Startup To Scale

142. Using Data to Unlock Retail Success for Emerging CPG Brands

Foodbevy Season 1 Episode 142

Join us in this insightful podcast as we dive into the world of data-driven decision-making in the retail industry. Discover how emerging CPG brands can leverage data not just to measure success but to inform and drive growth strategies.

Learn from experts like Patrick Dougherty from Nielsen IQ as we explore the importance of understanding market dynamics, measuring incrementality, setting meaningful benchmarks, and integrating data across the organization. Whether you're a small CPG brand or an industry enthusiast, this podcast will equip you with the knowledge you need to navigate the competitive retail landscape successfully.

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Startup to Scale is a podcast by Foodbevy, an online community to connect emerging food, beverage, and CPG founders to great resources and partners to grow their business. Visit us at Foodbevy.com to learn about becoming a member or an industry partner today.

 Using Data to Unlock Retail Success for Emerging CPG Brands  (NIQ)

Jordan Buckner: [00:00:00] Welcome everyone to today's ask an expert session. Our guest is Patrick Dougherty with Nielsen IQ and Patrick is an expert, all things data, but more importantly, how to tell your story as a CPG brand using data. One thing that I know from running my brand Teasquares in the past is that, you know, data can be kind of interesting when you're looking at sales numbers and velocity numbers, but it can also be challenging to know how to translate that into.

Something that will really move your business for how to use that for retailer meetings, how to use that for category reviews and investor meetings. So for today, Patrick's going to give us just a quick overview of kind of the work that he does to set some context. And then we'll open it up to Q& A from our audience.

Some of you submitted questions in advance, and so what I'll do is invite you on to ask your question live to Patrick. And then if anyone else has questions as well, feel free to just drop those in the chat. And then I will invite you [00:01:00] to... Come up and ask that question live as well. So Patrick, I'd love for you just to give a quick two minute introduction on yourself and the work you do at NIQ and how you help out emerging brands.

Patrick Dougherty: Yeah, thanks. So my name is Patrick Dougherty. It's great to be here. Thanks for having me. I've been with Nielsen IQ for about 10 years, and my team specializes in helping emerging brands ingest data, teach them how to use it a little bit, start to get them on that pathway, be a resource. So we definitely specialize in those companies that do anywhere between You know, even pre startup, all the way to about 200 million in store sales tends to be where our wheelhouse is, but we really do specialize in, you know, helping those organizations, whether they have executives that come from.

You know, big legacies, CPG companies like a craft or a Pepsi or a proctor and gambler, whatnot or just somebody starts their own business , and kind of takes up and knows nothing about data and needs that full introduction, full education. So , like was referenced, you know, starting to tell [00:02:00] that sales story, starting to set your own benchmarks, communicating with investors or buyers, how to start to.

strategically go after growth and communicate that story is definitely in where we specialize in helping newer brands start to uncover their story through data. So that's what we do. 

Jordan Buckner: I love that Patrick. So when you think about data that's available for emerging food and beverage companies, where does that data usually come from?

And then what kind of data is accessible through Nielsen IQ's visor platform? 

Patrick Dougherty: Yeah, so there's a lot of different ways that that we see a lot of clients start, you know, of the time when a client starting out in the space is they'll be heavily reliant on shipment data. You know, some retailers will access to portal where they're just able to see their own data.

But I think a lot of times, some of these clients that we work with, as they're just starting out, get really focused on just being able to say , how much sales they're doing or how many shipments are sending out or how many POs they're getting. And they're not focusing enough on [00:03:00] the greater picture, not being able to communicate effectively, how that Growth, you know, whether it be through shipments or new accounts, new doors, how do we start to translate that into a way that we can communicate it in a uniform way across buyers, investors, internal partners, consultants, brokers, things like that.

So. One of the big areas that we're most known for and has kind of been the bread and butter of the CPG data industry is what we call retail scan data, which is data that comes directly from retail registers. You scan the item across the register at a store point of sale system captures that UPC code, it tells us how many units were sold at what price point at what time period and that data all gets sent to us where we're able to collect that organize it and report our figures for.

You know, our clients own brands and the whole, the, their competitor brands within their category, within adjacent categories to kind of give a very full picture of not just what am I shipping out, but what's actually selling through to the consumer. And where are those pockets of growth? [00:04:00] Where are , those opportunities?

