Bullhorns & Bullseyes Podcast

What Is Your Data Telling You? (Or Not?)

Guests: Mark Gaskill & Christopher DuBach
March 19, 2024
Play Video about Bb Epis16 Gaskill Dubach

Episode 16
This week, the guys shift their focus from storytelling to data — welcoming data experts Mark Gaskill and Chris DuBach of the Michigan-based omni-channel marketing agency Phoenix Innovate. Curtis introduces the concept of the OODA loop, which stands for observe, orient, decide, and act, and the four go on to discuss its application in decision-making with respect to marketing and advertising.

The guests from Phoenix Innovate highlight the challenges of data overload and the potential of AI in data management. The discussion also covers the power of good data in measuring performance, interpreting data, and improving messaging. What if you have bad data? …or NO data at all?!

The conversation explores the alignment between sales and marketing, the importance of research, mutual accountability meetings, data reporting and feedback, data privacy and security, addressing the gap between sales and marketing, the need for collaboration, and the growing concern for privacy.

Takeaways:
 
  • Alignment between sales and marketing is crucial for success.
  • Research is a powerful tool to understand the target audience.
  • Mutual accountability meetings help align sales and marketing efforts.
  • Data reporting and feedback provide insights for improvement.
  • Data privacy and security are becoming increasingly important.
  • Collaboration between sales and marketing is essential.
  • Addressing the gap between sales and marketing leads to better results.
  • Why you need to add an ‘M’ to the OODA loop! (measure)
  • Privacy concerns are growing, and organizations need to address them.

Phoenix Innovate | https://www.phoenixinnovate.com/

Tom Nixon (00:02.618)
Alright, Curtis, you win.

Curtis Hays (00:05.183)
I win.

Tom Nixon (00:06.664)
Yeah. Well, last week, we did an entire episode on storytelling and I feel like I monopolized the conversation with our guest. This week, I’m out of my league as an English major because today, we’re talking all about data.

Curtis Hays (00:19.37)
Data’s right in my wheelhouse. So it’s gonna be a fun conversation today. Hopefully I get a chance to learn something today. I think you got schooled the other day with some why how what type stuff.

Tom Nixon (00:24.391)
Yes it.

Tom Nixon (00:33.648)
Yep, I got taken to school. I can admit it. Yep. Well, let’s see what our guests do in terms of education. Before I bring them on, though, I wanted to as an English major, relate to you my favorite quote in the history of literature about data. And it comes from a Sherlock Holmes tale. And he says, Sherlock says, it is a capital mistake to theorize before one has data.

Curtis Hays (00:36.231)
Yeah.

Tom Nixon (01:03.068)
instead of theories to suit facts. Your thoughts, Curtis.

Curtis Hays (01:09.494)
I, it always takes me, it’s a great quote. Um, I’ve had this philosophy. I don’t know if you guys are familiar with this at all. And we’ll have the guys jump in and we do an introduction, but. This concept of OODA loop. Have you heard of OODA loop? Um, so, you know, crazy story, but everybody knows who Top Gun is, right? Movie. There’s the real Top Gun pilots, um, from, uh, the Vietnam war area.

Tom Nixon (01:23.616)
Mm.

Curtis Hays (01:38.938)
And I think he was a Colonel who was teaching the fighter pilots. He invented this concept OODA loop, which the OODA, O-O-D-A, is observe, orient, decide, and act. And that was a continuous cycle. And he taught pilots how to make split second decisions because it’s life or death up in that fighter plane. And in the eighties.

Tom Nixon (02:04.916)
Right. Yeah.

Chris DuBach (02:06.495)
Curtis, do you know who this was?

Curtis Hays (02:08.478)
this concept got brought into business, which again, you observe the data, orient yourself around what it actually means, make a decision, and oftentimes, these last two pieces get missed, which is you have to actually act on a decision, you have to implement something.

And then you have to observe again, based off that decision, what the impact was. So it is this constant loop. So again, it’s just been a good reminder for me and process of like, anytime I’m going to do something to take a look at data, it’s gotta be meaningful data, it’s gotta be relatable to what it is we’re doing, orient myself around it, what does it mean? What’s it telling me? Come up with a hypothesis, a theory based off that data.

Tom Nixon (02:35.974)
Yeah.

Curtis Hays (03:00.006)
Make a decision, implement it, test it, rinse and repeat.

Tom Nixon (03:04.612)
Yeah, excellent. All right. Well, I’m glad I got my licks in early because I’m overwhelmed here. So, let’s bring in our guests and maybe they can react to that as a first step. So, we are blessed to have joined us today. A couple of gentlemen that I have collaborated with in the past, both professionally and personally, my friends, Chris Duback and Mark Gaskell of Phoenix Innovate. Gentlemen, welcome to the podcast.

Curtis Hays (03:06.506)
Does that go well with your quote?

Chris DuBach (03:11.493)
the

Curtis Hays (03:12.004)
Hey.

Chris DuBach (03:31.935)
Good morning. Thanks for having us.

