If your sales team is chasing dead-end leads or wasting time on manual research, you’re in the right place. This guide walks you through setting up automated lead scoring in Provarity so you can spend more time selling and less time guessing. If you lead or work on a B2B sales team and want to get real about who’s likely to buy, keep reading.
Why automated lead scoring matters (and what it can’t do)
Manual lead scoring is tedious and, let’s be honest, inconsistent. Automation promises to rank leads for you, so your team can focus on the ones that matter. But it’s not magic. If you put in bad data or set it up wrong, you’ll just get faster bad results.
Automated lead scoring in Provarity can:
- Save your reps hours each week
- Give you a consistent, data-backed way to prioritize leads
- Help marketing and sales get on the same page
It can’t:
- Read your customers’ minds
- Fix broken sales or marketing processes
- Instantly solve bad data hygiene
So, use it as a tool—not a silver bullet.
What you’ll need before you start
Don’t skip this. Before you set up anything, make sure you have:
- Access to Provarity with admin or lead scoring permissions
- A clear idea of what a “good” lead looks like for your business (industry, company size, budget, etc.)
- A list of the data fields you have on leads (demographics, engagement, etc.)
- CRM integration set up (if you want lead scores pushed automatically)
If you don’t have these, stop and get them first. Otherwise, you’ll just end up redoing the setup later.
Step 1: Define what a qualified lead actually is
Automated scoring is only as good as your definition of “qualified.” If your team can’t agree, you’ll just automate confusion.
What to do:
- Gather your sales and marketing folks. Get everyone in the same (virtual) room.
- List out your best current customers. What do they have in common? Think industry, revenue, team size, tech stack, pain points.
- Be specific. “Decision maker” is too vague. “VP of IT at SaaS companies with 100–500 employees” is better.
- Map behaviors that indicate buying intent. Things like “requested a demo,” “visited pricing page 3+ times,” or “responded to outreach.”
Pro tip: Don’t overcomplicate it. Three to five core traits and two to three key behaviors are plenty to start.
Step 2: Audit your data sources and clean up junk
Automated scoring is only as good as the data you feed it. Garbage in, garbage out.
Checklist:
- Check what data you actually have. Download a sample from your CRM or Provarity.
- Identify missing or inconsistent fields. Are job titles formatted the same way? Are company sizes up to date?
- Fix junk data. If your source data is a mess, fix it before you automate. It’ll save you headaches later.
What matters most:
- Contact info (email, phone)
- Company info (name, size, industry, location)
- Engagement data (email opens, site visits, demo requests)
Skip scoring on data you don’t have or can’t trust.
Step 3: Set up lead scoring rules in Provarity
Now you’re ready to get into the weeds with Provarity.
- Log in and go to the “Lead Scoring” section.
- Create a new scoring model. Name it something obvious (e.g., “B2B SaaS Scoring”).
- Add your demographic rules.
- Assign points for things like company size, industry, or job title.
- Example: +15 points for “Software” industry, +10 for “500+ employees.”
- Add behavioral rules.
- Assign higher points for actions that indicate real interest.
- Example: +20 for “Requested demo,” +10 for “Opened 3+ marketing emails.”
- Set up negative scoring.
- Subtract points for red flags (e.g., generic email domains, unsubscribes, no engagement).
- Set thresholds for what’s a “hot,” “warm,” or “cold” lead.
- Example: 60+ points = Hot, 40–59 = Warm, below 40 = Cold.
Don’t chase every possible signal. Focus on the actions and traits that actually predict a sale, based on your real customers.
Step 4: Test your scoring model on real leads
Don’t trust your new rules blindly—test them.
- Run your model on past leads. See if your “hot” leads were actually the ones who closed.
- Ask your sales reps for feedback. Are the scores matching what they see in the field? If not, tweak the weights.
- Look for false positives/negatives. Are you scoring tire-kickers as “hot”? Are good leads showing up as “cold”?
Pro tip: Expect to adjust your scoring rules at least a few times. The point is to get closer to reality, not to be perfect on day one.
Step 5: Automate lead scoring sync with your CRM
If you want scores to show up where your reps actually work, connect Provarity to your CRM.
- Go to Integrations in Provarity and select your CRM (e.g., Salesforce, HubSpot).
- Map the lead score field from Provarity to your CRM’s contact or lead records.
- Set sync frequency. Real-time is best, but daily is fine for most teams.
- Test the integration with a few dummy leads before going live.
If you skip this step, your fancy scoring will just sit in Provarity and no one will use it.
Step 6: Train your team—and enforce the new process
Even the best system is useless if nobody follows it.
- Show your team where to find the lead score. Demo it live.
- Explain what the scores mean. What’s a “hot” lead vs. “cold” lead? What actions should they take?
- Update your sales playbooks. Spell out how reps should handle leads in each bucket.
- Don’t let reps ignore the scores. If someone keeps cherry-picking cold leads, call it out.
Pro tip: Lead scoring only works if it changes behavior. Make it part of your sales process, not just a reporting tool.
What to ignore (for now)
- AI-based “intent scoring” that promises to read buyers’ minds. Most of it’s smoke and mirrors unless you already have great data and a mature process.
- Endless tweaking. Set a calendar reminder to revisit your scoring model every quarter. Don’t obsess over tiny changes week-to-week.
- Overly complex models. If sales reps can’t explain how scores are calculated, your model is too complicated.
Troubleshooting: Common issues and how to fix them
- Scores aren’t showing up in CRM: Double-check field mappings and permissions. Sometimes it’s just a sync setting.
- Too many “hot” leads: You’re probably assigning too many points for easy-to-get data. Tighten your rules.
- Sales ignoring scores: Get their feedback and adjust. Bad scores mean bad adoption.
- Data is missing: Fix your data sources before blaming Provarity.
Keep it simple, keep improving
Automated lead scoring in Provarity can save your team a ton of time—but only if you keep it simple and actually use the results. Start with the basics, get feedback, and improve as you go. Don’t chase shiny objects or overcomplicate things. The goal is to help your team focus on the leads that matter, not just to have a fancy new dashboard.
Now, go set it up and start seeing which leads are worth your time.