How a Lead Generation Company, a PhD Cosmic Ray Data Analyst & 200 Million Data Points Uncovered a Goldmine

Join Alexander Willemsen as he shares REAL data analysis insights from his lead generation company which have caused him and his team multiple “WTF” moments. Alexander will show you how he applied some of those results to his own affiliate campaigns and how this has hugely increased conversion rates.

Speech by Alexander Willemsen | Affiliate Expert

Alexander Willemsen Speech Transcript

Alright, thanks. Thank you all for coming to this presentation.

Two and a half years ago, I made a pretty bold move. I was doing affiliate marketing for quite some time already.

And one of the biggest verticals I was running, and still am running to this day, is sweepstakes. If you look at sweepstakes as a business model, that’s like a company, at the end of the day, they collect data and after that they find clients to sell the data to.

So, as an affiliate, I was thinking, “Okay, I’m running big numbers right now, why not cut out the middleman?”

And with the middleman in this case, I don’t mean the network, but I actually meant cutting out the advertiser. So, what happened is I partnered up with 3 others, also experienced in the industry already. We decided to just start this venture.

Beginning Of The Journey

And now, we’re two and a half years later and the lead generation company is active in 8 different countries. We have over 40 employees, we have 3 offices in different cities in the world. I can tell it’s quite a success, so far.

After that, we hired people, we were active in different countries. We did another very interesting thing, in my opinion.

We decided to hire a PhD in cosmic-ray data scientist. And this was a friend of a friend of our CEO. At first, we were thinking, “Okay, the link with online marketing is pretty far off but at the same time, he knows how to work with data.”

And these guys, you can just hand them any data set you want and they will find whatever you want them to find.austr

Bad Quality?

So, the beginning of this year actually, we saw his first value. He was working in a company for over a year, but the beginning of this year, what happened is all of a sudden, our clients told us you have bad quality.

First thing we did was like, “Hey, can’t be true, we have high quality, we have good validation, we know how to work with the traffic, we haven’t had these complaints before.”

So, the first thing we did was like look at our traffic sources and be like, it’s your fault or it’s your fault or it’s your fault. And, after we couldn’t really find anything, we started looking internally.

It should have been all the way around obviously, but we did it this way.

And what we found out is that 16% of all the leads we were selling to our clients we’re underage.

This was like, “Wow, what’s going on here, this is not how it’s supposed to work.”

And this is where Stefan, our data analyst actually proved his first value because this is the point where we said like, “Okay, please find out what’s going on, please find out how we can fix this, especially.”

What The User Sees Versus What The User Does

Now, the funny part comes, of that 16%, 73% of all the leads had as a date of birth, the same date as the lead would sign up.

So, I can better show it with an example of how it actually worked.

Here, you can see one of our sweepstakes. At the left-hand side, it’s just a form, where it’s not filled out yet.

And I took for granted that if someone sees, they have to fill in like the gender, they have to fill in the first name, last name, email, that it would be pretty common sense that if you see day, month year, that you also have to fill in your date of birth there.

But it did it happen.

What actually happens was that people or well 73% of the underage people, filled in the same date as when they registered on our sweepstake. And this was like a moment for us, where we were like, “Wow, what is going on?”

The Amazing Fix

The fix was really easy. The fix was literally this.

As soon as someone would enter the date of today or something that doesn’t really make sense, we will just show them an alert saying like, “Hey, are you sure you’ve filled this in, correctly?”

And the result of this was that as opposed to 73% of all underage leads signing over the same day, it went back to 0%.

So, all of a sudden, our clients were happy again. We didn’t have to block out any traffic sources or whatsoever, and we fixed the problem.

Einstein made a very interesting quote years and years ago, obviously. He made a quote where he said, you know, humans aren’t that smart and I’m not trying to say that he is right.

But what I am trying to say is that in this specific scenario, I took it for granted so much that if you see a day, month, year that people would know what would happen.

Actually, I was the one who was a little bit stupid, in this case, because I made an assumption. And this is actually what I want to talk to you about today.

Easy To Make Assumptions

I want to talk to you about how, as an affiliate, it’s really easy to make small assumptions or big assumptions just because you use your common sense. And what you should do as an affiliate is actually use data.

It’s pretty obvious, everyone knows it. You can read it on STM and you can read it everywhere. But still, some things you take for granted so much that you think like, testing is not even needed.

The 4 things I want to talk to you about today. are shown on the screen right now.

I’m actually going to prove them wrong by using the data we have from staff and our data analyst. And, you’ll be surprised by the results.