Where are those gaps that you can help fill and how do we start to identify some of these key KPIs that. You know, an emerging brand needs to stay on track for their growth plans. That's where our visor tool can come in and start to really help clients get a very visual way of being able to digest that information in a very easy to digest format as well.

So that tends to be where people, you know, kind of start off. And then as they evolve, we just kind of start to slowly incorporate a little bit more as the companies grow, as they get more comfortable with the data and their team gets more comfortable with the data. It kind of becomes ingrained in that culture and they can really start to have much more strategic conversations about your brand, tell your story in a much more effective way.

Jordan Buckner: Perfect. I love that. Opening up to some of their questions. And if you're able to join us up, I believe you had a question asking as a small brand, what category and customer insights data would a buyer find helpful? 

Patrick Dougherty: Yeah. This thought that, you know, why would I get the data [00:05:00] if the buyers already have it?

And what can I show them that they don't already know? And I think there's a bit of fallacy there. So a lot of buyers do have access to some sort of point of sales system. Pretend that they're actually diving into this data really deep on your brand before you show up is often not the case, especially if you only have a 15 minute meeting or you have something going on there, they're not necessarily diving into the data deeply before, you know, surrounding your story before you dive in.

So anything, you know, typically just to back up a little bit, when some of these really big clients in these categories go in, you know, if you look at your crafts or your proctor and gambles or your coach or whatever it may be, they get. Hours often with that buyer where they're presenting heavily all the different insights that they're seeing.

And oftentimes it's going to be tilted towards what that manufacturer wants to show. So whenever you're going in, if you have any different you know, selling points to your brand, or you're going after a specific niche, specific attributes. Let's say you make organic muffins or you make gluten [00:06:00] free bread or something like that.

And you want to be able to dive in and really highlight a story surrounding what makes your product unique? What niche does , your product fall into? Where are those gaps in that assortment that are on the shelf that you fit into? I think there's a lot of buyers that don't truly know their categories necessarily as well as they used to 10 years, 20 years ago.

Buyers are getting shifted around categories all the time. You know, you can have a buyer that's buying candy this year and in a year or two, they'll be buying, you know, personal care. And that's to make everything more data driven. So they, you know, the culture of CPG has evolved to where a lot of these buyers rely heavily on their to provide product and to, you know, provide inventory for their sales, but also to be that knowledge resource.

Nobody knows your category as well as you do. Nobody knows your story as well as you do. Being able to communicate that story and what exactly is going on, highlight why your product and the different trends that your products , are a part of, why they're outperforming, why they belong on the shelf.

That [00:07:00] always goes very well. And I think, you know, we just had a long conversation a couple of weeks ago with a Whole Foods buyer. And one thing that he brought up that was very important, I think, for small brands is a lot of the small brands go in and they're providing data that, you know, it's very heavily, especially up front.

Look how great my product tastes or smells or whatever type of practice. Look how great my packaging is. Look how big my social media following is. But you also have to think there's limited space on that shelf. So if they're putting you on something either has to come off or they have to create space somewhere, being able to go in with an active recommendation to say, Hey, look at this, you know, 17 percent of your bread is gluten free your competitors across the way, or they're at 20%.

 They're outperforming your category. Here's why you need an additional gluten free item on the shelf and take away one of these. You know, white bread items or something like that, having that specific recommendation, having a view into what that buyer is being graded on, essentially, and help keeping in that mindset that you're there to basically help that buyer outperform the [00:08:00] rest of their market.

That really can start to transform that conversation that you're having with that buyer. To make it much more strategic, help them visualize what's going on on the shelf and how you specifically fit in there. And that is what is going to take away some of that risk aversion that a lot of these buyers, not all, but many who aren't , as knowledgeable on their category, help give them that help ease that risk aversion to give you a shot on the shelf.

Jordan Buckner: I love that answer, Patrick. And I think it brought up, you know, one of the things that. Category managers and buyers are looking at, right. The assortment of their shelf, what other data points are really key to telling that story? Things like, is it velocity? Is it really looking at like your product velocity?

Patrick Dougherty: Is it looking at the category as a whole and that growth, right? If a new brand only has 10 to 30 minutes and the, what are those key data points that are going to really be strong? Yeah, velocity is king, especially for small or emerging brands, especially because that's usually when you have a really good story to tell when you're in a more specialized store that, you know, where your products are going to move much faster.

Being [00:09:00] able to tell that velocity short story and see show how your product is moving faster than your competitors showing that growth rate when you have it as you're kind of. Rising up and you have those big growth rates because you're going from nothing to something. But even as you're a little bit more established, really focusing in on that velocity and how it's comparing to your competitors.

