Pod Insights MarTech Podcast ™ // Marketing + Technology = Business Growth What To Do When Your Company Data Isn't Easily Accessible About this episode Cofounder and CEO / President of Zappi, Steve Phillips and Ryan Barry, discuss strategies for dealing with inaccessible company data. They delve into the importance of leveraging consumer insights to enhance advertising and product ideas, emphasizing the need for faster and more affordable solutions in the creation process. Zappi, a company working with global enterprises like PepsiCo and McDonald’s, focuses on integrating consumer insights at every stage of product development. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
Transcript 0:00 Speaker 00 The Martech Podcast is a proud member of the I Hear Everything Podcast Network. Looking to launch or scale your podcast? I Hear Everything delivers podcast production, growth, and monetization solutions that transform your words into profit. Ready to give your brand a voice? Then visit iHereEverything.com.
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0:53 Speaker 00 Welcome to the Martech Podcast, a member of the I Hear Everything Podcast Network. In this podcast, you'll hear the stories of world-class marketers that use technology to drive business results and achieve career success. Here's the host of the Martech Podcast, Benjamin Shapiro.
1:15 Speaker 04 Welcome to the Martech Podcast. I'm your host, Benjamin Shapiro, and today we're going to discuss overcoming data accessibility challenges. Joining us are both Steve Phillips, the co-founder and CEO, and Ryan Barry, the president of Zappi, which brings pre-launch consumer insights into every phase of the creation process. Working with over 350 global enterprises and more than 1,000 companies, Zappi is a wonderful example of not only a beautiful brand, but also a tool that can help you understand your customers before you even have your product ready. Yesterday, Steve, Ryan, and I talked about what it means for companies to be data-rich and insights-poor. And today, we're going to continue the conversation, talking about what you can do when your company's
1:59 Speaker 04 data isn't easily accessible. All right, here's the second part of my conversation with Steve Phillips, the co-founder and CEO, and Ryan Barry, the president of Zappi. Steve, Ryan, welcome back to the Martech Podcast. Thank you, Ben. Psych to be.
2:13 Speaker 05 Thank you, Dan.
2:14 Speaker 04 A treat. A pleasure to have you guys here. We had a great conversation yesterday talking about what to do when you've got so much data and you don't know what to do with it. And my takeaway was there's five W's. Who, where, when, what, and why? And the problem is us marketers are forgetting the why. All we're doing is focusing on what data do we have and how do we optimize against it? Not figuring out why it's showing up. What does it mean? So let's talk a little bit about not only figuring out the why behind the data, but a little bit more of those first four W's. What do you do? We've all talked about third-party cookie deprecation and privacy regulations and, oh, my God, all the data is going away. How are we going to market? How are we going to run a business?
2:57 Speaker 04 What do you do when your company data isn't easily accessible?
3:00 Speaker 05 We probably know from experience because we probably didn't prioritize connecting our own data early enough.
3:06 Speaker 04 Well, don't tell everybody that. People are listening.
3:09 Speaker 05 Go ahead, Steve.
3:10 Speaker 06 The trouble is it's bought by different people in large organizations. So you have different people buying different data from different suppliers. So you automatically start off with a silo problem. Now, you have a silo problem and you don't necessarily, I mean, we've talked to enterprises that have like two different DMPs or consumer data buckets, right? So you have to think of your data as part of your key asset. And I think I've talked to you, particularly for larger organizations, the waves of technology that have hit us in the last 30 or 40 years have often been really advantageous for small companies. They've allowed you to start up quickly, get a website, enter e-commerce really quickly. You know, changes in manufacturing just in time, just enabling companies to, or someone out of their garage to start a new vodka brand.
3:55 Speaker 06 Well, the thing that big companies really have an advantage of is lots and lots of data. But they're not seeing it strongly enough as an asset and not aligning that data properly. So if you start by really focusing on the data alignment, it is then that you have built the capability to add in all the exciting things that AI could do that really will become the moat for the enterprise in the future. And that's why it's just natural that it hasn't been aligned. It's been a bit of a problem that hasn't been aligned. It's becoming a really important problem that the companies are beginning to focus on because they realize that that is increasingly the asset that they have. That is increasingly the moat.
4:37 Speaker 04 What I'm hearing from you is that big brands, I'll use a poker metaphor here. I have a dad's club poker tournament twice a year, and I get to the final table every year, and I've finished fourth. The top three are in the money. So I hear you. My point here is that big brands don't realize that they're the big stack. You can always push more chips into the table and make the little brands nervous so they back off and don't serve as competitive. They have more data. Now, what's the way where big brands are saying, "All right, look how big of a brand I am. Let me clear out some space. Let me throw some elbows," to use a basketball metaphor. "We can go Draymond Green in the 2022 finals if you want to."
5:20 Speaker 04 I know you're a Boston fan. Talk to me a little bit about the ways that big brands can leverage that data. It may be there. It may be accessible, but they're not using it the same way.
