Why Your Top of Funnel ROI Sucks (and How to Fix It)
Highlights from this Episode
Highlights from this episode
Today we're going to discuss waste in the top of funnel for B2B demand generation initiatives. We'll talk about what you can do about it as well. LeadCrunch[ai] uses artificial intelligence to drastically improve the performance of B2B demand generation campaigns through account-based "lookalike" modeling. Click the link for more information. https://leadcrunch.com/solutions/
Posted by LeadCrunch on Friday, August 2, 2019
Hosts: Dave Green & Jonathan Greene
Topic: B2B Targeting
Subtopic: Artificial Intelligence
Duration: 20 minutes
In this episode of the Green & Greene Show, the LeadCrunch B2B podcast, seasoned marketing experts discuss why your top of funnel ROI sucks and how to fix it.
- How Shoddy Targeting Puts Your Career in Jeopardy
- Intent Data: What’s It Really Telling You?
- The Value of Lookalike Audiences & Content Syndication
- Eating Our Own Dog Food: Marketing AI IRL
- Typical Ad Spend ROI by the Numbers
- Getting More Value from Programmatic Display Ads
[0:00:05.1] ANNOUNCER: Live from the city with the most perfect weather ever, San Diego, California, all the way to the gleaming shores of Jacksonville, Florida, it’s the Green & Greene show. Here are your hosts, Dave Green and Jonathan Greene, goofing off instead of working while unlocking the mysteries of demand gen. The Green & Greene Show is brought to you by LeadCrunch, which creates B2B lookalike audiences.[EPISOSDE]
[0:00:26.8] JG: Sing it, girl. Too young to talk about forever, Dave. I don’t even know what that means, but it’s actually existential as heck.
[0:00:38.4] DG: I know, that’s way too deep for me, man, I’m from California. I think you have to be from the East Coast to be thinking about existential.
[0:00:46.7] JG: Yeah, well, you know, we’re all like that over here.
Let’s talk about the top of funnel. I’ve got a lot going on in my mind about the top of funnel these days, man.
How Shoddy Targeting Puts Your Career in Jeopardy
[0:00:59.2] DG: You know, it’s more like a bottomless pit than the top of a funnel. There’s a huge amount of money that is just being wasted, and a lot of media sales reps have gotten rich because of that. A lot of poor marketing slobs have gotten fired when the finance team looks into the numbers and says, “What’s the return?”
[0:01:26.1] JG: It’s a catch-22 because you’ve got to have top-of-funnel traffic in order to get anything moving, obviously, through the funnel, but I don’t think a lot of demand generation marketers realize, because they tend to be disconnected from the financial outcomes. For a lot of businesses, that vertical is siloed, so you’re responsible for lead delivery into the funnel, and you don’t necessarily get called to account for the cost per lead or the cost per new sales appointment generated, or ultimately, the cost of acquisition of a paying customer.
You tend to be divorced from those things, so you don’t realize the waste that shoddy targeting at the top of funnel directly contributes to the profit margin of the company in a very meaningful way.
[0:02:12.9] DG: Yeah, it’s one of those things where the lower the cost of, say, the CPM or the CPL, usually, that has an inverse relationship to the value you get downstream from that. There are so many what data scientists call false positives. It looks like you’ve got a bunch of stuff going on that’s good, but it doesn’t really pan out.
[0:02:42.5] JG: Yeah. Cheap leads are not good, and good leads are not cheap. In a more meaningful way, what I think I’m approaching, what I’d like to talk about today, is just sort of that demand generation function and the way that they target and how that’s inherently wasteful.
For instance, if I go to market and I’m targeting interest-based targeting for LeadCrunch—and this is actually a real scenario, we tried this, we went through this in real life. I came onboard, and we wanted to target interest-based targeting for people who are interested in demand generation, which we did. It’s very easy to execute on, fundamentally, from a targeting perspective.
