#034: Live from eMetrics...it's the Digital Analytics Power Hour!

The following is a straight-up machine translation. It has not been human-reviewed or human-corrected. However, we did replace the original transcription, produced in 2017, with an updated one produced using OpenAI’s WhisperX in 2025, which, trust us, is much, much better than the original. Still, we apologize on behalf of the machines for any text that winds up being incorrect, nonsensical, or offensive. We have asked the machine to do better, but it simply responds with, “I’m sorry, Dave. I’m afraid I can’t do that.”

00:00:04.00 [Announcer]: Welcome to the Digital Analytics Power Hour. Three analytics pros and the occasional guest discussing digital analytics issues of the day. Find them on Facebook at facebook.com forward slash analytics hour. And now, the Digital Analytics Power Hour.

00:00:29.54 [Michael Helbling]: Hi everyone. Welcome to the Digital Analytics Power Hour. This is Episode 34. You know, the concept of a lobby bar started at a conference, well actually a conference this exact conference. And it was a location where all of us, data nerds, and visualization specialists, and storytellers, and miss grants, and all got together. And if the sessions are sort of the bricks, the lobby bar is the mortar. And it kind of gave us a chance to go up to our favorite speaker and ask the question. What did you mean when you said that or sitting next to somebody who just so happened to share the same exact problem that you thought was unique to just you and your company’s struggles. And so the lobby bar became this place and sort of an institution. And along the way, three friends met, and in seeking to recreate that experience, we created the Digital Analytics Power Hour. You know, in full awareness of the meta-ness that this is, where we’re now taking the lobby bar and trying to stick it into an actual session, I want to introduce you to my other two co-hosts. I’m Michael Helbling. I lead analytics at Search Discovery. And I want to bring to the stage right now and give him a warm welcome, because it’s very cold where he comes from. It’s Jim Cain. He is the CEO of Napkyn and Babbage Systems. And rounding out our roster is a guy who needs no introduction, but you might not recognize him because of his shaggy mane of hair. It’s Tim Wilson, senior partner at Analytics to Miss the Five. And I’m excited to announce that we have a special guest on this episode of the podcast, you. So thank you so much for being with us today. And we are excited to hang out with you. You know, I don’t know if we’ve got some extras. So if you have a glass, you know, just come get some after.

00:02:45.87 [Tim Wilson]: Come and get it during.

00:02:46.93 [Michael Helbling]: Let’s hang out. We’ve been sort of saps listening to it while you’re running, thinking the last thing you want is bourbon while you’re jogging. We’ll start this off. We’ve got some questions that I’m going to put to the team. But I’d bring your questions and we’ll just have a conversation about analytics a la the lobby bar. So let’s do it.

00:03:05.21 [Jim Cain]: I feel like this is going to be the mortar that holds the bricks of the whole event together, I think.

00:03:13.38 [Michael Helbling]: Somebody tweet that. Alright guys, here we go. Transitioning successfully to the other microphone. Now since I’m holding my beverage, I can’t open my notebook, but it’s okay. My beverage is more important than that. Let me ask, let’s throw it out to you guys right away. What have you heard this week that was intriguing? Or what have you not heard this week that would have intrigued you?

00:03:43.65 [Jim Cain]: So this is the second or third E-metrics where I really enjoyed the E-metric sessions and I wish I was smart enough to go to predictive analytics. Oh, wow. No, we’re not all dumb. I’m dumb. Because some of the sessions, the titles are cool and then I sneak in and it feels like I’m getting an ice cream headache and then I come back to the E-metrics events. So it’s not that we’re not doing Interesting topics in this one, but it’s that I would love to see a little bit more crossover than the standard one person from each goes over because There should be I mean with their next door. They’re doing a lot of the same things But where we use a hammer they might use a nuclear warhead or are or whatever it is that they do But the but the guys at the door are like checking like crazy.

00:04:25.07 [Tim Wilson]: It is tough to I had trouble getting into my own session to speak I got like stopped and grilled and it was rough

00:04:30.75 [Michael Helbling]: That was one thematic element. There was much better door security this year.

00:04:34.92 [Tim Wilson]: Door security was amazing. Might have been the hair. I just looked like an unsavory character. Yeah, a theme that I was going to haircut you. My hair got longer and uh, Rochelle, five feet of dynamite’s hair got shorter. I, I thought there was a theme, which I don’t think, uh, I don’t think the session wasn’t, didn’t have the session this time that was the like three frameworks for doing analytics, but the different sessions going through and I, there were a lot of sort of frameworks of kind of how to approach analytics. And I don’t think it was earth shattering. I sort of was, and I present sort of a framework in my session. So I did sort of, it sort of hit me that, It’s, nobody has the right framework, like any framework will work, but it seems like a lot of people who have had success have said this is kind of how I structure and organize what I do. And that seemed like a, for me a little, oh yeah, that’s kind of nice. Everybody has to organize how they’re approaching things.