Leads From Pops Are Bad Quality

So, first one is that we were under the assumption that all the leads that were coming from pop traffic as a traffic source was bad quality.

And, why did I think it was bad quality because there is this general assumption about where pop traffic is coming from. I was running dating about 7 to 8 years back, on sources like AtCache and WeGotMedia.

And from my experience back then, they were mostly being shown on torrent websites, on like watch free movies online or video games or something similar like that.

But what actually happened is that torrent sites, they became mainstream. And how did they become mainstream, because there was a lot of media outages about, for example, the torrent websites or people actually start thinking, “Hey, these torrent sites, I can actually use them.”

And it’s not just the tech-savvy persons who know about internet that use them nowadays, but it’s also just a general population.

What I want to show you next is data we gathered from 3 different countries, in three different part of the world.

Demographic Pops

I’m going to show you the demographics of Brazil, UK, and Australia. I was very surprised when I got this data from Stefan. Hope you will be too.

So Australia first. In Australia, 73% of all our leads were actually over 26 years old, 73% over 26 years old.

So what about the UK?

UK, you would think, okay people are more known with the concept of pops, but it got even better.

In the UK, it was 77% of all the leads that was over the age of 26.

Now, you can think okay, Brazil. Brazil is a way younger country in terms of internet users and all that.

In Brazil, I was blown away by this fact.

Brazil, it was a total of 81% of all the leads that were over the age of 26.

It’s really hard to say, like how this is possible. Of course, because I don’t have insights in everything and our affiliates are also not willing to share everything for example.

But there is some common sense that you can use here, which actually is that 7 or 8 years ago, there weren’t any mobile pops, etc.

And so what really changed a lot about the entire pop inventory available on pop as traffic source, it’s they’re coming off from mobile.

Either way, point one, where we were standardly thinking like, “Okay, leads from pops is bad quality.” It’s been proven wrong.

Convert The User As Fast As Possible

Next point, is that as an affiliate, I was always taught right from the beginning, you have to convert the user as fast as possible. If you can leave away some information, which you think won’t hurt the conversion rate, then please leave it away.

Because we as affiliates in general, we don’t care about quality, really. We care about getting the click to lead ratio or click to sell ratio as high as possible.

And the advertiser has to care about the quality part, that’s their part.

Now, before I get into details about this one, I want to show you a little bit from how the business model of sweepstakes actually works.

How Sweepstakes Work

You have three big steps.

First step is you have the form, where people fill in their information. It’s also the same form where I showed earlier, where people put in the wrong date of birth.

After that the affiliate pixel fires. So at that moment, if you would be running sweepstakes, that’s when you get paid.

But at that moment, as a sweepstake company, you didn’t earn money yet because what happens after that is that the user gets put in a survey, in a questionnaire. That’s a middle part.

And in this questionnaire, we ask anywhere between 10 to 85 questions depending on the country. And our clients who can give the questions in there.

So you have to think about it that’s like, there is an electricity company who wants to get new customers, so they would approach us and be like, “Hey, we’re looking for leads who are interested in saving up to 20% on their electricity bill” for example.

So then you would have a question in the middle saying, “Would you like to save 20% on your next electricity bill? Yes or no?”

The moment a person clicks yes, that’s the moment when the leads actually gets sold to the client. So that’s the middle part.

Then at the end, when all the questions are done, someone gets sent to an exit offer that’s not really relevant for us, but it’s really about the main part about the survey, where the money is made for us.

With this affiliate mindset, what we were thinking is we have to keep the questions as short as possible. Like please don’t try to take too much time away from the user because you might lose them that way.

Going Through The Entire Funnel

Now, after Stephan joined the company, he also dove into this kind of data and looked at how many people actually end or go through the entire funnel.

The result was quite surprising because 81% of all the users who filled in the initial form on step one would stay until the end.  And by the end, I mean the moment they answer the last question and they go to the exit offer.

What’s also really interesting is that on average, people take 13 seconds per question that is being asked in a survey. I was highly surprised by this.

This is specifically for Australia, we have an average of 64 questions in the entire survey, which actually means that from start to finish, people take an average of 14 minutes to complete the entire sweepstake.

Now, how this helped us big time is that before, for example, they don’t want to show logos, we didn’t want to make very extended questions, we wanted to keep it as short as possible kinda, but this really changed our own mindset.

Because we were thinking “Okay, people are willing to read if they are highly engaged with what they can get.”

“win an iPhone”

In this case, with sweepstakes, it would be something like, “win an iPhone.”