Then the leads started flowing in and they’re $5, $6 leads which makes everyone very happy. Then, by the time we combed through them all, about one out of every 200 or 300 leads was the demographic and psychographic and firmographic that we needed in order for them to be viable candidates to work with our business.
It looks like a $5 lead, but by the time you’re done combing through the 300 of them that you need to get to the one that is actually going to work, it’s more like a $1,500 lead. We did that, and look, I had to try because you know, there are a lot of scenarios, particularly in B2B instances, where that will work and you can drive a ton of pipeline that way.
But, if you’re in the B2C vertical and you’re trying to do demand generation, I suspect you’re going to have to do a little better than that with targeting.
Intent Data: What’s It Really Telling You?
[0:04:24.9] DG: Yeah, interest is one of those things that, of course they call it “intent” now, which is probably one of the great marketing-hyped pieces of merchandising, because it’s not intent, it’s interest. That’s all it’s ever been is interest, and interest isn’t the same thing as an actual intent to buy.
I have an interest in the New York Yankees, but I’m not going to be able to play baseball for them tomorrow. Those are just not the same things, and I think you see that a lot. There are lots of people who have curiosity or interest, but they don’t have any need or authority to buy.
[0:05:07.4] JG: Yeah, unfortunately for us, most advertising platforms and mediums are devised for B2C activity, and as B2B marketers, it’s actually sort of tough for us to get a start. This is why we’ve seen the rise and the success of account-based marketing because it really does limit and put the Kibosh on a whole bunch of wasteful targeting at the top of funnel.
I think there’s a way to go even beyond that, which is kind of what I wanted to get into today. Account-based marketing is certainly the way to go. I think people will find that there are very stratified, well-established data sets out there by which you can slice and dice your ABM campaigns and your initial targeting. I think the problem is that they’re not inclusive and there’s a lot of middle-ground companies, people, individuals, contact-level data that is not in those data sets.
If you just go ABM strategy with the strict segmentation using Discover.org or anything else, you know, even a very good data set, you have to understand that you’re still leaving targeting on the table.
The worst part of that is if you just go to the mass market and try to target you’re leaving revenue profit on the table so there has to be a sort of a happy medium.
[0:06:28.2] DG: Yeah, I was just reading something for a CMO and it was actually one of our clients’, I won’t mention the company or the name. I was reading an article and he said something that was completely reasonable: “We like to start with the size of the company.” Whether it’s revenue or head count, that is not uncommon. It’s actually widespread. “We want to go after companies that have 500 employees or more.” Whatever it is.
The problem is, whether it’s revenue or employment, those things are not equal. I looked at this a while back. Tech Data is a distributor of computer technology and their revenues, I think in 2018, were about the same as Facebook’s. The difference is they had like microscopic profit whereas Facebook had massive profits. Even though both of them are the same size from a revenue standpoint, they’re a completely different companies from a buying capacity standpoint because one has cash curving off the earth and the other was you know, not in that spot.
You got to be a little bit more nuanced than that in order to get to who you’re really after.
[0:07:54.5] JG: The problem is, if you live in ABM world, you’re dealing with imperfect data and probably leaving customers on the table. If you live in platform world where all these interest-based targeting and intent targeting and all that crap lives, then you’re probably leaving revenue on the table by being wasteful.
That is really the catch-22 of this vertical that we find ourselves in, the B2B demand generation vertical. What excites me and what makes me really happy is that people are starting to come up with answers for what we might be able to do. One of those is the lookalike audience model that LeadCrunch has been applying to middle of funnel, content syndication type marketing for quite some time.
You want to talk about that for a second?
The Value of Lookalike Audiences and Content Syndication
[0:08:48.0] DG: Yeah, the idea is that you give us a set of best customers, it could be best customer for a product, it could be all the big spenders because it’s an ABM list, it could be a segment like SMB. Whatever that market is that you’re trying to go after, you give us a list of those people, we build a lookalike model of who are companies that have those characteristics out in the marketplace, and then we’ll introduce your white paper or eBook and generate a lead.