5:31 Speaker 05 I think part of the challenge is, and it's actually interesting, because we've helped a lot of businesses that are on the rise. I think SoFi is a great example of a bank that was repurposed and is just flying, and their CEO bet on data and system intentionality when they were 50 million, and they don't have a problem. I think when we started helping our customers think about their data, one of my favorite examples, we sell to a lot of big companies, and one of them told me that they have 15 different ERP systems across the globe. And that's just ERPs. Now, think about their media agencies where they would have had 50, and that's one of their biggest expenditures, let alone consumer insights. So I think there's been this rise of the chief data officer, and that person is sort of tasked with bringing it all together. But it's quite hard if the system intentionality isn't there, because the data
6:16 Speaker 05 just isn't as accessible. So the opportunity is worth it, but we always talk about this. The people and the processes associated with getting the data harness is actually the hardest part.
6:26 Speaker 04 I feel like this conversation is just inherently going to turn into a basketball conversation. For everybody listening at home, Ryan now has a Celtics hat on. I'm screen sharing pictures of Steph Curry playing.
6:37 Speaker 05 Remember, I'm English, so I don't know what you're talking about.
6:39 Speaker 04 You've got a black and white shirt on. You can be our referee. Forget marketing. Let's just talk hoops, guys. All right, maybe everybody here wants to learn a little bit more about data diversity.
6:49 Speaker 05 We'll talk data.
6:50 Speaker 04 All right, all right, fine, data. We all got our championships. Everybody won their gold medal. Sorry for everybody not in the United States. Where did we leave off here? Catch me up.
7:01 Speaker 05 Yeah, just about. The big companies have this major opportunity, but it's harder because there's so much inertia against the data being harnessed because there's disparate systems, because you think about if you're, if you're trying to attack local P and Ls, you try to give local autonomy to speak to the German market the way you need to, the British market, the way you need to, and there wasn't really any central governance around technology. There was just a ton of adoption on it. So now that the management consultancies are making a lot of money on digital transformation strategies and chief data officers or chief transformation officers, whatever you want to call them, are increasingly getting more power and teeth inside these organizations, they're trying to harness it, but because of the disparity of the systems, the data doesn't speak. And then because of the way the people and processes were set up, it's
7:44 Speaker 05 not as easy as it sounds to get it together. So getting each data set to be packageable, workable within the UI in which you buy it, but also exportable is something that's really key. But a lot of companies do struggle with it, but when they get it under control, they make more money, they hit their number, their ads are more effective. So the juice is definitely worth the squeeze.
8:03 Speaker 04 Steve, as the referee, before you get in here, I'm going to go back to my poker metaphor. What I'm hearing you say is this is not the, the big companies have the big chip stack. There's a problem. They've got plenty of cash. Some of it's in their pocket in their wallet. Some of it's tied up in their PayPal account. They've got a little bit in Venmo over here. Maybe if the poker game is getting really hairy, they got to sell their watch. And in the meantime, the smaller companies are sitting here saying, I put all my cash into these chips and they're in front of me and I can be faster and more mobile. So Steve, let me turn this back to you as our referee here. Help me figure out, maybe you should be our referee and coach. What's the game plan here? If you're a big
8:43 Speaker 04 company and you're facing this problem of disparate systems that have data and you're having trouble analyzing, aggregating, making sense of it, and you're not being mobile enough to compete with your smaller competitors, what do you do?
8:59 Speaker 06 Taking the poker analogy, the trouble is their chips are on different tables, right? So they're playing 15 games all simultaneously and they need to amalgamate it and play one game. And of course, when you're trying to do that as a chief data officer, and we understand why, you're going to start off with the data that's most easily accessible and then democratize that. So you start with one data stream and maybe it's sales data. But that's not necessarily the most insightful data. It tells you where you've been, it doesn't tell you where you're going. So what you have to think is going back to the conversation we were having yesterday about insight. So you want insightful data being democratized, not just data being democratized. And at the moment, it tends to be the biggest, easiest, most accessible data that people will immediately go, okay, let's do this in an agile way. Let's make that democratized.
9:43 Speaker 06 Everyone gets access to it, but no one knows what to do with it. So you have to have a much more holistic view about what data do what people need to make decisions instead of to have a dashboard so that they know what's going on. And so you need just a more strategic overview of how are we going to approach data? What data helps us do what things? And often, particularly in terms of consumer insight data, our data is really powerful. Everyone knows it's really powerful, but the accessibility has always been hard. We've now solved that problem. So let's make sure we take our data and put it into the why data into the hands of the people making decisions about where the brand and where the innovation goes. So it's a more holistic view of that data democratization.
10:24 Speaker 04 To take the poker metaphor to the nth degree, essentially what I'm hearing from you is big companies' problems is saying, well, we don't have gold, but we've got lots of pay dirt. And we can't use it to play poker because we haven't refined it down. We know that there's gold in the hills, we own the hills, we just can't use it. And you need your insights team to be able to not only mine the data, figure out what the insights are, but then also you need distribution. You need the way to make it accessible. And I'm pretty sure that's part of what Zappi is there for. So without turning this into a total sales pitch, like, am I getting it right? Is that kind of the Zappi layer where you live? It's just not necessarily getting access to the data.
