Joe Seale is VP and Digital Analytics Manager at Fifth Third Bank, headquartered in Cincinnati, Ohio. Previously, he served as the bank’s Senior Human Capital Analytics consultant. He’s also a web entrepreneur who founded the site mommydaddydeals.com, which offers weekly online savings on items and activities of interest to parents.
Key Learnings:
1. When presenting your analysis to a client, give your recommendation(s) first, then follow with the “whys.”
2. No analytics professionals have all the answers. It is wise and even essential to ask questions.
3. Companies considering a new analytical platform should first reflect on why people are visiting their site. Why is the site there in the first place? What are the digital properties being used for? Also, what type of information have you always wanted that was out of reach?
4. Keep learning all you can. If you aren’t learning, you’re losing ground.
5. “Data scientist” is now one of the world’s sexiest jobs. Really.
Interview:
ML: When you go through the process of analysis, I can imagine that a lot of times you have to then present your findings or share reports with the audience. How do you keep these actionable? A lot of times we get so caught up with doing the insights that the presentation is just a combination of Excel sheets and graphs and charts and often there is no story. Do you have a secret sauce for not just doing the analysis but then presenting it in such a way that your audience is interested in taking the next step?
JS: No, I guess there’s no silver bullet or magic sauce and I think a lot of times when you’re presenting an analysis or showing a monthly review, what you’re seeing on a site or within an app, it’s like a black box. They don’t really know how the details of the analysis came to be, but I’d say, as we talked about earlier, keep the audience in mind as you’re doing the analysis, keep the customer in mind as they’re creating the data.
But from a presentation or communication standpoint I’d say “Don’t bury the lead” is something we’ve talked about from the beginning of the conversation. Come straight out with the recommendations. Say, “You need to do X, Y and Z and I’m about to tell you why.” Now, get them interested from the outset instead of pulling them along your analysis of that’s how you arrive at the recommendation. Instead, start with the recommendation that will perk their ears and really interest them, and it will also cause them to ask more questions and say, “Why would I do it that way and not this way?” With that in mind, you know you need to be on your toes and have all your bases covered because when you come out strong with the recommendation, you need to have thought through all the different possibilities.
ML: Very clear. So, if I understand you correctly, the framework is “Here’s what you should be doing,” and then once the organization is compelled by the recommendations, then you explain to them why and the proof that you have.
JS: Right. That immediately makes them start to question, “Why would he recommend that? I hadn’t thought about that. Why would he or she come with that recommendation when we’ve been doing it X, Y, Z way for the last 10 years?” So I’d say, if you don’t have a recommendation, then why are you doing the analysis? Is it just for someone to have a number to bring into a meeting? If so, maybe that’s not the best use of time.
ML: So often when I’m talking to executives or even at conferences, there’s this common statement, “Everyone is overwhelmed with data. We have more data than we can handle.” This question may be in two parts. Do you also feel that way, or do you feel that maybe it’s that we are overwhelmed with data, it’s that we don’t know what the right data is, so it seems like we have a lot, not the right one?
JS: As a data guy, I always want more, more, more, but at the same time I do, at some point, feel like “Wow, there’s just too much here. Where do I start?” I would agree with the sentiment that “There’s too much information out there.” There’s a lot of information, but not a lot of insights, and maybe that’s just the easy sound bite but just personally, from our initial implementation, when we went live with the redesign in November, we had a lot of new information collected from a digital standpoint. We’re working through absorbing the data that we’ve collected now, and doing the QA process to say, “Is the data being collected in the way that we expected it to? How do we make sure that we communicate that and build those dashboards and marketing-level dashboards in a way that can be easily adjustable?”
[bctt tweet=”There’s a lot of information, but not a lot of insights, and maybe that’s just the easy sound bite…” via=”no”]
One thing that I have found…you can’t just drop a marketer or a business individual straight into platform without having distilled or curated a lot of the analysis already. That can be overwhelming. They’re not going to know where to go, how to navigate within the tools to answer the questions they have. I think from an analyst’s perspective, it’s our responsibility to make that data as digestible and easily used as possible.
ML: Very clear. Let’s shift gears for a second and talk about the technology stack. When companies are considering a new analytical platform, like Adobe Analytics, IBM Coremetrics and Google Analytics or Google Analytics Premium, what should the organization look at? Obviously, you went through that process. What are some of the areas that were important to you and would you advise other organizations to look at?
JS: When you’re looking at a new vendor and the implementation, you have to remind yourself why people are visiting your site. Why’s the site there in the first place? What are we using our digital properties for? Also, what type of information have I always wanted? Ask yourself, “What’s the silver bullet? What is it that I’m not getting today that I feel this new tool would give me?”
One thing that I’ve sworn against in this life and past lives is this: Tools do not replace a strategy. So if you want to do any testing, you can’t just get an A/B testing tool and expect it to solve all your problems. If you want to make better decisions on content on your website, having Google Analytics or Adobe Analytics isn’t going to give you better content. As you go through that process, ask yourself what kind of questions you want answered.
