If you’re tired of chasing dead-end leads and want a no-nonsense way to spot the folks who actually want to buy, this guide is for you. We’re digging into how to set up and automate lead scoring workflows in Pocus. Whether you’re in sales, revops, or just trying to make sense of your inbound mess, you’ll get the real steps (and the real talk) here—no fluff, no magic bullets, just what works.
Why Bother with Lead Scoring (and Why People Get It Wrong)
Lead scoring is supposed to help you focus on the right people, not just the loudest ones. The problem? A lot of teams overcomplicate things. They track 30 signals, build Rube Goldberg machines in their CRMs, and end up with “hot” leads who never reply.
Here’s the truth: Simple, clear lead scoring that matches how your best customers actually buy is better than any fancy model. Tools like Pocus can help, but only if you keep things grounded in reality.
Step 1: Get Your Data House in Order
Before you build anything in Pocus, you need to know where your data lives. Pocus does a good job connecting to lots of sources (CRMs, product analytics, enrichment tools), but junk in means junk out.
What to check: - Are your CRM fields actually up to date? - Is product usage data (logins, actions, etc.) connected? - Do you have basic firmographics (industry, size, etc.) for your accounts?
Pro Tip:
Don’t try to score leads using data you don’t trust. If your product analytics is a mess, leave it out for now. Use what’s reliable, even if it’s just a handful of fields.
Step 2: Decide What Actually Makes a Good Lead
This is where most teams get tripped up. Don’t just copy someone else’s scoring model. Think about your last 10 closed deals. What did they have in common?
Make two lists: - Fit signals: Company size, industry, tech stack, title—stuff that doesn’t change much. - Behavioral signals: Opened an email, started a trial, hit a paywall, booked a demo—stuff they actually did.
What works: - 2–3 fit signals (don’t overthink it) - 2–3 clear behavioral signals (but not just “clicked an email”—go deeper if you can)
What to ignore: - Vanity metrics (e.g., “visited our About Us page 10 times”) - Overly complex combinations (if you can’t explain it at lunch, it’s too much)
Step 3: Build Your Lead Scoring Model in Pocus
Now you’re ready to actually do something in Pocus. Here’s the basic process:
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Connect your data sources:
Pocus has integrations for Salesforce, HubSpot, Snowflake, and a bunch more. Set these up in the settings. Don’t get distracted by every possible source—start with what matters. -
Define your segments:
In Pocus, “segments” are groups of leads that share certain traits. For example, “SaaS companies with over 50 employees that started a trial in the last 7 days.” -
Assign points (but don’t get cute):
For each signal, assign a score—maybe 10 points for company size, 15 for a key action. Keep the math simple. If you need a spreadsheet to check your work, you’ve gone too far. -
Set thresholds:
What score makes someone a “hot lead”? Pick a starting number (e.g., 30 points) and adjust later. Don’t stress about perfection.
Honest take:
Most “AI” scoring features sound cool but rarely outperform a thoughtful, simple model—especially when you’re starting out. Trust your gut and your data, not buzzwords.
Step 4: Automate Lead Routing and Alerts
Lead scoring is only useful if it leads to action. Pocus lets you automate what happens when a lead hits a certain score.
Here’s what you can do: - Assign leads to reps: Set rules so that certain leads go directly to the right person or team. - Trigger Slack/Email alerts: Notify your sales team when a lead crosses the threshold. - Sync to CRM: Update lead status or add them to a sequence in Salesforce/HubSpot.
How to set it up: 1. In Pocus, go to the “Workflows” or “Automations” section. 2. Choose your trigger (e.g., “Lead score > 30”). 3. Add actions: assign, alert, sync, etc. 4. Test it using a few sample leads.
Watch out for: - Too many alerts (sales will ignore them) - Leads getting “stuck” if your routing is too complicated - Reps not knowing what to do next—give them clear next steps
Step 5: Review, Tweak, and Don’t Be Precious
No lead scoring model is perfect out of the gate. After a week or two, actually look at the leads your workflow is surfacing. Are they any good? Is sales following up? Are deals moving?
What to do: - Ask your team: “Are these leads actually worth your time?” - Adjust your point values or signals based on real feedback. - Don’t be afraid to drop a signal if it’s not helping.
Pro Tip:
If you’re not sure where to tweak, look at the last 10 leads that scored high but went nowhere. What did they have in common? Remove or downweight those signals.
Step 6: Keep It Simple (and Ignore the Hype)
It’s tempting to keep stacking on more signals, more automations, more integrations. Resist. The best lead scoring workflows are the ones your team actually uses.
Stick to: - Clear, explainable logic (you shouldn’t need an engineer to debug it) - A short list of meaningful triggers - Automation that saves real time (not just looks impressive in a demo)
If you find yourself spending more time fiddling with the model than talking to customers, take a step back.
Summary: Good Enough Beats Perfect
Lead scoring in Pocus can absolutely help you spot better leads and waste less time—but only if you keep it grounded and practical. Start simple, automate what’s actually helpful, and don’t be afraid to change things up as you learn.
Set it up, see what works, and keep it moving. You’ll get more out of your leads—and your sanity will thank you.