An engagement scoring model is often the signature move for a demand generation team – and they’ve been around for a long time in the marketing world. Most campaign teams use them as a way to understand when a “lead” is ready to be routed to sales. Some teams use simple off-the-shelf models from their marketing automation platform and others develop sophisticated models that include other predictive signals to weight the scoring so that the right companies or buyers have a lower activity threshold before they are sent for follow up. Sounds simple right? But the scoring model actually represents the opportunity cost balance that a demand gen team sets for the GTM motion – when do they decide that sales capacity should be used to go after an opportunity.
The battle between sales and marketing has always been about this opportunity cost balance. When is a lead qualified enough to put money into the sales development team qualifying it and the sales team pursuing it? Sophisticated demand teams get this balance right by constantly improving the mix of their engagement scoring models to include activity (often called first party intent), third party intent and predictive scoring to pre-weight scoring for the right accounts and buyers.
Let’s talk about why opportunity cost is so important and why it’s at the heart of the sales and marketing “is it a good lead” frustration. Let’s take two cases – the high velocity sales team and the high-value sales team.
Imagine a selling market where minutes really count where enriching, scoring and routing the lead within 2-3 minutes makes the difference between winning or losing to the competition. It’s typically a single-buyer buying team with a deal size less than a few thousands per month and a sales cycle that is in days or weeks. The high-velocity sales team is all about getting the right contact information and the strongest signals possible to time their pursuit. They are looking to close a high volume of deals and they typically can’t afford to spend a lot of time in the qualification process. Step one is all about lead enrichment – are you routing the lead to the right territory and is there the right phone or email or LinkedIn contact information so that they can quickly engage. Step two is the scoring – enough information so that they can quickly get the most compelling product value proposition in front of that prospect. And they might only have one or two times to make that pitch. Scoring must be tuned to arm that sales person with this – can they tell which product that’s most likely to be sold, what are the intent topics is that account showing for that product, which buyer persona do they fit so that the value prop can be tuned and have they attended any webinars, downloaded content, or even just raised their hand to speak to a sales person. Time and precision is of the essence for these velocity teams.
Now let’s turn to look at a different selling market where the deal size can be in the hundreds of thousands to millions and the sales rep might only be able to pursuit 5-10 deals every quarter. These deals have a long selling cycle – months to sometimes years. They have complex buying teams – often 7-10 influencers. This value sales rep is thinking about how to qualify and align the value of the company’s portfolio to that lead. They are thinking about whether the account is the right kind of company that has successfully bought their product and whether that person is influential enough to go after. Who are all the buyers who might be influential in the process. And are they engaged? Is this a customer already so that they are already pre-qualified in the procurement system. The scoring model here needs to focus not so much on timing but on the odds of that business being closable. Propensity to buy and intent are important to get those odds right at the account level and figure out which product is the right way in. It might take into account the buying team in addition to the individual buyer engagement into the scoring model. Are all of the buying team personas engaged?
In both the high-value and high-velocity selling motions, getting profile enrichment right is key. And enrichment happens not only in all of the core systems or data warehouses, it happens on the inbound lead funnel and in the real-time web interactions. And it’s always a combination of first and third party data in blended company and person profiles. Profile enrichment starts with regularly updating, cleaning and validating data, removing duplicates, and standardizing information. The profiles must take into account information not only from the RevTech stack but also the company’s operational systems, and financial systems. Building trusted profiles is only half the battle – the next step is to integrate them across the Customer Relationship Management (CRMs) and Marketing Automation Platforms (MAPs) to ensure sales and marketing are operating from the same, active data in pursuit of the same goal. Integrating systems provides a unified view of customer information and interactions, resulting in several significant advantages.
The next step is the scoring. As invaluable as engagement scores are, they’re not particularly useful by themselves. You know someone has engaged with your content, but… does their company match your ICP? Has their company shown intent for your type of product? Does that person have the buying power or persona necessary to buy from you? Knowing someone has engaged with your content doesn’t mean you start dumping your sales & marketing resources in pursuit of that person’s business. You need to qualify them first. There are simply too many unknowns that need to be known before you allocate your valuable, limited sales and marketing resources. We don’t want to waste precious time and money chasing down leads that aren’t likely to close in the first place, so how do we determine which of the high-engagement scoring people are most likely to close? How do we prioritize them?
So let’s talk about what should be in the scoring model. Clearly the activity-based scoring is critical. The prospect is revealing their interests and intent through the webinars/events they are intending, their engagement in the social channel, the content that they are downloading on websites and the frequency by which they are doing it. More points are given for higher value activity. Points are taken away if the activity isn’t recent. The activity part of scoring is always about the direct pulse of activity. Activity engagement isn’t enough however when we are talking about opportunity cost. If two leads do the same things, which should you prioritize first for sales?
Sophisticated marketing teams add or subtract points with predictive signals as well. If the account has a high propensity to buy, 50 points might be added to the score. As the intent level increases at the account level, 10 points might be added per level. The buyer persona fit might be used to give negative points for students or interns and higher points for prospects who show certain skills and interests. Weighting the engagement activity scoring with predictive scoring is the tie breaker. It means that the prospect who fits all the predictive criteria might only have to do half or a quarter of the activities before they are routed to sales.
The Weighted Engagement Scoring Model
So let’s go through the elements of the scoring models to identify the right company, the ready company, the right person, and the ready person. Engagement scores represent the ready person. But again, the ready person doesn’t necessarily mean they’re the right person from the right and ready company. We need to correctly weigh and apply our scoring models in the right order. So what should be in a Weighted Engagement Scoring Model?
- Company Fit or Propensity to Buy Model – The Right Account: An AI-model built from your historical conversion data set (opportunities). Applies scoring that indicates a company and/or person’s likelihood to be a good target buyer. Use cases include propensity to buy, inbound lead conversion, higher LTV, upsell/cross-sell, etc.
- Company Intent Model – the Right Time: A weekly set of customized signals that monitors your accounts for intent (third-party and/or first-party), and applies scoring based on the level of intent activity specific to a customers’ products/category.
- Buyer Persona Model – the Right Person: An AI-model based either on standard personas, or your custom persona profiles, to 1) score the existing database and inbound leads based on their closest persona fit (including skills and other identifiers), and 2) find net-new contacts within accounts that lack the right buyers using persona targeting.
- Buyer Engagement Model – the Right time: Your external first-party scoring model that is built through either simple point scoring for engagement in a marketing program or interaction with website content. It is typically implemented within the Marketing Automation Platform (Marketo, Eloqua, Pardot, Hubspot, etc.) and the higher the score the more engaged the buyer.
The sales teams are very familiar with weighted models. Their revenue forecasts are all about applying a weighted average of how far a deal is in the selling process, what’s the urgency that the sponsor is applying, and how complex is the procurement process. It’s time for marketing to move beyond simple engagement scoring models based on activities to Weighted Engagement Scoring Models that are a combination of predictive signals and the engagement activity. In conclusion, the Weighted Engagement Scoring Model is the answer to striking the right balance between sales and marketing investment. By applying Fit, Intent, and Persona models, then bringing in your first-party engagement scores, you can determine which opportunities to focus on, then get the right campaigns in front of the right targets at the right times – as efficiently as possible. Then the Weighted Engagement Scoring Model makes the decision of when to route that lead to sales for the most effective and efficient selling. It’s all about finding and creating closeable business. Get the full Revenue Radar Guide to see how Leadspace can add the AI targeting to your scoring model.