00:05:37.52 [Michael Helbling]: I think something that stuck out to me was I was hearing a lot more about data storytelling this week than I think I’ve heard in other e-metrics. And maybe I’m just out of the loop, many sessions and really useful content. I learned about, what are they called, small multiples? Small multiples, two sessions at least mentioned them. I’ve seen them before, never used them, thanks Lea Pica. And Ryan Sleeper. Yeah, you won a visualization prize with a small multiple, that’s pretty awesome. So yeah, I thought data storytelling, that was kind of interesting. It’s kind of emerged again and again for me.

00:06:15.75 [Tim Wilson]: So it’s a quick little aside. When we actually normally record this, it’s been a challenge to get the audio correct when we’re three guys in remote places. Is Michael fading a little bit because he keeps doing this kind of working away from his mic? Hey, I talk with my hands, you know. I mean, I can’t help it. I was, you know, one thing that I really missed and I was kind of shocked is that nobody actually highlighted that it was the year of mobile unless I just missed that session. So I don’t know. I think it’s, that was last year. That was, maybe we’re just waiting until it really comes.

00:06:49.61 [Michael Helbling]: Are there industry challenges? So you guys have been in the industry for a long time. Are there industry challenges that we’re not facing today that we used to face in the past?

00:07:01.68 [Jim Cain]: I think we have a lot more executive buy-in. I mean, this is like a recurring theme on the show, right? But we have legacy customers where we would fight and fight and fight to get something, whether it’s technology stack or dashboarding or people buying into analysis. And we would fight to kind of get it to trickle up. And we’re seeing, even in some of those customers, now the C-suite is going, oh, shit, we were doing that already. Great. Now I care. Now you’re allowed in the boardroom. So I find it much easier to get executive sponsorship for this kind of work right now.

00:07:32.16 [Tim Wilson]: I agree with that. I think there’s also, we’re having to do a whole lot less hacking with the platforms, because the maturity of the different platforms, both for capturing the data, so I think your Google Analytics or your Adobe Analytics, your storage of the data, has also gotten more sophisticated. We’ve got BigQuery and Hadoop and these other things. And then even accessing the data, Tableau wasn’t around. I don’t know, when was Tableau? Audience participation, Ryan, when was Tableau founded? Let’s just say you can’t hear it on the mic. He gave the correct answer. And you listening at home can Google. So I think the tool set is there’s now more tools as opposed to we used to say, how can we hack calls going to Adobe or to Google Analytics? How can we manage this data? How can we work with our IT team to develop a data warehouse that’s in Oracle with a schema that we can access? I think there’s a lot less of that because there’s been advances in kind of handling the volume and complexity of data as well as accessing it. I haven’t had to log into WebTrans in about a year for anyone, so that’s a win. Only a year.

00:08:48.92 [Michael Helbling]: You know, it’s been a long time since it had a vendor panel at any metrics. Yeah, you know what else is interesting, and I think it’s been a change, it’s been ongoing, but maybe we can do like a little thing. How many people here are practitioners working for a company? We need inspired by audio.

00:09:07.68 [Tim Wilson]: By a show of hands. A show of hands? Are you fucking kidding me?

00:09:10.32 [Michael Helbling]: What are the other options? Do you do analytics? A show of feet.

00:09:16.81 [Tim Wilson]: Can we do an applause meter?

00:09:20.32 [Michael Helbling]: Yeah, applause meter. We’ll add that in a post. So how many of you that raised your hands would raise your hands again to say, I’m the only one at my company who does this? All right. Well, actually, that was more than I thought. So, all right.

00:09:38.21 [Tim Wilson]: Okay. For everybody who raised their hand, the first question, which was, do you do analytics?

00:09:42.88 [Michael Helbling]: Yeah, are you an analyst?

00:09:43.66 [Tim Wilson]: Can you applaud? Okay.

00:09:46.69 [Michael Helbling]: Oh, wow. Okay.

00:09:49.69 [Tim Wilson]: I’ve listened to live, live recorded show, podcast shows before. For everybody who, you’re the only person doing analytics, can you applaud? So it’s fewer.

00:09:59.36 [Jim Cain]: If you think Tim’s on a power trip and he just likes making you do stuff, yeah, feel free to raise your hands and applaud.

00:10:07.94 [Michael Helbling]: No, but one of the things is there’s back in the good old days. Moest of us were individuals trying to get analytics up and running by ourselves at whatever company we were at is no matter how big it was. And you see more and more teams of people, groups of people coming and being part of that. So there’s more, like, I think it goes back to what you said, Jim. There’s more investment in the industry, but there’s more people now in the industry, not nearly enough people. We’ll just make that clear. But I think that’s one thing I’ve seen.

00:10:45.51 [Tim Wilson]: I mean, I think I was an individual. You’re an individual. We do have a double CEO. I think he was always kind of a split personality. So you might have been multiple. You were multiple. He was a small multiple.