11:07 Speaker 04 But as you said, democratizing those insights, making sure that everyone not only has access to them, but understands what's happening with the consumers.
11:16 Speaker 05 Yeah, I mean, by systematizing the adoption of how you learn and then overlaying the nuance of how each brand needs to speak about its brand or price or what have you, you can then put user controls in place to let anybody get access to the data that we learned today. And that's important because that's going to drive productivity and consumer centricity kind of as we make decisions. I think where things get really exciting is when the data warehouse has the customer in it, but it also has the supply chain, it also has the media data, it also has the CEO's preferences, and you can turn those into data agents that are going to go and actually ask all of those questions. We're doing some really fun things with customers now where without actually talking to customers, we're querying all those different data sets to come up with six or seven ideas that we
11:58 Speaker 05 already know will work to then allow the company to refine them. And that goes from agile, getting consumer insights to instantaneous really quickly. We both live by the worldview that the testing of consumer insights being outside the creative process is over. It has to be inside it. And marketers have been underserved with that why data. So giving them something where in a workshop, they can write into a chat box and ask all the things they know about their operations, their feasibility and what people love, and then how to win in an after-work snack is a really big advantage for them. But they have to be intentional about the way they put their data together.
12:31 Speaker 04 All right, it's time for a big finish here, and I want you guys to help me out. Normally, I monologue and wax poetic about everything that I know about marketing. In this case, I'm not going to pretend to be the expert. I'm going to re-ask the original question. I want both of you to give me your big finish sentence. What do you do when your company data isn't easily accessible?
12:49 Speaker 06 You have to work on systematization, but bear in mind the payoff now. So we were talking about data mining earlier. You don't have to mine data anymore. If you set it up properly, you can get LLMs to mine your data. AI and agents that we're using can do all of that work for you. As long as the data is structured, you can have more insights, better insights available at the touch of a button to anyone trying to make a decision. And that world is incredibly exciting.
13:14 Speaker 05 My sort of summary would be if you're a CMO and CFO and you're spending money on consumer data and it isn't harnessed, you're kind of wasting your money. The way to start is to audit all the questions you're asking, audit the way you answer those questions, pull together a cross-functional group of empowered executives to go on the journey and fix thing by thing. And it's not that hard. There's a lot of steps that you can use to do this, but you have to look at your systems, your people and your processes in the round. And within a year and a half, you can get this to be a major competitive advantage for you.
13:44 Speaker 04 The word that sticks out to me with what you said is journey. And often we think about the customer journey. Hey, somebody heard about us from word of mouth and then they Googled us and then they left. And then they came back because they heard us on a podcast. And then three years later, they saw a Facebook ad and now they're our customer. And we understand how and why. That's not the only journey that matters. The journey is also understanding what's happening with your data and understanding what makes those consumers do what they do. And there is a journey inside of your organization, just like there is a journey with your customers, which is how do we put our disparate systems together, make sense of them and build that internal understanding of the why?
14:27 Speaker 04 Why do our consumers go from word of mouth to Google, to nothing, to something, to all of a sudden, they're our most valuable customers? If you can understand the why, the mindset, the rationale, the motives behind your consumer actions, you're able to replicate, you're able to match, you're able to extend. And that wraps up this episode of the Martech Podcast. Thanks for listening to my conversation with Steve Phillips and Ryan Berry from Zappi. If you'd like to hear more from Steve and Ryan, you can find a link to their LinkedIn profiles in our show notes. You can visit their website, which is zappi.com. And on zappi.com, you can find the Inside Insights Podcast. You can read their book, Consumer Insights Revolution. And you can sign up for their weekly newsletter, which covers AI and customer insights.
15:12 Speaker 04 Just one more link in our show notes I'd like to tell you about. If you didn't have a chance to take notes while you were listening to this podcast, head over to martechpod.com. We've got summaries of all of our episodes, contact information for our guests. You could subscribe to be our next guest speaker. You can also sign up for our weekly newsletter. Of course, you can always reach out on social media. We're publishing more and more content on YouTube, LinkedIn, Instagram, Facebook. We're starting to do live streams, social shorts as well. Hit us up on social if you want to chat. And if you haven't subscribed yet and you want a daily stream of marketing and technology knowledge in your podcast feed, we're going to publish an episode every day this year. So hit the subscribe button in your podcast app and we'll be back in your feed tomorrow morning. All right, that's it for today.
15:54 Speaker 04 But until next time, my advice is to just focus on keeping your customers happy.
16:24 Speaker 00 Thanks for listening to the Martech Podcast, an I Hear Everything production. Looking to launch or scale a podcast like this one for your brand? Then visit iHearEverything.com.
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