UserVoice Increases MQLs by 37% Using Predictive Marketing

Many of our customers come to us with a common problem: they have no good way to differentiate best-fit prospects from the tire-kickers, and are often left to rely on “gut instinct” when it comes to prioritizing who they should target. This was a particular pain point for UserVoice, who needed a way to more efficiently prioritize lead flow so their reps could focus their effort on those prospects with the most revenue potential. Additionally, both the sales and marketing teams wanted more transparency into what attributes defined an ideal customer profile so they could personalize and prioritize high-value outreach to these buyers.

UserVoice deployed a fit-based Infer Predictive Scoring model, and is now able to identify and prioritize leads based on how likely they are to purchase the company’s product management software. Armed with new predictive insights, the company saw a 2x increase in conversion rates and a 37% increase in marketing-qualified leads.

Connor Fee, COO at UserVoice, recently joined us to share his company’s predictive intelligence story, and how Infer has become a core technology in their sales and marketing stack:


The Front Lines of Predictive Intelligence

This article was originally published on the Hubspot Blog by Infer customer, Nicholas Heim, Director of Inbound Marketing at Hotjar.

HotJar HubSpot

Hypergrowth SaaS businesses like my company, Hotjar, are often faced with the happy problem of too many free trial leads flooding into HubSpot. Thanks to lots of word of mouth buzz around our mission to democratize user analytics, and some clever advertising, we took off fast a couple years ago.

I wasn’t around for the early “fresh-out-of-beta days,” but as a newer team member, it’s quite nice to stand on the shoulders of an amazing product and founders who are true visionaries. When I joined around nine months ago, it had become challenging for our team to vet which leads (out of around 600+ new users each day) to target for premium business and agency plans.

While we get tons of value from using HubSpot for both our CRM and marketing automation needs, we couldn’t properly segment and personalize messages for our highest potential users out of the gate.

That is, until we added Infer Predictive Scoring to the mix. Now, we have a custom predictive model that works with HubSpot and our Intercom customer messaging platform to provide accurate data-based predictions of how well each lead matches Hotjar’s ideal customer.

Here’s what we’ve learned by using predictive intelligence to inform more advanced sales and marketing tactics.

In the next 5 years, we are going to see a reimagining of automation through AI: An Interview with Sean Zinsmeister

This interview was originally published on TechSeen by Sean Zinsmeister, Vice President of Product Marketing at Infer.

While Artificial Intelligence was one topic that was covered ad nauseam in 2016, Infer, a predictive sales and marketing platform predicts that technology is going to evolve even faster from here on out. And this also bears an impact on martech solutions as organizations strive towards better accuracy, targeting, performance and engagement.

Sean Zinsmeister, VP, Product Marketing, Infer in an exclusive interview with Techseen discusses the growth of modern sales and marketing technology and how AI is all set to make a mark in 2017 too.

Techseen: While some predict mass unemployment or all-out war between humans and artificial intelligence, others foresee a less bleak future. What’s your take?

Zinsmeister: I think Google CEO Sundar Pichai had the best analogy, that AI is the new mobile. Given the saturation of smartphones and mobile apps, it would be insane not to include mobile in your digital strategy, whether for product development or go-to-market. Companies need to start thinking the same way about AI, and little by little add predictive and prescriptive analytics into workflows to increase the quality and productivity of everyday work.

With any new technological innovation, there is always some vocational disruption, but the upside is that AI has the ability to remove redundant tasks, increase productivity, and improve overall quality of work. It’s less about the removal of jobs and rather the evolution of jobs.

For example, sales and marketing professionals are overwhelmed with the amount of data they are faced with everyday. Sales reps need to know who to sell to, and marketers need to know who to market to, but there’s no way to employ enough humans to accurately answer these questions. AI helps companies automatically sift through troves of data to make sure they are picking winners and spending time in the right places.

