Linda Harrison:

Hey, thanks Scarlett.

Jeff Patterson:

Thank you.

Scarlett Burks:

Jeff, I love that you called yourself a student of data on LinkedIn and talked about how you collected, captured, and catalog data points on everything as a kid, not to judge, but I think that implies you were a data geek from a very early age. Give us a snapshot of your background and tell us how you came to be in your role at Acxiom today.

Jeff Patterson:

Yeah, well, since I was a little kid, I don’t think I realized it was data. That was the late 70s and early eighties, but I loved baseball. I loved baseball cards, but I’m not really like the graphics. That wasn’t my thing. It was the stats and taking those stats, creating new ones. I ended up kind of turning that into game design over time, so always kind of had data in mind before I really knew it was data, and I guess that’s probably what led me to my career. I started off in the 90s at a company called ALC or American List Counsel. Now Adstra got a really good education on data from a lot of experts who had been doing it a lot longer than I had, compilation. Later, went to PMX, now Assembly Global on the agency side.

I was there for 17 years. I ran my own agency internally, part of product, and ran product, part of the analytics team, part of the digital team before I headed off to one of our competitors Data Axle and got a pretty good education there as well. More on the sales side than anything, which is something that I never really never had as part of my resume, and spent a little time in between there and Acxiom, playing with data clean rooms at LiveRamp. I feel like all the things I’ve done led me to this role and being able to jump in and contribute really quickly.

Scarlett Burks:

Awesome. So you liked data before. That was cool.

Jeff Patterson:

I’m not saying I was cool. Let’s just put that…

Scarlett Burks:

Oh yeah. Oh yeah. Well, I think it’s fair to say we’ve been around this industry for a while, a few decades at least for all of us. So Jeff, what is the biggest change you’ve seen? And then on the flip side, what has consistently stayed the same?

Jeff Patterson:

Well, I think if we just think about channels from that perspective, that’s the biggest change. If I think back to the 90s, we really had three things that we were working on at that point in time. It was direct mail. I didn’t really play an insert or print, but those were the three primary channels. Email still wasn’t a big thing. So obviously since then we’ve had a pretty solid run of new channels, whether that’s display, social, CTV, OTT, whatever’s going to come in the next couple of years.

But one thing that hasn’t changed it is data itself. The privacy around it’s changed, but all the stuff I learned back then still applies now. I still put a lot of those same practices into play. And I think in all honesty coming up at that point in the industry, I got such a good education on data and I don’t know if that always carries over to all the companies that we work with. We looked at it in such a different way. I feel at times. Not so much here at Acxiom, but if we think broader data sets have gotten a lot more broad in nature, in my opinion, and how we use it with audiences moving away from lists, but the crux of data, how we use it, how we deploy it, why it’s so important in the overall mix. I think all that stuff’s still the same.

Scarlett Burks:

Linda, anything different you would add in terms of change?

Linda Harrison:

Well, I’ll agree that the old days taught us a lot about analytics, about finding the right people. That’s the part that hasn’t changed, that I’m still, no matter what channel I care about, finding the right person for the right thing. And how I do it, where I do it has changed how much I pay for it, do I pay for it? Things like that have changed. And how I’m retargeted, remarketed overtime, that has all changed, but really the whole industry is finding the right person.

Scarlett Burks:

It comes back to that.

Linda Harrison:

So Jeff, you’ve worked across numerous industries and you’ve focused on about every channel campaign type. What’s your process for helping a client find and match the right tactics to the objectives they want to achieve?

Jeff Patterson:

Yeah, I think when I kind of first meet a client and we start to work together, what are your goals? What are your budgets, what do we have to work with at that sort of starting point? Once I get a little deeper on that and have an understanding, I want to talk about KPIs. So how are we going to judge this campaign or these campaigns that we’re going to run and put together? I like to then move over to audience development thinking one about what are the campaign goals? Structurally, what are we building? I want you to then take those insights into how we build audiences, and that could be in part how we ask for data if we’re going to do some models or do a data portrait analysis just to get better insights from a bullion segmentation perspective. But I think that’s all super important in how we cut that initial file to build those audiences off of.

I’d like when I can to have those conversations around creative to make sure that the offered audience messaging strategies tie up and link together and we’re not off anywhere, and then I’d just like to see it through deployment and have a hand in the measurement as well. Not from a grade our own work kind of play, but just to ensure the measurements done properly so that whatever we learned from that campaign, we can feel good about those findings so that we can continue to move that forward, make the edits we need to make, continue testing, beating controls, et cetera, if I take a pretty structured approach.