They really want to win that iPhone so they’re also willing to put in the effort to actually read all the questions and go through the path as good as possible.

In our case, it actually means that we don’t have to convert a lead as fast as possible. How I would apply it to any other campaign is that again, for this one, it’s an assumption that’s being made.

Like you have to convert it as fast as possible, but did you actually ever try it with a longer pre-lander or a longer offer page?

Conversion Rate Is Highest After Dinner

Point number 3, I guess this was also a mistake made by me again, where I was thinking like, okay how the general life of someone looks is, you get up, you have breakfast, you go to shower. And then you spent the next 8 or 9 hours at work.

After that, you come home, you have dinner. And then your free time starts.

That’s the moment when people would actually convert, that’s what I was thinking where the conversion rate would be the highest.

But is that really true?

The next graph I’m going to show you, is a graph of all the data combined from all the different countries we are alive in, and it shows when a conversion rate is the highest, at what point of today.

And it looks like this.

Conversion Rate

It’s actually really surprising to me because it means that right around lunchtime for sweepstakes, right around lunchtime, people are most engaged to actually sign up to the sweepstake.

Okay, so we got this data, we were thinking, okay maybe it has to do with like one specific country or something where the conversion rate would be higher and it would kind of distort the data we have here.

Then we took the data from all the different countries.

And there is actually only one exception where it’s not true, and that’s the UK.

Don’t ask me why. UK, it’s at the highest, the conversion rate is actually right before people leave work.

But still it’s if you think about this, like how many times have you been thinking for example, “Okay, I have to launch my campaign at a good time of the day so that the initial conversion rate will be highest and I’ll have like a good idea if the offer works or not.”

What I would be doing before is I would always launch it around 7:00 PM. Because then, people are actually at home. They’re willing to convert.

But this data actually shows that it would be best to launch it early in the morning.

So, again for us, point proven wrong.

Women Are Better Quality Than Men

Last point and at the same time, this was also the most interesting one, in my opinion. And that’s where we were always thinking that women would be higher quality than men.

The reason why I was thinking it, is that when I was running sweepstakes directly to our competitors right now, they would always tell me, “Please only send traffic for women who are 25 plus, because they are the highest quality.”

I was saying, okay I’ll take it for granted, why try to invent the wheel twice when we start this company. We would also be focusing on women opposed to men.

And we could reason it with ourselves because we were thinking like, okay, women like discounts, they like to sign up for offers, for voucher campaigns, they like to win stuff.

While men are only interested in gadgets and electronics. And they don’t have patience.

That’s what we were thinking.

This part is again important in order for you to understand what I’m going to say next. As I told you before, as a sweepstakes company, you make the money in the middle part in a survey.

RPT: Revenue Per Transaction

And how we actually calculate the value of a user is with a term called RPT, its Revenue Per Transaction.

What it basically means is that, let’s say you have 10 questions in your survey. And for each question, you would get paid 10 cents if it’s answered positively and someone answers 5 questions out of the ten positively, it would mean the RPT for us would be 50 cents.

Now, for us in order to look at quality, we actually look at the amount of questions that are answered positively. And at the end of the day, that means that we’re looking at what our RPT is.

What we found out at first is that men actually convert 1.5 times more positive than women, overall, in every single country.

This data was like, I didn’t understand it. I would think it was more equal or that it would answer a different type of questions or anything but it didn’t okay.

What about ROI? For obvious reasons I can’t show you our exact numbers but I’m going to take a baseline, meaning that I will show you an RPT of $1 in every country and then I’ll show you the equivalent how men would be looking percentage wise.

So first one, Australia. Difference isn’t that much. It’s only 4%. The sale is 4%.

Next one, UK. For every $1 we make for a woman, we make $1.08 for men, 8% difference.

The one where I was, again, most surprised by is Brazil.

In Brazil, we have 30%, we earn 30% more for men than we do from women.

Time Per Question

Another very interesting fact is that we were thinking that women would take more time to actually read the questions and to actually engage more with the entire survey in the beginning.

The graph I’m showing you right now is showing the average time it takes per gender to complete one of the questions in the path.

And again, also for this one, you can see that men are actually performing better than women. So, the patience part is also not true. In our case, at least.

Point being that we actually made a really big mistake in the beginning, where we were just assuming that women would be converting better than men.

I showed you a lot of points right now and a lot of data. And of course, it doesn’t necessarily apply to everything.

But the point I’m trying to make is that you always need to be thinking, you always need to think smart, you need to think bold.