But another thing to also keep in mind is that we also really want to be paying attention to not just how you're performing, but how it's performing. To a benchmark out there. So if you have a meeting with Publix, for example, going in and saying, look, my velocity is best in class at this store, but we also have to keep in mind, like, what is that environment that that Publix category is within and who are they competing against going in saying, I'm up 10%.

My velocity is up. 13%. You know, I'm able to take price effectively and not show a slowdown, but then you have to take that in context of what's going on within the public store themselves to be able to really tell a compelling story because you could be up 10%, but what if Publix's shelf is actually up 15 [00:10:00] percent and you'd actually be underperforming there, or that velocity might be down a little bit, but I would definitely focus heavily on velocity right now a really big one is like looking at unit volumes.

Unit volumes are soft everywhere right now, not everywhere, but most places. So we see a lot of high dollar or not high dollar growth, but we're seeing dollar growth everywhere. But if you're able to tell that story, especially from a unit perspective, that you're moving units and you're growing that unit volume, that'll be very.

powerful to a lot of buyers and then being able to show, you know, especially , if you have those different unique pieces, you know, especially a lot of the emerging brands have a very powerful story to tell in many cases, having that story backed up with data that proves that it outperforms and that it fits is just as important as.

Those velocity figures, you have to think about the incrementality of the category. , you know, is my product actually going to add incremental? Am I just stealing revenue from other, you know, cannibalizing revenue from other brands on the shelf? Being able to take all these different puzzle pieces and put them together into a one holistic story.

My velocity is great. I'm growing.,[00:11:00] I have a great price point. That's not. You know, stealing anything for private label. And I have a unique value proposition that fits within to the consumer 

that fits in the shelf and adds incremental volume is all really big in terms of gaining successful distribution data.

Jordan Buckner: Great points. Samantha, do you want to come up and ask her question? 

Samantha: Yeah, actually, so my question was really similar to what you just asked. Like, it was basically, you know, what are some other important KPIs besides velocity? So I guess I would want to a little bit more background on, like, putting your numbers in the context you know, because I really liked what you said about understanding. Well, what is the store trending? And what's your trend compared to that? So, like, in terms of, like, the store, and even, like, the geographic location of the store, what's some data points that you could add for more context?

Jordan Buckner: I think Patrick as well is how that the data collection changes as you kind of grow from that early store stage to growth. 

Patrick Dougherty: Yeah. So I think, you know, to answer the first portion I, I think it's a lot of based [00:12:00] around like the, the market context. When we look at scan data or, or. Data, there's like four essential pieces.

There's what market we're looking at, what products we're looking at, what time periods, what metrics, you know, I think the key metrics and being able to tell that story about that, you know, are you promoting effectively or is your price point, right? Your unit volume, your velocities, things like that are all part of that metrics piece.

I think having the context of being able to tell that story and see that data across different markets and platforms. So if you are a regional brand and you're looking to expand out. Being able to draw those parallels using the same metrics, but looking at it across, you know, those remaining markets. I think it's like a very underutilized way of analyzing data for a lot of newer brands is they're not looking at those remaining markets well enough, or at least comparing it against the total.

 Like a total us or a total region that player is playing in same metrics, but using it over that region, I think is very important to be able to make sure that you're really put yourself in your buyer's shoes and think of that report card, which is their category growth compared to that rest of the [00:13:00] market, anything that you can do that shows that growth is going to be important, but there's a lot of tools that we can get into that will be much more.

Like we could do official assortment studies that will basically provide an actual figure for what that lift will be if, you know, you get on the shelf and how it will impact the other brands around you, but that tends to be one of those more. You know, pieces as you kind of get your feet wet with the scan data, you move into some panel data and start looking at, you know, who is my demographic and how does that, how does the shopper of my product gel with these different retailers that I'm getting into?

Or, you know, is there opportunity because I'm missing a big portion of who I think my target consumer should be in this. Retailer A, B or C is a great fit and would add these additional, you know, consumer groups that I'm missing that I think would resonate well with my product. There's a lot of different pieces that you can start in , that puzzle gets more complex as you grow and get bigger.

So as is, you know, but I think it's very critical that companies that are in that emerging space, Start to walk [00:14:00] before you run a little bit, just because the data can be you know, a lot of times companies will have like one person that's really doing the heavy analysis and that data stays very siloed with them.

