Send reps only the leads that are ready
AI lead scoring ranks every contact by real buying signals and explains why, so your team always works the hottest leads first.
What is lead scoring in MarketPadHQ?
Lead scoring in MarketPadHQ automatically ranks each contact by engagement, form submissions, and activity, so your hottest leads rise to the top with a clear breakdown of why — and can be routed to the right rep automatically.
Send reps only the leads that are ready
Score every lead on the signals that matter — email engagement, form submissions, and site activity — then route the hottest ones to the right rep automatically so nothing slips through the cracks.
- ✓Custom scoring rules
- ✓Automatic lead routing
- ✓Real-time score updates
What lead scoring actually solves
Most teams do not have a lead problem. They have an order problem. The leads are already in the database — sitting in a list of a few thousand contacts, in no particular order, where the person who filled in a pricing form ten minutes ago looks exactly like the person who downloaded a guide eighteen months ago and never came back.
Lead scoring fixes the order. Every contact carries a number that reflects how strong their buying signals are, and that number updates as they behave. The list your reps open in the morning is sorted by who is most likely to buy, not by who happened to be added most recently.
The practical effect is that the same team, working the same hours, spends those hours on better conversations. Nothing about the volume of leads changes. What changes is which ones get called first.
How the score is calculated
Scores are built from behaviour rather than from what someone typed into a form. Email engagement, form submissions, pages visited, how recently they were active, and how that activity is trending all contribute. A contact who opened three emails this week and returned to the site twice scores very differently from one who did the same things last spring.
You control the weights. If demo requests matter far more to your business than newsletter opens, you say so, and every score recalculates. The rules are yours; the arithmetic is automatic.
Recency is deliberately weighted. Buying intent decays, and a scoring model that ignores that will keep recommending contacts who have gone quiet.
Scores that explain themselves
A score with no explanation is a number a rep has to take on faith, and most will not. MarketPadHQ shows the reasoning behind each one in plain language — which signals pushed a contact up, which held them back, and what changed since last time.
That matters for two reasons. Reps trust a ranked list they can interrogate, so they actually work it. And when the model is wrong, you can see why it was wrong and adjust the weights, instead of quietly losing confidence in the whole system.
From score to action
A score is only useful if something happens when it moves. When a contact crosses your threshold, MarketPadHQ can route them to the right rep, add them to a sequence, or trigger a campaign — without anyone watching a dashboard for it.
This is where scoring stops being a reporting feature and starts being an operational one. The hot lead is assigned while they are still on the site, not on the following Monday when somebody exports a list.
What this looks like day to day
A small sales team with too many leads
Three reps and four thousand contacts. Scoring decides who gets called today, so the team stops working alphabetically and starts working by intent.
A long, considered purchase
Buyers research for weeks before they talk to anyone. Scoring surfaces the moment their activity picks back up, which is the moment a call is welcome rather than annoying.
Marketing proving its contribution
When every contact carries a score and a reason, it is straightforward to show which campaigns produced genuinely interested people rather than raw volume.
Re-engaging a stale database
A list nobody has touched in a year is not dead — it is unsorted. Scoring finds the few hundred contacts still showing signals and puts them at the top.
Questions, answered
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