Mark Gaskill (03:32.31)
Well, great. Yeah, glad you did be here. Yeah. Thanks for having us.

Tom Nixon (03:34.748)
Yeah. Would you rather respond to literature from the 18th century or Vietnam War era pilot theories? Chris, are you familiar with that?

Chris DuBach (03:44.499)
Well, the pilot theory is very intriguing to me only because I’d love to know who made that quote. My mom, well, let’s just say her boyfriend, she’s been, she’s, you know, my mom’s almost 80. Her boyfriend is 80, but he was one of the very first F-16 pilots and he was a training pilot. He flew A7s and prior to Vietnam. And then when the F-16 came out, he was one of the first, I think,

or pilots to fly that, the new aircraft. So I’m interested to see, but interested to know who that was because I guarantee he will know that and he’ll have an expanded story about the whole thing, I’m sure.

Curtis Hays (04:16.821)
Yeah.

Tom Nixon (04:22.563)
Mm.

Curtis Hays (04:22.678)
Sure.

Tom Nixon (04:25.56)
Absolutely. Huh? Yeah, there you go. Excellent. Well, Mark, I wanted to ask you first because like I said, we’re going to talk all about data. Curtis couldn’t help himself. He’s already nerding out but for the purposes of today’s conversation data can mean a lot of different things to a lot of different people, right? So Sherlock Holmes is talking about evidence. What just for kind of shape today’s conversation when we’re talking about data, what are we talking about?

Curtis Hays (04:25.955)
Colonel John Boyd.

Chris DuBach (04:28.075)
Oh, he knows him. I’ve heard that name before.

Curtis Hays (04:29.94)
Yep.

Mark Gaskill (04:31.085)
There’s ya.

Curtis Hays (04:40.71)
Yeah.

Mark Gaskill (04:41.915)
Hahaha!

Mark Gaskill (04:56.174)
Typically what we’re talking about is clients data that they have captured over time that tends to be transactional in nature. Whether that’s a for-profit organization tracking sales, purchase information, contact information, or a nonprofit that’s tracking gifts, that’s typically in the world of marketing, that’s kind of a good starting point for the types of data that we’re working with. When we’re talking about just simply doing

insights from data that already exists. Obviously, you can go and research and create your own data sets, you know, to be able to help learn new things. But typically when we’re talking in these types of situations and working with our clients, it’s from an existing data set that they already have that follows into those kind of criteria.

Tom Nixon (05:43.632)
Yeah. And then data, I, to Curtis’s point, data then accumulates in real time. And so when you start with a client, you’re looking at existing data, as you said, but then are you immediately tracking data before, are you doing this OODA loop? Are you starting to observe and then orient before you decide and act? Or is Curtis talking out of his derriere here?

Mark Gaskill (06:05.162)
No, it’s actually, you know, I really enjoyed that example because that’s exactly what you do. The only thing I’d add, you know, there’s definitely an M that needs to be inserted there at the end for measure, because obviously we want to measure everything that we’re doing, but other than that, no, that’s exactly what you’re doing. But, you know, first, what you really want to do, and I think that’s kind of the beginning of the kind of OODA loop concept is, you know, understand really what you have in the data. Is the data, how complete is the data? What, you know, is the data consistent?

Because over time data can collect and you can have three or four or five different data entry people over many, many years. And so you see different changes in how data was captured, which can really give you different kinds of readings or insights or sometimes some negative insights if one person does it dramatically different than another person.

Tom Nixon (06:57.772)
Yeah, and Chris, I’m curious where you think we’re heading now with AI, you know, in particular, but just if you look at the last five years, I feel like we are increasingly data rich, but perhaps knowledge poor. So, we’ve got access to all this data, whether we’re collecting it or not, it just exists. It’s everywhere, but it becomes overwhelming, maybe. And so, some companies either are

refuse to gather the data because it’s overwhelming or this there could be paralysis by analysis. And it’s just so much you’re constantly observing and you’re never iterating and measuring. So do you think, first of all, do you agree with that? And then how do we guard against that as we go forward? And it’s going to be easier in you’re going to be able to collect more data at greater scale going forward.

Chris DuBach (07:47.327)
Okay, there’s a lot there, but great questions, by the way. So I would definitely agree with both points. Oftentimes, paralysis analysis is a difficult thing to get clients over, right? If there is a lot of data or they are overwhelmed by what data sets are available to them or even what they have sometimes, right? Sometimes they have a tremendous amount of data. And when that gets in front of the right person, they don’t even realize really what’s there.

and it becomes that overwhelming motion starts to happen. So I think that’s one and then the other is definitely, or they just don’t realize what data they have or even how to collect it. Sometimes it’s just as simple as one-on-one, right? There’s data out there and they have never really taken a thoughtful effort on how to collect that data in a way that is meaningful. So both in one can lead to the other. So,

you know, while data is insanely important, and the whole, let’s stay on the Oodaloo concept, right? We’ve got to have some data to gain insights from, to move, to make a decision from. Yeah, these two things can cause, you know, all kinds of non-starters. So, AI, you mentioned AI, Tom. I think we’re AI, in my personal experience,

where AI is going to help some of this is AI is going to have some opportunity to look at data sets if AI has been driven or has been built the correct way, and then filter out some of those things or make it easier to filter out some of the things maybe you’re not that you know you don’t want to see in the data or things that maybe aren’t relevant to what you’re trying to achieve with that data. So I think AI is going to play an important part in trying to, for the average person or the average

system, clean up data in an efficient manner. At least that’s the way I see AI right now. As far as AI starting to make decisions from data, I think that’s where the hope is, but unfortunately I think AI has been developed by man. It’s going to have its inherent concerns and issues from its base build.

