633: 5 Ways Your Brand Can Leverage Data to Drive Better Results w/ Andrew Fischer

ABOUT THIS EPISODE

In this episode we talk to Andrew Fischer, the CEO and Co-Founder of Choozle.

LinkedIn: https://www.linkedin.com/in/andrewfischer11/

Looking for a guaranteed way to create content that resonates with your audience? Start a podcast, interview your ideal clients and let them choose the topic of the interview, because if your ideal clients care about the topic, there's a good chance the rest of your audience will care about it too. Learn more at sweet fish Mediacom. You're listening to the be to be growth show, podcast dedicated to helping be to be executives achieve explosive growth. What you're looking for techniques and strategies or tools and resources? You've come to the right place. I'm Jonathan Green and I'm James Carberry. Let's get it into the show. Welcome back to the BE TOB growth show. Today we are joined by Andrew Fisher. Andrew is the CEO and Co founder at Choosel Andrew, welcome to the show. Thank you. I appreciate you having me on. Jonathan, excited to be here. Well, we're excited to have you, Andrew and and today we're going to be talking about sort of this idea five ways that brands are leveraging data to drive better results, and I'm excited to dive in. You've you send me sort of the the breakdown ahead of time. But before we get into today's topic, I'd love to hear a little about what you and and your team at choosel are doing these days. Yeah, again, I excited to be here and looking forward to chatting data with you and how we work with brands on a lot of data and our agency partners to and yeah, I guess you know, we create a chooser as a self service data driven advertising platform and we typically work with independent advertising agencies and brands direct to help them leverage data, Boast First Party and also third party data to both build, optimize and make more effective their digital advertising campaign. So that's the space we play. We've been doing it for a little over five years. We were founded in the fall of two thousand and twelve and have...

...continue to grow pretty rapidly. I think we were rated as the inks hundred thirteen fastest ground company last year. And Yeah, we're excited to help our partners and continue our growth in a two thousand and eighteen and beyond. That's fantastic. And and yeah, actually, the the ink list is definitely one of the reasons that we sat up and took notice and actually reached out to you so that we could kind of tap into your expertise, you know, for our show and and share that expertise with our listeners. So you're definitely the right person to be here with us today talking about this the again, the five ways that brands are leveraging data to drive better results. I'd also like to say really quickly I kids when you said been around for five years. I founded in two thousand and twelve. That sounds like two thousand and twelve shouldn't have been five years ago. I don't know where the time is going, but and there was two thousand and twenty before we know it. Here it's a little cow. My goodness, you're not wrong. So yes, congratulations on your five years of success. So let's Andrew. Let's just dive in. Where are we? Where are we starting today? kind of I think this idea of there's an interplay between marketing automation. You the CRM and they add automation. Tell us a little about that. Yes, absolutely, and again, functionally we often work out at the advertising agency level because a big part of our platform also is the media or the ad buying piece. But I'll speak kind of from the marketers point of view. Knowing that the agency is typically involved, if not the facilitator, of this enterplay. Marketing Automation, you know, pretty straightforward, whether using hub spot, Marquetto Aloquoi or even, you know, I would say, more price friendly platforms, basically about communicating with current clients with prospects, developing sequences, leveraging content in terms of either selling new prospects that you have in your database or cross selling, up selling or building relationship for engagement etc. Marketing automations a pretty...

