If you’ve ever stared at a pile of leads and thought, “Where do I even start?”—this is for you. Automated lead scoring promises to sort the wheat from the chaff so you can stop wasting time on tire-kickers and focus on deals that might actually close. But if you’ve tried to set it up before, you know it isn’t magic. In this guide, I’ll walk you through setting up automated lead scoring in Mylighthouse without the usual headaches, hype, or “just trust the algorithm” nonsense.
Let’s get to it.
Why bother with automated lead scoring?
Automated lead scoring isn’t a silver bullet, but it is a reliable way to:
- Prioritize sales outreach so your team focuses on leads that look promising.
- Cut down on manual sorting, freeing up your time for…well, better things.
- Spot patterns in what makes a lead “good” (or not).
But — and this is important — no system scores leads perfectly out of the box. Think of your scoring as a living thing you’ll need to tweak as you go.
Step 1: Get clear on what a “good lead” actually is
Before you even log into Mylighthouse, grab a pen (or open a doc) and jot down what makes a lead valuable for your business. Don’t overthink it:
- Which leads have actually closed in the past? Look for patterns: company size, job title, industry, engagement level, budget, etc.
- What are the deal-breakers? Are there red flags—like wrong geography or missing budget—that instantly disqualify someone?
You need at least a rough list of criteria before setting up automated rules. If you just copy whatever scoring model is “recommended,” you’ll waste time chasing the wrong folks.
Pro tip: Ask your sales team. They’ll tell you who’s a waste of time—and who’s gold.
Step 2: Prep your data in Mylighthouse
Automated lead scoring in Mylighthouse only works if your lead data is clean and consistent. Garbage in, garbage out.
Check these before you start:
- Are all your important fields set up?
- Common ones: Email, Company, Job Title, Industry, Website, Lead Source
- Are required fields actually filled in?
- If “Industry” is blank on half your leads, don’t base scoring on it yet.
- Is your data standardized?
- “VP Sales” and “Vice President, Sales” might mean the same thing, but Mylighthouse can’t read your mind.
If your data’s a mess, spend an hour cleaning up the basics. You’ll save yourself 10x the frustration later.
Step 3: Map out your scoring criteria
Now, let’s get specific about what you want Mylighthouse to score. Here’s what most people use (and what actually works):
- Demographics (things like company size, industry, title)
- Behavior (opened emails, visited your site, downloaded resources)
- Source (where the lead came from—referral, ad, event, etc.)
- Fit (do they match your “ideal customer profile”?)
How to pick your criteria
Don’t try to score everything. Start simple, with 3-5 criteria max. For each one, decide:
- Does this make someone more or less likely to buy?
- How important is it, really?
Here’s a sample scoring sheet:
| Criteria | Points if matched | Points if not matched | |---------------------|------------------|----------------------| | Company size > 50 | +10 | 0 | | Title = Director+ | +8 | 0 | | Visited pricing page| +5 | 0 | | Used personal email | -5 | 0 | | Wrong country | -10 | 0 |
You don’t need to get cute: keep it obvious and easy to explain.
Step 4: Set up scoring rules in Mylighthouse
Finally, time to get your hands dirty in the software. Mylighthouse’s lead scoring engine is flexible, but not always “intuitive” for first-timers. Here’s how to set it up:
1. Go to the Lead Scoring section
- Log in to Mylighthouse.
- Head to Settings (gear icon, usually top right).
- Find Lead Scoring in the sidebar.
2. Create a new scoring model
- Click Create New Model (or similar; the wording changes sometimes).
- Give it a clear name, like “2024 Standard Scoring” or “Inbound Lead Score.”
3. Add your scoring criteria
For each rule: - Select the field (e.g., Job Title, Company Size) - Set the condition (e.g., “is Director or above,” “greater than 50 employees”) - Assign the point value (see your earlier scoring sheet) - Choose positive or negative points
You can usually add both “must have” (positive) and “deal-breaker” (negative) rules.
Example: Adding Title as a criterion
- Field: Job Title
- Condition: contains “Director” or “VP” or “Chief”
- Score: +8
Example: Penalizing bad fit
- Field: Country
- Condition: is not “United States”
- Score: -10
Don’t overcomplicate it. If you’re not sure what value to use, start with a rough guess and adjust after a few weeks.
4. Set thresholds (optional)
Some teams want to label leads as “Hot,” “Warm,” or “Cold.” You can do this in Mylighthouse by setting score ranges.
- For example:
- 15+ points = Hot
- 5-14 points = Warm
- <5 points = Cold
If you don’t have enough data yet, skip this for now.
5. Save and activate
- Double-check your rules.
- Hit Save or Activate.
- If there’s a “Test” or “Preview” mode, use it to see how scores will look on existing leads.
Step 5: Test your scoring—and don’t trust it blindly
Here’s where most people screw up: they turn on automated scoring and assume it’s gospel. Don’t.
Spend a week or two spot-checking:
- Are your “Hot” leads actually good?
- Look at a few each day. Would a real salesperson want to call them?
- Are any great leads getting low scores?
- Figure out why—they might be missing data, or your rules are too strict.
- Are you getting too many “Hot” or “Cold” leads?
- Tweak your thresholds. Better to start conservative and loosen up than flood your pipeline with junk.
Pro tip: Involve your sales team early. If they ignore your “Hot” leads, your scoring needs work.
Step 6: Build workflows and alerts (optional, but powerful)
Once your scoring is working, you can kick off automations in Mylighthouse—like alerting sales when a lead goes “Hot.”
- Send notification to sales: Trigger an email or Slack ping when a lead passes your Hot threshold.
- Move leads to a new pipeline stage: Automatically assign leads to a rep or move them from “New” to “Engaged” based on score.
- Suppress low-quality leads: Route “Cold” leads to nurture campaigns instead of sales.
Don’t get lost in automation land. Start simple, and only automate what actually saves you time.
Step 7: Revisit and tweak (seriously, don’t skip this)
Your first scoring model won’t be perfect, and that’s fine. Every few weeks:
- Look at which leads are converting.
- Ask sales which ones were worth talking to.
- Adjust your scoring as you learn.
If you set and forget, your scoring will get stale fast. Treat this as an ongoing experiment.
What to ignore (for now)
A few things you might be tempted to fuss over—but can safely put off:
- “AI-powered” scoring: Unless you have thousands of deals’ worth of data, you’ll get better results with simple, transparent rules you understand.
- Scoring every possible field: Stick to the basics. Overly complex models just confuse everyone.
- Trying to be perfect: A rough scoring model that gets you 80% of the way there is better than no scoring at all.
Wrapping up: Keep it simple and iterate
Automated lead scoring in Mylighthouse isn’t magic, but it does save you a ton of time and guesswork—if you keep it simple and review your results regularly. Start with a basic rule set, get feedback from the folks who actually work the leads, and don’t be afraid to change things up as you learn.
Over time, your lead scores will get sharper, your pipeline cleaner, and your sales team a little less grumpy. And that’s the goal.