Linda Harrison:

I couldn’t say more, knowing the KPIs, what success from the client is such a key care about that, we tend to just gloss right over. It’s just, let’s get going instead of what’s a win?

Jeff Patterson:

I agree, Linda, and I think that’s also where us doing a little bit of work to understand those KPIs, put together some figures on expected response rates, conversion rates to make sure that we even have a shot to hit their goals and targets. I don’t think any of us want to put the time and effort in for a one-off, right? We’re looking to work with someone for a long time, do great work, iterative work, and it has to be something that we feel good about being able to accomplish, otherwise we’re just wasting everybody’s time and me. And that though sometimes leads to better questions. Why are those your goals and where did those KPIs come from? I think about different markets and what those KPIs look like and what they’re looking to get back and how LTV doesn’t or does factor into that? So many questions, and I think it’s really imperative to spend the time upfront with whomever we’re working with, agency or brand to understand that, to put the whole package together.

Linda Harrison:

So I’ve been working a lot with our product email connections, formerly known as eProspecting, and the qualification process is critical because you want to make sure that at the end of the day you’re moving the needle. I don’t do as well selling bubble gum on an email campaign or a direct mail campaign. And I’ve had people ask me to do a bubblegum campaign digitally to people who don’t chew very much gum, and I thought, I chew a lot of gum at least till I got braces. Now they won’t let me. But I chewed, I don’t know, 15, 20 pieces a day. I mean, I’m in the high heavy user. To get me to buy more gum was a heck of a lot easier than to get the non gum chewer to start. So you have to balance those rewards of moving the needle, getting lifetime value, encouraging new versus pushing up a layer, people who are already using your product.

Scarlett Burks:

I love that. Y’alls conversation gives me a perfect word picture of sitting in front of a control panel with all these different levers you can adjust to get to, like you said, to that ultimate destination, what’s that win for the marketer? So Jeff, when I think about millennials and Gen Z, my kids, who have grown up with technology as a constant presence in their hands and lives compared to my mom who still wants to know if it’s okay to order something online using her credit card, how drastically do you see tactics change when marketing to different age groups?

Jeff Patterson:

They are pretty drastic, but at the same point in time, I think the one thing that the smartest brands get is that you can’t treat everyone in a generation the same. It’s a good qualifier, but I can even think about myself and my brother. We’re less than three years apart, my sort of aptitude for technology is significantly higher than his. And the same thing with if we look at the boomer population, they’re not all the same. Some of them are incredibly advanced with technology more so than Gen Zs or millennials. So I think we have to factor all that data in. It’s almost like when you think about the importance of identity and how that can tie all the pieces together within that CRM or within that CDP, that’s incredibly important.

When you have all those kinds of signals and insights, you can think differently about someone, I would definitely caution against generational marketing as a whole and just using it as your persona only. But certainly from a creative messaging standpoint and language, there are things going to connect a lot better with Gen Zs than they are Gen Xers or boomers or whomever, just because we do speak a little bit different language. But I certainly would caution against making broad swatches of beliefs because you’re going to get burned eventually with that, and that’s why we use a lot more data than just one data point typically to come up with segmentation strategies.

Linda Harrison:

Yeah, I agree. There’s psychographics, there’s early adoption technology stages. My husband’s not that much different in age for me, but I am totally the IT specialist at the house, and even for my daughter who is in Gen Z, right? She’s like, would you fix this mom? And I’m like, yeah, I got you. So we’ve got to use more analytics, more data, big data to figure out really who’s in market or the product or service that’s going to fit that person and to not talk down to me just because my age, right?

Scarlett Burks:

Right. Yes, that tech-savvy Boomer can be completely different from the Gen X that, like you said, doesn’t have much of an apt for technology at all. All right, Linda, is there anything new you can share from Acxiom’s data and services toolkit to help advertisers deliver more relevant experiences?

Linda Harrison:

We’ve got more and more analytics on our side. I’m really working with the analytics team on making them more robust, easier to get to at Acxiom, remove some of those barriers, help our sales team find the right opportunity for our client so that we really dig deep and find what’s going to work for them. So we’re doing more analytics, more models, more data portrait analysis, and Jeff has brought to me a whole bunch of calculators, so…

Scarlett Burks:

Ah-huh.