Tom Nixon (09:47.464)
Yeah.

Chris DuBach (10:07.539)
You know, you’d want to be careful of where that directs you if you’re going to use AI to start creating directions.

Tom Nixon (10:14.26)
In Curtis, this is very much a left brain, right brain podcast by design. Right. So the reason that you and I have hit it off professionally outside of the fact that I like men in cowboy hats, um, is the fact that like you and I. Exercise different lobes of our brain, I think. So I’m like to consider myself the creative type. You are very much an engineering mindset. So what do you, when you’re looking for data, you’re not just looking for data. Cause you like to crunch numbers.

Curtis Hays (10:25.723)
Ha ha ha!

Curtis Hays (10:31.453)
Yeah.

Tom Nixon (10:46.556)
So what does good data allow you to do from a marketing standpoint? And at which point did you need to bring in a creative person that execute on something like that?

Curtis Hays (10:58.01)
Right. Yeah, Mark, I do appreciate you bringing up, you know, measuring and adding the M because that is an important piece. I think oftentimes the first thing we’re doing with a client is measuring performance. So I think that’s helpful because it creates accountability. Data does create accountability so that…

We have specific KPIs we’re measuring to, we’re measuring performance to see if certain things are working appropriately, or even coming in as a third party to measure the performance of other parties who are assisting a client to, again, hold everybody accountable to the goals of the organization. And then I think that creates a good environment to have meaningful conversations because…

you’re hopefully speaking about truth. I’ve mentioned this before, we’re not talking about feelings in a quarterly report. It’s not like, I don’t feel like this is working. That’s the wrong conversation. I feel like early in my career, I sat with clients and…

Mark Gaskill (11:54.167)
Mm-hmm.

Tom Nixon (11:58.789)
Aw. Come on.

Curtis Hays (12:14.202)
A lot of feelings were brought up in meetings versus, you know, really talking about data. And, but that was in a world where there wasn’t as much data as we have today. So I think that’s been great. Um, I think it opens the opportunity though, to certainly misinterpret data. And I think one of the biggest areas in that, and that I see AI sort of helping with sort of, to kind of get nerdy about what Chris was talking about is.

Mark Gaskill (12:21.71)
Mm-hmm, yeah.

Curtis Hays (12:41.158)
A lot of the platforms we work in, like Google Analytics and stuff, they’ve built data models to measure attribution, where you can kind of see where you don’t have maybe direct conversion data. You don’t have the bullhorn type activities we talk about, Tom, where you’re doing branding, you’re doing other of these campaigns that don’t lead to a direct conversion action, but they’re supporting conversions, but it’s hard to model and determine whether or not they’re effective.

Tom Nixon (13:08.48)
know it. Yeah. Or they do it.

Curtis Hays (13:11.102)
Well, they, and that’s what I mean. So what Google’s trying to do from an AI perspective is build modeling to help you see that they are helping. It was actually working with LinkedIn recently where they have modeling that they can connect to your Salesforce data and model based off your Salesforce contacts, who’s actually looking at your ads, who’s engaging with your ads. Now that they’re not showing you the individual people, but they’re saying on average.

You know, the companies that are in your target accounts monthly are seeing, you know, five impressions or on average you’re getting two engagements from users, right? And then they can build a model that shows based on what’s in your pipeline from those contacts, we see that we’re supporting that pipeline because we know that people who are associated with those opportunities are seeing your ads. Again, this is not a direct attribution model. They’re not filling out a form.

Mark Gaskill (14:08.418)
Uh-huh.

Curtis Hays (14:08.594)
But they’re seeing the ads and now you can attribute some level of credit to what’s in your pipeline.

Mark Gaskill (14:18.017)
Yeah.

Tom Nixon (14:18.056)
So I’m going to turn it over to Mark here because you mentioned attribution. So that’s obviously one thing that data helps with. Um, you didn’t answer the left brain or right brain question, which for me is the messaging, right? You get better data and it forms better messaging. Mark, what else, why are you such a data, um, advocate, um, aside from the fact that maybe you’re, you have an engineering mindset as well. What, what do you see as the outcomes of good data management and observers?

Curtis Hays (14:24.232)
Yep.

Mark Gaskill (14:44.374)
Well, I think one of the things we probably can all relate to an experience when we start working with clients is, you know, we’ve all walked into that client where has the sacred truth that they hold on to closely because, you know, somebody called out of the blue and didn’t like their ad or didn’t like their postcard and they were really venting. And so, so right. So that customer is like, well, I will never do that again. Right. Because clearly it doesn’t work because one person just with the loudest voice, you know, decided to make that call. Right. And.

