Practitioner's Guide
Lead Scoring in Paminga
A practical guide to understanding contact, activity, and engagement scoring in Paminga — and how to activate on it once a record shows real fit, awareness, and intent.
Why Models Lose Credibility
Scoring works when the model separates fit, action, and intent.
Paminga surfaces three separate score types, each measuring a different dimension of a contact's relationship with your brand. That separation keeps your model from overvaluing a single signal and gives your team clearer context before sales gets involved.
Measure who they are
Title, company size, location, persona tier, and other fields that tell you whether the person fits your ICP.
Measure what they did
Form fills, event registration, account sign-up, email clicks, and other actions that show awareness.
Measure what it meant
Event attendance, repeat content visits, portal logins, conversions, and other signals of deeper intent.
Key principle
Contact score should accelerate, not qualify. A high-fit ICP record should move through your funnel faster than someone with an unknown title and a personal email, but demographic fit alone should never be enough to MQL.
Contact Score
Your demographic layer answers: is this person a fit?
Contact score is built from who the person is, not what they have done. Typical inputs include job title, persona tier, company size, industry, geography, region, and any other field that helps identify fit.
Use subtractors to keep the total honest.
If a contact matches criteria that signals they are not a fit — wrong region, irrelevant industry, student email — subtract points. Without subtractors, the wrong record can still accumulate points and appear qualified.
Use required rules when fit is non-negotiable.
A required rule means the condition must be true for the contact to qualify at the threshold level, regardless of total score.
Example
You require job level to be Director or above. A contact who hits the full point threshold as an individual contributor never qualifies, no matter how engaged they are. Required rules keep the score from being gamed by volume alone.
Activity and Engagement
Activity says they did something. Engagement says it mattered.
Activity score is the action layer: broad, high-volume, and relatively low-signal on its own. Engagement score captures the quality and depth of interaction, not just that the interaction happened.
Registered for a webinar
Attended the webinar
Received a newsletter
Clicked every newsletter for six months
Clicked a link in an email
Clicked a link and converted on the destination page
Signed up for a portal account
Logged into the portal 5+ times in 30 days
Run frequency matters
Each activity rule has a configurable run frequency. Set a rule to fire automatically when the qualifying condition is met, or throttle frequency — for example, award email click points no more than once every two hours — to avoid inflated scores from one hyperactive session.
Thresholds and Actions
Scoring becomes useful when it drives action.
Once contacts accumulate scores, Paminga lets you define what happens when they hit certain levels. You can set an MQL threshold for total score, then add minimum score requirements per category so a contact cannot qualify entirely on demographic fit with no engagement.
Example threshold
MQL threshold: 40 points total. Minimum requirements: Contact score ≥ 10, Activity score ≥ 5, Engagement score ≥ 15. A contact with 35 demographic points and 5 engagement points does not qualify because the engagement minimum is not met.
Global Action
Any record that hits the threshold, such as enrolling in a nurture workflow when engagement score reaches 15.
Use when the same follow-up should happen for every qualifying record.
Conditional Action
Records that meet the threshold and an additional condition, such as creating a Salesforce task if engagement reaches 15 and last activity was 90+ days ago.
Use when the next step depends on context beyond the score itself.
Actions can move work forward.
Enroll in a workflow, create a CRM task, send an internal notification, add to a paid ads audience, or sync a field to your CRM.
Falling below a threshold can matter too.
If engagement drops beneath a certain level, you can automatically add the contact to a re-engagement or nurture sequence.
Building a Model That Holds Up
Pressure-test the math before you activate.
A lead scoring model is only as good as the math underneath it. Before launching, map out scoring rules and calculate how many realistic activity and engagement signals a contact would need to hit your MQL threshold.
Max sums per category
Know how much each category can contribute so one dimension does not overwhelm the others.
Build in decay
Let scores cool as intent ages, especially when a contact stops engaging.
Subtract intentionally
Use negative signals to prevent poor-fit records from looking qualified.
Pressure test
High-value actions like demo requests or live event attendance should carry more weight, but they should be the exception. If your model generally needs only one or two interactions to qualify a contact, your threshold is probably too low or your point values are inflated.
Worked Example
What good looks like in practice
A Director of Marketing Ops at a mid-market SaaS company submits a form on a migration guide page. It is a meaningful signal — right persona, right content, right moment — but it is not enough on its own. The journey to MQL combines fit, activity, and repeated engagement.
Contact Score
20 points- Director-level title in a priority persona tier: +15 pts
- Company size in target range: +10 pts
- Personal email domain: −5 pts
Activity Score
12 points- Downloaded the migration guide: +5 pts
- Registered for a webinar: +5 pts
- Clicked an email link, capped at once per two hours: +2 pts
Engagement Score
18 points- Attended the webinar live: +8 pts
- Visited the platform comparison page three times in 14 days: +6 pts
- Clicked an email link and converted on a second asset: +4 pts
This contact qualifies because the model confirms ICP fit, awareness of Paminga, and active engagement. A global action can enroll them in a sales-touch workflow, while a conditional action can create a Salesforce task with context for the assigned rep.
Final thought
Lead scoring works when it reflects how your team actually thinks about buyers: not just who they are, but what they have shown you. Start simple, pressure-test your thresholds, and let the model evolve as you learn what actually predicts a good conversation.
Lead Scoring in Paminga
See how the scoring engine handles real MOps complexity.
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