They'll use it in like a board meeting or a board review to explain to everybody what's going on or to set those benchmarks or whatever it may be. Then. As we kind of layer on some of those more complex, more in depth studies, it kind of falls off with the rest of the team. So being able to start to integrate that data, not only with your sales people who are making those pitches to buyers, but also with the marketing teams, also with.

you know, the CFO or production to be able to start to forecast how much product they need to be able to make or what that manufacturing capacity is or shipping rates, things like that because of anticipated POs. There's a lot of different things that we can start to use this data across the organization that then allows you to kind of take those further steps that allow you to integrate the data across all the functions within your organization or within your brand.

So to recap that I know that was kind of a complex answer. [00:15:00] I think. You know, there are a lot of different metrics that we can share that would be kind of unique to what your story is and what your data is showing. I think that velocity piece is king and being able to show it not only across, you know, the markets as you're already in, but be able to compare that across.

You know, some of those markets you're going to be going into having the data for those specific trends and making sure that you're on trend and highlight those different pieces that make your brand unique, that are unique to your selling story and being able to show how that works or , where those gaps are in that retail that you're trying to sell into versus the rest of the market or across a total marketplace.

You know, showing your price point is right showing that you're going to be promoting or have promotional support and that it's effective and that it's strategic. And then you can start to tie in some of those consumer demographics and start to show, you know, here's who my consumer is and here's why this is a great fit with.

You as a retailer, and this is kind of as you start to get bigger and you grow a little bit more and your organization becomes more comfortable, you start to take a look at that leakage and be able to go into a retailer and say, [00:16:00] look, X percent of your shoppers are buying my product over here. Here's why you need to put me on the shelf.

Here's where went my trial and repeats look like when I get brand new distribution on the shelf. All this type of information kind of starts to flow together as you start to grow. 

Jordan Buckner: Awesome. Love all those Patrick. And thanks for the question, Samantha. Just wanted to send a reminder to everyone. If you have any general questions or specific questions, feel free to drop those in the chat and we'll make sure to answer those.

So Anne has a question. She asks, as a pre product brand, how do I estimate competitor sales and market share? And I'll add to that, are there specific visor reports that can lay out that information that she should be aware of? 

Patrick Dougherty: Yeah, definitely. And I think this actually kind of feeds into a bit of a broader tactical way to use data a little bit.

So we have a lot of resources where you can just buy a one time report. It can be very inexpensive where you can start to get that lay of the land. And I think that's a very critical thing for new brands to do to really understand who those players are and , what the marketplace looks [00:17:00] like for that category.

Get those category dynamics, understand, you know, take your brand out of it for for a second and make sure that you really understand the trends that are taking place within a category before you even start to dive into your own. It's very difficult to tell a story about why your brand. Is going to work, why it's going to be successful on the shelf.

If you don't understand that those category dynamics that are already happening and that have happened in the past, so we can always provide a, you know, a one time snapshot that just basically shows here's your category. Here's every single player in it. And here's how much. Dollar volume they do. Here's how, what their distribution levels look like.

Here's what their, you know, 17 or 20 percent of their sales are on promotion. And this is the type of promotion they're on. And you can start to really gauge what that looks like. What market shares are there? What retailers are big for this type of product. And you can start to kind of figure out where that fit is, uncover who those new and upcoming brands are, identify, you know, what those trends are in terms of different product attributes is gluten free or organic or, you know, [00:18:00] clean label, a big trend here.

Again, keeping in mind what your What is part of your story? Cause the whole purpose of this is to tell a story that has that fact based data driven narrative behind it. But how do we start to uncover all those different pieces that when we do finally start to dive into our brand and tell our story, we know whether it's on trend or not, we know if it's outperforming or not.

We know what the different pieces to push, what buttons to push to really get that buyer excited about showing why you're going to be successful on the shelf. And we get a lot of feedback from brands that are like, Oh, I'm too small. I don't have any sales yet, but I think we have to keep in mind data.

Isn't just to be like, look at how well I'm doing. That's in fact, that may be about 50 percent of. The goal of it, a bigger goal that I think a lot of people are that we're trying to kind of really start to shift people's mindset on her a little bit is to use this data more proactively. It's just as important to show that you're a good fit and that you're on trend or you're ahead of trend or whatever the case may be, then just.

