you don't buy access to that data, you might not have it. Or with smaller stores, you can also ask your, you know, your account rep or someone at the store to sometimes pull that data for you.
And oftentimes they will, and that can be an inexpensive way to get some understanding of what's going on as well. Oh, that's
Ian Cook: great. That sounds like a very relationship based kind of situation is, you know, just somebody who's willing to be helpful because they're trying to sell. You're trying to sell.
It's better off if everybody's, you know, got a higher velocity. But speaking about velocity, are there some key? Pieces of information, some key metrics that a young startup CPG or even CPGs that you've seen in a little bit larger, just check all the time. Velocity, the units per week per store is clearly one of them, but what else are they looking at to sort of make that daily or weekly decision about how they're doing?
Jessi Freitag: Yeah, the, the velocity is super [00:14:00] important. I would also say that it's kind of data adjacent maybe, but just watching and understanding the cash to cash cycle in the business and being able to track all of those pieces. So, let's say for example, if you're working with a co manufacturer and you're, they have a 12 week lead time for a production run, you may have to place a 50% deposit for that production run 12 weeks before.
Then you got to wait 12 weeks to get your inventory. Then you got to get it to the warehouse. Then it goes to the distributor. Then it gets to the store and that it may take the distributor, you know, three months to pay you. Then they may not pay you all the way. There may be chargebacks that you then may or may not need to dispute.
So you may be looking at Six months, and you had 12 weeks from when you put 50% of the cash out to the co manufacturer. And so really understanding where your cash is at different points in the cycle, and can you make it to the next cycle? Can you plan ahead for where you think you might get chargebacks and those pieces?
I [00:15:00] think that's another critical piece that's really important to watch because it's easy to kind of overbuy inventory or overplan, and then all your cash is tied up and nobody's paying you back because it hasn't been... sold in and it hasn't been invoiced. And so, again, not quite the same as velocity data, but I think it's another area that's super important to track and understand for your business to be viable long term and to understand when you might need to do fundraising or when you might need to pull other levers and work with your co manufacturer to reduce costs or more of those type of things.
Ian Cook: You, um, mentioned earlier that some of this stuff is still a little bit rudimentary. Is, is that kind of work still being done and tracked in Excel? Or are people sort of adopting now more sophisticated accounting tools? And, and, or is this again, um, you know, in my head there's a Early days is a logbook and two people trying to sell something out of the back of a truck, and then there's sort of steps as you get more mature.
Is high end accounting tools something that comes much [00:16:00] later, or are people starting to get more into that kind of, um, sophisticated tooling earlier
Jessi Freitag: on? I think a lot of this can definitely be done in Excel and Google Sheets, and that's a lot of times what I see is lots of, lots of, you know, Semi complex Google Sheets can knock this out.
You know, you, there are inventory planning softwares that are coming out that are a little bit more affordable and that can help with some of this. But a lot of it, it doesn't have to be complicated. It sounds complicated, but it can just be some rough notes and templates that you create to track some of these pieces.
And that can, a lot of times, get you as far as you need to go. It, I think part of it is just. the confidence to write down some numbers. I run into a lot of founders that are like, I don't, I don't know how to forecast. And I'm like, I, you, you, you probably do like, you know, what did you say? Like, let's just look at what, let's just look at it.
Let's write down some numbers. And I think there's some intimidation when it comes around data and Excel. And a lot of times it's, it's very basic, very formulas that people can, you know, Once you do it, it actually feels really achievable, but it [00:17:00] can be intimidating. Understandably, I've, I've been there and you're like, I don't, I don't know what's going to happen, but you usually know more than you think about your, your business and can, once you put it to paper.
Ian Cook: That intimidation rolls possibly into just data in general. So when you're intimidated a little bit by data. Are you hoping that someone can bring kind of already made insights to you to say, these are the types of things that are going on. We know what kind of questions you're asking. This would be more helpful.
Or do you find that most people really do want the raw data and be able to, to work with it themselves?
Jessi Freitag: Usually people don't want the raw data, I would say. And also, my husband is a, is in finance and works, has worked in big, big CPG and nobody ever wants to see the raw data that he loves to look at all day.
Um, everybody wants the, everybody wants the insights. And so even like with spins as an example, I remember getting a report and being like, I don't know what to do with all of this information. Like, I don't know how to [00:18:00] look at it. And then, thankfully, someone from the account team sent a little PowerPoint.