And so what I love about data is it takes a lot of those types of sacred cows, if you will, out of the equation and helps to kind of disprove them, right, to be able to initially say, well, that’s a great opinion. I like to look at those as, you know, just differing opinions. Well, let’s kind of take the opinions out of the equation. Let’s use data. Let’s use some strategic approaches. Let’s measure what we do so that we can really take my opinion, the client’s opinion, everybody’s opinion kind of out of the equation to be able to show real measurable results for the actions that we take.

You know what I love about that is that you can take that and that allows you then to assign a real emotional aspect which, you know, all good marketing has an emotional aspect to it too, right? Being able to then take those different types of emotional messages, be able to test them, be able to track them and really be able to differentiate not only what’s working and what isn’t from an overall perspective, but then take that a step further and get more granular when you look at kind of audience segments within data. You know, we work with a lot of clients that

We’re not communicating with five people or 10 people. We’re communicating with 50,000 people. And how do you start to think, well, yeah, one message is good across the board to all 50,000. But if I can have five messages that resonate with 5,000, 10,000 group subsets, then I’m going to be much more successful in that.

Tom Nixon (16:30.224)
Yeah. What about the client? This happens to me a lot, particularly not to throw anyone under the bus, but with law firms that I work with that they have no data or think they have no data. So, I mean, I’ve worked with law firms. We’re talking AM 100 law firms that don’t even have a mailing list like a database of contacts because in professional service, they have nothing. They don’t even have an Excel file because every attorney’s got their contacts in their PDA. Now, what do they keep on your phone?

Curtis Hays (16:48.531)
They don’t have a CRM. They’re not even using CRM. Yeah.

Mark Gaskill (16:57.73)
Not on your phone yet.

Tom Nixon (16:58.56)
Yeah. But so there is no central data. So what if so? Yeah. Oh, God. Yeah. It’s a I can digitize that problem. But so what do you do if somebody says either I have no data or we think our data is bad. It doesn’t mean anything.

Chris DuBach (17:00.443)
Neurolydex?

Mark Gaskill (17:02.288)
Yeah, your Rolodexes, right?

Chris DuBach (17:04.135)
Hey, I still see one every now and then. They’re out there.

Mark Gaskill (17:15.094)
Yeah, you know, I think that’s a great question. You know, in a lot of cases, you know, really it depends on what is your, the client’s goals are, right? Are they looking to retain their customers? Are they looking to acquire new customers? If they’re looking to acquire new customers, you know, you can go out and find plenty of third party avenues for buying lists. You know, you might not have without an existing dataset, you’re missing an asset that you can really utilize to be able to kind of investigate who is in that database and then look for like people.

that you might go out and acquire. So you’d have to kind of make more assumptions. But yeah, there’s plenty of avenues out there for data to be able to get data, build data. That’s one of the first things. How do we dump out of the guy’s phone all those contacts and start to manage them a little differently would be one of my recommendations. But I think what’s really important when you look at data too, I mean, it doesn’t begin and end with what the client has in their database. There’s plenty of ways that you can take a bad data set, make it better.

might have never updated the addresses, let’s say. And you know, what is it? I think industries say that people move on average, like 15% of people in an area move every single year. So you’ve got constantly, you’ve got addresses moving, people moving, so, but there’s ways to solve that, you know, through NCOA updates, you can use third-party data sets to not only do address lookups, email additions, appends, but also start to drill down even deeper, which is what we like to do to get more attributes about your audience.

things like their education level, their age, their household incomes, their net worth, how many children they have in the home. Again, a lot of these things are all dependent on what’s the problem you’re really trying to solve, what kind of organization you’re working with, and what are some of their challenges that you’re trying to solve.

Tom Nixon (19:00.808)
Chris, I’m curious is you’re typically working on the front end of relationships with new clients, right in a business development capacity. So, I’m curious a couple things. What do you rely on? Because I know Phoenix innovate has a different approach compared to almost every other quote unquote marketing firm, right? In a lot of it comes back to this data. Where do you see the light? Either what do you it could be the same answer. What do you like to pull out of the toolbox to maybe?

Chris DuBach (19:09.148)
Yes.

Tom Nixon (19:31.048)
reorient a prospect’s thinking around data or, and, or where, where do you see the light bulbs go off when you’re having these conversations? I know good salespeople can always see, Ooh, I think I’ve, I’ve hit a nerve in which maybe we should poke at it a little bit.

Chris DuBach (19:46.319)
Yeah, this is a great question. Yeah, no, no question. No question here, you’re a professional. So first part of that is, I think the first thing we like to utilize or try to understand is, in any of their marketing efforts, just what is the base level of assumptions that have been made, right? And try to get an idea from an early perspective.

Tom Nixon (19:48.6)
I’m a professional here. So don’t be surprised.

Mark Gaskill (19:50.83)
Thanks for watching!

