So, your sales team is drowning in leads, but only a handful are worth their time. You want a system to sort the gold from the noise—without turning your CRM into a science project. If that’s you, you’re in the right place. This guide is for sales managers, ops folks, and anyone who wants to set up automated lead scoring in Pick that actually works for real people, not just spreadsheets.
Let’s get straight to it.
Why Bother With Automated Lead Scoring?
If you’re reading this, you already know manual lead triage is a pain. Too many leads, not enough time, and your AEs end up calling tire-kickers. Automated lead scoring promises to fix that by ranking leads based on how likely they are to close.
Honest take: Automated lead scoring can save your team a lot of time, but only if you set it up thoughtfully. Garbage in, garbage out. If you just copy-paste some default scoring model, you’ll end up with a bunch of “hot” leads that never buy.
Step 1: Get Clear on What Makes a Good Lead (for Your Team)
Before you even log in to Pick, talk to your sales reps and managers. Get specific about what a “good” lead looks like. Forget generic traits like “has a website” or “clicked an email”—you want signals that actually connect to deals closing.
Ask yourself: - What do our best customers have in common? - What red flags do reps spot right away? - Which data do we reliably collect on every lead?
Common scoring factors (pick only what matters): - Company size or industry - Job title or seniority - Website activity (but be skeptical—lots of clicks ≠ real interest) - Response to outbound emails - Whether they booked a demo (this one’s hard to fake)
Pro tip: Less is more. If you try to score on 15 things, you’ll dilute what matters.
Step 2: Prep Your Data in Pick
Once you’ve got a shortlist of relevant criteria, check what you’re actually tracking in Pick. Automation is only as good as your data hygiene.
- Double-check lead fields: Are you collecting the info you need at the point of capture (web forms, imports, integrations)?
- Standardize values: “VP” vs. “Vice President” vs. “V.P.”—make sure Pick isn’t confused by small differences.
- Clean up duplicates: No one wants to call the same company twice and look clueless.
If your data is a mess, fix that first. Otherwise, your scoring will just reflect back the chaos.
Step 3: Build Your Scoring Model in Pick
Now, let’s get into the nuts and bolts. Pick’s lead scoring setup is pretty straightforward, but don’t be fooled by the shiny UI—what matters most is your logic.
3.1 Decide on Point Values
In Pick, you assign points to different actions or attributes. Don’t go wild with decimals and tiny differences; keep it simple.
Example: - +10 if job title contains “Director” or above - +8 if company is in your target industry - +5 if they opened your last campaign email - +15 if they booked a meeting - -10 if company size < 10 employees (if you sell to mid-market)
3.2 Set Up the Rules
- Go to the “Lead Scoring” section in Pick.
- Click “Create Rule” for each scoring factor.
- Choose the field (e.g., Job Title), set the condition (e.g., contains “Manager”), and assign the points.
- Repeat for positive and negative signals.
Honest tip: Don’t try to automate “gut feel” stuff like “seems friendly.” Stick to hard data.
3.3 Save and Test
Once your rules are in, save and apply them. Pick will rescore your existing leads.
Test on real leads: Grab a few leads your reps already know are good or bad. Check if the scores match reality. If not, tweak the points.
Step 4: Automate What Happens Next
Scoring is only useful if it changes what your team actually does. Decide what happens when a lead hits a certain score.
Examples: - Over 20 points? Auto-assign to an AE. - Under 5 points? Put into a nurture sequence or mark as “cold.” - 15–20 points? Flag for SDR follow-up.
Set up automations in Pick (usually under “Workflows” or “Rules”) to handle this. If you rely on reps to manually check scores, you’re wasting the whole point.
Step 5: Train Your Team—and Get Feedback
Don’t just roll this out and hope for the best. Your reps need to know: - What the scores mean - How they’re expected to use them - Who to talk to if something seems off
Run a short training session, then check in a week later. Are good leads slipping through? Are reps ignoring high scorers? If so, the model needs adjusting.
Step 6: Monitor and Iterate (Seriously, Don’t Skip This)
The first version of your scoring model will be wrong. That’s fine. The real value comes from tweaking it over time.
What to track: - Are high-scoring leads actually converting at a better rate? - Are reps complaining about “junk” leads getting high scores? - Is your sales cycle getting shorter (or longer)?
Schedule a review every month or quarter. Adjust points or rules based on real outcomes, not guesses.
Pro tip: Ignore the temptation to automate everything. Some leads will always need a human touch.
What Works, What Doesn’t, and What to Ignore
Works well: - Clear, simple rules based on real data - Regular tweaks based on feedback and results - Automating handoff from marketing to sales
Doesn’t work: - Over-complicating with too many variables - Relying on marketing engagement alone—busywork ≠ purchase intent - “Set it and forget it” mindset
Ignore: - Fancy AI scoring tools (unless you’re at huge scale) - Scoring based on vanity metrics like social media follows - Overweighting form-fills—anyone can fill out a form
Keep It Simple, Iterate Fast
Automated lead scoring in Pick can make your sales team’s life easier—if you keep things simple and focus on what actually moves the needle. Don’t get sucked into endless debates over point values. Launch a basic model, see what happens, and adjust. Your best leads (and your reps) will thank you.
Now, go set it up and see how it works in the real world.