A lot of people have asked us to pull back the curtain on how we build our predictive models. This two minute video provides a simple, step-by-step explanation. If you have question or want to learn more contact us, and we’d be happy to help.

 

I was in a meeting with a prospect today talking about Infer. We were demoing the slider and explaining how we set buckets for the A, B, C, and D leads.

It was pointed out that the D leads contain a tiny percentage of the overall revenue.

The prospect then jumped in with something that caught me a little off off-guard. He said, “I can’t wait to give all our D leads to my new reps!”

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Now as a former inside sales rep, I sat there thinking, wow that’s a little cruel. Poor new guy. They’re going to spend their first month trying to sell to people who aren’t a fit for the product. That’s a tough start. And at what point do you tell your new rep that they’ve only got D leads in their queue?

This short video provides a visual explanation of the value unlocked by predictive scoring. When you turn on Infer you see this instant change in behavior across all of your reps. All of a sudden your effort is almost perfectly aligned with the revenue opportunity.

Turning on Infer unlocks a huge amount of dead weight. That energy can be shifted into more productive endeavors; whether that means doubling down on your top performing leads and following up more aggressively, or finding new sources of profitable leads.

The comparison below highlights why Infer’s Predictive Lead Scoring is a home run initiative. It’s low risk, easy to implement, and the impact is quantifiable upfront.

Time to Value for Automation Projects

With CRM or a Marketing Automation System, this is what a typical implementation looks like:

Time to Value for Cloud Applications

To maintain their amazing growth trajectory and stay one step ahead of the competition, AdRoll has instilled a culture of data driven decision making. Infer helps them scan thousands of signals from across the web so that they can identify which customers are most likely to convert. At AdRoll they have one set of leads that convert at 4x the baseline, and one set that will never convert. Infer helps them tell the difference between the two. As their Sales Reps think about who to call out to, Infer ensures they’re focused where they’ve got the best shot at winning.

We’ve got a brand new demo to showcase how companies are using Infer’s Predictive Lead Scoring inside of Salesforce. See how it works, how easy it is to setup, and why it’s a game changer for sales and marketing. For more videos visit or Infer’s Demo Center.

This post originally appeared on the Salesforce Blog

While some companies aggressively pursue every lead that is created, others are leveraging lead scoring to work smarter. If you can programmatically spot your good leads, chances are you’ll be able to increase win rates and conversion.

So what makes a good lead?

A good lead has two key ingredients

Fit Score (also referred to as an explicit score)

Intended to capture how much an incoming prospect resembles a likely buyer. For example you might look at the lead’s company size, geographic location, industry, and job title, to determine if it is a fit. A quick look at its employer’s website might give you other clues regarding their business model or online presence.

Activity Score (also referred to as an implicit score)

Intended to capture how much a prospect is engaged with your company. This could include the lead’s website visits, form completes, email clicks, and maybe even application usage data.

We’re excited to share our AppExchange App just in time for Dreamforce! It includes custom fields, pre-built dashboards, and a configuration tab to define your lead buckets. You are welcome to install the package and check it out, but we’ll need to build you a model to light up the scores. The process is fully automated so it requires no work on your part. We have pre-built connectors for Salesforce, Eloqua, and Marketo. If you’re interested in learning more, contact us and we’ll get you started.

Infer's AppExchange Listing

Marketing automation systems like Eloqua, Marketo, and Pardot support lead scoring. In fact, most Infer customers are already using one of those three application. So how is Infer different?

Infer's Predictive Lead Scoring

Sales and marketing folks have been talking about lead scoring for years, so we often get asked “what’s different” about Infer’s way of doing things. One of the reasons Infer’s models perform so much better than traditional lead scoring is that our system pulls in several thousands of external signals, going well beyond what most organizations track in Salesforce.com or other CRM and marketing automation tools.

Signals

Broadly speaking, Infer gets these signals from three sources: crawling the web, purchasing data, and inferring signals from raw data sources. The last of these is the most subtle, and it’s our equivalent of Google’s secret sauce for web search.