Curtis Hays (19:52.111)
I’m sorry.

Chris DuBach (20:15.827)
Um, is, you know, and I just guess I’m always just like the in sales, right? A storyteller. And I think the best way is to say, look at it. If we’re, if we’re talking to a certain client and we’re all the way up the ladder, we’re, we’re the executive team and that executive team feels like. And I use the word feels Curtis, um, feels as if feels as if, um, there’s, you know, that their marketing efforts. And.

Tom Nixon (20:34.701)
You also said storytelling, so I’m listening.

Curtis Hays (20:36.822)
Thank you.

Mark Gaskill (20:36.844)
Ha ha ha!

Chris DuBach (20:45.491)
and the data that they’re utilizing all has opinions. Mark used that word and they’ve got opinions about how that data set and how they’re using that data set is affecting their overall marketing efforts. And that may be also assumptions into what their real audience looks like. We can go to a major university and talk to…

five different people in a leadership role there. And they’re gonna have really five, typically five differing opinions on why students come there, why students pick that school, why they wanna look at them. And oftentimes it’s not led by anything other than assumptions and opinions. So we like to, in the early sales process, try to vetting that out can be a little bit taxing,

once we get there, then like you said, Tom, then the light bulbs start to go off as to, oh, you know, because it is just questions, right? You know, you say that, you know, students come to this school for this reason, what leads you to believe that, right? And that’s the start of a question. And you can start to drill down from there. And when you realize that maybe there are a whole lot of assumptions being made, then we can start talking about how Phoenix approaches it differently and how we wanna use data.

And we will go the route of even offering research, right? Research is a powerful tool that we feel like gets missed a lot as an opportunity, especially, you know, you’ve got a formal research project to really drill in and understand, again, going back to 101, what does your end user, your consumer, your student, whatever that may be, what is it they really want? And have you really ever asked them?

or has it been decades of assumptions that have led you to where you are? I hope that answers your question, Tom.

Tom Nixon (22:46.928)
It does. It also brings me back to Sir Arthur Conan Doyle is speaking for Sherlock Holmes. You mentioned research, right? The capital mistake to theorize before one has data because you twist theories to suit or no, you twist facts to suit theories and not theories to suit facts. So Curtis was an Amy Schuster that came on the show early on when we started this podcast that we talked about the like the gaping chasm between the sales department and the marketing department in terms of reporting back and forth, right?

Chris DuBach (22:59.935)
Yes.

Curtis Hays (23:06.644)
Yeah.

Curtis Hays (23:16.262)
100%, yeah, she’s a chief marketing officer, fractional chief marketing officer, and that’s one of the first things that she does when she comes into a new organization, is to make sure there’s alignment between sales and marketing, yep.

Tom Nixon (23:28.988)
And you bake that into your process, which also impressed me when we first started working together, you call these, I think, mutual accountability meetings, rights, and you bake that into your process. So there’s a monthly reporting. How do you do it? It’s a monthly reporting and sales has to communicate what in marketing, it’s communicate what.

Curtis Hays (23:36.039)
Yep.

Curtis Hays (23:45.99)
Right. So we’re doing a lot of lead gen activities, helping clients with lead gen. So we don’t have any commerce platform or something like that. That’s giving us real time data on sales and, uh, with lead gen and some organizations that lag to, uh, to sale sometimes is a few months, sometimes six months, so do those organizations have a CRM, how are they reporting in that CRM? Can we get access to that data? So, uh, our accountability meetings.

are yes to report on the KPIs that we’re sort of responsible for traffic and spend in campaigns and conversions, form fills, phone calls, but we need feedback as to the quality and it’s the CRM and what happens from a sales perspective and that feedback that really gives us insights into what’s working and what’s not. And in addition, if we can take that data now.

and feed the algorithms with the qualified leads and the converted leads so that the algorithms get better and better. And I think we would do a disservice. We don’t have to talk about this now, but I think we should address privacy in this conversation that if we’re gonna talk about data, really talk about privacy. And I think we oftentimes as marketers or companies,

don’t care too much about privacy. We want as much data as we can to effectively market to individuals. But when we’re the consumer on the other side of it, obviously we want privacy.

Tom Nixon (25:26.648)
Right. And the client will often ask for lack of privacy, right? They were on a note. Can we get the email address of the person who filled out a form? Well, if they didn’t provide which we’ll come back. We’re yeah. Well, let’s come back to data security. Cause I wanted to get Mark’s thoughts on the prior notion of you say Mark that data needs to be an organizational focus and not a department focus, which kind of goes back to what Curtis was preaching.

Mark Gaskill (25:26.829)
Mm-hmm.

Curtis Hays (25:32.358)
Yeah, exactly. Yeah. Do we really need to have that cookie consent on the website? Like, you know, those types of things. So.

Mark Gaskill (25:34.453)
Oh yeah.

Mark Gaskill (25:39.07)
Uh huh. Right.

Curtis Hays (25:45.675)
Yeah.