You know, showing look how [00:19:00] well I'm doing in my select number of retailers that I'm in because that's no guarantee that you're going to do well, if you could be doing great and in this handful of retailers that are, you know, over in this area that buyer is not going to. You know, it's still going to have that risk aversion there unless you really blow them away with your story Unless you can prove that fit is there and that's partly why our buyer platform does make every retailer available to you like if you were to Not to go into a sales pitch, but it's kind of a theory behind why we build this stuff the way that we do is we want to help these brands start to use this data more proactively, the same way that these big brands do identifying those gaps of opportunity, identifying where you can start to really make an impact on the categories.

Incrementality is big. So as a pre brand, it is very important to get that lay of the land, understand, you know, where everything is, , what the category dynamics look like. Look what that market, how fragmented is that market? Are there a bunch of different brands? Is it a bunch of small brands making it up?

Is it dominated by three big players? And then there's a bunch of, you know, smaller folks in there having [00:20:00] that view. Not only from a category, a brand perspective, but also a retail perspective, a geography perspective, where are these trends taking off? Where is this received? Who is the consumer? And I don't think it all necessarily has to come from buying data.

I think there's some. Areas where you can get that information just by going to a store and checking things out and starting to get a feel for it that way. And then when you get that light bulb moment, think, Oh, I fit here. That's when you can come to us and we can really help you drill down to the specifics of that argument.

Even if you just, you know, you're putting one slide together to show that investor so that you can start that brand up because you're pre launched and you just need that hard hitting fact, you can come to us, we can get. You know, you have that hypothesis say, Hey, can I get just a brief thing on these three brands?

I just want to see, you know, how this brand evolved over the past five years, we can do something like that very easily on a very ad hoc basis where it doesn't involve some big, you know, subscription all the time. It can be very, you know, if you have that one little piece, you really just need to provide that meaty tidbit for that presentation.

We can help you with that [00:21:00] too. 

Jordan Buckner: Awesome. I love that, Patrick. And I want to use this halfway point to really highlight our partnership with N ielsenIQ they're offering everyone in the food bevy community, including everyone on this webinar, three free reports to actually pull to see how your category and brands are performing.

So if your brand's in market and I'm showing up in the data, then you can actually see what your performance looks like. And even if you're pre market you can use these three free reports to see how the category is performing So that you know, you can use those for your buyer meetings for investor meetings and the link is in the chat So feel free to save that and we'll also send that out as a follow up.

The other thing I'll highlight is using that link as well. You can actually sign up for a one on one call with the Nielsen IQ team to ask specific questions and saying, you know, hey, I want to tell a story around, you know, just use your example earlier, like why my gluten free bread should. Be an ex retailer and then the team can really help you figure out, Hey, here's the data to look at to [00:22:00] help you tell that story, right?

Because if your first time using data, it can be a little overwhelming to like, know how to pull the report, which retails, which regions, all of those things. And so the team is really making themselves available to make sure you're getting actionable information to tell your story. And not just getting lost in data.

So definitely be sure to take care of that. The other call out that I wanted to say that's interesting as well is in Patrick, interesting to hear your thoughts on is with data, right? Let's say you're looking at a new retailer and they have no gluten free breads there.

Does that mean you should launch in that retailer because there's a white space or that you shouldn't because that retailer isn't supporting that category? Maybe those customers aren't shopping there at the store or looking for it. And so it's really all around, like how you kind of tell and craft that story and do more research.

So do you have any examples of just from your experience, like how you've been able to leverage different data points to really share stories around, like when you should launch into a new retailer or a new kind of distribution? 

Patrick Dougherty: Yeah, I think those types of challenges are unique. Of, you [00:23:00] know, I don't think there's that don't have gluten free bread, but a lot of brands that will come to us and say, there's nothing like this in the market.

Like, how do we start to create story that. There should be something here or that we deserve that distribution. And I think this is, we're having, if you're in that type of position where you're going to category established or doesn't have anything that's similar there is then we have to kind of look broader to be able to get that shows that this is a unique bit. So, an example that we have that we could do is we have a panel, you know, the gluten free bread.

what I was getting to is we have a lot of different tools that can help tell that story. So in the example that you gave with gluten free bread, if there's a store that doesn't have any, we have a panel where we are able to measure ailments.