00:10:56.21 [Michael Helbling]: Nice. Brought it back. All right. So we’ve talked about challenges we don’t face anymore. Have we created new ones? Are there new challenges that we weren’t running into before?

00:11:09.90 [Tim Wilson]: We used to just analyze the website, right? And now no one is talking about, no one is accepting or saying that we can just analyze the website because the buzzword bingo, the consumer experience has become much more fragmented across multiple channels and devices.

00:11:27.47 [Michael Helbling]: It was like as if Rand Fishkin was on this very stage saying engagement was, yeah.

00:11:35.34 [Tim Wilson]: That was actually interesting in Rand’s session that he, that all of a sudden he was saying, it’s all about engagement. And I feel like social media, kind of from a, from a different perspective, like he was like, I can point, he’s got evidence that says, if you want to drive your SEO, like engagement and here’s why, because the machine is saying, if you take an action, this stuff is relevant and appropriate and I feel like social media for a while it went from number of fans to reach and impressions to engagement and now it’s kind of who the hell knows for social media. So it was kind of I’m used to seeing engagement with a big old ex, like the social media guy saying, it’s not, it’s not engagement. So it was kind of refreshing to say, ah, there’s a place where like very specific, it’s not, I’m using engagement as a soft and fluffy thing to try to value while I’m doing something, value why I’m doing something. Rand was saying engagement literally is kind of where it, where it’s at for getting organic traffic.

00:12:40.82 [Jim Cain]: Anything new problems, new problems? Well, I just think it’s, it’s the inverse of the old problems or, you know, I was saying now that there’s executive buy-in. So when we, when we were drinking in the lobby bar, I think the first time was E-metrics, New York, like what, five years ago?

00:12:55.34 [Tim Wilson]: Who knows? Who knows? Yeah.

00:12:56.40 [Jim Cain]: A blacked out. Because we were intoxicated. I don’t recall, but yeah. But like the standard complaint at the bar was no one listens to me. Like I did all this work. I found this awesome thing. No one’s listening.

00:13:06.07 [Tim Wilson]: Be careful what you wish for.

00:13:07.43 [Jim Cain]: Well, and now people are listening. So, you know, you get that response where it’s like, I really like where you’re going here, but you added it up wrong. Um, you know, you didn’t catch something. So now like before it was, how do I get someone to listen? And now it’s, how do I get someone to QA what I just did? Cause they’re listening and I don’t want to get pinned to the wall if I’m wrong, right?

00:13:28.30 [Michael Helbling]: And back in my day, you could get away with analysis and Excel. Now you have to learn cool new tools like Tableau and stuff like that. I’m getting left behind. And the CEO makes you rebuild it in Excel. All right. Well, we’ve gone to the Twitter sphere because we want to be good listeners. And we’ve got some questions that came in. So this one’s from Justin Goodman, Analytics Pros. DAA rising star finalist, Justin Goodman. At Electric Mice, Justin Goodman. So yeah, give it up. All right, so this question, this is for Jim Cain. No, actually it’s for all of you, but how do you differentiate reports, dashboards, and analysis to clients?

00:14:12.56 [Jim Cain]: I use the subject line of the email to say report or dashboard or analysis. That’s an answer.

00:14:20.67 [Michael Helbling]: Maybe not what he’s looking for. You want to swing?

00:14:24.25 [Jim Cain]: You do the Hollywood Squares. I mean, to go to the session right before us, a lot of it is in the design and what people are expecting to see, right? So the way that we would send out a report to a stakeholder, there’s a little bit different than the way that we would design and provision a dashboard, and it’s a little bit different than we would design and deliver analysis, right? So an analysis could be, in the body of the email, a dashboard better not be, you know? But I think it’s more design cues than quality or content.

00:15:00.31 [Tim Wilson]: I think I will coach them a little bit definitionally that to me, and I think that’s, it’s the sort of, this is like total lobby bar type, the heated debate about what’s the report versus what’s analysis. And I definitely think. We’ve come to blows on this before, yeah. It was. That’s where Jim’s a nimble little one. He’s very scrappy. Very scrappy. Very scrappy. But to me, a dashboard, I tend to even label them when I’m delivering them as performance measurement. Like this is your one page, ish, you know, snapshot view, clearly understandable, well designed, the data may change, but the layout doesn’t. This is aligning with your business. That’s all it is. It’s not insights, it’s not recommendations, it is low latency, it is, you need to have a pulse on what’s going on with the business. Reports, to me, are recurring, and there is some operational need for You know, I manage our internal search site. I need to get a list of all the terms with these metrics, and I need to be able to interact with it a little bit. But it also needs to be automated and recurring, but tied to a very specific task or need. And then, to me, analysis is definitionally ad hoc. When somebody says, can we redo that analysis? I’m like, why? Like, if we did the analysis right, we validated a hypothesis, and we’re moving on to the next thing. So that’s how I will speak to clients about it. But I also try to avoid the discussion because people will talk about, well, your report doesn’t include any analysis. So it’s one of those where you can wind up in this semantic discussion that’s just frustrating and annoying.

