Confessions of a Marketer Podcast:

Deep Dive Into Data

A Lively Q&A About Marketing Data on Confessions of a Marketer

On episode 20 of Confessions of a Marketer, host Mark Reed-Edwards took a deep dive into marketing data with Rob Weedn, founder of DealSignal. The transcript of the discussion is below. You can listen here or download the podcast on iTunes.

Mark: [00:00:00] We all live with data around us all day, every day. And we know it’s critical to our marketing efforts. But what does it all mean? Rob’s firm is all about data–the freshest, most accurate, most relevant data. With that background, Rob has a unique perspective on data in marketing. Hope you enjoy the chat.

Mark: [00:00:03] Rob Weedn, it’s great to have you here on Confessions of a Marketer. Welcome.

Rob: [00:00:04] Thank you. Nice to be here.

Mark: [00:00:06] There’s an old quote attributed to Henry Clay that statistics are no substitute for judgment. When you use data to drive a marketing campaign. How do you weigh your judgment or the judgment of others against what the data tells you?

Rob: [00:00:22] Well, you know this really strikes at the heart of where DealSignal began and where it is today and I’ll say to Henry Clay’s point, without a large enough volume of data, without enough historical data, and without enough data points it’s often too early for statistics or predictive or AI.

Rob: [00:00:43] There are just not enough data to actually prove a pattern and definitely not enough data to give that pattern to an engine. So what’s interesting about humans is they actually have complex cortexes and the best performers often have the best human intelligence.

Rob: [00:00:59] And so what we see is gathering the best team of marketers and salespeople, who are often the best performers on the sales side, will help you come together to identify what you need to focus on, whether it be personas or messaging or target accounts or those kinds of things and we see people often try tools and find them to be indicative, but not the answer, and then revert to you’ve got to get alignment between sales and marketing anyway, let’s get together let’s get in a room.

Rob: [00:01:31] Maybe you have some insights to bring to that meeting, but we need to have people, the best people, thinking about how this will work for us based on anecdotal data based on initial evidence and based on what people believe will work. And then you have to test it. You have to get much more into an agile framework for running smaller bite-sized modular campaigns and things like that, seeing how they perform and then optimizing from there or flushing it if it was the wrong focus area, period.

Mark: [00:01:59] So what are the two or three points about using data and marketing that you think marketers should know and put to use?

Rob: [00:02:05] Well, bad data is really painful–is really the main point. Bad data can just absolutely destroy–it’s painful.

Mark: [00:02:16] Rob can you define bad data?

Rob: [00:02:19] Absolutely. So in marketing we need to reach accounts, we need to reach people in marketing campaigns, so bad data is bad data about an account, bad domain for example, or the wrong company size information–we think we should be spending a lot of energy on a company that’s been acquired and they no longer make their own decisions. In fact they have no employees anymore that work in that division. Right? So account data that’s either out of date or inaccurate can harm routing or focus or it can mess up how you look at your target market or target accounts. Bad data around contacts can literally prevent you from reaching them and if it’s out of date, inaccurate, or otherwise the contact info is wrong, you don’t reach people. To sell to people, to market people, to engage them, you have to reach them. You have to reach them on multiple channels, so we feel like, you know, great data is when you can have a great insight into their persona and how they can be segmented, how contacts can be reached via e-mail—and I’m going to come back to that as the second point—how they can be contacted by phone, how they can be reached across social channels, not just Twitter, but even other channels for either insights or outreach, and if you have all of that perfected—and that’s one of our goals and missions in life, to perfect that data—then you have maximum reach, maximum contact-ability…so drilling back to what are the two or three points: bad data is the first problem, how that impacts performance is the second problem, and so, if you use bad data, you’ll get a bounce rate that could really take a system offline for you, like marketing automation. Bad data can upset salespeople and if they get a ream of bad data they could lose trust in the marketing organization. So, bad data can corrupt your systems. It can corrupt your process, and it can corrupt your trust between sales marketing. Those are the three problems you’ll see coming from bad data.

Mark: [00:04:26] And I guess theoretically, it could also ruin your online reputation, right?

