September 5, 2016

This Just Got Personal: How To Convert Leads Into Revenue

Franz Aman, senior VP of marketing at Informatica, explains how to use data analytics to cut through the marketing mess and make some serious cash.

How do you think the marketing sector is developing?

When it comes down to it, today businesses are pretty much powered by data, whether it’s the Ubers, AirBnB’s, whatever. More than ever people rely on data and analytics to drive their business.

I’m a marketing guy but I come from a technical background. I believe that marketing has become more technical and you really need to understand the data these days.

Marketing used to be more about wedding planning, events, logistics. Those times have come and gone. So much of the buying experience now is happening online and customers research everything they buy online. When we pick a restaurant what do we do? We use Yelp, we use TripAdvisor. And with other business, more and more of this is happening. Consumers will use Google. Naturally, for the marketer it’s all about digital. It’s all about figuring out what people research. You’re trying to find the people and their intentions.

Digital marketing is something I have in my portfolio as well. I run all the paid for and web search for Informatica. We’re actually bidding quite a bit on Google keywords because with paid media, if people search for something there’s something going on, they’re working on a project. They’re researching that keyword for a reason. If I look at the quality of leads we’re getting through paid search, it’s higher than anything else in terms of finding someone who actually has something going on. So, in marketing now, digital is the lion’s share of what really matters.

How can analytics help marketers?

I’ll give you a simple example. If you look at a digital marketing team, a lot of the time they are told to bring in more leads and lower the cost per lead (CPL). CPL is something that matters incredibly to marketers, but is that really the right optimisation? I would argue that most marketers don’t have the end-to-end line of sight. They don’t really see how many of these low CPLs turn into revenue, and how much revenue. What’s the average sale for these leads? They’re just happily optimising within their scope pipe, within just the digital world. It leads to them eventually leaving some of the most attractive leads behind. They may not be the least costly but they might be the most attractive. We had an external consultancy review some of our marketing and give us some recommendations. One of the recommendations was to load more money on page display advertising. It was our lowest CPL area, our lowest lead quality area. Subsequently, we killed all of our display marketing, with the exception of retargeting.

We’ve invested in predictive lead modelling, predictive lead scoring. We have built a marketing data lake using big data technology, so we’re drinking some of our own champagne.  It’s been a phenomenal experience.

When I look at marketing now, every marketer has their own app. There’s an app for everything and when you talk to marketers about their biggest challenge it’s the challenge of making sense of all this, getting line of sight and integrating all these different pieces. As a CMO, what do you know? What do you invest in? What works and what doesn’t work?

Is analytics just for the bigger companies with more cash or can smaller firms benefit?

One size shoe doesn’t fit all. If I was a smaller company would I invest in a data warehouse or marketing data lake? Probably not. Would I have to figure out how to integrate some of the most basic components? Absolutely yes.

How challenging is it to find marketers with technical knowledge, or to train them up?

There may be some limitations. If you have a marketing team focused heavily on events management, for example, it’s going to be difficult to find the skillsets among those people to really understand technology and how to work with data. But what I’ve seen is that more and more marketing organisations are building marketing operations teams that are fairly technical. They understand data, databases, data quality. You really have to hire those skillsets and bring the resources in. You can’t just build it from a more traditional marketing team. You will be upskilling some people at times. Other times, you’ll just be hiring the skills.

How can marketing teams improve the quality of the leads they’re getting?

First off, you need to understand which ones are the high quality leads. In the mess you have I bet there are going to be a couple of high quality ones. But how do you know which ones they are and where they came from? This is something I take very personally because a couple of years ago we had a struggle with our sales team. Sales said that marketing generates tonnes of pipeline but it doesn’t convert to revenue. They said we were showing great numbers but it wasn’t converting. They thought the leads weren’t good. I took that very personally. In the end, we invested quite a bit in connecting all of the systems in a way where we could really see what was going on. As a marketer, you have to understand the whole picture. We integrated all the systems and poured everything into the data lake. From that, we created a predictive leads score and we trained it on which demographics and what marketing responses turn into revenue. It’s essentially marketing to revenue conversion. I didn’t want to have another discussion with sales about how we only crank out pipeline that doesn’t turn into revenue. We started this in 2014 and analyses it in Q1 this year. Four our licensed products, 94 per cent of the revenue comes from leads that score A, B or C. A, B and C forms just 30 per cent of our leads. That means we can just focus on 30 per cent of our leads and we can literally drive more than 90 per cent of the revenue out of that slice. That’s the kind of stuff that makes a big difference. We know what the high value leads are.

How do you think the EU Data Protection regulations will impact UK marketers?

Some of it is just nonsensical. It’s bureaucrats making up rules when they don’t even know how people can live by them. Marketing teams being unsure if they have to keep or delete data if a customer wants to be removed from a mailing list is a classic example. If someone unsubscribes you have to have a data record of that. You need to keep at least some data so that you know you shouldn’t be sending anything. You’ve got to be pragmatic and think about what you need to do in order to do the right thing by the customer. Over the next couple of years I think marketers will become more pragmatic and will figure out how to do a good job for customers regarding things like that. At Informatica, we have an unsubscribe link on every email we send out so it’s very easy for people to opt out of emails. We keep a record of everyone who opts out. Sometimes we’ve had people complain that they have received emails from us after they have opted out. Because we keep that data we’re able to backtrack and see what’s happened. In those circumstances, we find that customers have opted in for other emails on a separate occasion and with a different email address.