00:16:46.37 [Jim Cain]: So analysis has the most words in it. Reports have less words, and there shouldn’t be a whole lot of words in a dashboard. Could we do that?

00:16:55.98 [Tim Wilson]: Possibly. I mean, I think lots of things get labeled as analysis that aren’t grounded in the hypothesis.

00:17:03.16 [Michael Helbling]: Yeah. I think you present analysis as part of either research or insight generation, whereas the other two or something are probably happening on a more consistent basis or, um, yeah, consistent sort of cadence.

00:17:16.38 [Tim Wilson]: You guys caught that Jim Stern came up and gave, got himself some bourbon, right? Quick by a round of applause. How many people drink bourbon? Okay, all you gotta do is find a receptacle. We’re not gonna call you out.

00:17:30.08 [Jim Cain]: Why don’t we give away one?

00:17:31.40 [Tim Wilson]: I’m taking a red eye tonight, and I’m not gonna finish that up.

00:17:33.84 [Michael Helbling]: Well, we’re about to. We have one more Twitter question. Yeah, take it. Thank you.

00:17:37.37 [Tim Wilson]: Ooh. Actually, just pass it around. Pass it around.

00:17:42.12 [Michael Helbling]: It’s weird for people to have to come up and get it, so it’s better that way. Great. So this one’s for you, Tim, because it’s super hard. It’s from Mike Harmonos. He says, what’s the most effective way you’ve explained multivariable analysis to someone? Preferably that someone’s not like a five-year-old.

00:18:01.88 [Tim Wilson]: I actually see if I made any connections with somebody a predictive analytics world and then defer the question to them. I don’t know. I mean, to me, I assume the question is kind of how do you explain something like interaction effects? And I think it’s not so much an explain as a show.

00:18:23.72 [Michael Helbling]: Yeah, I mean that because that’s it analysis is fundamentally right figuring out the difference between two things. Yeah, what we do is we can kind of boil it down like that. And when it’s multivariable, then yeah, it’s how do those things all interact to explain the difference between those two things.

00:18:41.24 [Tim Wilson]: So, yeah, I guess my answer is I show and I’ll spend a lot of time on a, there are lots of things.

00:18:47.22 [Jim Cain]: If only we’d done a show on this with someone who’s an expert in one armed bandits and. Yeah.

00:18:52.83 [Tim Wilson]: If only there was. If only we could recite Matt Gershaw from Conductorix was on a fantastic show.

00:18:58.72 [Michael Helbling]: Yeah. All right. Well, we’ve got some more questions, but I feel like we’re ill using this awesome crowd. Let’s ask you guys, what’s going on at E-metrics for you? What have you heard? What do you have questions about? Tim Wilson is actually very smart. And Jim Cain and I are here.

00:19:16.33 [Tim Wilson]: Despite your impressions from anything I’ve said from the stage. So you can ask anything.

00:19:21.40 [Jim Cain]: And we’ll have an opinion. First two questions get a data-driven business cup of some kind. With chocolate in it. With chocolate in it. That you can put liquor in.

00:19:30.71 [Michael Helbling]: Also, you can claim to have been a guest on the Digital Analytics Power Hour. The only explicit analytics podcast on iTunes. Put it in your LinkedIn profile.

00:19:41.34 [Tim Wilson]: Come on. There we go. Somebody had to break the mic. I see how many people have listened to a podcast in the last week by round of applause? I’m curious.

00:19:51.61 [Other]: Okay. So I didn’t actually have a question until I got the mic, but I’m going to make up a question on the spot just to thank you.

00:20:01.16 [Tim Wilson]: You’re our kind of person. Did come up and get the bottle of bourbon that was sitting on the front of the stage, and maybe it goes to her head really quick.

00:20:07.99 [Other]: Okay, so if you’re hiring for an analyst, what is the key thing you’re looking for today?

00:20:19.05 [Jim Cain]: You’re the HR guy.

00:20:19.89 [Tim Wilson]: I don’t have to hire analysts.

00:20:22.45 [Michael Helbling]: Yeah, so I guess as the person who is the most always hiring person on the stage right now.

00:20:29.11 [Tim Wilson]: Go to searchdiscovery.com slash careers for it’s a great place.

00:20:33.25 [Michael Helbling]: I love it.

00:20:34.51 [Tim Wilson]: All right.

00:20:35.04 [Michael Helbling]: So it depends on, I think it depends on a lot of things and you probably know this too. Obviously, if you’re looking, what level of experience you’re looking for, you probably are looking for certain things, but fundamentally beneath any analytics skill set, there’s three things that I’m trying to figure out about a person. when I’m interviewing them for a role as an analyst or someone in digital analytics, the first is problem solving competency. So what are they, how do they approach solving a problem? So usually in the interview process, it’s giving them sort of some hypothetical things like, you know, how many whiskies could Tim Wilson drink before he passed out? You know, like, and then how they break that problem down.