You are then letting us know what happened so that the model can get better and better over time which, by the way, doesn’t happen with any other platform that I’m aware of. If you have some learning, it’s not like the platform gets smarter next time. Maybe you get smarter and maybe you do more things to be more segmented, but the platform’s just a platform. It doesn’t care.
[0:09:55.3] JG: Yeah. The recursive learning is the first big advantage point that I see. The second is that all these other people, even people who are claiming to do lookalike audiences, are all pivoting on the same data, which is the same exact firmographic stuff that we talked about a minute ago. How big is your company, how many people work there, what is the revenue, etc., etc.? Even if they do lookalike audiences, they’re not giving you a bigger piece of the pie like we talked about. They are just using the same exact data sets.
What we’re doing is assembling the whole known universe of businesses, to the extent that we are able, and we are using artificial intelligence in a way that nobody else is. There has been some effort there to redefine the way targeting is done, so they don’t use firmographic targeting in the AI. They use what we call vectors, which are like the deep dive.
It includes lots of things: Connectivity that the human brain could never visualize. Deep language processing, so it knows things that other intelligences do not know. As a result, you get a target set that other intelligences could never deliver to you. It covers a greater percentage of the blind spots, the missing points in the market that people could identify.
Eating Our Own Dog Food: Marketing AI IRL
[0:11:17.1] DG: The reality is that the ideal target for a particular product is probably unique to that product, unless it is highly commoditized and it is just another “me too” product, and the right data for that product is probably unique to that product. We eat our own dog food here. We call it our R&D lab because we are marketing guys. We like to jazz it up a little bit.
When I sit down with our head of data science, we talk about, “All right, what are the characteristics that are typically true of people who are good candidates for us to go market to?” One of them is that they’re B2B. Well, I defy you to go find, in your firmographic list, that data set. You don’t really get to that, because a lot of companies are both. I said, “A lot of times, they’re licensing content, the high premium content from companies like Gartner and Forester and Frost & Sullivan and SiriusDecisions,” so we did a keyword search around those kinds of terms showing up on their website, and they have a resource-type page.
You know, I could tell a lot of different nuanced things about who we’re looking for in order to help him help me target who we’re after. That’s really what you have to do if you’re going to get beyond, “Give me everybody with a hundred employees except the people in the government,” or whatever your firmographic slice is.
[0:12:49.1] JG: Yeah. We are very good marketers, I think. We could have the whole team and we could rent a conference room off-site for a week. We could sit around that conference room and spitball targeting ideas for seven straight days, and we would never come up with “resource page”. They all have a “resource page”. We should target companies with “resource pages” or companies that mention the word “Gartner” on their website.
We would have never arrived at that conclusion, regardless of how smart we were, but the AI picked up on it in an hour.
[0:13:25.9] DG: Not only that, even if we did come up with it, what do you do with it? “Oh, I am going to call up my list broker and ask can you give me all the websites that have a resource page that are B2B and blah-blah-blah?”
“No. I can give you a list of opportunity seekers. Do you want that? We have 12 million of those.”
[0:13:46.4] JG: Who has a website? One or zero, they probably got it. Well, I can give everybody with a website, does that help?
Typical Ad Spend ROI by the Numbers
[0:13:54.3] DG: You know, to bring home how bad this is, this top of the funnel problem, for those people who maybe are having a little bit of friction with their sales organization and they don’t really have their salespeople behind the leads that they’re ultimately generating with their top of the funnel traffic and lead generation efforts, WordStream, which is one of the companies that, if you’re into paid search and SEO, they have some tools for that and they do this really wonderful benchmark study.
It has about 14,000 companies, a bunch of their customers, I guess. They published what, in different industries, is the conversion rate, and for display ads, it is around 4/10ths of one percent. That means out of 99 people, not even one of them. That is like a 400 to one ratio or whatever it is. It is a really small ratio, and you think, “Oh, okay, well, that’s bad. I guess that’s why we call it banner blindness.” Then you go look at the traffic and again, for them, it’s around 8/10ths of 1%.
