Throughout this Revenue Radar blog series, we’ve discussed how to use Leadspace predictive AI models to determine the companies within your Total Addressable Market (TAM) who need your product (highest Fit scores), which of those companies are actually ready to buy your product (Intent scores), and which buyer Personas are best for you to pursue (highest Persona score). Now let’s move on to the final step to optimizing your Revenue Radar – determining and prioritizing the specific people to pursue. Have these individuals been on your website? Who specifically has been searching for your type of content? Who specifically has engaged with your previous marketing efforts? With this final piece of information, you can focus on the right people from the right companies who are ready, able, and eager to buy your type of product or service – ensuring you don’t waste time, money and effort chasing down leads that aren’t likely to close. This is where an engagement model comes into play.
An engagement scoring model is a tool that monitors and scores engagement (account buying teams, contacts, leads and prospects), and applies scoring based on the specific user actions and digital activity specific to customers’ products/category. This involves scoring their engagement at the person-level using your marketing automation platform (Marketo, Eloqua or Pardot for example). An engagement model – often called a scoring engine – measures the amount of effort and time that someone has spent on your website, in your events or in meetings. Not all engagement is scored the same. For example, if someone clicked on an email they might only receive a few points, whereas if they downloaded high-value content they’d receive several points. And if they asked to be contacted by a sales person – the so-called hand raising – they might be immediately scored and routed to a sales person. A person’s overall engagement score will be the total sum of all points assigned for each of their individual incidents of engagement.
Engagement Model Use Cases:
- Optimize your ABM investments – create and activate precision segments by level or type of interest with engagement and other account or buyer personalization to optimize conversion rates.
- Leverage Leadspace Personas with engagement scores to populate and design customized persona-based buyer journeys and engage top prospects with relevant and compelling content through the right channel, at the right time.
- Match your Marketo, Pardot or Hubspot scores against your Salesforce prospects and accounts, then use persona scoring with engagement scoring to identify the best engaged contacts/prospects to go after for outbound calling. Use this to optimize meetings for sales calling campaigns.
According to a recent marketing leadership conference survey, more than 80% of companies use engagement models alone to score leads – but be aware, engagement models can often be very noisy as they can be used by non-buying researchers, competitors or job seekers. It’s important to understand that engagement is best used in context. Is this person at a company with a high predictive fit? Has that company exhibited intent for your products? Is this individual a persona that matches the type of buyer that is likely to have the budget and need for your product? If the profile of that person is a great fit for these first three signals, buyer engagement shows that he or she is warmed up and showing buying interest. All of these signals can be put to work with products like Leadspace for Salesforce to deliver the right account contact details, buying signals and propensity-to-buy scores and an understanding of their individual level of engagement directly in front of your reps to prioritize leads and opportunities in their pipeline.
Revenue Radar Conclusion:
Account targeting is easy once you have models and put the four radar signals to work – Fit, Intent, Persona and Engagement. Better sales/marketing targeting is all about “lift” – territory and ABM investment based on GTM science. With account targeting, you can prioritize account assignments by tiering accounts into categories by closeable odds (the right accounts) and accounts that are showing intent (the ready accounts). Persona and engagement scoring takes it to the right person. With the right CDP solution, you can utilize AI-predictive models to filter your TAM further by firmographics, technographics, Fit, Persona, and Intent. This enables you to plan territories and target accounts beyond just job titles, locations, and company size, as it algorithmically determines who is likely to close and where to focus your sales and marketing efforts. In short, utilizing a CDP solution will give you the information you need to achieve closeable business as you target the right people, in the right company, with the right outreach, at the right time. Get the full Revenue Radar Guide to see how Leadspace finds your best customers with AI models for account targeting.
