If you’re running a B2B sales team and tired of chasing random leads because “the algorithm said so,” this guide’s for you. Building a lead scoring model in Kuration can help you cut through the noise and actually focus on deals that might close. But only if you keep it simple, avoid wishful thinking, and don’t let the software do all your thinking for you.
Let’s dig in. Here’s how to set up a lead scoring model in Kuration that’s useful, not just another dashboard.
Step 1: Get Your Basics Right Before You Touch the Tool
Look, no software can save you if you don’t know who your best customers are. Before you open Kuration, sit down with your sales team and answer:
- What does a truly “good” lead look like for us? (Think: company size, industry, pain points, buying signals.)
- What’s a red flag? (e.g., tire-kickers, companies too small, wrong geography)
- Who usually signs the deal, and who drags their feet?
Don’t skip this step. If your team can’t agree on what a good lead is, your scoring model will just automate confusion.
Step 2: List Out the Data You Actually Have (Not Wish You Had)
Kuration can’t score what you don’t track. Before you start clicking, make a simple list:
- What data do we reliably collect on every lead? (e.g., company name, job title, industry, website activity)
- Where do gaps exist? (If you only have “First Name” for most leads, don’t pretend otherwise.)
- Which data points are most accurate? (Website activity is usually more real than self-reported revenue.)
Pro tip: Don’t build your model around “dream data.” Stick to what you can actually use right now.
Step 3: Map Your Lead Stages in Kuration
In Kuration, leads can move through custom stages. Don’t overcomplicate it. For B2B, you probably need:
- New
- Working
- Qualified
- Proposal Sent
- Closed (Won/Lost)
Resist the urge to add ten extra steps like “Initial Outreach” or “Discovery Call Scheduled.” More stages mean more confusion—and your reps will just ignore them anyway.
Step 4: Pick 4-6 Scoring Criteria That Actually Predict a Sale
Here’s where most people get it wrong. The goal isn’t to use every data point, it’s to focus on the handful that matter. In Kuration, you can set up scoring rules based on:
- Firmographics (Company size, industry, location)
- Demographics (Job title, decision-maker status)
- Engagement (Opened emails, visited pricing page)
- Behavioral Triggers (Requested demo, downloaded whitepaper)
What works:
- Giving more weight to actions that show real intent (e.g., asking for a demo is better than just opening an email)
- Penalizing for obvious mismatches (e.g., freelancer at a Fortune 500 target)
What doesn’t:
- Over-valuing vanity metrics (number of LinkedIn followers = useless)
- Relying on vague “lead score” numbers from third-party sources
Ignore:
- Social media likes
- Job titles that sound fancy but don’t have buying power (“Evangelist,” “Champion,” etc.)
Step 5: Set Up Scoring Rules in Kuration
Now, get into Kuration and start creating your model. Here’s a simple way to structure it:
- Go to your lead scoring settings in Kuration.
- Add your criteria (from Step 4).
- Assign point values—make sure high-impact actions get higher scores.
- For example:
- “Requested demo” = +30
- “Company size: 500+ employees” = +15
- “Opened 3+ emails” = +10
- “Student email address” = -20
A few honest tips: - Don’t let every department add their “pet” criteria. Keep it focused. - If everything gets a score, nothing matters. Prioritize ruthlessly. - Test your model with real leads and see if the top scorers actually converted.
Step 6: Define What “Qualified” Means—And Make It Obvious
Set a clear threshold for what gets handed from marketing to sales. In Kuration, you can automatically flag leads that hit a certain score as “Qualified.” Pick a score that means something, not just a round number.
- If too many junk leads get qualified, raise the bar.
- If sales complains they’re getting nothing, lower it a bit—but only if you trust their feedback.
Document this. If nobody knows what “Qualified” means, your model’s just a black box.
Step 7: Review and Adjust—Don’t Set and Forget
Your first model won’t be perfect. (No one’s is.) Every month or so:
- Look at closed-won vs. high-scoring leads—are you actually prioritizing the right ones?
- Talk to your sales reps. Are the “hot” leads actually hot, or are they duds?
- Adjust your scoring weights and criteria. Don’t be precious; if a metric isn’t working, kill it.
What works:
- Short feedback loops
- Being honest about what’s not working
What doesn’t:
- Waiting six months to make changes
- Letting the model get so complex nobody understands it
Step 8: Don’t Fall for Magic Numbers or Hype
There’s no “perfect” lead score—just a model that helps your sales team focus better than before. Don’t obsess over decimal points or let AI buzzwords distract you.
- If a vendor claims their scoring is “98% accurate,” run.
- Use Kuration’s automation to save time, not to replace thinking.
Remember: the best lead scoring model is one your team trusts and actually uses.
Step 9: Train Your Team—And Keep It Simple
Even the best model fails if your team ignores it or doesn’t know how it works.
- Walk them through the scoring logic.
- Show real examples of good and bad leads.
- Make it easy to give feedback (“Hey, this lead was scored high, but here’s why it’s wrong.”)
Don’t turn it into a science project. The goal is faster, smarter prioritization—not endless debate.
Wrapping Up: Keep It Real, Keep It Useful
Lead scoring in Kuration should help your team focus, not create more busywork. Start simple, use data you trust, and keep the loop tight between scoring and real results. Iterate as you go—nobody nails it on the first try.
Remember: complexity is the enemy. If your reps can’t explain the scoring model over coffee, it’s too complicated. Build, test, tweak, repeat.
Go get your best leads. Leave the hype behind.