[bctt tweet=”If you want to make better decisions… ask yourself what kind of questions you want answered. ” username=””]
When we think about Google Analytics and Adobe and Core Metrics, a lot of them do a lot of the same things. I think they’re differentiating on the way that the tool is used by the analyst, they’re differentiating on the way they integrate with other platforms. But with the data, at least from a digital analytics perspective, a visit is a visit, a unique visitor is a unique visitor. Those conversion points are defined by the code you put on the site and each of those tools will do what you’re asking of it. Focus more on what type of metrics you need to manage your business and with that in mind, make sure you have the right individuals on your analytics team to make that implementation come to life.
ML: Could you share with us what your digital analytics stack looks like in terms of analytical platform tech management system, data management platform, whatever you could share?
JS: Without getting into specifics on the tools that we use, I can talk in general terms about what types of tools we use. A lot of your readers can just go straight to the site now and get a view of what types of tools we’re using.
In general, obviously, we have an analytics platform measuring visitors to our site and what actions they take. That’s kind of critical stakes; you need to have that web analytics platform. I really see the stack broken down into a variety of different tools, so we’ve got the analytics platform itself, whether that’s GA or SiteCatalyst or CoreMetrics, but a tag manager is also something we’re leveraging today and that allows us to be much more flexible in terms of our implementation.
So instead of being constrained to a bi-monthly or quarterly application release cycle, we can, as an analytics group, absorb a lot of those requests that have typically gone to IT and allow IT to continue to focus on more complicated issues and more of the problems they’re interested in solving in terms of their release cycles and the items within their release.
With the Tag Manager there also comes that responsibility to “first do no harm,” to make sure we’re not breaking pages and breaking application flows. In order to do that we need to have the QA tools in our stack as well. When I say “QA tools,” I think that is a pretty broad term. You’re very familiar with the site inspector tools, knowing where your tags are and where they’re not, how long those tags are taking to fire; and outside of just the analytics tags, we have a variety of other marketing-type tags for re-marketing and audience development. Are those tags where we need them to be? Are they taking too long to fire? Where on the page are they firing? All that information is key for us to know that we can make sure we have accurate measurements and also make sure, as a release goes out, that we’re in line with the QA teams to make sure no harm is done.
On top of the QA Tools, there’s a variety of plug-ins for Chrome or tools like Fiddler, Bloodhound, Charles, that we use every day to make sure variables are firing as we expect them to. We’re capturing data across a variety of device types…iOS, Android, Internet Explorer and all the various versions of that platform. So QA is something that we have this huge focus on here.
ML: Are there any new point solutions that you are interested in or considering for adoption? For example, I heard some very interesting things about tools like Snow Plow; also, I’ve interviewed some new technologists, so is there anything new that is on your radar or maybe a technology that you’ve been very interested in yourself?
JS: There are a lot of new tools in the marketer’s tool belt, so how marketers are spending their budgets, the programmatic and addressable space is definitely something we’re interested in. From an analytics perspective, because we have the ability to identify certain audiences and be a lot more prescribed and specific with who we want to reach and be more conscious of effective marketing than programmatic and addressable from an analytics perspective, which is something I’m certainly interested in.
ML: OK. You pointed out there are a lot of different interesting tools, new tools that become available every single day, so how do you stay current on all things new when it comes to digital analytics, even on best practices or new technologies? There is such a fog of information, a lot of really good information. Do you have any habits for staying ahead of the curve?
JS: I think it’s the old adage that “If you’re not learning, you’re standing still; you’re falling behind.” Just reading up on blogs like yours, going to conferences and getting help from behind the screen and out from the data itself and just talking with people. That’s really where a lot of that insight comes from. Asking questions of like-minded analytics folks saying, “How do you overcome your challenges? We’re having trouble with X, Y, Z. Have you encountered that? What have you done?” Reading up on industry publications, but also being in user groups and participating in some of those conferences to really step out of your comfort zone and reach out to other like-minded individuals on a personal level.
ML: Perfect. Let me again shift gears and ask a few questions about current trends and maybe looking ahead a little bit. All the projections I am reading are projecting a shortage of analytical talent, and I’ve actually interviewed a couple of people from the recruitment industry who rarely discuss this topic. What should companies do to address this shortage when there’s so much competition?
JS: I’m trying to remember the publication I saw it in but I never thought I would see the sexiest job in the world as a data scientist. I think that was the headline I ran across the other day. I think depending on the skill set, there is certainly a shortage. The amount of time it takes to fill certain roles is problematic.
One thing that we’ve done is to reach out to the community from a university perspective. How do we align with new graduates? In this day and age, they were born and raised with the phone in their hand. They’re very familiar with the digital world. I think getting the insight from new graduates is certainly helpful from an analytics perspective because having grown up in that space, they can ask questions that maybe someone like myself (couldn’t)…I’ve grown up with a digital mind, but not a mobile phone in my hand. I’d say leaning into the universities and growing that talent is something that we’re interested in here, so instead of waiting for that diamond in the rough to come along and finding that specific ready-based skill set, you’re kind of dependent on growing that skill set from within.
ML: How many years have you now been in the digital analytics space?
