Today’s post is written by Andrew Angus
Here at Infer, we eat our own dog food when it comes to demand generation and sales development, and we believe in sharing successes in order to contribute to the growing community of forward-looking predictive practitioners. Here are three of our own use cases that we hope other sales development teams can leverage:
Inbound Lead Management
Our sales development reps (SDRs) only see inbound leads that are scored an “A” or “B” (the top 35% of leads that our model predicts are the best fit for our solution).
Leads scored as a “C” or “D” go to a nurture campaign and only bubble back up to the SDR team after hitting a stricter scoring threshold based on their behavioral scores. For example, if we’re seeing a flurry of marketing activity with a C lead who’s downloading a bunch of our predictive playbooks or attending a webinar, our model might predict that they’re exhibiting enough buying behavior to indicate an impending purchase.
The team’s Service Level Agreement (SLA) on what to do with different types of leads differs depending on the lead’s predictive score. For A and B leads, an SDR first qualifies them based on the contact’s authority to make or influence a purchasing decision and their company’s needs (i.e. a sales or marketing challenge where Infer can offer value). C and D leads go to the marketing team, who places them in a nurture campaign. If they eventually show more interest, we have SDRs qualify them more rigorously based on their authority, need, urgency and budget before routing the lead to an AE. We don’t waste time calling leads that are unlikely to convert, because we can use that time to stay on our A and B leads and call new leads faster.
All new leads are put through our own internally built tool, which assigns leads to SDRs based on lead score so that each SDR has an equal number of A and B leads. A notification goes to the assigned SDR, who follows up within 5 minutes of the lead’s first contact with our company. We’ve even set up our model to send an alert to the whole SDR team via Slack messaging every time a new A lead comes in.
This inbound lead management process minimizes our response time and increases the number of meetings we book. On the other hand, if you’re spreading your SDRs evenly across all leads and spending time with each category (good or bad), you could be wasting a lot of time that would otherwise go towards increasing the attention you can give to leads that really matter.
Outbound Prospecting
The key to effective outbound sales and account-based marketing is to focus on the right group of target accounts. We start by using data from InsideView, ZoomInfo, SalesLoft, and other firmographic, technographic and demographic signals to score our entire universe of accounts. Only leads with A and B scores are added to our sales database for outreach. Since everything is analyzed before it even enters our system, we have cleaner data and a better focus for outbound efforts.
Once we have this list, we work to refine it in alignment with the broader sales team. We want to make sure we are working not just the accounts that the data says we can sell to, but also the accounts that our sales team is going to be fired up about selling to. After we have a foundational list that’s been signed off by marketing, sales and the sales development team, we then assign an equal number of A, B, C and D leads to each SDR. Less than 25% of these accounts turn over from quarter to quarter and since ABM is such a long, high-touch process, we want to make sure we have just the right accounts in our mix.
Marketing & Sales Alignment
Everyone’s heard that marketing is from Mars and sales is from Venus, but with predictive scores, both sides of the house can come together and use a scientific, rational approach instead of arguing about what makes a good lead. At my previous company, it was very hard to implement an SLA between sales and marketing because it was tough to get agreement. You know the drill — a sales manager says “We’re not getting enough leads,” to which marketing responds with “What about these leads? Why haven’t you followed up with them?” Sales inevitably comes back saying, “Those leads are crap. We need more good leads!”
This endless debate can be put to rest with a common definition of good that both sales and marketing trust. Our predictive scoring has eliminated the finger-pointing that’s so common because there’s no need to try and hash things out based on individual team members’ intuition. We can all see the performance of the predictive model in real-time on our InsightSquared reports, and if a particular campaign is producing too many low-scoring leads, we have an easy conversation about why that wasn’t a great use of resources. Not only do we have all the metrics we need, but we can see them and manipulate the data to get what we need in order to make good decisions. With everyone on the same page, pet projects and guessing games are a thing of the past.
Today’s author is Andrew Angus.
Amazing photo by Bixentro