Predictive Meets Inbound Marketing

This week, we’re celebrating all things inbound at the annual HubSpot Inbound conference in Boston, and it’s been great to see the enthusiasm around this exploding breed of marketing.



What’s even more exciting are the many discussions around the rise of predictive. HubSpot is the latest software player to join the AI Spring, announcing today that it is adding basic predictive features to its product. This is a great way to get started with predictive if you want to minimize your marketing automation configuration burden, but don’t yet have a significant customer base or aren’t ready to jump fully into advanced predictive lead scoring.

How to Calculate the ROI of Predictive Lead Scoring

With content marketing, freemium products, and list-buys, marketers are generating more leads than ever before — but only a fraction of them are good prospects. Predictive scoring solutions like Infer help filter out the noise by programmatically researching every lead and identifying high-potential MQLs. That not only saves sales reps time, but just as important, it gives you an objective way to measure lead quality.

We’re continuously documenting best practices in order to provide a framework for measuring the ROI of a predictive scoring initiative. One approach that lends a lot of clarity to this process is to look at three simple metrics — your number of sales reps, your average cost per rep, and your percentage of bad leads. With this information, you can quantify the cost of wasting effort on bad leads.

ROI_01However, cost savings is only one way to measure the impact of predictive scoring. Most companies want to quantify the top-line impact as well. By looking at your average leads per month, conversation rate and revenue per opportunity, you can understand the potential revenue increase you’re likely to see from predictive scoring.

Congrats to CRM Market Elite Winner

It’s great to see the smart folks over at Concur be recognized for their impressive results with our predictive lead scoring. CRM’s 2015 Market Elite Customer Company winners all demonstrate how technology can impact operating costs and efficiency, and Concur is no exception. Here’s an excerpt from the company’s profile in this month’s issue of CRM Magazine:

Infer’s predictive lead scoring helps Concur close more deals more quickly

The Infer solution helps Concur identify and prioritize the marketing-qualified leads that are most likely to convert to closed deals. It pulls in thousands of external signals, going well beyond what most organizations track in their basic CRM and marketing automation tools.

Greg Forrest - Concur“We’re finding leads a lot quicker and getting them into the pipeline a lot faster,” Forrest states proudly, “and we’re closing at a much higher rate.”

Based on the results Concur has seen in the first six months, the company is expanding the Infer solution to its cross-selling and upselling activities, account scoring, and direct marketing.


  • Five thousand marketing-qualified leads were uncovered in its database, leading to a dramatic run-rate increase.
  • The number of leads converted to closed deals tripled.
  • Conversion rates increased by 150 percent, from 0.8 percent to 2 percent.
  • Closed deals for new solutions were boosted by 76 percent.

For more details, check out the magazine’s full story on Concur.

Does “Intent” Data Live Up to the Hype?

Originally posted on VentureBeat

With all the talk about predictive-driven sales and marketing, a new question is emerging – which data is most valuable? Many B2B businesses are achieving unprecedented customer insight by leveraging all kinds of external demographic and firmographic data to see if a company is a good fit for their product. Some are pairing that with signals from their marketing automation systems and web analytics to predict whether a prospect might be ready to buy soon.


Now, another breed of “intent data” has emerged. External data providers like Bombora, The Big Willow, IDG and TechTarget are aggregating information about web visitors on B2B publisher networks to help businesses figure out when certain prospects might be in the market for their product. This kind of insight presents an exciting new frontier for data-driven marketing.

SmartBug Media Q&A with Infer’s Sean Zinsmeister

Inbound marketing agency SmartBug Media does a great job of educating its clients on new ways to increase marketing ROI and grow their business. Recently, the company’s director of marketing, Dolly Howard, sat down with our own Sean Zinsmeister to talk about the value HubSpot customers can enjoy by adding predictive scoring to their technology stack

What is predictive lead scoring


Here’s a an excerpt from their Q&A:

How is predictive lead scoring different than custom lead scoring in HubSpot? There are two big differences between predictive lead scoring and the kind of custom lead scoring in marketing automation platforms (MAPs). The first is that predictive uses both internal data from your CRM and MA systems plus thousands of external signals from a variety of data sources outside your company. The second major distinction is that predictive scoring solutions use machine learning to look at all kinds of combinations in the data that humans could never grok on their own. Whereas MAPs require you to manually come up with points-based calculations formed through your gut instincts, predictive solutions take the guesswork out of the equation and do all that work for you in order to better predict higher converting leads.

Using Predictive Lead Scoring to Measure Demand Gen Campaigns

One of the best things about working at Infer is all of the brilliant strategies and tactics we learn from the smart marketers in our community of customers. Adam von Reyn is one such inspiration. He’s the marketing director at InsightSquared, a popular sales analytics app that takes the pain out of business intelligence so executives can get the information they need to forecast pipeline and grow revenue.

It’s only natural that such a data-centric business would excel at leveraging data to evaluate its own marketing programs. In a recent blog post, Adam gives a great overview of his team’s thoughtful approach to determining which demand generation campaigns deliver the best (not just the most) leads.

IS2 Blog Post Image

Infer Partners with HubSpot to Bring Predictive to Inbound Marketing

Press Release: Infer’s Pre-Built Integration Helps Marketers More Quickly and Easily Target Top Prospects

Infer - HubSpot IntegrationInfer Inc. today announced a new connector for HubSpot (NYSE: HUBS) that feeds predictive scores into the inbound marketing platform for better targeting and segmenting. Infer helps businesses predict and prioritize their highest potential prospects using advanced data science and external buying signals. Many fast-growing organizations such as BlazeMeter, Virool and HubSpot itself use Infer Scores inside HubSpot software to infuse their marketing campaigns with valuable insights about leads and contacts.

“The new integration makes it easier than ever for HubSpot customers to pull accurate predictive scores from Infer right into the software they use every day,” said Megan Keaney Anderson, director of product marketing at HubSpot. “As a result, our customers can hone in on their very best prospects and know which to send immediately to sales, and which to nurture with targeted email journeys, content, offers or campaigns.”

The Behavioral Scoring Test

Every B2B marketer wants to do a better job of identifying which prospects are in-market and ready to buy, and which are just kicking tires. While there are a lot of vendors who say they’ve got behavioral scoring figured out, the degree of accuracy and coverage can vary widely. If you can avoid scores that sales doesn’t trust and instead find an approach that predicts winners at a very high rate, you’ll reach hero status in your organization. Below are four questions to help you evaluate behavioral modeling techniques:

1. Does the model tell you when prospects will buy?
Many behavioral models simply add points for different activities, but in order to know if someone is likely convert in a fixed timeframe, say “the next three weeks,” you need to take timing into account. A good behavioral model will look at the concentration of activity, the breath of engagement, and it will decay activities at the appropriate rate.

Infer’s New Behavior Scoring Predicts Imminent Buyers with Unprecedented Accuracy

Press Release: New Relic Boosts Win Rates by Using Infer to Model Nearly 10 Million Monthly Marketing Automation Signals and Uncover Prospects Who Will Convert within Three Weeks

Infer Inc., a leading provider of predictive applications that help companies win more customers, today announced the general availability of its behavior scoring solution, which helps sales and marketing teams predict which prospects will convert in the next three weeks. Infer is the first company to extensively mine the full spectrum of detailed activity data that is summarized in marketing automation platforms, and use advanced machine learning and predictive analytics to produce highly accurate behavior scores. Already delivering results for several rapidly growing businesses like AdRoll, Chef and New Relic, Infer has generated over 30 million behavior scores for New Relic alone by modeling 47 million activity records.