And we can measure a lot more than just ailments. We can measure a lot of different things where we could take a look at anybody Who has gluten intolerance and show that retailer look at how many people who are have gluten intolerance are shopping at your store like and you don't have any options for them so they're buying you know apples and bananas at your [00:24:00] store but then they're leaving to go to another store to buy something else when you could be capturing that you could be converting that shopper into that category you bring new shoppers with this category and you're missing out on that because you don't have this option there's things like that we can do More specifically, I think if you don't want to go that route and keep it really simple, it could just be as simple as doing the same thing that we were just kind of discussing is looking at what's happening at stores around that market or around that retailer, seeing what, how is gluten free bread performed there and is there actually incrementality there, you know, I think there's an example that we use a lot with chocolate milk and you think about, you know, a retailer has a big case of milk.

And then they'll have like one or two or a couple chocolate milk skews, but every data report in the world will show that white milk is outperforming chocolate milk just because people are buying white milk all the time. So we have to think. Not just in terms of is my product selling higher dollars and something else, or is it, you know, moving faster, have a higher velocity.

We also have to keep in mind that other part of the story [00:25:00] of that incrementality and think that white milk shopper like chocolate milk isn't taking away from a white milk shopper. It's purely additive. It's capturing a purchase that wouldn't happen otherwise. That's where we can start to also tell that story with a lot of products that emerging brands have that are innovative, that might not directly compete with something that's exactly the same, but you're still can make space on the shelf, even if you're not outperforming.

Somebody else because it's a purely incremental spend. We can help measure that incrementality or start to do some modeling to show that as well. But another way even outside of that is just to see how's gluten free bread performing in the rest of the market within that same retailers footprint, but You know, outside of that retailer and start to say, look, this is bringing in X number of dollars outside.

Here's why, you know, give us a test run. It's like, there's a read or start to understand why they don't have gluten free bread. But that usually those are 3 ways that we could approach it pretty easily. And directly

Jordan Buckner: Patrick when looking at, promotions. I know a lot of brands are investing in trade [00:26:00] spend and they're trying to figure out was this promotion effective or not.

And so how do you think about using data to measure things like the You know, lift and sales during a promotion and sustained lift after. 

Patrick Dougherty: Yeah. And we have a lot of tools that help you do this really effectively. Basically we're able to create using the category as a whole, and also using your brand's historical performance.

We're able to create a baseline based on all these different. Variables that are going on, like what would you be selling absent any type of promotion? That's when you hear about base metrics and your base dollars or base units and it's an algorithm that runs that basically says Absent any promotion, here's what we would expect you to sell based off what everybody else is doing and based off all those other variables like anybody else that's promoting or, you know, if there's a Super Bowl and you're in hot dogs or something and naturally that you see a lift there even without promotion, we're able to then layer the actual sales during that promoted period over that baseline to be able to create that lift or not create them to be able to measure that [00:27:00] lift.

And then we can also you could cross reference that with your cost , of that promotion to be able to see how effective was it. And that's kind of how we would measure it. But then we also have tools that can go really deep into basically identifying those trends over time. Like let's say, or the break it down every single week over the last year, uncover those, that seasonality of the category and cover the different trends within that category and how these different brands are evolving.

And we can actually tell you specifically which Like two or three weeks out of the year are the best ones to promote where we're able to isolate that using some of these very complex models that we build. It's the same models that your Procter and Gamble's and your Coca Cola's and Tyson's and everybody uses.

But it's kind of in a way that's very easily digestible to be able to show you, you know, here are the different types of promotion we're measuring, whether it be a feature ad or a display or a Temporary price reduction, we're able to measure those lifts and how effective they have been on the category in the past.

And then we're able to take a look at those category dynamics and say here's where this would be most effective based off of, you know, historical data [00:28:00] and what we model into the future. So there's a lot of different ways that we can measure it and we'll be able to also take a look at that promotional behavior across those different promotional types and tell you what types of promotion are best.

Or you could even, if you don't want us to tell you which one is best and you just want to see the measurement of it. We can do that. We can take a seven week period before the promotion, a seven week period during the promotion, a seven week after, and be able to show you kind of what that looks like.

And then go back a couple of years and you're able to see very easy what that lift would be. If you don't want to use the metrics that specifically highlighted, but we have all the tools to help you really dive deep into that and to be able to start to negotiate a little bit more with those retailers in terms of what is that best promotional strategy.

And that is super. Important, especially now, because we've been seeing this inflation kick up and the price sensitivity so high, we've been seeing promotional effectiveness jump through the roof over the past few months, where that those promotions are seeing extra extra amount of effectiveness over the past few months.

And they have in the past because of how sensitive consumers are about price at the moment. 

