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Lead, Prioritize, Win: Moving to Predictive Prioritization

As B2B marketers, you’re now challenged to understand dynamic customers, increase pipeline quantity and quality, and boost campaign ROI. You might be achieving these goals by expanding the top of your funnel, allowing more inbound leads than ever before. But while having endless inbound leads may sound like a nice problem to have, it can actually be your worst nightmare.

It’s not as simple as handing good leads over to Sales because let’s face it, just because someone is active on your website, that doesn’t mean he or she is ready to buy.

Pursuing each and every inbound lead isn’t worth the time and money – you have to be selective.

Traditional scoring models don’t cut it anymore, so stop wasting time and effort on bad leads and use predictive analytics to redefine how you prioritize inbound prospects. We’ve talked about improving campaign ROI and attracting the right accounts for a campaign, and outlined a number of use cases in our predictive playbook. Now, we’ll show you how to build an action plan using predictive scoring so you can identify your best leads for Sales and provide account details that enrich sales conversations, inform better personalized messaging, and guide nurture tracks -improving the quality of leads you hand over to Sales and identifying which leads need personalized nurture tracks.

Switch From Traditional To Predictive Scoring

Scoring is a great tool for prioritizing leads so Marketing and Sales know where to invest their efforts. However, not all scoring methods give you the best results.predictive-prioritization-data-iceberg

Traditional lead scoring uses simplified models that require frequent manual updates. While that’s great for identifying bad leads, it’s not very good at identifying who is more likely to buy.

That’s where predictive scoring comes into play.

Predictive scores are far more accurate because they’re built to access large external datasets and use machine learning – making use of explicit and implicit signals you don’t have in your marketing automation (MAT).

With predictive prioritization, you can create an effective action plan, allowing sales to focus on the right opportunities and reach out to prospects most likely to buy.

Redefine Your Scoring Model

So you decided to switch to predictive prioritization. Now what?

It’s time to redefine the way Marketing and Sales work together. Plan on discussing sales bandwidth, lead volume, and lead quality, since those are important factors for Marketing and Sales success. You’ll need to revamp your nurturing programs, move away from generic lead flows, align on content plans, and identify triggers that matter most.

Marketing and sales alignment is key to maximizing conversion rates and influencing prospect purchasing decisions. Here are some ways to get started:

  • Think simple. You can always add to your scoring model later. It’s much easier than deconstructing a complex system.
  • Know your customer profiles. Both Marketing and Sales need to align on what they consider an ideal lead.
  • Understand how leads move across the Marketing and Sales funnel. For example, someone who fills out a form and downloads a whitepaper is definitely a candidate for a nurturing campaign. On the other hand, if someone requests a demo, they’re ready to go straight to Sales.

Build An Action Plan With Predictive Scores

After you align on the new scoring model, you’ll need to build out a plan and get the message across to everyone in Marketing and Sales so they know what actions to take. And with predictive scoring, those calculations are done for you.

Radius, for example, takes an explicit-first approach to predictive scoring, calculating how well-suited a prospect is for your product using firmographic data. Compare implicit scores, which show how engaged a prospect is with your company and by extension, their buying intent. You can get implicit scores from your MAT.

Once you have your scores and grades, the next step is to combine them in a scoring matrix, and then create a rating system. By combining explicit and implicit scores, it’s easy to show what action to take based on fit for your product and behavior that demonstrates engagement with your company.

predictive-prioritization-scoring-matrix

Once you put the matrix together, it’s time to describe each lead rating and create an action plan. Here are some best practices around mapping lead ratings to actions. Letters represent explicit score and numbers represent implicit score.

Action Plan Best Practices

predictive-prioritization-scoring-plan

Measure, Evaluate, and Optimize

Predictive prioritization isn’t a set-it-and-forget-it solution.

Though predictive scores adapt to changing conditions and conversion trends, you’ll still want to measure your model’s performance based on your action plan. A good way to start is by regularly collecting feedback so you can find opportunities for improvement. It’s a good idea to review every 30 days until you’re happy with the outcome. Then, create a reevaluation schedule that aligns with the length of your sales cycle.

Know your benchmarks by reviewing and measuring your conversion rates, lead quality, and lead and opportunity volume. Make sure to take note of the average deal size, and the cost of time and dollar spend for both Marketing and Sales efforts to determine if your new scoring model helps reach your goal.

Here are some questions to consider:

  • What percentage of A leads are closing?
  • What percentage of B and C leads are converting from MQL to SAL?
  • What is the sales acceptance rate?
  • What are some reasons for disqualified or rejected MQLs?
  • Has the number of days in the sales cycle decreased or increased?
  • Has the average deal size increased?
  • What are the total number of MQLs per week?

Want to target the right prospects and increase campaign conversions? Download our predictive playbook to learn how you can use predictive lead scores to build and execute campaigns that move the needle.

predictive-lead-scoring-playbook

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