Linda Harrison:

He’s good at math. So we’ve talked about being able to understand what is it going to take to make this campaign work for you? Where’s your bottom line? What’s your incremental return on ad spend that you need to have happen, and what will we have to have to make that go through? I had a client come to me and say, if you can double the return, I’ll do it. I was like, I don’t know. We’re not changing anything, but switching to Acxiom, you’re bringing your own creative, you’re bringing your own segmentation. All it is my team doing the work? That’s a push, right? I mean, we’re good, but you have to let me change another attribute in order to make it happen. So we’re really being fundamental in the analysis portion and making sure that we’re going to make the right choice for you and your clients.

Scarlett Burks:

Jeff, we’d like a guy who’s good at math. And can you Googly in a sentence, I just have to tell you that. So Jeff with an advertiser told you they didn’t know where to start to improve campaign performance. What would you advise them are the three first and most important steps?

Jeff Patterson:

Yeah, I mean, great question because we hear it pretty much every day, and I think the first step in that process is to dig in and what did you do? Let’s look at the creative, let’s look at the audience. Let’s look at the channel or channels that they deployed in, get a sense for what was done. I think then it’s we take data in or I would like to take data in to get a sense of who their customers really are. Because what I find typically when someone has a poor campaign, something was off, and typically it starts with audience or creative. It’s one of those two things almost all the time. So I would like to get under the hood and understand that, and again, keep being cautious not to tear apart what they’ve done, but just show them how we could do this better through analytics, through strategy, through data, really, how can we come up with a better process here?

And whether that’s us handling everything or just having a seat at the table, but I really want to make sure that channels married in. So again, kind of back to if we’re going to build a model and build some custom audiences for them, let’s have a seat at the table around what they send us. A lot of times we’re just so happy to get data in, but data’s not created equally. And if we’re trying to accomplish, let’s say we only want to go after those very high value customers, but they send us a cross section of their database, that’s not a helpful way to do it. What I want to see is, well, how do you define those customers and let’s take a cut of them so we can start with the right audience and build the right audience. Because a lot of times it’s limited resources, so if you can get a tech person to pull data for you, you take whatever they send, but that’s not the best way when you’re talking about the kinds of investments that marketers are putting into these programs.

So I really would just pull it apart and kind of rethink it, make sure that structurally there was nothing wrong. And if there is, just show them the light and how can we get to that next phase where we have a successful campaign that we can start to build on and improve from. But also the other side of it, the biggest question or two biggest questions, were your KPIs logical? So did they really make sense? Were you ever going to be able to hit those KPIs from a starting point? And then back to measurement, how did you measure this campaign and was that really a best practice or did we miss a whole lot of conversions that really made this campaign look poor, but was really actually a strong campaign if a different measurement process was put into place?

Linda Harrison:

You can’t rely on QR codes alone or on personalized unique links. That’s not going to be the end of the day. People could come into your store, they could go to the website naturally, things like that. So you can’t count just one… Or a coupon code, you can’t just count it one way. You have to look at the whole compared to a true control file that’s representative in nature.

Jeff Patterson:

And that’s a good point, Linda. And I think back to one time something similar happened and I said, okay, let’s get to the bottom of this, but first, how’d run your measurement and they ran it in Excel and it was just exact matches. And if you think about Jeff Patterson, I can show up as Jeff, Jeffrey, JP. The way they ran it didn’t account for any of that. It had to have everything exact. So of course the measurement looked horrible because there was no fuzzy logic baked into that, nothing else was taken into account. So we see all sorts of reasons why campaigns either don’t perform or appear to not perform. So I think that’s our goal is to get to the bottom of it a little bit of investigative work

Scarlett Burks:

And helping them take that holistic view. I like that. All right. Well, I had a big milestone yesterday, you guys. I connected on LinkedIn with my middle child.

Linda Harrison:

He must not have known it was you. He didn’t know it was you.

Scarlett Burks:

No, actually he gave me permission, but he hadn’t put his photo on there yet, so I was like, did I get the right person? But he is the kid that has the finish line insight for college, thus the LinkedIn profile and applying for internships. But I have another younger one who is deciding where she will go and what major she will choose for college. I find myself talking about computer science statistics a lot. What guidance would both of you give to millennials and Gen Z entering the workforce about dipping their toe into this industry we work in?

Linda Harrison:

I’d say it’s a lot of fun.