What we did by hiring our cosmic-ray data analysts is something that was against what a lot of other opinions were of other people. Because they were saying like, “Hey, online marketing what’s the connection with them? Why would you give him such a responsible role, such an important key factor in your company to someone with zero experience?”

We took the dive, ended up really well. What I’m trying to say and this is kind of cliche but it is true.

Think outside of the box. Don’t think there is a box. Do something different.

No Emotions, Just Data

Next thing, I want to show you or tell you actually is to really cut out your emotions.

The screenshot you see here is from a movie called Moneyball. And in that movie, it’s based on a true story, it’s about how baseball changed.

How it used to work is where you would have scouts going to different games and look at different people. They would pick people based on how their swing is or just looking at them and not actually fact-based or anything.

So what happens at some point is that there was a team in the US. And this team, they didn’t have much money at all.

The very expensive players at the biggest teams, they would be too expensive for them.

Then there was one analyst who started using the database of all the baseball players around. He would just make decisions on hiring players based on the actual statistics.

In other words, they didn’t care how people looked. They only cared about actual results.

Keep Testing

For us affiliates, it’s really easy to make assumptions nowadays. You are not willing to test. But at the end of the day, what I’m trying to actually say is at any point, even if you think something is so common, is so true, keep testing.

That’s it. Thank you.

Q&A

Rishan:

Awesome, thank you very much for that. I really, really learned a lot. You probably know that I’m a closet nerd. I used to be an actuary previously, so data was my whole life. And it’s really cool to see that people are bringing it into performance marketing, to affiliate marketing. So we’ve got a few minutes for questions. I had one off the bat just to get it rolling.

Alexander:

Go for it.

Rishan:

At what point, what volume of data do you need to make it worthwhile to employ somebody to start analysing it right? Because there’s some kind of tipping point, where now you’ve got enough and you kind of assume that this person is going to more than pay for themselves and give you some valuable insights. Was there a clear point where you waited for enough data or you felt that you had enough in order to make it worthwhile?

Being At The Right Spot At The Right Time

Alexander:

It was more the other way around where we were thinking we were tracking everything by the way, so every single click that was happening, and every event that was actually happening in the sweeps, we were tracking. So, we were storing everything in the database, but we weren’t doing anything with it. And then there comes a point where you’re like okay, it’s really cool to have all this data, we have database tables of gigabytes full of points that were was not being analysed. I guess, it came at the right time as well, like we weren’t actively looking for someone like that. We had it in the back of our head that we at some point needed to do with, but this was I guess a case of being at the right spot at the right time.

Rishan:

Right, good timing. So you’d already had built up this data, it was sitting there. And then, the opportunity came along to have somebody qualified analyse it and you grabbed it with both hands.

Alexander:

Yeah.

Biggest Insight That Came From The Analysis

Rishan:

Yeah very cool. What was the biggest insight that came from the analysis that proved a previous assumption correct? So you shared with us a ton of stuff that, you know, you’d assumed, like man versus woman and the data proved it wrong. Was there something that you’d assumed before that was kind of traditional knowledge that the data did prove correct?

Alexander:

Yeah, quite a lot as well. Because how it works nowadays is that Stefan is proactively looking for weird things by himself. How we had to do it at the beginning was we had to give him points which we were thinking that they were untrue.

Rishan:

Right.

Alexander:

But then, I guess we were thinking the right way because they were actually true.

Rishan:

Got you, so most of the traditional assumptions in marketing….

Alexander:

It’s a lot of like, one of the points, I was really curious about actually and we spend a lot of time trying to figure something out that would be really cool to show here, as well. I was really under the assumption, for example, that the terms and conditions of sweepstakes would be read quite a lot. And it turned out as like everyone thinks about it, that people just don’t read. They don’t read it. So that was a shame but…

Rishan:

Very cool. Okay, so I’d like to open it up to the audience questions. There are a couple mics scattered around. If anyone has any questions, Alex would love to answer them, I’m sure. Well, there may not be as many nerds in the audience as we think.

Alexander:

I’m sorry?

Shortening The Questionnaire

Rishan:

Maybe they’re not as many nerds in the audience as we think. Data guys. Well, here’s another one from me. You mentioned that it took about 14 minutes for them to complete the question.

Alexander:

Yeah.

Rishan:

Yeah, have you guys have thought of shortening it or would that reduce the value of the data? Was that a discussion that ever came up? Was that even an option?

Alexander:

Yeah, it was before because, at some point, you’re thinking, okay we have so many questions right now and we were so much under the assumption that the more questions we would have, the more people would drop out.

Rishan:

Exactly.