00:21:17.78 [Tim Wilson]: Do you have a standard set of those questions? which I’m not going to ask you to share, because I would just tip the phone.

00:21:22.27 [Michael Helbling]: I mean, only a few of them are related to you personally. How many?

00:21:25.23 [Tim Wilson]: They’re not all? Yeah. I was thinking there’s the old, how many pennies would fit in this room?

00:21:28.87 [Michael Helbling]: How many Tim Wilson’s can you fit into 747s? Yeah. So those kinds of problems help you understand, not that somebody’s smart enough to just know the answer to that stuff, but how they attack the problem. Because that’s so much of what we do is having a tenaciousness to go after the problem. The second thing is, Sort of just the innate intellectual curiosity, right? Whether that’s something that comes through personality type or whatever or it’s learned, but like they can show and demonstrate. They’ve really kind of thought through things and then lastly probably critical thinking skills or lateral thinking skills. How can I apply experience and knowledge from one area to another?

00:22:07.10 [Tim Wilson]: So on the personality type, do you guys do like a personality profile? as a part of the hiring process.

00:22:13.76 [Michael Helbling]: Internally, while when someone’s part of search discovery, we use a book called Strengths Finders, which is awesome. I wasn’t asking you to plug that. Yeah, I knew you. Well, I knew you love it though.

00:22:25.23 [Tim Wilson]: Where’s is Leah Pickett here? Does she, does she already know what her strengths are? The one of the newest hires? She does not know her strengths.

00:22:33.40 [Other]: My strengths are on my LinkedIn profile.

00:22:36.64 [Tim Wilson]: We get along. You just went from being five feet dynamite to four and a half feet dynamite.

00:22:41.67 [Other]: What? No, I don’t think so.

00:22:44.24 [Tim Wilson]: Awesome. What about you?

00:22:46.86 [Other]: Real quick, Michael, I want to follow up on your question. When you ask a question and try to gauge someone’s problem-solving ability, that’s all well and good, and you hear a lot of interviewers do that, but I don’t know how to effectively evaluate that. If someone’s giving you an answer and you see them go through that thought process, you see the wheels turn in their head, but then how do you really evaluate what you like or what you don’t like with those kinds of responses? And I’ll give up the microphone now because I’ve had it too much.

00:23:24.50 [Michael Helbling]: Yeah. Honestly, it has something to do with whether or not they themselves feel satisfied with it. Like they, if they just end it, they’re like, I’ve worked it out and it’s this. And I don’t think that they’ve kind of wrestled with it enough. And that tells me they’re not going to pursue a problem. as far as they need to pursue it sometimes.

00:23:45.91 [Tim Wilson]: But are you asking like behavioral questions about, tell me about a time that you have and see how they respond to that?

00:23:49.96 [Michael Helbling]: Well, obviously there’s lots of other stuff you ask. You’re trying to figure out culture, attitude, and all these different things.

00:23:55.89 [Tim Wilson]: No, no, no. But I’m saying behavioral, like when you’re evaluating, so one of the problem-solving ways is we give them a problem. Here’s a data set. Do you guys do that with certain roles?

00:24:06.42 [Michael Helbling]: Not as much with analytics. Uh, problem specifically, like I don’t, I used to do that. I used to give people a log file and tell them to tear it apart, but that’s so many years ago, like nobody can do that.

00:24:18.79 [Tim Wilson]: Now you just grill them on what the different server response codes are and be like, yeah, exactly.

00:24:23.37 [Michael Helbling]: What is a 206 return code? Go. I think that’s Detroit. So close. As everyone else here knows, that’s the partial success return code. Yeah. That’s right. Very important to set that up as a filter and web trends so that you didn’t get your PDF downloads. Yeah. That’s right. In IE. Exactly. That’s old school right there guys. All right.

00:24:51.92 [Jim Cain]: I have a couple of anecdotes in the HR one. Go. The first one is that we’re not doing enough when we’re hiring again because we build a lot of our analysts. So we’re not looking for a whole lot of do this use case. We look for a lot of lateral thinking because I find that there’s a lot of tools that are designed to do one thing. But if you spin them a little bit, you can do some. So we’ve used like paid search intelligence tools to actually help predict someone else’s inventory. So that way their competitors can keep their product mix up. So we look for a lot of lateral thinking.

00:25:24.28 [Tim Wilson]: How do you actually evaluate that in an interview process?

00:25:28.47 [Jim Cain]: Well, I just make them work for free. It’s called an internship. No, so we ask a lot of high level questions about digital, like we do a lot of e-commerce, so we’ll pull up an e-commerce site and say, what do you think the primary and secondary goals are of this site? What are the kinds of things that you, like we kind of like work someone through a problem to see how they respond and why they respond? But I had a couple client meetings this week in town and one of them was with the CTO for a large publishing company and they’re trying to build their own analytics practice internally and he said, What are the criteria for my one analyst that I should hire? And I said, you’re a billion dollar company, so you hire three people. Because there’s no criteria for one analyst. Because they’ll hate their life and quit. And there are more recruiters than there are analysts. I don’t know if you guys have noticed that. So.