Scarlett Burks:

We do have a good time. Don’t we, Linda?

Linda Harrison:

We do, and you get to reinvent yourself with data and statistics because things change a lot. I don’t think there’s another industry that changes as quickly and in unforeseen methods. So I think it gives them a broader idea of where they want to go next.

Scarlett Burks:

How about you, Jeff?

Jeff Patterson:

What I would say, and so I have an 11-year-old nephew, or soon to be 11 year old nephew. I don’t have kids of my own. And he has a really high aptitude for math. So I’ve been talking to him about data science. There’s an unbelievable shortage of data scientists out there. I think it’s a phenomenal career, and if you can dual track it with some kind of technology field, whether that’s computer science or whatever it is, I think that can put together some pretty amazing tools for that person for the future. When you think about where data science is going, what data scientists have to know about their tech stacks, I think that’s where I would push a kid with the right aptitude for that.

But I do love this industry. I wouldn’t want to work in any other, as much as I think the client side’s interesting, we get to do something different every single day on our team. We get to work across pretty much every vertical, touch all the products. So it is fun for the right kind of person. You got to be a little nerdy probably, but if you sit in that space, I think it’s a great career.

Scarlett Burks:

I agree. I’ve been at Acxiom a long time and people will say, ah, how have you been there that long? And I’m like, but it hasn’t felt like working at the same company the whole time, just because of what both of you said. The industry, the technology, the people, the channels have all changed so much. It’s been quite the ride.

So back to those Super Bowl ads I mentioned earlier, when I was previewing some of the ads that had been released early, I saw that the theme for this year is definitely bring on the celebrities, Miles Teller, Nick Jonas, Meghan Trainor, Sylvester Stallone, Steve Martin, and even Elton John, got into the act for Doritos. Are there any you have had a chance to see and give us thoughts on what the brand’s data strategy might have been? Linda, you want to go first?

Linda Harrison:

I looked at the booking.com with Melissa McCarthy, and I thought that was very humorous. And of course at the end, she goes, as long as they have childcare. That she wants to go anywhere as long as they have childcare, which is funny, but it doesn’t resonate with everyone. I want to go where you don’t need childcare because I want adults only vacation. But it does bring up that whole idea of adults only in a way too. And then I also like to the Workday ad with KISS and with Ozzy Osbourne.

Scarlett Burks:

Oh yeah.

Linda Harrison:

And that everybody’s a rock star, and you can’t be a rock star. They are the real rock stars. But you know what, we’re also rock stars.

Scarlett Burks:

There you go.

Linda Harrison:

I mean, I don’t know what their segmentation strategy is, but I found those the most humorous and in touch with my timelines.

Scarlett Burks:

Yeah.

Linda Harrison:

Jeff, did you see any of them? You probably just watched all the beer ads.

Jeff Patterson:

I have not watched a single ad. I do my best every year not to and kind of take them in during the game and keep account of what I liked and what I didn’t like, but I try not to see any of those. If I have seen them, I didn’t recognize them as Super Bowl ads yet, so I guess we’ll just wait for Sunday to get in and see who the big winners and losers are.

Scarlett Burks:

Well, there you go. That brings us to our wrap up question. Jeff, who’s your pick for the Super Bowl on Sunday?

Jeff Patterson:

As a Steelers and Giants household? I just can’t say the Eagles. So sorry to all, I love Philadelphia, but I’m going to have to go with the Chiefs.

Scarlett Burks:

What about you, Linda?

Linda Harrison:

Yeah, I’d prefer it if the Chiefs won, but at the end of the day, it doesn’t really change my life. Just saying. And they don’t know if I’m cheering for them or anything.

Scarlett Burks:

Yes, I would agree. I’m not super invested, but I do like Patrick Mahomes, so I would make it unanimous for the Chiefs on this podcast.

Jeff Patterson:

It’d be fun to see him win with a little bit of hobble in them still, but I think it’s going to be a great game.

Scarlett Burks:

Yes. Well, it was heavily rumored that Treylon Burks from the Arkansas Razorbacks was going to go to the Chiefs at one point. So, very sad that didn’t happen, and we don’t get to cheer for him. But anyway, by the time this podcast is released, we’ll know the final score of the game and how good all of our instincts were. Thanks so much for the conversation, Jeff and Linda. For our listeners, you can find all our Data Guru podcast episodes on your favorite podcast player or at acxiom.com.