Alexander:

That’s what we were thinking, like, okay at some point there must be a tipping point where people are like, “I can’t do this anymore, screw your iPhone, I’ll go for something else” but it didn’t happen. Actually, people just keep going. What really did make a difference as well is that, and my thing at least, is that right from the start, we had a little progress bar at the top. So people knew how far they were off of actually completing it. We never tested it to remove it because it makes so much sense to have it there, but I think it does make a difference.

Rishan:

Gotcha, so you definitely tested using less questions but you felt the drop off didn’t justify the reduction in data that was collected?

Alexander:

I’m sorry?

Shortening The Questionnaire Wasn’t Worth It

Rishan:

So, you tested it having fewer questions but it just wasn’t worth it, long story short. Because the same amount of people completed it.

Alexander:

Exactly. At that point it doesn’t make sense to have the option to earn less revenue if you know up front that you will earn more it all the way around. Does that make sense?

How To Deliver Leads To The People That Are Buying Them

Rishan:

Yeah. So, a technical question not to do with the data analysis, I guess. How do you deliver the leads to the people that are buying them? Is there a platform that you use kind of a white label solution or did you have to do something manually?

Alexander:

We started off with Cake. Actually, Cake has a sub-platform which makes this possible. I hope there’s no one from Cake in the audience, but Cake proved to be the wrong platform for us, to say it politely. So then we started developing our own platform. And this, I guess, this is also the main strength of our company right now that we have a very custom solution with very much validation and there why we are able to deliver high quality.

Rishan:

Very cool, okay. So last call, if there are any questions from the audience?

Finding The Buyers For All Leads

Audience:

Hi Alex, I was just wondering how difficult it was for you to find all the buyers for all the leads in so many different markets.

Alexander:

How?

Audience:

How, yeah. How involved was the process especially like if you have Brazil and AU and all these other different geos? Was it hard? Were there marketplaces you were able to tap into or did you have like connections already from when you were doing sweeps as an affiliate or…

Alexander:

As I told you before, I started the company with all our partners as well, and actually our CEO is probably the best sales person I know. So he knew how to get the clients in. And I knew how the traffic worked. So that was kind of like a good match. Honestly speaking, I’m not involved in a sales process at all. So I don’t know how they hunt them, but my assumption is LinkedIn and just searching online for people who have newsletters because they will be interested to buy data.

Audience:

Cool, thanks.

Alexander:

Welcome.

Audience:

Yeah. I was just wondering and I’ve done a bit of sweepstakes, what’s up with the other competitors, I guess. Like with the 25 plus women. They never test it or how do you explain that?

Alexander:

So, if I understand your question correctly it’s?

Audience:

Like your assumption that women 25 plus are performing better compared to men, which is still going on today, right?

Alexander:

I think it’s still the case, yeah. I just know that whenever I was sending younger people I would get cut off from the other sweepstakes companies out there.

Testing The Difference Between Men And Women

Audience:

So basically they just don’t test the difference between men and women or…

Alexander:

Seems to me that that’s the case.

Audience:

Okay. Cool.

Alexander:

Welcome.

Rishan:

Another question that Hugh just mentioned was, he’s tried to hire somebody like this to analyse his data and it was pretty challenging. In your case, I think you briefly mentioned it was a friend of a friend.

Alexander:

Yeah.

Rishan:

Do you have any suggestions or did you try to hire through a more traditional channel, previously?

It’s All About Analysing

Alexander:

I think honestly speaking, if I would want to hire someone for this role, I would also look into someone who has like at least knowledge of online marketing. But if you really think about it, and I also talked to Zeno about this right before this speech, it’s all about analysing. So if you know how to analyse data, it doesn’t matter in what field you specialise, you should be able to work with any data set. If I would have to do it again right now, I would just look up what kind of studies are there that involve like statistics and data analysis, and make your pool a lot broader them then just visioning someone who already has marketing experience.

Rishan:

Gotcha. Yeah, because there is a big pool of people, big data is a big upcoming market.

Alexander:

Yeah. Something that is very important though is you always have to keep it challenging for them. So for us, it was really challenging I guess or for Stefan it was because we actually had like huge amount of data and no one else ever analysed it before. So he was the first one who could also really work with it, which is like a challenge for those kinds of people. And we were very happy with it.

Rishan:

How did you have to deliver the data to him, was he pretty flexible in the format that he took it or did it take a lot of technical work, database manipulation.?

Alexander:

He has like his own workflow. So, we pretty much gave him access to the database and he took it from there.

Rishan:

Awesome. That’s what’s amazing.

Alexander:

Yeah.