4 Easy Tactics for Infusing AI and Predictive Analytics Into Sales Processes

This article was originally published on the Salesforce Blog by Sean Zinsmeister, Vice President of Product Marketing at Infer.

Unless you were hiding under a rock this year, you probably heard a thing or two about the rise of artificial intelligence (AI) for sales. As machine learning and predictive analytics technologies have rapidly matured, a whole community of forward-looking sales and marketing leaders are emerging as predictive innovators. Rather than relying on human intuition to inform their processes, these early adopters are leading the arms race for data by reinventing how their businesses operate based on intelligence that’s generated by AI and other related data science techniques.

In this environment, I’ve noticed four easy ways that smart sales leaders are hacking their team workflows to insert valuable data signals and key insights into day-to-day tasks—saving vast amounts of time and making sure all of their rep’s hard work is tightly aligned with the impact it delivers.

1. Use analytics to inform sales follow-up

There’s no doubt that confident and focused reps bring more opportunities into the pipeline. But it’s hard for them to feel confident when they’re given sparse lead records with little or no information about key buying signals – like a prospect’s fit for your product, or their likelihood to make a purchase soon based on marketing engagement. In order to avoid wasting hours every week researching leads, many teams are leveraging the latest predictive scoring and profiling technologies to create a habit of fast and efficient follow-up. When it’s easy for reps to prioritize the right prospects and plan their outreach, they follow-up more consistently, and as a result are more likely to hit their numbers each month.

For example, Shoretel is a company with a huge influx of leads, which market development reps individually call in order to qualify opportunity-ready MQLs. After adopting predictive analytics, the team started prioritizing their best-fit leads to qualify first, and MDRs went from having to call 100 leads to find 1 MQL, to just 12 calls per MQL – a huge productivity improvement.

With detailed information about each prospect, sales reps can also personalize every conversation for better engagement. By using advanced profiling techniques to create highly-segmented lists of prospects based on specific attributes and data signals (such as “VPs of Sales, in California, who use Salesforce, and have interacted with one of our marketing campaigns in the past 6 months”), reps can quickly sort out the best way to approach each group. For instance, that might send a particular piece of content or invite the prospects to a local meetup. Some tools even let you set up alerts for important events, auto-assign tasks to reps in Salesforce, and get recommendations powered by machine learning on which segments to invest more time into.

Carolyn Wellsfry Cheng of Shoretel Discusses Integration, Adoption, Closed Loop Reporting, and Combining Cloud and Location Based Solutions [Podcast]

We’re back with another episode of Stack & Flow! This week we’re joined by Top Predictive Innovator Carolyn Wellsfry Cheng from Shoretel to discuss the differences between account-based marketing and selling, which strategy she predicts is here to stay, and why buying flashy tools isn’t always the best choice.

Infer Launches New Predictive Behavior Scoring; Expands Sales Intelligence Capabilities

Press Release: Company Further Accelerates Product Innovation and Extends Open Ecosystem

Infer Inc., a leading predictive sales and marketing platform that helps companies win more customers, today announced several enhancements to its product portfolio. The latest improvements to Infer Glance, a sales and account intelligence application, as well as Infer’s new predictive behavior scoring for Salesforce Pardot, reflect the company’s strategy to continue deepening integrations with other enterprise systems. Infer’s open architecture makes it easy for sales reps and marketers to infuse predictive intelligence into their decision-making in order to close deals more quickly.

The significant product improvements we’ve made in 2016 reflect how we’re helping businesses reimagine automation through data science,” said Vik Singh, CEO and co-founder of Infer. “The market for AI solutions is rapidly expanding, and Infer fuels predictive adoption by serving as a guide that intelligently and continuously identifies revenue whitespace in a company’s funnel. In just a few years, I’m confident that every modern enterprise with a CRM system will also be leveraging predictive analytics and AI to supercharge its revenue growth.”

Infer Glance Sales Intelligence Powers More Productive Conversations