If you're tired of chasing every lead with the same energy—only to find half of them are a waste of time—you're in the right place. This guide cuts through the fluff and shows you step by step how to set up custom lead scoring models in ExportApollo.com. No magic tricks, just practical advice you can actually use, even if you’re not a data scientist. Whether you’re in sales ops, a founder, or just the only person who cares about lead quality at your company, this one’s for you.
Why bother with custom lead scoring?
Before we dive in, let’s be real: default lead scoring models rarely fit your business. Every company’s “hot lead” looks a little different. Setting up your own scoring:
- Saves time chasing unqualified leads
- Helps sales reps focus on what actually converts
- Lets marketing measure what’s working—without guesswork
But don’t expect a silver bullet. A lead score is only as good as the inputs and logic you use. Garbage in, garbage out.
Step 1: Get clear on what matters to you
Don’t start with the tool. Start with your business.
Grab pen and paper (or a shared doc) and jot down:
- What makes a lead “good” at your company? Think job title, company size, industry, website activity, location, etc.
- Which traits or behaviors actually predict a sale?
- Are there red flags? (e.g., students, competitors, Gmail addresses)
If you don’t know, dig into your CRM. Look at closed-won deals from the past 6–12 months. What do they have in common? What’s missing from deals that never closed?
Pro tip: Don’t overthink it. Start with 3–5 clear signals. You can always adjust later.
Step 2: Prep your data in ExportApollo
Log in to ExportApollo and head to your leads or contacts list. Before you start scoring, make sure your data isn’t a mess.
Check for:
- Duplicates
- Missing key info (like company size, email, or industry)
- Weird formatting (all caps, typos, etc.)
If you have custom fields in ExportApollo, now’s the time to clean those up. The cleaner your data, the less time you’ll spend chasing ghosts.
Ignore: Trying to score leads before your data is usable. It’s tempting, but you’ll regret it.
Step 3: Map out your scoring criteria
Now, translate your “good lead” traits into things ExportApollo can actually score. You’ll usually want to focus on:
- Demographics: Job title, seniority, department, location
- Firmographics: Company size, industry, funding, tech stack
- Behavior: Email opens/clicks, site visits, demo requests
Decide if each factor is a “must-have” or just a “nice-to-have.” Assign point values to each. Here’s a dead-simple example:
| Trait | Points | |-----------------------|--------| | VP or C-level title | +20 | | Company > 100 employees | +15 | | In target industry | +10 | | Opened marketing email | +5 | | Visited pricing page | +10 | | Personal email domain | -10 |
What works: Weighted scoring is straightforward and easy to tweak.
What doesn’t: Overcomplicating it with 10+ variables or fuzzy logic. You’ll just confuse yourself and your team.
Step 4: Set up your custom lead scoring model
Now for the hands-on part. In ExportApollo, you can build custom scoring models using their lead scoring feature. Here’s how to do it without getting lost:
1. Navigate to Lead Scoring
- Go to the “Settings” menu.
- Find the “Lead Scoring” tab (usually under “Customizations” or “Automations”).
- Click “Create New Model” or “Edit Model.”
2. Define your rules
You’ll see a list of available fields—standard and custom. For each, set up a rule, like:
- IF “Job Title” contains “VP” or “Chief” → ADD 20 points
- IF “Company Size” is greater than 100 → ADD 15 points
- IF “Industry” equals “SaaS” → ADD 10 points
- IF “Email Domain” is “gmail.com” → SUBTRACT 10 points
You can usually stack as many rules as you want, but keep it simple at first.
3. Set Thresholds
Decide what scores qualify as “hot,” “warm,” or “cold” leads. Example:
- 40+ points: Hot
- 20–39: Warm
- 0–19: Cold
Label these in ExportApollo so your team knows what’s what.
4. Save and Test
Save your model. Then, run it against a sample of your actual leads. Spot-check: are your “hot” leads actually good? If not, tweak your rules or points.
Honest take: No model is perfect on the first try. Expect to iterate.
Step 5: Put your scores to work
A lead score is pointless if nobody uses it. Here’s how to actually make it useful:
- Filter and sort: Have reps start with the hottest leads first.
- Trigger workflows: Use ExportApollo automations to assign hot leads to senior reps, or send them straight to sales.
- Track results: Measure conversion rates for each score group over time. If “hot” leads aren’t converting, your model’s off.
What to ignore: Fancy dashboards that don’t change what your team does each day. Focus on action, not reporting.
Step 6: Review and tune your model (seriously)
Don’t “set and forget.” Block 30 minutes every month to review:
- Are your top-scoring leads actually closing?
- Are you missing good leads because your model’s too strict?
- Are reps complaining about junk leads marked as “hot”?
Tweak your weights, add or remove criteria, or run a quick manual audit. Real-world feedback beats theory every time.
Pro tip: Don’t let perfection slow you down. A B+ model in action beats an A+ model that never launches.
Common mistakes with lead scoring (and how to avoid them)
- Overfitting to old deals: Just because something worked last year doesn’t mean it works now. Keep updating.
- Too many rules: More isn’t better. You’ll just make it hard to maintain.
- Ignoring rep feedback: If sales says the model is off, listen. They’re the ones using it.
- Not using the score: If nobody actually filters or sorts by score, you’ve wasted your time.
Quick FAQ
Can I use machine learning in ExportApollo for lead scoring?
If you’re hoping for a magic ML button, ExportApollo isn’t that kind of tool—yet. But honestly, most companies don’t need AI for lead scoring. Start simple, and only get fancy if you outgrow basic rules.
How do I handle leads with missing data?
Give partial credit, or set up a default score. Don’t automatically mark them as cold—sometimes a missing field just means bad data entry.
Should I change my model based on new campaigns?
Yep. New campaigns, new ICPs, new products—it all affects what a “good” lead looks like. Schedule a quarterly review.
Keep it simple, ship it, then improve
Don’t get paralyzed by overthinking. The best lead scoring models in ExportApollo are the ones that actually get used—and get tweaked over time. Start basic, listen to your team, and make small improvements. You’ll save everyone time and close more deals, without falling for the latest sales tech fad.