00:26:22.37 [Other]: We have another question here. Yeah. This is also related to hiring, which came up a lot at the conference. So the need for data scientists is high. And a lot of people have said, you know, analysts, junior analysts can’t fit that role or can’t become that role. Is that true? And if so, where are the data scientists supposed to come from?

00:26:44.08 [Tim Wilson]: And what is a data scientist?

00:26:46.18 [Michael Helbling]: Yeah, I mean, historically, we’ve had a hard time defining the term data science. If you recollect like episode two or three or something.

00:26:53.37 [Jim Cain]: I think I called them the Y2K programmers of 2015 last year.

00:26:58.13 [Michael Helbling]: Well, I mean, so. It’s a really good question. One where we’re going to go all around and not answer. And no, you have to, that’s probably correct because, you know, how I define data scientists, probably not how anyone else does, but my personal definition is pretty specific to a certain skill set with a high degree of programming capability. statistical methods and those kinds of things and experience with sort of platforms and things like that that kind of help with dealing with large data sets in kind of meaningful ways, so R and Python and those kinds of things. Those are kind of the walls that I build around data scientists and then I go back to the same thing with what the other answer was, sort of how do you fit, how do you solve problems and how do you critically think.

00:27:52.41 [Tim Wilson]: think that definition, which I like, I think is the future of this entire profession. It’s actually, and I’ll try to work it out in a coherent way.

00:28:00.40 [Michael Helbling]: It says the guy who’s been tinkering with R lately.

00:28:02.76 [Tim Wilson]: Well, and E-metrics Chicago in June, like I have committed to trying to actually explain and articulate that. And fun little E-metrics social media win on the way here. I was at the Bart station at the airport. And I got a little notification that one of my sort of light bulbs going on is a guy named Michael Healy who works for Michael Helbling and that can’t get confusing ever. But he was one stop up on the train and heading my way. And so I got to actually ride from Bart all the way here and to downtown with Michael. And he’s one of the guys that I’ve realized that skill set is coming. I think that the traditional, the simpler world of we’re doing line graphs and we’re showing trends and we’re just building a dashboard. I think all of that is going to shift to be much more technical in five to 10 years. I think the people who get really excited about that, what you disagree. Can you, which mind number is that? Can you shut that off? So I, and I, and I may be dead wrong, but I feel like it’s the analyst. I think our last episode, they’re talking all over each other. Like now we just screwed up the editing, but this time we’re talking all over each other. So I, I think they’ll have to, and I kind of, I’m old enough that I could probably coast it out doing, you know, simple correlations and line charts and cluster.

00:29:34.06 [Jim Cain]: Custer or not cluster analysis scatter plots if I could do a cluster analysis, then I ran away to management So you disagree yeah, I think that So you know the whole history of web analytics like log files and the marketing found out blah blah blah I’m not gonna do the routine again But I think now if you take a there was an episode with Jim Stern or we went through the history of web analytics and a whole bottle of wiki and But so, wiki? I have a beer here. So I’ve been awake for three days. So here’s a clearly bounded problem. And I’m a liberal arts level analyst. Like I’m a me analyst. I’m someone who wants to talk people through defining why there’s a problem and then get enough to explain how to fix it. I’m going to approach that problem in a very, very specific way. It’ll be a tableau way. It’ll be an interviewing stakeholders way. Now let’s say I’m an engineer. I’m going to try and hammer that nail with a completely different approach, and I’m going to try and engineer my way through it. And I’m going to use R, and I’m going to use Redshift. So this whole discipline that we’re in that had a relatively straightforward track, and a lot of people came from a more technical background and had to learn more of the storytelling and the visualization. We now have two different disciplines, but I think we’re trying to solve a lot of the same problems, but like humanities versus engineering.

00:30:56.01 [Tim Wilson]: But I think we had traditionally metrics. Jim gets stern, gets some people from very large companies dealing with very large data sets. I’m going to say eBay and now I’m blanking on Twitter. We had various people. And there have been times in the past where it’s like, You look around the room and you’re like, how many people have the luxury of dealing with a, oh yeah, shit, just do a 1% test. You know, everybody does a 1% test and you get a gazillion things to work with. And that was kind of like, yeah, you needed these data scientists to deal with this large, these large data sets. But I think we’re shifting and the tools are shifting. Google Analytics is shifting this way that now a more modest set of traffic, you can start to get a lot more data because you can get a lot more granular and you can say I can roll up this this atomic level data and do your performance measurement dashboard and I can have a tool that helps me do that but now I’ve got a broader set I’ve got a more detailed larger set of data with less traffic because I’m not just dealing with the aggregated data that Google Analytics was providing or web friends right web friends was all aggregation I mean that’s how they stored it that’s how what they what they put it in so I think, I may be dead wrong, I think 10 years from now, we’ll be looking back and saying, ha, remember the days when you could log in to googleanalytics.com, or google.com slash analytics, and you could, you know, you had three chart types, and you could screen capture that and drop in, please never screen capture from any web analytics tool. But, so, I don’t know if that answers it, but I think it’s, people, they don’t just need to shift that way or they’re gonna have limited careers.

