6 Ways to Hone Your Lead-Scoring Skills

Your company has a CRM system that employees love and use regularly, and marketing automation tools to help streamline and automate all of your online marketing activities. That’s a great start, but did you know that most marketing qualified leads, or MQLs — more than 94 percent by some estimates — don’t convert to paid customers?

That doesn’t mean your sales and marketing information systems aren’t doing their job, but it could mean they’re not optimized for lead scoring. Your organization may need to operate differently to help improve those conversion scores.

As a former marketing exec, I’ve seen my fair share of marketing automation lead-scoring systems. Across all of those implementations, some patterns have emerged — and they help me determine if a lead-scoring program is likely to work or not. Following are my top six tips.

No. 1: Stick With the Facts

Lead scoring fails when it relies only on the assumptions marketing and sales teams make: gut intuition, trends in the news or dated logic. Instead, lead-scoring processes should look closely at recent historical patterns of your paying customers: their behavior, profiles, and purchases.

The lead-scoring rules should be updated continuously, to keep pace with the reality of your business today. Let the data signals of who your customers are today dictate how you should score in-bound leads. Lead-scoring systems that are based only on gut feel and aren’t regularly updated usually miss the mark completely up front or over time.

No. 2: Be Inclusive

Lead-scoring systems may track only those prospects who have come in through your website. What about customers coming from leads manually entered by your sales reps into the CRM, or acquired at events or from uploaded lists?

Your lead-scoring tools should be able to work with all sources of leads from relevant business systems for sales follow-up activities.

No. 3: Build Consensus Up Front

A major benefit of lead scoring is the improved flow of quality leads between sales and marketing, which requires consensus on definitions of a “lead” and the point values assigned to leads.

If consensus on lead and score thresholds is not reached, sales reps will disregard lead scores entirely and follow their gut instinct. That can lead to poor sales outcomes, bad blood between sales and marketing, and inefficiencies all around. Get sales and marketing alignment up front if you want your lead-scoring program to succeed.

No. 4: Purge Low-Performing Lead-Gen Programs

If you’ve got too many different campaigns going on all the time, or your marketers are engaging on social platforms where your target customers don’t often go, you’re making the process more complex for no reason.

Audit your marketing activities to ensure that you’re spending money and time on the highest potential lead-generation activities, not just throwing content — and funds — into the digital wind.

Lead scoring should be able to show you which lead sources and marketing campaigns bring in the highest-quality leads, giving insight into which campaigns to double down on and which to cut.

No. 5: Focus on Quality Over Quantity

I’ve seen too many marketers focus on how many leads they hand to sales instead of the quality of what they’re delivering. If a significant portion of the contacts you’re sending to sales is a poor fit, sales eventually will start to ignore the scores, no matter how good the model.

It’s better to deliver fewer leads of higher quality to sales and focus on the marketing programs that deliver the most cost-effective “A” leads.

No. 6: Don’t Let the Model Go Stale

No lead-scoring model is perfect the first time around. The model will need refining over time as new business closes — and as you enter new markets, add new products, or relaunch your website.

In building the scoring model, include a method for reassessment to ensure the model remains relevant. Minimally, at the close of every quarter, marketing and sales should sit down and review new wins to see how well the scoring model predicted success. Look for signal correlations in industries, company sizes, activities, and any other data you can access.

Lead scoring is never a simple “set and forget” process. Make sure you’ve got buy-in from key stakeholders, are incorporating all the right signals with the right weighting, and are regularly re-evaluating and updating the scores so the model can keep pace with your business.

Doug Camplejohn is founder and CEO of Fliptop, which helps B2B companies increase their pipeline and win rates through data science.

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