...straightforward concept that most people are leveraging nowadays. Then how that interplays with the CRM, as I mentioned, which is typically going to be your customer database and your customer data platform, the repository where you keep a lot of that information and most of those systems, you know, talk pretty seamlessly nowadays, where you can get information from your campaigns to your marketing automation, whether it be email or otherwise, and how that can be then appended in to a sales force, as an example on the crum side, but again people using Zoho, sugar, any number of crms. Then where we would play would be kind of what we call add automation and discussing how that date is kind of transferred between the two. Is kind of to illustrate how we would be leverage. So system like choosels, which is, you know, what we would call on the demand side of advertising, or the Byside, is we can absorb data directly from a crm system, typically in the form of emails, and then once that's data is on boarded into Choosel, will do a digital match. So on the desk top that would be matched to a cookie and in a mobile environment to a mobile ID. Match rates typically or between fifty and seventy percent. If it's a consumer facing type of cerrum list and it's be to be there, typically a bit lower. And once that date is match, we can provide, you know, a couple key pieces analytics and so we can provide a ton of rich information on those individual users. And this would be an aggregate and anonymized but we'd be able to tell, you know, a client that, hey, did you know that twenty two percent of your current folks in your crm you drive this type of car, they've got this type of purchase behavior. They are information sciences. They carry a se level title, literally tens of thousands of bits of information that we can provide on the analytic side. Then of course that then feeds into the media execution piece. So these are our best clients, let's target them with this type of campaign or model that data and find other people that look like them. So it's kind of a basic enterplayer between the marketing automation see Drm, and then where we would say it would be this advertising automation piece.

Interesting and so and I know one of the things that we were also going to talk about today is kind of understanding the difference between First Party data and third party data. What does that look like? Yeah, absolutely so, as you can imagine, intuitively, First Party data is essentially data that you own and the most common relationship for a brand into where its agency is a current customer, someone that's purchased a product from them before and or someone who has signed up for an email list that has opted in to be a part of a relationship with this brand. And so anytime that data is collected or stored and you've got permission, that would be your first party data and it's a highly valuable asset obviously, and brands, more than ever, have a lot of ability to leverage that data for growth and it also becomes even more important. And not to get too far to the weeds, but regulation that's changing in Europe, which is called GDPR, is going to make it even more difficult to leverage anything but first party data where you've got a direct relationship. So to contrast First Party data with third party data, third party data, would almost be thinking of it as other data that you can essentially rent or leverage for the purposes of targeting, study up campaigns etc. So, as an example, within the chooser system, we have a highly extensive database powered by multiple third party partners. You know, everyone from you know folk like experience that are in the data field, to Master Card, to publicly available census data, etc. So these data segments. Again, irrespective of whether you have first party data, you can always leverage third party data to build a campaign. And then how they often enter play is, you know, on boarding your first party data, the data that you own, typically customer records. Once you've provided rich annalytics and you say wow, okay, we've got a very high propensity for folks that drive this type of car with this type of job level in this geography, then you can model after the...

...third party data to create a bigger audience. If that process is automated, it's often called look alike modeling, and then you can have a bigger pool third party data for targeting new prospects, as an example, and that's a pretty common flow and it's often referred to as account based marketing. So pulling my accounts, I can do set up campaign specifically to them digitally. By the way, when it's not talking about a campaign, we primarily playing the display world, so think of banner advertising, Video Advertising, mobile advertising, anywhere across the web. I'm not talking about search and social, which are often complimentary, but not from our platform. So that's kind of how you can leverage first party data to set up campaigns and also how it would work to third party data and the distinction between the two. And again, to summarize again, first party data is really the data that you own, that's day you've collected with permission from current clients and prospects. Yeah, and and so I you know, and I know that I'm sure most of our listeners are from familiar with the concept of third party data. But that's also you know, it's there's there's also an investment. There you are. It's like you said, it's it's a data that you are renting or buying and there's a lot that can go into it. But you know who you're who you're getting that information from, how it's being scrubbed. You know that, just in terms of the effectiveness of that. That takes a lot of it takes a lot of research to know what you're doing. But I think you also have some some ideas on really how to enrich the this first party data with analytics. Let's talk about that. Yeah, absolutely. So you know, and you should think of choose a little almost as a kind of your seat into this data space, and we partner with a lot of larger companies, enterprise level companies in the data space, which will include in your live ramp and axiom, the Oracle data cloud, and there subsidiaries including Blue Ki, and so choose all does. We have our own choose IDs. We have a data graph with the ideas that we're going to enrich your first party data...

