Tired of guessing which leads are actually worth your time? You’re not alone. If you’re juggling a pile of signups or demo requests, lead scoring can help you focus on the folks most likely to buy. This guide is for anyone who wants to use automated lead scoring in Spiky—whether you’re a sales manager, a startup founder, or just the “techie” on the team.
I’ll walk you through every step, flag what actually matters, and help you avoid common traps. No fluff, no hype. Let’s get into it.
Why bother with lead scoring?
Quick reality check: not every lead is created equal. Some visitors are just kicking the tires, while others are ready to talk pricing. Automated lead scoring helps you:
- Prioritize your outreach (so you’re not wasting time on dead-ends)
- Spot warm leads faster (before your competitor does)
- Get sales and marketing on the same page (at least a little)
But—lead scoring isn’t magic. If your data’s a mess, or your scoring rules are wishful thinking, you’ll just automate bad guesses. Let’s keep it practical.
Step 1: Connect your data sources
Spiky’s lead scoring is only as good as the data you feed it. Before you set up scoring, make sure Spiky is pulling in the right info.
Connect the basics:
- CRM (like Salesforce or HubSpot)
- Marketing platform (Mailchimp, Marketo, etc.)
- Website analytics (if you want behavioral data)
- Any forms or chat tools you use for lead capture
How to do it:
- In Spiky, head to Settings > Integrations.
- Add connections for each tool. Most just need an API key or OAuth login.
- Test the connection—don’t just assume it’s working. Check that leads are actually syncing.
Pro tip:
Garbage in, garbage out. If you’re missing key data (like company size or lead source), your scores won’t be accurate. Take the time to fix messy fields now.
Step 2: Decide what makes a lead “hot” for your business
Before Spiky can score anything, you need to define what a good lead looks like. Don’t just copy the defaults—think about your business.
Ask yourself:
- Who actually buys from us? (Size, role, industry, etc.)
- What actions do our best leads take? (Demo request, pricing page visit, webinar signup)
- What are red flags? (Generic emails, students, competitors, tire-kickers)
Make a list. Even a quick table on a napkin works:
| Attribute | Good Sign? | Bad Sign? | |-----------------------|-------------------|--------------------| | Job Title | “VP,” “Manager” | “Student” | | Company Size | 51-500 employees | 1-2 employees | | Website Visits | >3 pages viewed | Only homepage | | Email Domain | Business email | Gmail/Yahoo/etc. |
Don’t overthink it.
It’s better to start simple and tweak later than get stuck for weeks designing the “perfect” model.
Step 3: Set up your scoring rules in Spiky
Now, put those ideas into Spiky. The app lets you build rules that assign points based on attributes and behaviors.
How to do it:
- Go to Lead Scoring > Rules in Spiky.
- Add a new rule for each signal you care about:
- Example: “If Job Title contains ‘Director’ or ‘VP’, add 20 points.”
- Example: “If Company Size is 51-500, add 15 points.”
- Example: “If Email Domain is Gmail/Yahoo/etc., subtract 10 points.”
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Example: “If user viewed Pricing page, add 10 points.”
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Set the point values. Don’t stress about getting them perfect—just make the good signs add up higher than the bad ones.
- Arrange your rules in priority order if Spiky asks for it.
Pro tips:
- Start with 5–8 rules. More than that, and you’re probably kidding yourself about your data quality.
- Don’t double-count. If “visited website” and “filled out form” are always together, pick one.
- Negative points are your friend. Use them to weed out students, bots, or obviously bad leads.
Step 4: Test your scoring model
Before you unleash this on your team, see what scores real leads get. Otherwise, you might be sending your best prospects to spam.
How to do it:
- In Spiky, go to Lead Scoring > Test/Preview.
- Pick a few recent leads (good, bad, and in-between).
- Run them through the model—see what scores they get.
- Does the model’s “hot” score actually match real deals you’ve closed? If not, adjust your rules or points.
Watch out for these headaches:
- Scores are all bunched up: Spread out your point values more.
- Too many “hot” leads: Your bar’s too low. Add stricter rules or negative points.
- Obvious duds scoring high: Check your rules for missing negatives.
Don’t skip this step, or you’ll be chasing down the wrong people.
Step 5: Set up automatic actions for high-scoring leads
Lead scoring is pointless if it just sits there. With Spiky, you can trigger actions when someone hits a certain score.
Common automations:
- Assign the lead to a salesperson
- Send an alert (email, Slack, etc.)
- Add to a special CRM list
- Fire off a personalized email
How to do it:
- Go to Automations in Spiky.
- Create a new automation:
- Trigger: Lead score crosses threshold (e.g., 50 points)
- Action: Pick what you want to happen (assign, notify, etc.)
- Test it with a dummy lead. Make sure the right alert goes to the right person.
Pro tip:
Don’t set your threshold too low. If everyone gets flagged, no one pays attention. Start higher and lower it if you’re not seeing enough action.
Step 6: Monitor, tweak, and avoid “set it and forget it” syndrome
Your scoring model isn’t done once you turn it on. Reality changes—so should your rules.
What to check monthly:
- Are your “hot” leads actually converting?
- Are good leads slipping through the cracks?
- Are reps ignoring the scores or complaining?
How to improve:
- Adjust point values if the wrong people are bubbling up.
- Add/remove rules as you spot patterns (or get burned).
- Loop in sales for feedback—no, really, listen to them.
Ignore the hype:
No tool gets this perfect out of the box, no matter what the sales rep promised. Tuning your model is normal.
What to skip (for now)
You’ll see features for “AI-powered” lead scoring or “predictive intent.” Here’s the truth:
- If you don’t have much data, these are just fancy guesswork.
- If your leads are mostly similar, machine learning won’t magically pick winners.
Stick to rule-based scoring until you’ve got at least a few hundred closed deals to learn from. Then maybe test the fancier stuff.
Keep it simple, keep it real
Lead scoring with Spiky should help you cut through the noise—not add busywork. Start with basic rules, test with real leads, and don’t be afraid to adjust as you go. The perfect model doesn’t exist, but a practical one will save you time and help you land more deals.
Remember: iterate, don’t overcomplicate. The fewer moving parts, the easier it is to spot when something’s off.
Now go score some leads—and spend your energy where it actually counts.