Mark Gaskill (25:53.514)
Yeah, it’s kind of like that old adage, right? Failure to plan is planning to fail. And, you know, when you look at data, I think Curtis made some good points. I’ll use your kind of your marketing and sales analogy, but again, no matter who’s setting up the marketing, it really is a big part of the process is who’s collecting the data on the backend, whether that be a sale, whether it be a donation, whether that be an enrollment and making sure that they’re capturing as much of the information that then helps us attribute the efforts back to the marketing.

is extremely important. We’ve had clients where we’ve done fantastic campaigns for them and just for whatever reason the data person that day just decided, ah, you know, I was too busy. I couldn’t enter all the data in. So I only got the, you know, I put the check number in and I put the amount in. That was it. You know, but what they don’t realize right now is they’re missing the opportunity to say, okay, well, you spent a dollar. How many dollars did you raise from that dollar? And so…

Yeah, we’ve worked on it with a lot of organizations and it’s been an iterative process. Sometimes we have to go through one or two campaign cycles with them to really demonstrate to them, look, here are the things that you’re missing out on, and then work with them to develop processes, collaborate with them to document those processes, and then train people. Because like I mentioned earlier, you know, you might have a data person today that’s been well trained and that understands, you know, what needs to go in, what fields in your database to be able to attribute things properly. But when that person leaves,

and the next person comes in, now you’ve got this change in procedure which can really impact your overall results. That’s where to really get true value out of this stuff, you really need to have a longer term approach to collecting data. You can look at any one campaign and that’s great, you can make some decisions out of that but the real value that you get and the exponential value that you get comes month after month, year after year as you’re kind of looking at the trends.

of the work that you’re doing on the marketing side and what is doing for you on the sales side.

Tom Nixon (27:49.332)
Yeah, exactly. There’s a client who hopefully doesn’t listen to this podcast who recently reported that like, oh my god, our referrals are through the roof. Like, I don’t know if the marketing that we’re doing is working, but we’re gonna get a lot more referrals. So, don’t know why that might be. I’m thinking you don’t know why that might be. Okay, we’ve been emailing your clients and prospects every month with value. Reminding them why they stay with, oh, the retention’s

Mark Gaskill (27:54.318)
Thanks for watching!

Mark Gaskill (27:58.53)
Yeah.

Mark Gaskill (28:02.657)
Yeah.

Chris DuBach (28:05.127)
Hmm.

Curtis Hays (28:08.31)
Thank you.

Mark Gaskill (28:12.947)
Mm-hmm.

Tom Nixon (28:18.972)
which goes back to like sometimes I feel like sales teams are averse to report wins and losses and the marketing team is only concerned with the vanity metrics that Curtis just mentioned which is hey we’re setting look at all these clicks you guys got the clicks it’s up to you while you guys think both nodded your head when I said that earlier about this gaping chasm why does that exist and how are you fixing it?

Mark Gaskill (28:34.355)
Oh yeah, yeah.

Mark Gaskill (28:46.938)
I’ll go first. I mean, I think that exists because for one, you know, historically there is a just kind of a disconnect and understanding on the marketing side what it really takes to make a sale, especially when you’re talking about some of the sales like the Curtis mentioned where it’s we’re not talking about transactional sales, right? Those are pretty easy to measure. You run an ad, they go to an e-commerce website, they either buy the thing or they don’t buy the thing. But when you’re talking about more solution selling or kind of bigger investment type sales, those are longer lead times.

And that takes a real kind of personal nurturing that goes along with it. And I think that’s where marketers kind of missed the point on that. It’s more difficult to capture. There are tools though, that you can start to implement to be able to integrate those two together. You know, it all goes down to your, you know, your sale forces of the world’s. How many touches did marketing have? How many touches does sales have? Right. And at what point are we moving the client through the funnel? I think those are some of the key things that are often lost. You know, I’ll.

I do sales myself, so I’m going to bash on myself a little bit. It’s hard when you’ve got the sales mindset to kind of remember to put all that data in there, right? It’s because sales is ultimately a relationship business. And so being really focused on those relationships and nurturing that, you’re not always going to think to go click the right boxes or put those things in. So it is kind of a challenge. But it’s an important discipline that I think sales going forward here to really maximize this is going to have to master. And so what we’re doing here at Phoenix to kind of…

address that is, you know, we all have a seat at the table. So sales and marketing meet together. So when we have an objective, we define the objective first, then we work backwards and look at each side of the equation, who’s going to do what, each one of us agrees to what we’re going to do, we all have accountability, we work together to find ways to have that most integrated. But you know, even with that, it is it’s still it’s work every single day to make it happen.

Curtis Hays (30:36.807)
Thank you.

Tom Nixon (30:37.756)
Chris, I hope you play nice with the marketing team because I know in the worst case, there’s the sales person who thinks all the sales are because of the wonderful things that he did and when sales are down, it’s because marketing is not sending any good leads anymore, right? But they weren’t ever sending good leads in the first place because every sale was a relationship that I had. So, you’re right.

Mark Gaskill (30:56.518)
Yeah, right. Or that’s my favorite is, you know, I can’t sell anything because I don’t have a good brochure. That’s my favorite. Right, yeah.