It was like, here's how you can pull this information. Here's how you stack up to your competitors. And I was like, oh, this is what I can do with it. Like, this is actionable information. I can screenshot this and put it in a pitch deck. Or I can use this to understand how I plan our demos. Like, those, those stores are performing really well.
I'm going to send demo people to those stores. Those stores are... Not performing well, etc. So, I think usually people want the insights. It's just how do you get from the raw data to the insights if you don't have, you know, always a big enough team to help dive into those things.
Ian Cook: That is a huge question.
When you're talking to these companies and just think back about your own experience, has there been data that you've wanted that's just been very hard to get or in terms of things that you would have loved to have known but couldn't find somebody to sell it or it was just too hard for you to collect yourself?
Jessi Freitag: I think one, one area that can be [00:19:00] really tough for data, especially when you're in retail, is understanding your marketing spend and the lift that it has on stores. And, you know, you, you want to have this magic connection that, that shows like when you, when someone saw an Instagram ad and then that made them go to the fresh market.
And, you know, that, that, that level of data, just, you know, you can track some, you can track funnels online and then you can track some, you know. Uh, retail experience. So that part is really tough. I've been excited to see the emergence of tools like Social Nature and Aisle for some of these marketing areas.
So Social Nature, they have a community of like over a million shoppers, and they basically give physical coupons to shoppers to go try a product in store. And then there's a pre and post purchase survey. I participate in their community as a member and have discovered brands through it. I just think it's fascinating.
I love seeing their reports and everything because you actually then know what happened at the store level because someone completed a survey and that data [00:20:00] can be so hard to get. And also with like Aisle, which is where you're getting a text saying, if you pick up, if you purchase this product in store, Text us a receipt, and we're gonna Venmo you, magically, the money back.
And it's really cool, and you, then you get data of which store did the person go to, what else was in their cart, you know, what else did they check out and buy with your product. Maybe that helps your merchandising decision, so. Some tools are emerging around this, like helping understand people at retail.
Cause retail is just a little bit more archaic as far as data compared to when you're selling DTC on your website and those kinds of things. So I've been excited by tools like that. And I think, I hope to see more of that. I w I would love to have more things like that to be able to look at and understand how people are, how your marketing efforts are driving retail
Ian Cook: traffic.
So a lot of that. Sort of cause and effect. Did this actually result in an action? But also you're talking a lot about the behavior in the store. What is it I wanted to see? What could I have [00:21:00] bought together? What kind of affinities do I have? What kind of relationships am I thinking about in those types of areas?
Is that something that every CPG is thinking from day one? Or is this a, you know, benefit of having said like, all right, I'm in enough stores. Now I need to start working a little bit more on optimizing how much I sell per store.
Jessi Freitag: Mhm. I think the earlier that you can think about that is, is really helpful.
Just, and that all comes down to how you show up at shelf, understanding how people purchase your product. And that doesn't mean you have to have access to really sophisticated data that can be as basic as just, you know, looking at something like Instacart in your category and looking at Checking out, you know, if you're like, if you have a product, again, to use like the cookie example, you're selling a Better For You cookie, look up the Better For You cookies at a store that you're trying to get to on Instacart, and what does Instacart suggest that you should also buy with it?
What are the price points? What are, are there deals on anything? And so some of it can be, you know, um, I think the [00:22:00] sooner that you can look at that kind of data and understand who your competitors are, what people are buying with you and using tools that are, you know, free, anybody can just log in and look at Instacart for any store, which is a really cool way to just kind of understand what's going on.
Ian Cook: I love that. I had not thought about directly applying that. I know I personally enjoy when I go to say Amazon, the, what are other people buying? Who bought this? Now, of course, with the size and scope of Amazon, they could be. very, very different types of people doing it. But like you said, buying some better for you cookies or then along with putting together some health items into your cart, there's starting to be suggestions that you're kind of using what other people have put time and effort into figuring out and Instacart's kind of giving you a little bit of a window into where your product may sit with other people and with the things that they, they kind of buy.
Jessi Freitag: Yeah. And to add on to that. That's on Instacart because this is something I'm fascinated by with Instacart has partnered with ChatGPT and Artificial Intelligence and [00:23:00] so they have a an add on now on Ask Instacart where you can ask Instacart like questions like what do people buy with this or you can use ChatGPT to say make me a recipe for this and you can see what Brands, the AI recommends, and that's, I think that's really interesting data too, to, that you can now tap into for free and understand how other people are shopping in a category that may be similar to yours.