...with some of these major companies that are huge holders of first of their own first party data, which is your third party day, that you can match against, and that's what becomes really cool, and I one thing that we've done a choose little really democratize this based on our partnerships of a lot of these bigger enterprise level players, whereas it's very difficult to build a relationship directly athoricle, as you can imagine, just in terms of cost, you level of commitment, the time of a contract. You know, we've kind of democratize that. So even if you're a smaller, medium sized brainder agency, you can leverage the choosel tools more on a one offf basis. But so get the power of these these huge partners and in effect that would be you know, I take my ten thousand fiftyzero five million email addresses, on board them in a choose al and we're automatically going to match them against these multiple third party data partners. And so it's really neat. You know right off the bat you're going to get all this rich information and we break it in a specific categories of purchase behaviors, betb data buyers and tent demographics, and so as soon as you're on board the data within twenty four hours, you can do really cool things on the analytics level and you know the analysis. that we had now understand the breakdown and gender and demographics and household income and education, and you get even more grain learned to purchase behaviors and habits and what's cool about our platform and others that maybe like it is you can start to use that data analysis to start building out campaigns and say, you know what, we've got a product that we know is going to be from our high income users, but also have these other characteristics, and we can combine those data sets and what we call audience builder, so you can leverage your first party data match against the third party data for analytics and then really start to segment and build out specific audience targets and a campaign could just be limited to those people. You could say, well, I on board of this list, I know the recent purchasers, so I want to then segment out and say I want the high income people, so I want to try to resell across all this product. But also we can model the data, which means an algorithm will take let's say your twozo best customers are the ones that...

...purchase last month, and then we can use the data that's mashed against the third party data sets to say here's what these people actually look like, then let's go find in the universe of North America hundreds of thousands, if not millions, of people that look like that to create a look like audience for targeting as well. So those are some fairly straightaway kind of tools and methods of leveraging first Party data against Third Party Day for the purpose of typically growth. Got It. And so, Andrew, let's let's get into this idea of creating a virtuous digital marketing cycle. Tell me like kind of what that is. I I'm sort of I'm drawing a blank. I'm starting from scratch, so talk to me about it as if I was a child. Yeah, of course. So unique over the last few years is the amount of data, and again it can be overwhelming and somewhat intimidating as it's grown, and the over usage of certain terms including, quote unquote, big data, etc. But in a very straightforward example, about creating kind of a virtuous cycle. Right, we talked about the first part of that cycle, which would be leveraging of your first party data, and he and I do want to stress that you don't necessarily need to have first party data. Let's say you're a new brand or you're creating a new product sector, you can come in and leverage third party data based on your best guesses. And what's Nice about digital data driven digital marketing and today's world, especially via a self service platform, is you can test to iterate very quickly and that's a part of the cycle. So, again, whether the campaigns informed from first party data or you know, past information, or we're going to start doing some prospecting based on our best hypothesis of who we should be targeting, those campaigns can be set up very quickly. They can be set up to run. You're going to get real time information feedback on the success of the campaigns. And again, platforms like choose on on others. We can do this because we're measuring to a specific action. Typically that's going to be online. The can be offline triggers as well. That can be measured but, as imagine, the measurement cycle is much more manual and not in real time. But let's...

...say you're a be tob marketer and you're looking to drive downloads of a white paper, because we have our smart tag container on the client site, we can measure every time that that papers downloaded and then optimize to the source of where that came from. So the data real time is going to optimize the actual campaign and it's the simplest thinking of okay, we served, you know, two hundred Tho Impressions, a hundred thousand here and a hundred thousand there. The system is basically a be testing in real time to understand what successful and then naturally the system will then push impressions towards the source or the publisher that's producing a higher conversion rate. And it's doing that in real time and not just across two websites, often hundreds, if not thousands in real time to drive the best overall performance to a campaign, again against a specific action, and in this case would be the download of a white paper, to kind of complete the cycle. It's cool as the the the people that we have converted or download the White Paper One, we've captured their typically their information via email. That can be fed directly back into marketing automation and serum, of course, but even at the website level, on an anonymous and aggregate we're going to measure the analytics on those converters and so that is already kind of built an audience within the system that says here's the tune. You know, the two thousand people that downloaded the white paper. We've captured that particular ID and you know what, we're providing analytics against that subset as well. So of your brand new customers, you have a truly rich information on who they are. Can drill down on who downloaded this white paper. Again, all those same rich analytics that we would provide against your first party data, we can do it on the website level too, so that informs the campaign and its success. Now worked, and then that particular audience can then again be pushed into our audience builder, into the by side, and or modeled. So often a sequence. Maybe now that they're downloaded the white paper, let's serve a sequential message or campaign to them. That would make sense after they downloaded it. and Or, you know what, let's go find two hundred thousand people that look like those two thousand through data modeling and set up another campaign or, you know, poor more gasoline onto the current campaign.