Rob: [00:04:31] It could, if you’re reaching out to the wrong people, it actually can frustrate people. Yeah, I mean, there’s a negative feedback loop associated with reaching out to people in the wrong way and reaching out to the wrong people. And, you know, people can come back these days and Tweet about you or give you a bad review or a crowdsourced review site. And so if you look at Yelp reviews or you look at just Twitter storms. Those things can really effect you quickly, as in the course of hours, or 24 hours. So you really have to watch using that data wrongly, and from a larger system perspective, it hurts you in all these different areas. But, yeah, you make a great point, which is, it can come back and significantly damage you in a matter of hours or a day, you know?

Mark: [00:05:23] So can you tell me a few stories about how employing data sheds some light on a problem, maybe increased conversions or just generally made your life or your client’s life in marketing a lot easier?

Rob: [00:05:36] Sure, yeah. If we run with kind of the concept of the first major problem we see people be surprised about, like the insight that we’ve found the ‘aha moment’ is that in their current systems… and this is still shocking to me, to be able to say that this is an almost perfect pattern across, you know, 30, 40, 50 data points that we have across customers…most people are not marketing and selling to their full target audience, and that means they’re not covering all the accounts that would be likely to buy their software and they’re not contacting all the people that are in those buying committees, the stakeholders that would look at buying their business services or technologies.

Rob: [00:06:19] And so if you have 20 percent…let’s just start there. If you only go after 20 percent of all the people that would potentially come and buy your service or product, then you’re missing 80 percent of the opportunity, and we find that people have not often done that kind of bottoms up assessment and really understood that, and that’s probably step one for what we’d recommend—to have a full strategy and plan—is to understand your total audience. And then, the second point, to your question around personas is being able to break those down…all big problems need to be broken down into consumable chunks, that gives us, also, the ability to do agile…what I mean by that is, if I break down the most…again, just anecdotally, between sales and marketing, the best persona or series of personas with the best target accounts, running a campaign against those in a personalized way and measuring the performance of that and optimizing, with sales and marketing in alignment, is what we’re seeing is best practice. If you do that with great data, you know, just like a high octane fuel in a high performance engine, it will work really well and you’ll get great speed, volume, and conversion. But then, do it in a size…and we believe it should be broken up in chunks where you can then iterate and optimize…so break it down at a level that you can run it, get a certain open rate, a get a certain engagement point, whatever that is for you, and then get a conversion to a lead or a sales opportunity and then come back and say, like, which variant of the messaging worked well, which day of the week, which step the process. How do we tune that? How do we optimize that? This is a practice to build. This is not just something that you plug in and it works.

Mark: [00:08:18] Right, so if you’re trying to convince someone to start relying on data more what’s the argument you turn to most often? And I guess, then, a follow up to that is, does it work, or, you know, sometimes why doesn’t it work?

Rob: [00:08:32] I haven’t found too many people that actually believe that data is unimportant. So I think that how they view the data, like I said, this total audience concept, that people may only be speaking to 20 percent of 100 percent, is something that I think surprises people and it opens their eyes. I think that the one that’s more tried and true…you know, my dad was a doctor… I think the best situation for someone wanting your product is when they are in the emergency room, right? So if we flipped to the other end of the spectrum, where are people are most reactive? This total audience concept is a little more proactive, whereas people are more reactive, where they say, hey, I just sent out a campaign and it was a disaster because I got a 35 percent bounce rate. Oh, we used one of the systems that sales uses for data, I won’t name names, but, you know, we used one of those systems we pulled a list out of it or we bought a list from a list broker and now I just got a warning or got shut off from a marketing automation system and now, you know, I’ve had the worst experience I could have as a marketer. My process has been destroyed. I have to rebuild it. So that’s probably the other end of the spectrum: completely reactive. They now have the true pain of having bad data. And now they’re like, I must have the most perfect data that I can and that’s what we’ve been trying to harness and build and perfect. So that’s one example I hear, I can give you others.

Mark: [00:10:04] Yeah, give me another one.