JS: Really straight out of school and even within the internships in school, I’ve always been involved in the digital space. Maybe 15 or 16 years now. Long enough that it’s making me feel like I need to go to the reunion this year. I’d say it’s long enough to see a lot of things change from the origin of paid search and then as social sites became more popular and now it’s more of that programmatic, very specific, targeted television type advertisements.
ML: A follow-up question: in 16 years of analytics, what do you wish you knew about analytics when you were getting started? What’s the advice you would give the younger version of you?
JS: That’s a good question. I would say, “Don’t be afraid of not knowing all the answers. Nobody’s got all the answers. You learn by asking. You learn by raising your hand and saying, ‘I don’t understand what that jargon means.’” And a lot of times you’ll find out that maybe the person using the jargon doesn’t have all the answers either. Be more comfortable not knowing the answers. Don’t be afraid to ask questions. Surround yourself with people who are learning themselves. That rising tide lifts all boats. If you’re not afraid to ask questions and the people around you are willing to help, and the people around you are willing to ask questions of you, you can all grow together. Don’t be afraid that you don’t know all the answers.
ML: Yes, it often takes some courage and actually experience to admit that. That’s some interesting advice. When you have more and more experience you realize how vast digital and whatever industry you’re in can be and the amount of information when you are just getting started for job security or whatever. They are very cautious of asking for help, so it’s a great point.
JS: Yes, you have to know that there’s going to be someone who’s a subject matter expert in each space. Find your niche and follow your passion but don’t feel like you have to have all the answers on your own shoulders.
ML: So with that in mind, over the next few years, it seems like there will be a lot of new and exciting things when it comes to analytics. Machine learning, predictive analytics…is there a certain trend that you’re most interested in seeing how it develops or something that you’re kind of looking forward to?
JS:I feel like we’re really on the cusp of some new and exciting technologies, whether it’s in the syn-tech space or even autonomous cards. Just from an energy perspective, there’s a lot of different things that interest me, not just in the digital space. I would say in the next few years, I’m eager to see how that transition from cookie measurements into kind of a server information, seeing how that pans out. I don’t think it’s going to be an immediate…I’d say maybe five or 10 years down the road we will laugh at how we were measuring things today. Just the introduction and new methods for collecting data, that’s really something we have to keep our minds on.
ML: Is there anything that I didn’t cover that you would like to share?
JS: I wasn’t quite sure of what to expect. We’ve covered building the team and how you go about the implementation. One thing I will say is, we talked about not having all the answers and I think it’s important for any analytics team to make sure you are closely aligned with your IT partners, closely aligned with your marketing and product managers so that you’re not out in a silo running an analysis that maybe no one is interested in or off in a silo trying to implement a measurement that IT is about to change in the next two months. Ensuring that your analytics team is aligned with the end users of the data but also your IT teams, making sure you’re aligned with their road maps and really just sharing the data that you have. A lot of times I think we’re focused on “Here are the results of your marketing campaign digital display and paid search. Here’s the incremental impact we’ve had.” A lot of the times people forget that UX and design teams also need that information to help them with future designs. So putting the information in the UX teams and giving them the ability to see the fruits of their labor is something we’re working towards on our side as well.
ML: You mentioned growing your team. Can you tell me a little bit more about how you go through the process of actually growing your team? What do you look for when hiring people to join your analytics team?
JS: So we talked about how front end and back end stats equal statistical mindset vs. web development, marketing, knowledge of job descriptions and analytics implementations on the front end. I think with the help of our recruiters and with the help of an accurate job description, you can get people to respond.
They can say they have the skills on paper and asking the right questions to validate some of those skills is certainly something anybody would go through, but one thing that’s important to me is what is that person-to-person interaction like? Is this someone I can burn the midnight oil with? Is this someone that is going to be acclimated to opportunities? Do they have the personality and the work ethic to do the analysis and communicate the analysis? These are all things we look for.
ML: Very clear. Maybe one more question: You mentioned “cookieless” analytics, but is there anything else you think we can expect from digital analytics? What do you feel like will be the next evolution of digital analytics? Where’s the change coming from? Some people talk about it being very important to simplify the implementation, and you’re going through the implementation process of a new analytical platform, which obviously takes quite a bit of time so many people would like to see that simplified. Many people talk about more ease of implementation between different platforms. Is there anything that you would like to see the technology evolve to?
JS: I think we’ve seen and will continue to see a lot of those acquisitions. I am encouraged by starting to see some of those acquisitions really be integrated together so when we talk about Adobe’s Marketing Cloud or other vendors that have grown by acquisition, we’re really seeing those integrations happen, so instead of it being a separate entity under the same umbrella, seeing that things can play nicely together without additional tagging required and may be baked into something like a CMS or baked into a tag manager to say “Here’s the implementation we sold you on” and really making that come to life and “Oh well, we really have to still do X, Y and Z”, making that integration between all those different tool sets much easier.
ML: Those are all the questions that I have for us today, Joe. Thank you so much.
JS: Alright. I’m happy to talk shop anytime. I appreciate the opportunity.
Resources:
You can connect with Joe on LinkedIn and don’t forget to check out mommydaddydeals.com