Ian Cook: That's a fantastic piece of, uh, recommendation for those CPGs that are looking out for, or out there looking for how to associate their brand with something else or what they're selling with others. Obviously, you've had the opportunity to talk to a lot of CPGs, not only through the podcast, but through the work you do being a consultant for workflow and productivity.
Are there things that you routinely say to CPGs to pay attention to in data or routine areas that they come up against that you are advising them on? Some commonalities in the area of data and their data needs.
Jessi Freitag: Yeah. One of the first things that I'll look at, especially if someone is trying [00:24:00] to understand the breakdown of their per unit costs.
So their co manufacturer may give them, okay, this is your price per unit. So the first thing I'm going to want to Understand and may work with them to help gather the information is okay. How much of that is labor? How much is raw materials? What are the different components going into that? Can we get some transparency from the co manufacturer or can we build our own model to kind of understand where the pieces are?
So then we at least know what the different levers are and also starting to ask like, okay, as we scale, what is this going to look at? You know, what are, what is your forecast for down the road? If right now you're ordering the minimum order quantity from the manufacturer, we're not maximizing their, their quantities of scale because we're at their minimum order quantity.
So how can we get out of that to the next stage? How long is that going to take and trying to. Build some forecasting there. And then also understanding, like I said, that like cash to cash cycle, like if we're going to work together and be ordering, you know, how [00:25:00] much cash do you have? Do you have enough cash to place down payments at manufacturers to order raw materials if we're responsible for that?
And if they're not familiar with that. A lot of times I recommend people, if people aren't familiar with the good food CFO, um, Sarah Delavan, she has a really awesome community and some very affordable, like self paced courses to build out your like profit and loss and build out some cost estimators. And that can be a really great start for brands to kind of help build out the whole picture so that I can effectively help them within the operations field.
Ian Cook: That's great. Do you find that these companies are eventually hiring people to work on the data, or is this a skill that the people who are there just end up picking up out of pure need? As you said, not everybody wants to
Jessi Freitag: look at the raw data. I see, I see a mix. And sometimes, you know, there's a lot more, there's a lot more founders that have.
Some familiarity with data. People are getting more comfortable with data and will come in and they'll have a background from big CPG or just a big company and they'll just be more familiar [00:26:00] with the data. They'll just need to learn the nuance of CPG, but, so they'll be able to kind of pick it up.
Sometimes people are bringing in analysts or they're working with like a broker or a consultant or a fractional CFO to help pull some of these analytics. So it's, it's really a mix and it depends on the right fit for the business. If you're someone that, you know, is not intimidated by data and wants to learn about it, I think it's, You know, there's resources and tools out there to kind of pick some of it up and learn from other people so that I think, you know, to not be intimidated by data is just a great skill to have in general, even though you might not be the one eventually pulling all the insights.
If you kind of know enough to be able to know what, what's right, what's wrong, what's useful, that can be super, super helpful as you grow.
Ian Cook: We talk a lot, especially at my company, about CPG as a large scale thing, but one of the things I'm interested in is that there are subgroups, obviously, within that, there are different types of categories, and there's food, and there's non consumables, and lots of different things.
Have you seen that there are [00:27:00] differences in... For lack of a better word, maturity, we're using data among these groups. Do some groups come in and say, you know, we've got a lot locked down and we just need help getting to the next level. And another group tends to come in and say, this is totally new to us.
Maybe it doesn't even break down by categories. Maybe it's a different type of group.
Jessi Freitag: Yeah, that's a, that's an interesting question. And I think some of it comes down to maybe less by, I'm sure there's differences between categories, but also as far as, you know, units, uh, like the MSRP, something that's a lower cost and going to be used.
purchase more frequently, you maybe are going to need to understand the data quicker for like a beverage that's going to be at a quick stop. Like that's going to be high turn going, you know, going to be moving through a lot. If you're selling a baking mix that retails for, you know, 9 a box, people aren't purchasing those at the same rate as beverages.
So you're still going to need to understand your data, but something like beverage, I feel like a lot of times just has. [00:28:00] It's such a high velocity oftentimes that you're trying to achieve that you might need to dig into the data faster to just understand what's going on. But I would say across a lot of the categories, we do see brands really using the data.
Like, uh, one of the brands, uh, that comes to mind, I think of Toast It. They make, uh, frozen arepas. Uh, Cocoa and Mafé are the founders there. And they, they're really good at digging into the data around. They came from some data analytics background and. They use their data from their like D2C launch to then pitch to some smaller retailers.