So the data both informs the media execution and the optimization of the campaign itself, and then the results can then be analyzed and automated back into the by side of the system to kind of create that cycle. This the virtuous cycle, as we've discussed. Very cool. Well, and Andrew, as you've mentioned, as you mentioned earlier, you know, there is more data than ever and can be can be intimidating to think about how do I leverage it, what's important, what's not? I mean it's just you've got all this information out there, like, what do I do with it? So it's so fantastic that we're able to bring on experts such as yourself, well, obviously no, quite a bit about data, to come on the show and sort of share that information with our listeners. So, and Andrei, I had prepped to you before, before we got started. You know, you started, you help start choose all, like you said, five years ago. We've been asking a lot of our guests. You're a founder, a cofound or a CEO. What's kind of the legacy that you are looking to leave? I mean, whether it's through choose al or it's or you're, you know, even looking down the road do to something else. What is that? What does that legacy look like? Yeah, and you know, I've got many outside interests outside of choose a little that ideally you can pursue at some point down the road that might be much more meaningful than data driven advertising. But as we stand here today, you know, I my legacy, especially in relation to choose Al and what we've been doing over the last five years and what we hope to accomplish over the next several years. It really comes down to the people and you know, I highly doubt when too formal choose employees get together ten years from now, I doubt they're going to be talking about a specific campaign or a data strategy or a client. They really talk about their experience of working together and we've we've been very intentional about our culture since we started the company and we've grown over sixty employees now and it's it's my my greatest achievement is not necessarily revenue growth and or you certain...

...financial metrics or a new product that's been highly innovative, but the fact that we've been consistently recognized. You know, we were recognized as a age is number one best place to work last year and our retention rate has been extremely, extremely high, and that's the legacy I want to leave. I want to create an environment and a company that's an excellent place to work, and the one thing I've learned over time to that's not just about, you know, being a cool and or comfortable place to work right. It's not just about, you know, having kegs of beer and ping pong. All those are nice things to have. It's also really about challenging people and having them grow. So it really focus on both sides of that being a great place to work and its achieving that through making people grow and become better employees and better people, hopefully over time as well. So again, I hope that's our legacy, that when people look back and we've got this incredible network and fraternity and Sorority down the road at these these folks have had an amazing experience and we've helped to grow their career over time. Well, that's fantastic. I mean, of course the the revenue growth doesn't hurt, but I love that answer. It's fantastic, Andrew. If anyone in our audience, if any of our listeners, they're interested in following up with you about today's topic or they want to learn more about choose all, what's the best way for them to go about doing that? Yeah, you can find US online, of course, at our website, choose ALCOM s h o zeliecom. We've got a lot of great information on our product, our platform, a great blog with a lot of information. You can follow me personally at twitter. I'm at Andrew Fisher underscore one. Yeah, and we've got our twitter handerlay out choose at as well. We love to hear from anyone that wants to learn more. Yeah, and if you're curious learning more about data driven advertising in or just don't want to reach out personally to me, I'd be happy to happy to connect wonderful Andrew. Again, thank you so much for your time today. Was a pleasure having you on the show. Likewise, thanks for having me on. It's been awesome. There are lots of ways to build a community and we've chosen to build the BEDB growth community through this podcast.

But because of the way podcasts work, it's really hard to engage with our listeners and without engagement it's tough to build a great community. So here's what we've decided to do. We're organizing small dinners across the country with our listeners and guests. No sales pitches, no agenda, just great conversations with likeminded people. Will Talk Business, we'll talk family, will talk goals and dreams will build friendships. So if you'd like to be a part of a BEDB growth dinner in a sitting near you, go to be to be growth dinnerscom. That's be toob growth dinnerscom. Thank you so much for listening. Until next time.

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