Tom Nixon (31:03.488)
Well, it’s my favorite too because they hire me to do the brochure.

Chris DuBach (31:04.315)
Yes, that’s going back to you, Mark. Growing up or having almost 30 years under my belt in sales and a lot of that in heavily direct sales, right? Where I was the lead, the tip of the spear for whatever company I was working for. And I worked for some of the biggest companies in this country. And there is a…

to support what Curtis said, there’s sometimes just this vast chasm between sales and marketing. And it almost seems like the bigger the company, the bigger that can get. And it’s oftentimes, I think sales is always from a management perspective, if you look at whose idea of what sales should look like in any organization, if that person is, from a leadership perspective, is really just a

more of a classic sales, you know, sales should do everything. Sales should be the outreach engine. Sales should be the prospecting engine, right? Sales should be driving all of the, all of the activities to find and build new relationships, um, and marketing, you know, I’ve seen it where marketing is so disconnected from sales that sales has this, you know, this really built out process around driving the mountain of sales and marketing is just there to continue to keep the current client base or.

or to go out and do work around the brand or do work around company identity and things like that aren’t really sales driven. I mean, they can always help. So I’ve seen this huge chasm. And one of the things I love about here, when I came to Phoenix is, they were a client of mine prior to working at Phoenix Innovate. So that was a very different thought process and a very different…

Tom Nixon (32:37.853)
Yeah.

Chris DuBach (32:57.755)
way that they were approaching sales and marketing. And when I came aboard, Mark, who, you know, he leads our marketing efforts and I’m leading sales. We decided right from day one, we’re gonna work shoulder to shoulder all the time. And that marketing and sales, we both saw the value of understanding, if we work together, we’re gonna have, we’re gonna have better opportunities for sales and marketing is gonna have better information.

coming back as, like you said, Curtis, even just a simple CRM, right? If we have our sales team out putting in the work, filling out the data, so then marketing has actionable intel to work from, we have to do that. We have to make a decision to continue to work together and then look at it together. Get the sales team and the marketing team together and work and talk through these things. It’s alarming when you get out and start to look at the client base and you look at our opportunities to work with.

with companies of all different sizes and shapes and in different industries, how far marketing and sales are from each other or that they really never even speak. You know, it’s definitely an issue.

Curtis Hays (33:59.99)
Thank you.

Tom Nixon (34:03.064)
Yeah. It’s like I said, sometimes it’s adversarial in nature, which is just crazy to me. But so Curtis, let’s uh, I’ll let you close it out. You brought up the notion of privacy, data security. What do you want to pose to the guys? Um, as our final topic.

Chris DuBach (34:09.183)
I’m going to go ahead and close the video.

Curtis Hays (34:18.854)
Yeah, let me, let me add to what Chris just said before I jump into privacy. Um, I think, well, what I’ll often say to clients who hire us to do marketing, but the main KPI is to generate leads. Say stop and say, what you’re asking me to do is actually a sales activity. You’re asking me to fill the pipeline, which is what exactly what your sales people are doing, but you’re calling, you know, us that’s doing outreach digitally instead of picking up the phone and calling.

It’s still lead gen, which is really still a sales activity. So I think there’s this kind of gray area between what is marketing and what’s in sales and what the responsibilities are. And, um, so there is oftentimes an organization, some confusion if you don’t have the clear delineation between what the two, uh, parts of the organization are responsible for and what their KPIs are, and it might be fully functional and.

uh, operationally, uh, perform well if all marketing’s job is to support sales, provide brochures and do a little branding and it might still function right for that organization. I don’t think there’s necessarily a right or wrong, as long as you have alignment and sort of the, you know, the left hand knows what the right hand’s doing and so on. So, um, and anyway, you know, just closing that out there. I think the other thing that Amy said is there’s no one thing.

that’s gonna solve your problem from a sales or marketing perspective. So, you know, it’s sometimes the leadership is like, nope, we need to go and run Google ad campaigns and that’s gonna generate 700 leads this next quarter. And it’s like, that’s likely not going to work. And the data shows it’s not, because you don’t have an audience size that’s large enough or there’s just, you know, the amount of time to do that doesn’t make sense, so.

Mark Gaskill (36:03.34)
Mm-hmm.

Mark Gaskill (36:12.353)
Mm-hmm.

Curtis Hays (36:15.782)
the data collection side and aligning to the activities and setting the right expectations and KPIs is so critical in all of this. So then I think circling over to privacy, what I was just saying is, I think it’s just becoming the writing on the wall that we’re seeing at Kaleidoscope is it’s becoming more of a concern. I don’t think that’s coming directly. What I’ve seen recently is not coming directly from clients, but it’s coming.

from my client’s clients who are saying, hey, we’ve got this outstanding proposal, but in the contract agreement, we wanna look at your privacy policy. We wanna understand what you’re gonna do with our data, what you’re doing currently with data and make sure that you have the right procedures and policies in place. We’ve seen it recently with companies who need to get insured and their insurance companies are saying,

Mark Gaskill (37:00.328)
Mm-hmm.