Then they took the retailer data they got from the smaller retail to then pitch to Publix. And they got into Publix as a very small brand. And so I think depending, you know, on how, you know, on how you decide to use the data, you can, you can get pretty creative within which in whatever category you fall into.
Would it be
Ian Cook: wrong to say that that group found their ability to use data as a differentiator or a strategic advantage for them?
Jessi Freitag: I think so. And in that case, and I think [00:29:00] brands that do figure that out are able to really understand better. I also think of like Shameless Pets, for example, um, uh, James Bellow, the founder, they're all used to work at Target.
So he had some great Understanding of how Target worked. And so they used a very strategic approach of going into seasonal end caps at Target first, rather than trying to sell in and be a permanent item, because they're just like, we just don't know what that's going to look like long term, what the investment is.
If we can go in and be a seasonal end cap, we can gain really great data. Specific in and out of store date, and then we can use that to build our model for a national launch. And so I think founders that are being really smart about gathering bits of data and then using it in really precise ways are definitely, that's a strategic advantage.
Ian Cook: That's a really interesting point. One of the things that we talk a lot about, and internally again, is this idea that there's the people who know how to use the data and I can do a lot with data, but I don't have the domain experience. expertise. And it sounds like that case, somebody had the domain [00:30:00] expertise and thought, you know, what, this is a way to get in and be present without having to commit to a full presence.
That's a differentiator for us. And it's a way to start learning and growing a bit more when you're working with these companies. Uh, there is there still that kind of separation between the expertise and the data and where you see that growing together? Are they just all learning on the job and they just all learn together or will a small company try to find someone who either has that expertise or perhaps expertise with the data?
Jessi Freitag: Yeah, that's, that's a good question. I think I definitely see people growing into the data. And I also think this is a great place where community can be leveraged, whether it's a community like Startup CPG. Or there's smaller communities like there's Project Potluck or there's like Female Food Foundry on Facebook.
Some of these like smaller communities as well. Any community aspect where you can kind of see, just kind of pay attention to how other people are using data, schedule calls with people that, you know, that are in similar categories and say, Hey, what are [00:31:00] you doing this? Can you show me the report that you use?
That can be a way to kind of upskill yourself faster than maybe normal. And I think a lot of more, a lot more brands are talking to each other. So I think that that. That gap is getting bridged faster. Also like I said, when you bring in like a broker or a consultant or someone on a fractional basis, sometimes you're seeing the reports that they may pull and then, you know, you may not work with them forever because they're on a fractional basis, but then being able to understand, okay, we hired this broker, they had this cool report.
Now how can we create? Recreate it. So learning and building from experts as you go can sometimes be a good strategy. And that's what we see a lot of times in operations too. Someone will hire someone to help set up how they're going to run the operations and then they can hire someone with less expertise to run with it.
And with data, I think, you know, doing something similar can be effective.
Ian Cook: A lot of times when we bring in a lot of data, as you mentioned, you're kind of awash in all of this information. How do we make sure, or how, what advice would you give to these CPGs to [00:32:00] figure out what is just data that is out there and what is truly actionable?
Like, how do they find the things that they can say, ah, now I have something that I can go tell to the retailer or go back to the co manufacturer or go back to my own team on marketing?
Jessi Freitag: Yeah, and that, that a lot of times Prioritization comes down to first deciding what your priorities are and prioritizing, which prioritization, and this is not to understate how difficult prioritizing are, is at a startup.
You have a million things to do and you have limited time and just a few people. So prioritizing is really hard. But if you are deciding like, Okay, our, we have a revenue goal to achieve because that gets us to our next fundraising gate, or we need to pitch to this retailer and deciding what those goals are to then be able to understand, okay, this is what I'm going to need to support that.
And then I'm going to go after that data or be able to get creative with it. Or if you know, like this, Okay, I sold into this great store. I know I need to keep our velocity up. That's our priority. Then you can start tracking [00:33:00] demo data in even the most basic way, like when we, um, uh, grassroots demos, I love one of their tips.
They're like, buy a golf tally clicker and track the number of people that you handed out a sample to and write that number down. That's data. That's basic data that you can write down and is not going to, you know, you might think, Oh man, I sampled so many people today, but until you like actually track how many, you know, so it can be down to the most basic forms of data, but it comes down to prioritizing what's the right for your business and what your cash needs are, what you have the runway to get to.