Then you go follow that through to who buys, and again, it is below 1%. It is about one out of 500,000 people that you have your message out to will actually buy anything. I don’t think anybody is out there talking about this, and it bugs me because people are spending a massive amount of money and it is annoying. I think it is actually a big reason that GDPR is in play. We see so many irrelevant ads that we get sick of it. Why can’t we just be a little bit more relevant?
[0:15:34.9] JG: Yeah, and then it ends up being the situation where you have to buy hundreds of millions of impressions to fill your pipeline, which, if you think about it, is ridiculous. That is literally everybody in America, or of the 20,000 people you think you want to talk to 800 times a piece are not really the people that you want to talk to. That’s why they have not responded, right? Compare and contrast that to the early experiments that we ran with this AdCrunch product that LeadCrunch is releasing.
The click-through rates are several times industry benchmarks off the bat. Why? The targeting isn’t stupid, and it is simple. It just takes the people you have already had success with, which look, there is no better dataset than people who are already buying your product and loving it. You take that, you roll it up into the AI, the AI spits out a list of businesses that look just like those people, and then you serve ads to them, because we could have contact-level data and serve it to the trade desk.
You serve ads to those people, and lo and behold, the click through rate is tripled or doubled. I mean the difference is astounding, and it ought to be, considering what most people are doing with their targeting at the top of the funnel.
[0:16:56.7] DG: More importantly, for those people who maybe aren’t quite as sophisticated, not all clicks are created equally. You have things like time on page downstream to start to measure how engaged these people are with the content that I was trying to get them to engage with. Can you talk a little bit about that?
Getting More Value from Programmatic Display Ads
[0:17:18.5] JG: At any given top-of-funnel programmatic ads, there are going to be people who are genuinely interested in what you are saying and there are going to be people who are looking to screw around, just clicking through to see what is going on, so the higher the quality of your targeting, the less looky-loos there are and the more people who are genuinely interested.
Genuinely interested people will hit your page and they will read it, so their time on page won’t be 15 seconds. It will be three and a half minutes. Or, you could look at page depth. They will read one page, and they’ll go, “Okay, well that was interesting. Tell me more,” and they will click through additional pages. Their page depth won’t be one page. It will be four pages, right? By increasing the quality of the targeting, you also increase the engagement metrics of the traffic.
[0:18:07.2] DG: You know what? I think you just happened on a new meme. I do hope that people out there start to question why so few people click on their ads, why so few people are really engaged with the landing page that they have, why so few people convert into a lead, and why so few people who are leads convert into a sale. When you really add up the amount of money being spent on this, it’s pretty massive and it is wasted and there are hungry people to feed.
There are better things to do with money than just completely waste it. Just go up on the top of your building and throw a bunch of money off of it if you want to waste it. At least the people at the bottom of the building will luck out and get something out of it.
[0:18:50.5] JG: They will love you forever. Yeah, it’s programmatic done smartly. That is what I like about what’s going on with this artificial intelligence and this lookalike audience business. It is common sense applied at a massive scale, really good stuff.
[0:19:07.7] DG: I think that’s it, Jonathan. I think we’re all out of material at this point, and we are going to have to go back to goofing off.
[0:19:14.0] JG: I guess so. I am going to have to find the music real quick, so give me a parting message.
[0:19:18.3] DG: I think Jonathan’s head bob to start this show is just priceless folks, and Jonathan, for the rest of the audience if they are out there, I hope you do your head bob because it is really the best.
[0:19:38.0] JG: There it is.[END OF EPISODE]
[0:19:23.8] ANNOUNCER: Thank you for tuning into The Green & Greene Show by LeadCrunch. Green & Greene think differently about B2B and want to start a movement to transform demand gen. If you have ideas for topics or would like to be a guest, send an email to firstname.lastname@example.org. If you’d like to find more customers, visit our website to talk to one of our demand gen guides. www.leadcrunch.com.[END]