Curtis Hays (37:14.474)
Hey, we need to make sure that you have privacy policies in place, that you’re handling user data securely, that you’re giving users the opportunity to opt out or to request to have their data removed. So what are you guys seeing? Are you seeing that? Like I see 2024 as being potentially a year where…

Yeah, we got through GDPR a few years ago, CCPA, which was the California Privacy Act. Now Virginia’s jumped on board. They’ve got their privacy laws. For me, the writing on the wall is like, the United States is going to come around here. North America is going to come around. And if we don’t have it, yeah, if we don’t have it in individual law in each state, eventually there’s going to be a federal law. So what are you guys seeing there? I’m curious as to your take on privacy.

Tom Nixon (37:54.704)
Yeah, Europe’s way ahead of us

Mark Gaskill (37:56.994)
Yeah, for sure.

Mark Gaskill (38:02.333)
Mm-hmm.

Mark Gaskill (38:09.13)
I’ll go first. We deal with this a lot. We have some of our larger clients that are in the healthcare space. So we deal with a lot of HIPAA data. And so HIPAA data is kind of, it’s been around for over a decade, right? And this is, I think, kind of where we’re headed, right? With the control, the management, the protection of these assets for these organizations. Because as we’ve been talking here, right? Data is an extremely valuable asset in the marketing.

you know, arena, one of the most valuable, right? And so as organizations start to invest in that, understand that, you know, and start to work with partners like ourselves, right? The safeguarding of that data, the management of that and the protection that you put behind that is gonna be extremely important. You know, HIPAA data, the financial fines to go along with, you know, breaches and those types of things, I think maybe where we are headed as a nation.

and just all of this type of privacy data that we’re talking about. Because I think with the absence of that, I don’t know that you’ll get anybody to really take it seriously.

Tom Nixon (39:15.528)
Yeah. I think we should do a whole topic. Have you guys back, talk about data security, data privacy practices, especially as the SIG unfolds. So, for now, right.

Curtis Hays (39:24.978)
And what the impact is on marketing. Like, what’s the impact if we’re not able to collect some of the data that we’re using today? What’s that impact happen on marketing and sales?

Mark Gaskill (39:31.662)
Great.

Tom Nixon (39:32.348)
Well, this is why this needs to be a future topic. So now, going back to AI, what is AI doing or not doing with respect to data collection? You better make sure you know that as well. So, alright. Well, we’ll put a pin in it as they say on the internet. We will come back. For now, I just I open the show with a quote. I wanna close the show with a quote. Tell me if you guys know who said this. Whoever jumps in first wins. Through the innovative

Mark Gaskill (39:40.962)
Mm-hmm.

Curtis Hays (39:45.654)
Thanks for watching!

Chris DuBach (39:46.014)
I’m gonna go.

Tom Nixon (39:57.432)
application of data and technology. One can develop custom solutions that resolve challenges related to revenue, audience engagement, and regulatory compliance. Who said that?

Chris DuBach (40:09.576)
Mark Gaskell said that.

Mark Gaskill (40:10.862)
I was going to say that sounds like something I said but… Right, right, yeah. That’s one of her…

Tom Nixon (40:12.992)
website. Phoenix innovate.com website. So, just a long way,

Curtis Hays (40:16.351)
Hahaha.

Chris DuBach (40:19.609)
That would lead to our head marketing person, Mr. Bart Gasgill.

Tom Nixon (40:22.72)
Yeah. Yes. Mark Gas kill, right? Exactly, Mr. Dubock. Alright. Well, yeah. I just wanna do a roundabout way. Plug the website, PhoenixInnovate.com. Mark Gaskell, Kristen Bach. Thanks so much for coming on. Come back again. We’ll nerd out about uh data but if you ever wanna talk about

Mark Gaskill (40:25.59)
Thank you.

Mark Gaskill (40:40.27)
Oh, I would love that too. Yep.

Chris DuBach (40:41.723)
Yeah, that would be a cool session. And we’ll be back anytime you guys want us.

Tom Nixon (40:47.52)
cool. Alright. Yep. Thank you and we’ll talk to you next time. Hopefully not so nerdy next week on Bullhorns and Bullseyes.

Mark Gaskill (40:47.562)
Yeah, appreciate you guys’ time. Thanks, Tom and Curtis.

Chris DuBach (40:51.257)
guys.

 

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Additional episodes:

Episode 12

Episode 12: What is Marketing Attribution?

Tom & Curtis discuss the topic of marketing attribution, the methodology of attributing a purchase or lead to its source in a marketing campaign.

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Episode 5: Aligning Sales and Marketing

Fractional CMO, author and frequent podcast interviewee Aimee Schuster joins our pod to break down her view of what ails many sales and marketing departments in organizations today.

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Episode 4: Going Meta on Bullhorns and Bullseyes

In a very "meta" episode, Curtis and Tom discuss the meaning behind "Bullhorns and Bullseyes." What are some examples of "bullhorn" tactics, and what are some examples of "bullseye" methodologies?

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