And I actually, I just. Finish up a cohort course about, you know, some methods for prioritizing and just, you know, how to prioritize within your business because it is, it is really difficult and that can then inform what data do you dig into. There may be really cool e com data that you have access to, but if that's not your priority right now, then maybe you don't spend a bunch of time trying to dig into that.
Dig into what's the, you know, what's the most next actionable step for you. Thank you.
Ian Cook: Looking back on the people you've talked with, the [00:34:00] companies you've worked with, do you have a great example of one that truly leveraged the data and turned that into a real result for them? You kind of mentioned one before.
I'm wondering if there's others that you've seen this really work for.
Jessi Freitag: Yeah, another one that comes to mind was a little bit more on the e commerce side, but we had the opportunity to have the Transformation Factory, CMOS, uh, uh, founder on our show, Alexio, who is on Shark Tank. And that was really interesting with data because basically he was selling jars of CMOS, like with no branding or anything, and it was selling already like wildfire.
And he was then white labeling for someone else who had some branding and they were selling way more. And he was like, Well, this is interesting. It seems like there's a difference here. Like maybe I could do better. And he actually met a e commerce expert online and the person was like, Hey, you have all this data that tells you about your consumers and how you could market them and how you can adjust your branding.
Let's just use it. And he actually [00:35:00] worked for them for, he was supposed to work for free for like three weeks. And in two days, he like quadrupled. their sales or something by just digging into the data and actually resetting up the ads and, you know, from that expertise lens. And then he ended up like coming on full time and, you know, now they're like, they've quadrupled or 10x their business or something like that.
And that was a case where the founder was like, Hey, I know I'm sitting on this like gold mine of data. I just don't know. And reaching out to an expert who then was like, yes, and can make those little tweaks. And then we're like, And now we're on the right path. And so sometimes it does take having, you know, that outside view looking in to say, hey, here, here's where, here's where we can adjust our strategy.
Ian Cook: Fantastic. Now, feel free to not name any names, or maybe we should explicitly say don't name any names, but what about the converse? People who, uh, just sort of missed an opportunity, had they spent more time understanding the kind of situation they were in using the data, truly understanding how they were selling.
to make a, to get themselves out of what ended up being, um, [00:36:00] lack of growth.
Jessi Freitag: I see this. I mean, this happens a lot. So this isn't unique to even any certain company, but when you lose retail stores and, and it's a surprise, that's always a, a time where, you know, the, the data probably would have told you that, hey, look, your, your units.
MR ASHCROFT And Different devices allow you to share your data. Your data is not looking good, so that it's not a surprise. Some of this is about the relationships. I mean, it's a long list too, of knowing the right people to reach out to, to understand when things aren't good. Even though, if you might not be able to understand, you know, quite the numbers.
So, I think that's a lot of times where people get surprised is just how quickly a store or stores can just lose velocity without the right attention and care, without the right marketing support. We work so hard to get brands on shelf. It's such a feat and [00:37:00] achievement to get into the stores, but really the hard part is going to, the even harder part is going to be the long term of selling through and staying on shelf and continuing to make that your little section of the store worth it for the grocery store to keep you.
And so that's where I see a lot of times the data drop. People drop off looking at the data. They get so excited about selling in, but then once you're in, it's really easy to just kind of think that it's going to run itself rather than kind of continuing to dig in and be like, okay, let's send demos to this store.
Let's do a program with someone like aisle or let's do an email campaign. You know, let's, let's figure out ways to support our store or going into stores that you don't have the marketing dollars to support yet. And then just slowly watching your data, you know, you know, your velocities take a dive in the data.
That's. That's also not a fun place to be. I can imagine.
Ian Cook: Well, Jessi, I want to say thank you so much for this conversation. Obviously, you're the host of Startup CPG. You have a website. You can be found on LinkedIn. Where else can we find you? Yeah, if
Jessi Freitag: people want to learn more, they can definitely, yeah, you can find [00:38:00] the Startup CPG in any podcast player.
You can go to my own website, which is just jessifreitag. com, F R E I T A G, it's a German word for Friday, so jessifreitag. com. You can check out, um, the... Think, you know, the courses and, uh, I work on Notion a lot and those kinds of things, and you can also see my operations work and, uh, yeah. So we'd love to connect on LinkedIn.
Feel free to send me a message on LinkedIn. I love connecting with folks on LinkedIn.
Ian Cook: Fantastic. Well, thank you so much and continued success for another hundred episodes.
Jessi Freitag: Thank you so much. And same to you. Can't wait till you hit the hundred mark. And thank you so much for having me on the show.
Ian Cook: Absolutely.
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