If you’re running enterprise sales, you know the pain: too many leads, not enough time, and lots of “maybe” deals that go nowhere. Manual lead scoring is slow, inconsistent, and—let’s be honest—no one really enjoys it. Automating lead scoring in Vector can make your team’s life a lot easier, but only if you do it right. This guide is for sales and ops folks who want a realistic, no-nonsense approach that actually works, not just another buzzword parade.
What is Automated Lead Scoring, Really?
Let’s clear one thing up: automated lead scoring isn’t magic. It uses your data (good or bad) to rank leads based on criteria you set. Get the criteria wrong, and you’ll just automate mediocrity. Get them right, and your team stops wasting time on dead ends.
Vector is a sales automation platform that lets you pull in leads from different sources, track interactions, and score them automatically—if you set up the rules. This article walks you through the whole thing, step by step, with honest pointers on what’s worth your time.
Step 1: Define Your “Good Lead”
You’d be surprised how many teams skip this. Before you touch Vector, sit down with your sales reps, SDRs, and maybe a marketer or two. Ask: What makes a lead worth chasing? Look at your past closed-won deals for inspiration.
- Firmographics: Company size, industry, location.
- Behavior: Visited pricing page, booked a demo, opened three emails.
- Tech stack: Using tools you integrate with.
- Contact info: Did they give you a real business email, or a Gmail?
Pro Tip: Don’t get cute with a 50-point checklist. Pick the 3–5 things that really separate serious buyers from everyone else.
Step 2: Map Your Data Sources
Automated scoring is only as good as the data you feed it. In Vector, you can usually pull from:
- CRM (like Salesforce, HubSpot, etc.)
- Marketing automation (Marketo, Pardot, etc.)
- Third-party data enrichment (Clearbit, ZoomInfo)
- Website forms and chat tools
What to skip: If a data source is messy or unreliable, leave it out for now. Bad data ruins good scoring.
Step 3: Set Up Custom Lead Scoring Rules in Vector
Now, get into Vector and find the lead scoring module. Here’s how to set up rules that don’t suck:
- Go to Admin/Settings > Lead Scoring.
- Create scoring criteria based on your “good lead” profile:
- Assign points for each key attribute. (e.g., +20 for “500+ employees”, +10 for “requested demo”)
- Subtract points for red flags. (e.g., –15 for “Gmail address”, –10 for “student title”)
- Set up behavior-based triggers:
- Opened 3+ emails: +5
- Clicked pricing link: +10
- No activity for 2 weeks: –10
Don’t overthink it: Start simple. Too many rules just dilute the value. You can always tweak later.
Step 4: Test Scoring on Real Leads (and Don’t Trust the Defaults)
Most platforms, Vector included, offer “out-of-the-box” scoring models. These are rarely right for your business. Here’s what actually works:
- Score a batch of recent leads manually. Compare your gut feeling to the automated score. Are the “good” leads getting high scores?
- Look for false positives/negatives. If weak leads are scoring high, fix your rules.
- Get feedback from reps. If they say the scoring is off, listen. They’re the ones chasing these folks.
Pro Tip: Don’t be afraid to delete rules that aren’t pulling their weight. More isn’t always better.
Step 5: Automate Actions Based on Scores
Scoring is just a number unless you do something with it. In Vector, you can set up automations like:
- Assign hot leads to senior reps.
- Trigger follow-up tasks or emails.
- Push leads with low scores into nurture sequences.
- Alert managers when a whale shows up.
What to ignore: Overcomplicated branching automations. If you need a flowchart to explain it, it’s too much. Keep it obvious.
Step 6: Monitor, Tweak, Repeat
No lead scoring model stays perfect. Things change—new products, new markets, new ICPs. Make it a habit to:
- Review scoring rules monthly. Are you getting too many “hot” leads? Not enough?
- Check conversion rates on high-scoring leads. Are they actually closing?
- Solicit rep feedback. They’ll notice if the model drifts.
Warning: Don’t fall for “set it and forget it.” Automated scoring needs maintenance, like anything else you care about.
What Actually Works (and What Doesn’t)
Works: - Simple, clear scoring rules based on real data - Involving your sales team in setting up and refining the model - Using automations for obvious, time-saving actions
Doesn’t: - Relying on default scoring models or vendor promises - Overcomplicating the scoring system (“If a lead sneezes during a full moon, add +2…”) - Ignoring feedback from actual reps
Ignore: - Fancy machine learning models unless you’re swimming in data and have real data science help - Vanity metrics like “engagement score” that don’t correlate with closed deals
Pro Tips for Staying Sane
- Keep your criteria visible. Post your current scoring rules somewhere the team can see. If people don’t understand how it works, they’ll ignore it.
- Document changes. When you tweak the system, write down what you changed and why.
- Automate with a light touch. The goal is less busywork, not more.
Wrapping Up
Automating lead scoring in Vector isn’t rocket science, but it does take some thought (and a willingness to ignore the hype). Start simple, listen to your team, and don’t be afraid to adjust as you go. The best models are usually the easiest to explain. Get it working, keep it honest, and iterate as your business evolves. That’s how you build a system your sales team will actually use.