Infer’s scoring accuracy was quickly proven, and we built on our initial success by leveraging the scores as a lead routing trigger for moving people from being a prospect in our Pardot marketing automation platform to becoming a lead in Salesforce CRM
Marketing and Sales Ops, Prezi
San Francisco, CA
Infer Customer Since:
Predictive Scoring [Leads Fit Model], Glance
Each company we talk with uses predictive analytics to enrich sales and marketing processes in its own way. In the case of the rapidly growing visual presentation platform Prezi, the top applications for predictive revolve around scaling go-to-market efforts as the business evolves to focus on B2B audiences in addition to their large consumer audience. Prezi leverages predictive intelligence from Infer to help find ideal business customers among (and beyond) its community of over 85 million individual users around the world.
In fact, last quarter, the Infer platform accurately scored the top 25% of best-fit leads that drove 77% of the sales team’s won revenue.
In a recent conversation, Prezi’s Marketing Operations Specialist, Mike Schnell described why his company adopted predictive in the first place, and the success they’ve achieved by wrapping Infer’s system of intelligence around their sales and marketing systems of record.
Q&A With Mike Schnell, Prezi Marketing and Sales Ops
Q: What challenges led you to adopt predictive?
A: Before Infer, we were dealing with a flood of “contact me” leads from organic traffic to our web site, and needed a way for our sales team to help prioritize top leads. The process was very manual. For example, our SDR would try to route good incoming leads to two senior AEs who followed up with them, and I was focused on coming up with outbound campaigns to reach out to the best single user prospects from our consumer database. Predictive was definitely a great improvement, especially as we grew our sales team and started getting more leads coming through other sources.
Q: How do you use predictive scoring in Prezi’s sales workflows?
A: Once we had our custom Infer model in place and started pushing predictions into Salesforce, a few of our sales reps began using the fit scores to optimize their day-to-day workflows. A couple AEs preferred to stick with gut-based prioritization, so we were able to get an unbiased look at how the system was performing by comparing results across reps.
Infer’s scoring accuracy was quickly proven, and we built on our initial success by leveraging the scores as a lead routing trigger for moving people from being a prospect in our Pardot marketing automation platform to becoming a lead in Salesforce CRM.
We push leads to specific reps based on their Infer Scores. Senior AEs get all the Infer A and B-Leads, and our regular AEs work through Infer C and D-Leads.
We also worked with Infer to create another model for a new product we released last year (Prezi Business), so we now have two distinct scores for each lead that tell us 1)whether they are a good fit for our B2C product, and 2)whether they are a good fit for our new B2B product. The consumer side of our company has over 85 million users, and we use these new Infer Scores to look through our single user prospects for the subset within that group who could benefit from Prezi Business.
Q: What about marketing programs? Explain how your marketing team leverages Infer.
Infer has become a key part of our marketing processes, because it provides a proven lead quality metric that gives us immediate campaign feedback. Predictive scores let us easily see which campaigns are doing well, and figure out ways to push those to more people. Knowing as soon as possible about the quality of our leads really helps when it comes to what we are pushing out and our overall marketing efforts.
A: In addition, when we bring new lists of leads into Pardot, Infer helps us determine very quickly if any of those leads are good or not, so we can get the best ROI on our marketing spend. Through new demand generation programs we’re also getting good leads who have never used Prezi before, and Infer pinpoints the best-fit prospects we should reach out to for calls with our business sales team.
Q: Do you use Infer to architect nurture programs as well?
A: Yes, we use Infer fit scores, in combination with basic Pardot behavior scores , as the basis of our nurture programs. When leads reach a specific activity threshold in Pardot, we assign them to a specific rep or program. However, their Pardot score does not need to be as high if they’re given a top Infer Score, and if their Infer Score is lower, then we require a higher behavior score before putting them into a priority queue. We want to make sure that our best-fit leads get contacted more quickly, regardless of their behavior.
Q: Can you quantify any of the benefits you’ve seen since adopting predictive?
A: The biggest success we can clearly attribute to Infer is improved productivity and scale. Our team has able to boost efficiencies by greatly reducing time spent manually researching and qualifying prospects. Infer has played an exciting role in helping us keep pace with our marketing and sales activities as the company has grown. Predictive scores are now one of the main levers that we pull when it comes to managing our sales workload.
Are you ready to solve your biggest work headache? Get a lead scoring model that finally works.