If you’re tired of sorting through endless leads, guessing who’ll actually buy, and watching hot prospects slip through the cracks, this guide’s for you. Whether you’re in sales, revops, or just trying to clean up your CRM mess, automating lead scoring and prioritization in Persana can take some weight off your shoulders—and actually help you close more deals. Let’s get into the nuts and bolts, minus the buzzwords.
Why Bother Automating Lead Scoring?
Manual sorting is slow, inconsistent, and—let’s be honest—usually a mess. Automating lead scoring means:
- You focus on leads that actually matter.
- Nobody falls through the cracks (unless you want them to).
- The whole team works off the same playbook.
Persana claims to make this easy, but the real value comes from setting it up right for your business—not just flipping a switch and hoping for magic.
Step 1: Get Your Data House in Order
Automation is only as good as the data you feed it. Before you build fancy scoring models, make sure your lead data isn’t junk.
What to check:
- Deduplicate: Merge or remove duplicate contacts. Otherwise, you’ll waste time chasing the same person twice.
- Fill in Gaps: Make sure key fields (like email, company size, industry, revenue) are populated. If you’re missing critical info, Persana can enrich data, but don’t expect miracles with empty spreadsheets.
- Standardize: Use consistent formats for things like job titles, industries, and phone numbers. “CEO” and “Chief Executive Officer” shouldn’t be treated as two different scores.
Pro Tip:
Don’t try to automate your way out of a messy database. Garbage in, garbage out.
Step 2: Define What a “Good” Lead Looks Like (For You)
Every business has its own idea of what makes a lead valuable. Don’t just copy a template or use whatever default Persana suggests. Sit down with sales, marketing, and anyone else who cares about closing deals.
Questions to ask:
- What’s our ideal customer profile?
- Which leads actually close fastest? Highest deal size?
- Are there red flags (like free email domains or certain industries) we want to deprioritize?
Common scoring factors:
- Demographics: Job title, company size, location
- Firmographics: Industry, revenue, tech stack
- Behavior: Website visits, email opens, form fills, demo requests
- Engagement: How often they respond, attend webinars, download resources
Make a list of must-have attributes and nice-to-haves. Assign each a rough weight—does company size matter more than job title? Put a number to it.
Step 3: Set Up Lead Scoring Rules in Persana
Now the rubber meets the road. In Persana, you’ll need to translate your criteria into actual scoring rules.
How to do it:
- Navigate to the Lead Scoring Settings: Usually found under Settings > Lead Scoring, but search if you don’t see it.
- Create Scoring Rules: For each factor, set up a rule. For example:
- +20 points for “Director” or above
- +15 points for companies with 100-500 employees
- +10 points for a demo request
- -10 points for a Gmail address
- Set Decay or Expiry: If a lead goes cold (no activity for 30 days, say), drop their score automatically.
- Test Your Rules: Run a few real leads through the system. Do the scores make sense? Are your best leads showing up at the top?
What works:
Weighted scoring, with a mix of demographic and behavioral factors. Keep it simple at first—complex models usually just create noise.
What doesn’t:
Going overboard with dozens of rules or scoring every tiny action. More rules ≠ better results.
Step 4: Build Your Prioritization Workflows
Scoring is only half the battle. You need to actually do something with those scores.
In Persana, set up:
- Lead Buckets: Group leads into “Hot,” “Warm,” and “Cold” based on score thresholds you set (e.g., Hot = 60+, Warm = 30-59, Cold = <30).
- Automated Routing: Assign hot leads directly to your best reps or trigger immediate follow-up sequences.
- Notifications: Set alerts for when a lead crosses into the “Hot” zone, so nobody sits around waiting.
- Task Creation: Automatically generate tasks for reps when a lead becomes high-priority.
Pro Tip:
Don’t over-automate. Reps still need to use their judgment. Use automation to tee up the right leads, not to replace human decision-making.
Step 5: Test, Tweak, and Actually Listen to Feedback
Your first scoring setup won’t be perfect. That’s normal.
What to do:
- Review Closed Deals: Compare your highest-scoring leads to actual conversions. Are you surfacing the right prospects?
- Ask the Sales Team: Are they happy with the leads they’re getting? Are any hot leads actually duds?
- Adjust Scores: If you find that certain factors aren’t predicting success, dial back their weight or remove them.
- Watch for Gaming: If reps start “nudging” leads to the top by stuffing forms, tweak your behavioral scoring.
Ignore:
Blindly trusting the model over real-world results. The goal is to help your team, not impress your dashboard.
Step 6: Keep It Simple and Iterate
The best lead scoring systems aren’t the most complicated—they’re the ones your team actually uses and trusts.
Tips to stay on track:
- Start with 5–7 scoring factors, max.
- Review results every month (at least at first).
- Involve your sales team in the process. If they ignore your scores, you’ve missed the mark.
- Don’t be afraid to kill off rules that don’t work.
Don’t bother:
Chasing after AI-powered “black box” scoring unless you have a lot of high-quality data. For most teams, simple, transparent rules beat fancy algorithms.
Wrapping Up
Automating lead scoring and prioritization in Persana isn’t magic—but it can make life a lot easier if you stay realistic. Clean up your data, set up a few sensible rules, and focus on what actually moves the needle for your business. Keep things simple, listen to feedback, and don’t be afraid to tweak as you go. You’ll spend less time chasing dead ends and more time closing real deals. That’s the point.