Jordan Buckner: That's awesome. [00:29:00] Appreciate that. One thing that Founders. Ask me is like, how often should I be looking at data and how do I kind of build that into my strategic planning? Have any thoughts? 

Patrick Dougherty: Yeah, so that would depend on where you're at in your business cycle.

I think if you're a brand that's just starting out, you're pre-launch or you just launched I think it's often best. You know, especially if you don't have a team, that's really savvy with data to kind of take it slow right off the bat, meaning you have a meeting coming up and you're like, Oh, I really want to get into this retailer.

I'm meeting with them at a trade show, or I have this, I was able to get this meeting, we can get you that one time snapshot to help you prove internally that ROI to, so you can see with your own two eyes, how much that data will transform that conversation and just have. You know, one to three slides of , your presentation deck that highlights some of those key data points and where you fit in and highlight some of those trends as that starts to come into play and you start to, you know, gain some more retailers that are carrying your product, then you can kind of start to expand a little bit [00:30:00] more and make sure you're getting this data every quarter or every month.

To make sure that you're always ready for those line reviews, make sure that you can stay in and on top of what those trends are. You're not surprised, but if you go into that line review and you hear a buyer say, Oh, you're not performing too well, you're at risk of being, you know, delisted. Being able to stay on top of that stuff every month, every quarter is kind of that next step.

And then once we kind of are at that step where you're measuring those core retailers, you're getting some data periodically for those big meetings that you have. Where you don't have distribution, you're trying to gain distribution. Then it kind of evolves into, okay, I need an ongoing subscription that I'm have that flexibility to pull different retailers.

And when I need to, I can pull data more frequently that I can, you know, use this data internally to start to strategize much more deeply on all of these different elements. You know, we don't, to your point earlier, Jordan, I think this data can be very intimidating to a lot of brands that are, Starting to grow. So dumping everything on yourself right now, , and especially if you're limited on time or you don't have an analyst, tend to recommend that you start to take a little slow, start to get your feet wet [00:31:00] with it, start to communicate this data internally and get other people's eyes on it.

And then it becomes much easier to adopt once it becomes part of that culture of your business to be able to, you know, have those sales meetings where you're benchmarking your growth using percent ACV instead of just door pounds and you're starting to. Be able to target consumers more specifically using some of our panel data, then it becomes much easier to really ramp it up and not just be burdened by a bunch of data sitting on your desk or technically on your computer that you might not have the time to dive into as much as you thought you would.

So starting slow starting just. Getting one to three slides with some stuff in your presentation, seeing how that works and kind of tweaking your strategy from there, which we can always help you with. You know, we're here to advise you if you have any questions on how to use that, how to analyze the data, how to dig in deeper.

And if a buyer's challenging you on something, how do I respond? We can help provide the data to Do that and give you some pointers on how we would address it. And then you can kind of just grow it from there.

Jordan Buckner: And none of the past data has been really expensive. And so, you know, what does data look like in terms of, and like, how does it change in terms of [00:32:00] affordability?

So that founders can actually take advantage of it. I know I mentioned earlier, we have our three free Nielsen reports, but then like, , how much should brands be kind of paying for data if you're say under a million dollars in sales? 

Patrick Dougherty: I mean, it can be pretty affordable nowadays. So I do think, you know, part of the reason we've launched this Pfizer platform was to make data.

More available to emerging brands and make sure that you have the tools to compete effectively. And it's a model that's built to grow with you. So the size or how much revenue you're doing in the marketplace is. Arguably like the biggest factor in terms of what that cost will be so we can give you a full subscription that you have access to all of our retailers and you can pull data 10 times a month, and you can be paying 12, 000 a year.

If you need that full package, but if you're just looking to start out and you're even before that stage of having that ongoing data at your fingertips all the time. It can be as little as 1, 000. It can be 500. If you just need a tidbit or two, it can also be 2, 000. If you need like, show me this whole retailer and [00:33:00] show me every single item in the category across all these time periods, and it can be somewhere around that ballpark, there's definitely efficiency when you know, you need it.

You know, ongoing because then you get a lot more for your money, having that quick hit that you can see that ROI on tends to be important. Helping you see how that transforms the conversation can move things pretty effectively for you. Well, and we can always work with you. You know, we're not here to nickel and dime you or , to put something really big and expensive in your hands if you're not ready for it.

