What is predictive lead scoring?

We've all walked into a store looking to buy something…

You walk into a store and you tell the person who's in the store, let's say it's a Best Buy, you tell them what you're looking for. “I'm looking for a television.” Right off the bat they start asking you questions, “Are you looking for LCD? Are you looking for 3D? Are you looking for 4K?”

What they're doing is they're asking you about the features of a product.

Notice, they rarely ask, at least not at Best Buy, they rarely ask about you.

They don't ask what you're going to do with it or how big the room is. Some really great salespeople might ask that later, but the standard for sales, at least in consumer electronics, isn't very good.

They punch straight to, “Okay. What are the features you're looking for? Let me point you in the right direction.”

If you were to step into a car lot to buy a car you'd notice that the sales folks there are a little different.

People start asking you,

  • “How big is the family?”
  • “How many of you would be driving?”
  • “What kind of car you're looking for?”
  • “How often do you drive?”
  • “What's your commute like?”

They don't even always ask you this in a direct way. Sometimes it's in a back-and-forth as they share about themselves.

They're asking all these stuff because what they want to know is not just want you think you want. They want to know more about you. They want to understand your context.

What people care about in sales is two things

When it comes to sales, customers (and prospects) can be grouped by two different sets of data.

The first is demographic data. This is the stuff that describes you. Facts about you.

  • Are you young or old? That tells people about your disposable income. About your current costs, based on your stage in life. It tells people about your desire for the nice things in life.
  • How many people in your family? Again this tells a car salesman, for example, about the kind of vehicle you might need, but also whether you'll be into safety or speed.

Once the demographic data is understood, then it's time for behavioral data.

Behavioral data is one of those things that you don't experience immediately on a car lot. It's only there if you're the kind of person that visits, then leaves, then visits again. With each return trip, you're more likely to buy the car. But the salesperson may also be more likely to be emotionally engaged because of their own investment.

Behavioral data—whether it's on the car lot or on a website, is all about the context of the interaction.

The context.

  • How often have you been there?
  • How many times have you come back?
  • How long have you stayed?

The same thing happens when you go to a website.

When we go to a website where we're looking to buy, for the most part we get the pop up that just smacks us in the face. “Give me all your information right now.” Then we get every button on the website—all of them ready for the close right then. “Let's do this deal right now.”

But most of us get past that and do research. We spend a decent amount of time online evaluating and collecting data before we ever get ready to make a decision. That means we're spending several interactions online and creating tons of behavioral data.

The old lead scoring model

Why am I telling you all about demographic and behavioral data?

Because the old version of lead scoring, something I've embraced and loved for years, frankly never took off. It's out there. Tons of software, particularly in the enterprise space, tons of marketing automation solutions come with lead scoring.

And they all come with scoring solutions that start with behavioral data.

Let's look at an example.

You hit the website… Let's say you're going to checkout Eloqua because they're doing all sorts of marketing automation. You go to the Eloqua website, and as you're there, you click on some pages. As you're clicking through some pages, you finally get to this section where you're digging in deeper and want the case study. There's a little form and you fill it out.

What do they know about you?

  • Your exact path thru their site
  • The amount of time spent on each page
  • The page where you spent the most time
  • The form you filled out and the paper you downloaded

Sometimes you have to give them your phone number, which means in about 10 seconds your phone is going to ring, “Hi there Chris. I just want to make sure that you had no questions.”

Trust me, you'll be responding with, “I just downloaded the file. I haven't even read it yet.”

The old model of lead scoring was supposed to look at this data and determine where you were in their sales cycle and how “hot” you were.

The original intent was that we would define certain behavior and give it points. Based on those points, you could know how hot the lead was and pass it to sales. This is where almost every marketing department that looked at lead scoring said,

  • “This is fantastic.”
  • “This is amazing.”
  • “This is perfect.”
  • “This is going to totally help our sales and marketing teams.”

Then someone had to decide.

What is an event worthy of points? Then, how many points should I allocate?

In the big scheme of things, if someone comes to the website, if someone comes to my homepage, is that worth 1 point or 5 points, or 10 points?

If someone comes to my homepage and then goes to one of my case studies and downloads a white paper, is that download worth 5 points or 10 points or 20 points?

This is where most things end. The feature sounds awesome but it's rarely realized. Because most people just stop right there.

When people started using it what happened was that someone went in and said,

“Okay. I'm going to say, visiting the homepage and any product page is worth one point. Visiting the pricing page is worth two points. Downloading this thing is worth five points. Filling out this other form over here and checking this box that says you're going to make a buying decision within the next six months is worth 10 points. Checking the box that says contact me now, I'd like to make a purchase is worth 25 points.”

So what happens? You immediately find a person who is hot!

You think, “Okay. Great.”

Except the person is desperately looking for your pricing page and can't find it. They hit their homepage and then they go try and click on something else and then they end up clicking and going back to the homepage and then they click on something and then they click back and then go back to the homepage. They keep hitting your homepage, and eventually, they hit your pricing page. All of a sudden they got 15 points just been doing this all day long, or they did it over two or three days.

The lead goes from marketing to sales.

And then sales finds out the person was scored incorrectly because of your site design. They just had trouble finding what they wanted. They were never super engaged. Red herring.

But false positives always have cost.

Introducing Predictive Lead Scoring

Well, if lead scoring showed so much promise and yet hasn't worked, what's the real answer?

The answer is predictive lead scoring.

It's the same kind of lead scoring that we've been talking about. It not only monitors the behavioral dynamics, it looks at demographic data. What do you fill in your form? Are you a C level or a VP level person? That's going to count for something different than if you're just an influencer. Though, there's no “just” about being an influencer.

It will look at demographic data. It will look at behavioral data.

More important than that, given the last several years, the introduction of big data and the solutions around big data mean that software can actually look at the people who have purchased and looked at their interactions and behavior and determine dynamically the algorithms that suggest the weighting/scoring factors for what's a leading indicator that someone has interest in you.

If the current buyers of your product spend x amount of minutes before making a buying decision at your site, it can then look for others who've spent similar amounts of time.

If the current buyers of your product have x interactions in your pre-sales forum, they can look for others that are approaching the same metric.

The software can create leading indicators and look for them – dynamically.

And more importantly, if that changes over time, the algorithm changes over time. That's a lot better than a static algorithm that says, “I decided in March of 2013 that visiting my website was worth 1 point, and buying my e-book is worth 5 points, and getting a hold of me for a one on one call and consulting was worth 100 points, and coming to my event was worth 150 points.”

Even though that may have worked at one point. What happens when the algorithms adjust? What happens when behavior shifts? Wouldn't you want something that is more dynamic? Wouldn't you want something that takes some of that calculations out of your hands?

The good news is, these players are starting to show up. If they're starting to show up, it means at some point it will be available for you and me. Which is why you should keep your eye out for predictive lead scoring.