00:32:33.63 [Michael Helbling]: So there was, I think there was one more question over there and then we got to wait and see how far over Jim Stern’s going to let us go.

00:32:41.10 [Other]: What advice would you give us, the most important things a researcher should be doing to assert their value to their clients?

00:32:52.21 [Jim Cain]: Always be right and always have a dollar sign in the last sentence. Yeah.

00:32:57.14 [Michael Helbling]: Yeah, I mean, you know, and, you know, walk around with those things that show, like the research that shows the ROI of an analyst is, you know, 300 bucks to one or 1300 bucks to one. That’s great material.

00:33:08.85 [Tim Wilson]: Go to salary.com.

00:33:13.10 [Michael Helbling]: No, it’s true. It’s, it’s about tying your work to value that drives the business, right? So how you connect with whatever business you’re doing, how, and, and honestly, for digital analytics, It’s a bridge we all have to learn to cross unless you’re a pure play web company. You have to translate the digital metrics into metrics that correlate with business outcomes. So that translation process is really what drives that value because, you know, when you go and report to the CMO, you know, while they may be interested in bounce rate momentarily, I’m pretty sure their bonus is not based on that.

00:33:48.67 [Jim Cain]: You will die on the sword of interesting.

00:33:50.68 [Tim Wilson]: So I think that’s, I mean, oh man, the, the always tied to dollars. It’s, it’s, it’s true and awesome. But the fact, and we were talking, Adam Greco was talking about, he’s like, you know, if you’re basically, he was saying, if you’re, if your site you’re on is a brochure where site, because the nature of your business, which to me I heard is if you have a consumer package, good site, But I think there is a more practical that anyone can do, which is figure out what’s keeping them up at night. Or if they’re not that passionate about their job, just figure out having that conversation, getting inside their head, and trying to figure out what’s the question you can answer that they would say, this is useful to me. Because there are plenty of people who are at a level below the macro, I have to tie all this stuff to revenue. I didn’t say revenue, I said value. Okay, so I agree with you and as usual disagree with Jim. But Jim, as a guy who came from a sales background, I think there’s a lot that he says when it comes to the act of listening. You are trying, it’s cliche, like what’s keeping you up at night, but that’s the thing to what can the data provide that that person says, great. I now have that information and I can move forward and that’s figuring out what they’re being incentivized on, what they’re grappling with and it’s not always tieable to a dollar. How do you do social media? I mean there’s a legitimate reason to be on social that is for companies that otherwise you’d have all you’d be saying is my social media analytics says you need to just tweet direct, tweet direct response calls to action and turn it into a direct response channel. And I think there’s a way to approach marketing that says, no, you need to think a little broader than that.

00:35:47.20 [Jim Cain]: In most cases, I mean, you went with the most pure brand marketing example, and that’s fine. And we could chip away at it.

00:35:52.91 [Tim Wilson]: That’s because you’re wrong.

00:35:54.17 [Jim Cain]: Because I’m wrong. I don’t know how I tie that to that. But an example is a customer service portal for a company that does sell things online. So you log in, and you enter your question, or you chat with Live Help. Moest people don’t measure those as a successful session. They measure, did the site go down or like it’s generic technical metrics, right? There is a clearly defined cost for a telephone interaction with a customer. And if you say, if someone does this list of five things after they log in, they successfully completed something that meant they didn’t call us, I have a dollar, right? If you have a company that does a lot of consumer package goods, You do those people in the store and they like, you know, taste my disgusting cake or whatever. I mean, you know, you’re out there talking to people. If you can monetize what it costs to have someone in a particular community, you can subset Twitter traffic by community and be able to say, instead of putting people in stores, we did this and saved this much money.

00:36:57.52 [Tim Wilson]: I’m glad his drop the mic sound effect was not caught on the mic.

00:37:00.94 [Michael Helbling]: It’s not my mic. All right. You two quit fighting long enough, and maybe Jim will let us take one more question. I feel like maybe right back there, there was one right there.

00:37:10.11 [Tim Wilson]: It was like the second hand to go up by a millisecond. The poor guy hasn’t gotten to ask that.

00:37:15.06 [Other]: Well, that’s because I don’t have any alcohol, so. It’s over there. Is it empty? So my question was kind of based on what you guys were just talking about around social media and analytics and trying to show value of that. And so I’m just curious to what your thoughts about social media analytics in the industry, anybody that you see that’s doing it well, things like that, because I have the same issue going on within my organization around what’s the value of engaging some of these consumers via Twitter or via other platforms, what are we getting from that?

