Prospect Management Platform exposes data generating the score and uses it to build individual profiles, actions and recommendations.
Today, the Mountain View, California-based company is launching a new platform to add profiles and actions to those inferences. And in so doing, Infer says it is exposing and utilizing the many data signals that it previously kept hidden.
Called the Prospect Management Platform, the new product builds on the predictive lead scores to create profiles and to provide recommended actions to turn those profiles into customers.
Profiles are updated in real time, as new data comes in. Actions can include specific nurture campaigns, marketing content, alerts or advertising directed at that profile. The company said artificial intelligence is employed to create predictive simulations that measure the potential effects of certain actions on specific profiles.
“We’re leveraging prediction,” CEO and co-founder Vik Singh told me.
To position the new Platform, he cast the evolution of predictive lead scoring as three levels.
In Level 1, he said, a data-driven model is created to generate a score for a person or a company, based on whether they seem like a likely customer. This is what every predictive lead scoring firm does, and in addition to his own company, Singh placed competitors EverString, Fliptop (now owned by LinkedIn) and SalesPredict in this level.
He described Level 2 as going beyond a lead score, creating applications or use cases based on the score. For instance, there might be a use case on how to create a nurturing campaign for leads in a certain score range, such as a plan that all “A” leads get up to four contacts from marketing/sales. Infer and Lattice Engines do this, he said.
Singh describes Level 3, where he places his company’s new platform, as a “kind of new frontier.” It uses the score but also uses and shows the previously hidden data signals that created the score, to generate the profile and the recommended actions.
“These signals used to be our secret sauce,” he pointed out.
Customer profiles — sometimes called personas when they are built as a customer type — have been around for a long time. But, Singh told me, their key issue has been that they are static, without “a standard way to operationalize,” without real-time updating as a result of new data and without tracking analytics.
You might know that the profile indicates a CTO at a financial services company that employs Amazon Web Services and uses Salesforce, he said, but what’s missing are the specific ways to approach that person and the analytics tracking their success.
Here’s one screen on Infer’s new platform that will lead to recommended actions for specific profiles:
Singh pointed to a variety of companies that offer some part of this. Customer data platform Lytics, he noted, offers recommendations and profiles, while lead engagement software provider Coversica offers “some stuff about what to do next.”
He acknowledged there is also “some overlap” with customer relationship management (CRM) systems or marketing automation platforms. But a CRM doesn’t “guide you about what to do next, like an ad workflow,” he said. And marketing automation allows you to create workflows, but doesn’t walk you though the steps needed for each individual target.
“We think of a marketing automation system as a really good database,” he said, adding that the new Infer platform is trying “to push our workflows onto the automation system” so you can get more out of it. The platform integrates with Google Analytics, Marketo, Salesforce and other marketing tools.
What has been missing, he said, “is an advanced system to bring this together,” to provide the “brains.”
Infer points to business intelligence firm Looker, which has used the new platform to trigger Salesforce alerts for specific prospects. Document productivity company Nitro employed it to sync up its global teams around surfaced leads and to figure out what content marketing to send to each.
Online training platform Mindflash says the new Infer product helps it identify users with high predictive scores who also use Salesforce, so it can target them about its upcoming Salesforce AppExchange packages.
Although it’s built to leverage predictive scores and the data behind them, Singh noted that the platform can actually be used by companies that have little or no predictive data, such as brand-new startups.
After all, you can set up a profile as a collection of conditions, like supposing someone is a CTO at a financial services firm that uses Amazon Web Services. You can still develop strategies and employ the recommendations and actions provided by Infer’s new platform.
(Some images used under license from Shutterstock.com.)