If your sales team is drowning in “leads” that go nowhere, you’re not alone. Most B2B teams waste time chasing the wrong people just because their CRM says so. Automated lead scoring promises to fix this, but most setups are either too complicated or basically just guesswork with extra steps. This guide is for folks who actually want leads that close, not just a fancier spreadsheet.
We’ll walk through how to set up automated lead scoring in Tryleap, what to watch out for, and how to cut through the noise. No fluff—just what works, what doesn’t, and how to avoid wasting your time.
Why Automated Lead Scoring (Usually) Sucks—and How Tryleap Tries to Fix It
Let’s be honest: most lead scoring is just marketing teams assigning random points (“+5 for opening an email!”) and hoping for the best. It rarely lines up with who actually buys.
Tryleap claims to do this smarter by pulling in data from all your sources—CRM, website, emails, LinkedIn, you name it—and applying some logic (sometimes AI, sometimes just rules) to sort the real buyers from the tire-kickers. The promise: less time wasted, more deals closed.
But it’s only as smart as the setup. Garbage in, garbage out. So let’s make sure you set it up right.
Step 1: Get Crystal Clear on What “Good Lead” Actually Means
Before you even log into Tryleap, sit down with your sales team and answer this: Who actually buys from you? Not who looks good on paper, but who signs the contract.
Start with reality, not wishful thinking.
Some honest questions:
- What company sizes and industries make up your actual customer base?
- Which roles usually reply or drive purchase?
- What behaviors (downloads, demo requests, replies) have led to closed deals—not just pipeline fluff?
- Which “leads” looked great but wasted your time? Why?
Pro tip:
Pull up the last 10 deals you closed and the last 10 that fizzled. What’s the difference? Write it down. This is your real-world scoring foundation.
Step 2: Connect Your Data Sources to Tryleap
Now, log in to Tryleap and get your data flowing. Without good data, you’re just guessing with fancier tools.
Typical integrations to set up:
- CRM: Salesforce, HubSpot, Pipedrive, etc.
- Marketing automation: Mailchimp, Marketo, whatever you use.
- Website and chat: Drift, Intercom, or your web forms.
- LinkedIn & enrichment tools: If you use Clearbit, Apollo, or similar.
Don’t connect everything “just because.”
Only hook up the sources that actually track meaningful lead actions or have clean company/contact data. More data isn’t always better if it’s messy or irrelevant.
Heads up:
If you have tons of duplicate or outdated records, clean those up first. Tryleap can’t work miracles on garbage data.
Step 3: Define Your Lead Scoring Criteria (Don’t Overthink It)
This is where most teams get lost in the weeds. You don’t need 20 scoring factors. Start with a few that actually matter.
Common scoring buckets:
- Firmographics: Company size, industry, location.
- Role: Seniority, department (buyer vs. tire-kicker).
- Behavior: Website visits, demo requests, responding to emails, event attendance.
- Negative triggers: Competitors, students, or folks outside your market.
Tryleap lets you set up both “rule-based” and AI/ML-based scoring. Here’s the honest take: - Rule-based scoring: You decide the rules (“+10 if company is in SaaS, +5 if VP or above, -10 if from a non-target country”). This is predictable and great for starting out. - AI/ML-based scoring: Tryleap can “learn” from your closed-won and closed-lost deals and start predicting who’s likely to close. Sounds fancy, but only works if you have a lot of clean, historical data. If you’ve only closed 20 deals ever, don’t expect magic.
Pro tip:
Set up rules first—simple, clear, and easy to tweak. Layer in AI scoring later if your data is solid and you want to experiment.
Step 4: Build Your Scoring Model in Tryleap
Inside Tryleap, go to the lead scoring section and start building your model.
For rule-based scoring:
- Add criteria: Start with the 3-5 factors you identified earlier.
- Set point values: Don’t go wild. Use a simple scale (e.g., -10 to +10 per factor).
- Define “qualified” threshold: Decide what total score marks a lead as “hot” or ready for sales.
For AI/ML scoring (optional, and only if you’re ready):
- Upload clean historical data (closed-won, closed-lost).
- Let Tryleap analyze patterns and generate a model.
- Review the model’s logic—don’t just trust it blindly. If something looks weird, dig deeper.
Don’t set it and forget it.
Lead scoring is not Ron Popeil’s rotisserie. Expect to adjust your model every month or so, especially after you see what’s actually working.
Step 5: Test, Review, and Tune—Relentlessly
Here’s where most teams drop the ball. They set up scoring, get excited about “hot leads,” and then…watch nothing change.
What to do instead: - Spot check: Pull a list of “hot” leads and see if they actually look good to your sales team. If not, tweak your rules. - Feedback loop: Get regular input from reps. Are the “qualified” leads any better? - Track outcomes: Don’t just look at open rates or meetings booked. Are you closing more deals, faster?
Pitfalls to avoid: - Overcomplicating your scoring with too many factors. - Ignoring negative signals (“but they downloaded a whitepaper!”). - Blindly trusting any “AI” magic—especially if your data is thin.
Pro tip:
If your best leads always get hand-picked by reps anyway, your scoring model needs work. It should highlight leads your team would actually want to talk to, not just whoever clicks the most emails.
Step 6: Automate Actions (But Keep It Simple)
Once your scoring is halfway decent, set up automations to actually do something with it.
Examples: - Auto-assign “hot” leads to your best reps. - Trigger personalized email sequences for “warm” leads. - Suppress “cold” leads from sales follow-up (so you’re not bugging students or competitors). - Push “re-engage” nudges to marketing when a cold lead’s score rises.
Don’t go nuts with automations.
Automating junk just means you’re wasting time faster. Get the basics right first, then layer on complexity as needed.
Step 7: Rinse, Repeat, and Don’t Chase Perfection
Lead scoring isn’t a “set it and forget it” thing. Your market, product, and team will change. What works today might be outdated in six months.
- Review your scoring every month or two.
- Get feedback from the team.
- Keep your model simple—complicated scoring rarely works better.
If you find yourself building a 30-factor scoring model, step back. The best systems are the ones your team actually uses and trusts. Don’t let perfect be the enemy of good.
Quick FAQ: Things People Overcomplicate (and Shouldn’t)
Do I need AI/ML scoring?
No, not unless you have a lot of data and a stable sales process. Start with rules.
What if my data is messy?
Clean it, or expect bad results—no tool can fix garbage inputs.
Should I score every tiny action?
No. Focus on signals that actually tie to closed deals.
Can Tryleap replace my sales intuition?
Nope. It’s a tool, not a crystal ball.
Keep It Simple, Stay Sane
Automated lead scoring in Tryleap can save you a ton of time—if you keep it simple, honest, and grounded in what actually works for your business. Don’t chase every new feature or AI promise. Start small, iterate, and remember: the best lead scoring is the one your team actually uses.
Now, get back to those leads that matter.