Rob: [00:10:07] Well, I like ones that are much more hopeful than fear-based. So there are different models of politicians? I tend to like the ones that are more hope-based rather than the ones who just have Defcon 5 all the time. So I gave a Defcon 5 example because we see it and you asked what’s the most compelling reason people turn to us, right?

Mark: [00:10:29] Yeah I think many marketing organizations are run on Defcon 5. You know, so I think that’s a familiar environment for a lot of us.

Rob: [00:10:38] I’ll touch on one really quickly then I’ll go to one that it is much more interesting. So some people, to your point, are reactive and that, you know, they’re having a bad quarter, they’re in the middle of the quarter, end of the year, and then all of the sudden the problem is: top of the funnel! You know, we need a ton more leads! Right? And that call goes out at least once a year, it could go out once a quarter if a company is trying to go public, right? We need more leads, we need better leads, where are the Glengarry leads! Right? So being able to not just get a general list of executives with good data, but rather get any level of the organization, in any line of business in any industry in any region and to be able to go get 10,000 overnight and have them be perfect, on-demand? We hadn’t seen anybody be able to do that. We kept getting requests like that and then we said, you know what, this isn’t just about building a database with a data set saying, hey we’ve got the best data set for people that are in IT focused on analytics. No, I mean that was our first customer that had that need, but what we found was they pivoted, you know, they sold to IT and then they were selling to line of business. They were selling to executives and then they pivoted to selling to what they call practitioners; the more hands-on people who were trying products. And they kept pivoting around and we were like, we have to do this on-demand, and if we do that it makes them very happy, and we need to do it at volume with perfection. That is very hard to achieve. It’s taken us a couple of years to build it, but that’s what I would say is one of the best use cases.

Mark: [00:12:15] Obviously, you know, companies can turn to a firm like yours, DealSignal, but a lot of people want to have a staff member…someone who understands data, but finding those kinds of people, people who understand data and maybe can put it to use for marketers, is tough. How do you recommend marketers start their search when they’re looking for that type of person?

Rob: [00:12:40] Well, I think if you look at the way this practice or systems build: you have your CRM system, your system of record, you have a process automation for marketing and/or sales, that’s your process automation or system of engagement, you’re going to put data into that system to store it and then to run it, right? And so I think that people need a phenomenal…we’ve seen the best results where people have really good operations person that understands both the ins and outs of, like, a Salesforce and a Marketo or an Eloqua and they understand the business purpose so they can manage scope around what should or should not be customized, integrated, etc. And so that operations person is kind of an unsung hero but they are very valuable. It’s a higher level task and function than stitching together the organization, the system needs, rather than managing data. Another place we see people just having people manage data is in inside, you know SDRs, inside sales and business development. And what I would say is, if you want to hire folks that in the Bay Area may be six figure individuals, even though they’re more early in their career, and you want to have them…anybody you have in your sales organization you want to be selling unless maybe you have an operations group to manage, obviously, the deal desk, and the deals paperwork, the rest of the folks that are supposed to be doing sales. If they are spending 20, 30, as much as 40 or 50 percent of their time—and there are a bunch of statistics in the market to prove that that’s what happens—managing data? Number one there’s variability because you get now 10, 15, 25 people sticking data into your CRM system from various sources. You get a hodgepodge. You get very high variance in the results of what’s in your CRM system. Most importantly, they’re spending time managing data and it’s not easy to input data. They’re data entry, they are not sales, which not only harms them talking to people but building their practice of How do I sell? How do I qualify? How do I turn this into a deal? How do I get through all the stakeholders with the right message and ROI? You’re literally distracting them with the lowest level tasks that can be put offshore or given to robots or AI. And it’s a horrible career to build because those tasks will completely be replaced by robots and AI, so why would you want to ask people to spend their career on that or their selling time on that, as opposed to revenue generation and the art of communicating with customers.

Mark: [00:15:18] Rob, this has been a really enlightening discussion on data in marketing and it’s great to have you on Confessions of a Marketer. Thanks for being here.

Rob: [00:15:26] Mark, really nice to meet you. Keep doing what you’re doing and we’ll be listening. And thank you for having us.