So I would just be upfront with what you're looking at. And we can always. Make something work to get some data in your hand. We really start leadership all the time, too. And these three reports hopefully will start to get your feet wet a little bit. But there's definitely a lot of affordable options there especially built for emerging brands to be successful.

Jordan Buckner: Awesome. So we're coming up towards the end of our session today. So if anyone else has any last questions, feel free to drop those in the chat and I can make sure to ask those , to Patrick. Patrick, any other kind of major problems that you see in terms of like brands using data incorrectly or just like issues that they [00:34:00] have that are preventing them from using data as they should be?

Patrick Dougherty: I think a really big one that we see a lot is a lot of, even after people buy data and fully realize a lot of clients have limited time. Like you could just be a founder or you don't have that analyst, you don't have folks, and you get data for the first time and you realize, oh shoot, I haven't had time to do anything with this.

I'm just gonna take a snapshot, show what number I am in a category, post that on a slide. And that's, And I think, you know, we can help make some of this insight really jump out at you so you don't have to do a bunch of analysis. And I think being able to dive deeper into some of these different metrics, even if it can take a second, just changing the way that you're speaking about your distribution levels is a key example.

A lot of small companies or emerging brands will really focus on door count. I'm in 300 doors, I'm in 400 doors. And I, my goal is to get 500 more doors over the next year, but that's a metric that is wildly subjective to a point from a revenue perspective, because every door is not created equal [00:35:00] by starting to use some of this data.

And this especially goes towards like working with investors, things like that, and being able to set benchmarks in your team that are directly tied more specifically to what we can expect from a revenue perspective or from, you know, that money coming in sales perspective. Is very important to be able to take a look at more of that, you know, percent ACV methodology, where it's a weighted distribution metric that takes into account the volume that a store does allows you to tie everything in much more specifically, where instead of just saying I'm in 300 doors, you could say, Oh, I have, you know, 3 percent ACV.

And for every one percentage point of ACV, I'm bringing the next number of dollars. I can now directly tie that to. You know, if I want to gain 1 percent more ACV next year, I know essentially how much revenue is going to be coming in where 10 doors at Walgreens are not the same as 10 doors at Whole Foods are not the same as 10 doors at Walmart.

And that becomes much more difficult to kind of draw those correlations. So by starting to create some of those benchmarks, and some of those growth strategies using the data.[00:36:00] Will help you tremendously when you are to those investors, when you're able to start to strategize on a much deeper level, and you can even say, Hey, when I gain X number more sales next year, Oh, well, based on the data and based off what our velocity is looking at, we need to gain X percent more ACV, what, how many, you know, if I go into Publix, does that do it?

If I go into. Target, does that do it? You know, we can start to really strategize in a way that directly correlates those dollars to that distribution level and helps you stay on the same page with those investors and be able to have those investors take a look at what , you're doing and have that growth plan be much more predictable and then be able to see other brands as they're growing and benchmark yourself against those growth paths as well. Same with share, like looking at your share of the market and being able to have goals against, you know, a true dollar and unit share. There's a bunch of different benchmarks that you can start to set for yourself that really help you up that strategic aspect of your business and help you communicate it much more broadly and make sure that you're all on the same page.

I mean, the last thing an [00:37:00] investor wants to see is, is if you're saying, Hey, I have. 500 stores, well, let's get 200 more, but then the 200 stores you get aren't anywhere in the same ballpark as the ones you already had. And it just doesn't correlate to the sales and sales still aren't meeting those targets, but maybe those distribution doors are.

So there's a lot of stuff like that, that I think is something that a lot of clients are missing and really can help even when communicating with retailers really help you dive into that next level. 

Jordan Buckner: All super helpful. Patrick, thank you so much for joining today and sharing all these questions or all your answers.

One thing I wanted just to re highlight is make sure you click on the link that's in the chat and sign up for your free three reports with Nielsen IQ's visor platform. Even if you're like not sure exactly what you need right now, I recommend setting up a call with their team so you can talk through what your issues are and then they can help direct you to the data that will be.

Most helpful for you is also that you can have the tools and resources to be empowered so that you can face the challenge that is [00:38:00] retail right now and go in with your eyes wide open into how to succeed and how to grow your brand. Thanks so much everyone for joining today. We will be sending out a recording after the session in the followup with that link as well.

And Patrick's email is in the. Chat as well. If you have any questions on anything that you said today or would like to follow up. Thanks so much everyone and have a great rest of your Wednesday. 

Patrick Dougherty: Thank you.