I hate the word AI. But I love the concept of data-driven customer engagement. As CEO of DiscoverOrg, I have some strong opinions about data.

Here’s what shook up the B2B data world in 2018 – and what I think that means for our industry in 2019.

Henry Schuck interview high sales performance

From a big data perspective, 2018 was the first year I’ve felt our company actually started leveraging machine learning and predictive capabilities for ourselves.

This gives me confidence.

Most of the market is about 2-3 years from a widespread adoption of predictive/machine learning, which is exciting. I think, 3 years from now, it will be commonplace to talk to a company with 50 or 100 people driving sales through intent and activity data.

I see it used here and there today. But in a few years, data-driven go-to-market muscle will be widespread.

That means who my reps talk to – all their activities, in fact – will all be driven by insights that come from the CRM and the tools layered in there.

Operationalizing machine learning

What will this look like? AI is not as sci-fi as it used to be. It’s not robots, or Terminator.

The customer success use case

Here’s an example: Customer success reps will be able to instantly tell when a customer becomes less likely to renew, and they’ll be able to automate the most effective campaigns to re-engage them.

Bringing insights from machine learning into the buyer’s lifecycle is not possible without three things:

  1. Data on customer’s activities
  2. An advanced analytics platform that can show what different customers look like
  3. A tool that links to engagement platform in an automated way.

That probably means plugging data into tools like Tableau, Einstein, DataRobot, or other modeling software that visualizes patterns and suggests activities.

The sales use case

In sales, we’re already starting to use big-data driven insights.

Operationalizing machine learning

DiscoverOrg has a team of outbound sellers. Historically, we gave them 300 accounts and told them simply to work this cohort. Now, we give them 300 accounts plus deep, contextual data like Scoops, Intent, and leadership changes – and those 300 accounts are constantly recalibrated based on real-time signals.

Yesterday, for example, I should have called IBM first, but today I should call Microstrategy first – based on what people at each account are clicking, posting, and downloading.

Using this kind of data, sales reps can prioritize outreach, in real time, with data that’s being fed into Salesforce, analyzed, and spit back out.

Machine learning will reinforce effective behaviors

What we’re starting to see today – more so in the next 2-3 years – is data driving activities and getting smarter as a result.

If you call IBM based on a behavioral intent signal, and it turns into a closed deal – or say your response rate improves based on the time of your phone call – the model gets smarter. Or if you don’t close the deal and your response rates worsen at particular times – the model gets smarter, too.

We’re already doing that today.

This data-informed approach will become more widespread and refined in the coming months and years.

Bringing predictive data into the sales workflow

What will it take to bring data-driven insights into the mainstream?

build sales pipeline

A focus on hiring the right people, clear data input and lots of it, and all of that plugged into an analytical model spits out the analytics.

You’ll also need an ops person who can plug good data into systems and operationalize it. For example, the way Einstein feeds into Marketo or Outreach.

What will that take? They have to believe it’s a real thing. They have to see it working for someone. They have to believe that it’s real. It is. They just have to believe it.

When you see how predictive intent data works, it’s like you can’t believe it exists and we’re not using it.

If you knew that a company makes a decision within 3-6 months of doing X … why would you go to market any other way?

Companies who use this kind of data will have an advantage.

What is DiscoverOrg focusing on in 2019?

People might understand that it’s out there, but they don’t really understand how to use it. It’s incumbent on us to share how to operationalize it – not just that it exists.

How can you take the rest of our data and make it actionable with your sales team?

That still feels aspirational today. We need to put the camera on ourselves, so our customers know that they can do it too.

Our goal for 2019 is making sure the market knows how to put this new data into action.

Learn how to use Intent data (without creeping out your prospects) to get started down this path.


Let us know when you’re ready to start winning.



Contact data and scoops for the right buyer — at the right time.


Henry Schuck
About the author

Henry Schuck

Henry Schuck is the CEO of DiscoverOrg, an 8-time Fortune 5000 company, which he co-founded at the age of 23. He has extensive experience managing the sales and marketing activities of fast-growing information technology data companies.