00:38:00.26 [Michael Helbling]: Yeah, so I’m going to go ahead and plug a book by this guy named John Lovett called Social Media Measurement Secrets. Because I think that was the first place I saw somebody talk about social media in terms of what you were hoping the social media channel or platform was going to achieve for your business, and then measuring outcomes based on that. And I think that’s the That’s been the most common sense way I’ve seen.

00:38:24.43 [Tim Wilson]: And I’m a little familiar with John. I work with him. I was a fan boy, but specifically chapters four and five. Part of what using this, this, the idea of causal modeling of saying, you know, we’re on Instagram or we’re on Twitter. And ultimately we want to have a business value. We want to have a dollar outcome. We need to get in a room with smart marketers with, with the analyst and say, what is the map? There probably is value in being on Instagram, but we should figure out what the map is from somebody engaging with Instagram. How do we logically link that to business value? And let’s draw that out. And now let’s go as far downstream as we can with what we measure. And we’re still leaving a leap because you can’t get the ROI of a tweet. having that kind of alignment discussion of saying, yeah, I mean, we were doing brand marketing out of home in the 1950s and it wasn’t a waste of money. There was, there was value there. And in a lot of ways, a lot of social media is brand marketing, you know, akin to billboards in my mind. That’s part of it.

00:39:40.13 [Michael Helbling]: Now you can have direct response as well or customer service or engagement or outreach or whatever.

00:39:46.37 [Tim Wilson]: The outlines like sick or driving product innovation. Yeah.

00:39:48.96 [Michael Helbling]: Because I mean if you’re a brand and you’re on Snapchat like You’re not looking for a direct ROI from that. It all disappears in eight seconds, right? So that’s a whole different thing that you’re doing. But you’re building brand awareness, so that’s brand, and you should use brand measures to then, to measure it.

00:40:05.70 [Jim Cain]: So yeah. Sir, does the social media work that you do lead to clicks to the website, or is it purely, purely like, look at me, I’m Sandra DM on the web?

00:40:14.09 [Other]: Both clicks to the website.

00:40:16.89 [Tim Wilson]: Are there online conversions that you can tie dollar values to?

00:40:19.33 [Jim Cain]: Yeah, yeah.

00:40:20.06 [Tim Wilson]: So, damn it.

00:40:23.12 [Jim Cain]: So now you get to look at social as people, it’s almost like display. People that saw it, which I don’t think is worth very much. I think social has some value. Okay, not touching that. So someone interacted with us in social and there is a very finite value to that and a very big value to the agency that sold it to you in the first place.

00:40:43.96 [Other]: Yeah, we’re doing that and that’s actually a plus that we’re able to tie that back in but then there’s this other piece which is the organic piece that is really important to the CMO from a brand perspective about what our engagements are bringing back to us from a value standpoint.

00:41:06.21 [Tim Wilson]: So I’m going to throw one other quick one in there. If you go and say, you’re a CMO, do you want to get our brand in front of our potential buyers? And the answer is yes. Do you think we should do that where our potential buyers are spending their time? And the answer is yes. So you can say, I mean to me that’s like a, that is a no-brainer that there is a ton of industry research that says people are spending their time more on these social channels. It doesn’t fully answer the question, but it’s almost, there was the, What does it imagine the spoon? I’m going to botch my matrix reference. There is no spoon. There is no spoon. The matrix I should be able to get.

00:41:52.00 [Jim Cain]: Credibility destroyed.

00:41:53.30 [Tim Wilson]: It was a tall pour of Elijah Craig.

00:41:54.75 [Jim Cain]: This is the first time Tim tried for a pop culture reference and he flew it. It will never happen again.

00:42:01.12 [Tim Wilson]: Do you want to not be on Twitter? That just makes no sense. So there’s kind of this basis of if we can do it cost effectively at a bare minimum we need to be there, because that’s where our consumers are. I mean, maybe they’re not, but in many, many brands’ cases, they’re on LinkedIn, because it’s B2B.

00:42:19.43 [Jim Cain]: I also like rolling up all your social channels. People tend to go, we’re killing it on Twitter, and this is Facebook, but to some extent social is social. And if you can kind of roll up your active listening community, and emphasis on active, right? Into one group, it’s interesting. If you can trend on a weekly basis in a report that people care about, and again, you saw some great examples earlier on nice reports, if you can consistently show that certain activities lead to a larger or smaller active listening community, then you’re starting to show value, especially when you can connect it to conversions in the site. Awesome, good question.

00:42:59.88 [Jim Sterne]: Marginal answer. Ladies and gentlemen, this has been the Digital Analytics Power Hour Live brought to you by E-Metrics Summit. Please, a warm thank you to Tim Wilson, Jim Cain, Michael Helbling, Digital Analytics Power Hour. Cheers.

00:43:20.90 [Announcer]: Thanks for listening and don’t forget to join the conversation on Facebook or Twitter. We welcome your comments and questions, facebook.com forward slash analytics hour or at analytics hour on Twitter.

00:43:55.88 [Tim Wilson]: Rock Flag and E-metrics!

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