A full CRM with no clear priority
There are dozens of open leads and the team calls whoever came in last, not whoever is most likely to buy.
AUTOMATION / LEAD SCORING
Lead scoring with AI. Not every lead
deserves the same call.
We score every incoming lead by how well it fits your ideal customer and how much buying intent it shows, so your team spends its time on whoever is actually going to buy.
FROM AN UNSORTED LEAD TO THE LISTIllustrated process
01 / 04
What makes a lead good.
We work with you to define which variables really matter for your business: sector, budget, urgency or behaviour.
02 / 04
The score takes shape.
We build the model using fit and behaviour data: pages viewed, forms filled, response time.
03 / 04
Shows up with the lead.
The score appears directly in your CRM, next to every lead, with no separate spreadsheets.
04 / 04
Reviewed against real closes.
We compare the score against what actually closed and refine the model with that data.
- Explainable scoring
- Ranked inside the CRM
- Fit and behaviour
- Model reviewed with data
WHAT WE DELIVER
A list that ranks
who to call first.
It's not a note or a separate spreadsheet: it's a score with its reason, built into where your team already works each lead.
- 01A scoring model based on fit and behaviour
- 02The score visible next to every lead in the CRM
- 03A clear reason explained behind every score
- 04The model reviewed against the month’s real closed deals
PHX / LEAD SCORE Calculated
Your ranking
How your lead list ends up sorted
- Fit
- Sector, size and budget
- Behaviour
- Pages, forms, response times
- Score
- A 0-to-100 rating with reason
- Model
- Reviewed against real closes
01
02
03
04
Does your case fit? We will tell you what can be done, at no cost and no commitment.
Prioritise my leadsWHEN IT MAKES SENSE
When the team calls
in order of arrival.
Long, expensive sales cycles
Every follow-up call costs real time, and chasing someone who was never going to buy gets very expensive.
Marketing generates, sales discards
Plenty of contacts come in from campaigns, but the sales team doesn’t know which ones are worth real time.
Deciding priority by gut feel
Each rep prioritises by their own judgement, and two people on the same team would call different leads first.
WHAT CHANGES IN PRACTICE
Lead scoring is about ranking the contacts you already have by likelihood to buy, not about generating or contacting anyone new.
A lead scoring system scores every contact using two kinds of variable: fit — sector, size, stated budget — and behaviour — pages viewed, forms filled, response time. With those variables it calculates a score and shows it next to the lead inside the CRM, so the list of open contacts appears already ranked by likelihood to buy, not by order of arrival.
Lead scoring doesn't replace sales judgement: it sorts the list before anyone uses it. The score always comes with the reason behind it — why that lead outscores another — so the team can trust the order without treating it as a black box. And the model isn't left fixed from day one: it gets reviewed against real closed deals from the first months, because what predicts well today can change as more data comes in.
PeopleThe sales team keeps the final say on who to call; the score only sorts the list before someone decides.
SEO and GEOWe explain which variables feed the score, in sentences an AI assistant can cite. This does not guarantee rankings or placements.
QUESTIONS BEFORE YOU START
The important part,
explained well.
Scoring a lead badly costs more than not scoring any of them. Here are the six things worth getting clear before letting a model sort your list.
What exactly does lead scoring do, and what does it not do?
Lead scoring scores the leads you already have based on their fit with your ideal customer and their real behaviour, and ranks them inside your CRM. It doesn't generate new leads or contact anyone: that's what lead generation or AI automation does. It also doesn't decide for your team who to close: it hands over the list already ranked, with the reason behind every score, and the final call on who to phone stays with sales.
Can the score get it wrong?
Yes, and it's important to say so clearly: no model predicts with absolute certainty who's going to buy. What it offers is a probability based on fit and behaviour data, more reliable than deciding by gut feel or order of arrival, but not infallible. That's why the model gets reviewed against real closed deals from the first months and adjusted when something stops predicting well, instead of being left fixed forever.
How long does it take to get the model running?
Between 2 and 3 weeks to define the criteria and build a first model with the data you already have in the CRM. The first version is a reasonable hypothesis, not a final model: it takes 1 to 2 months of real closed deals to calibrate it with your own data instead of generic assumptions. From there it gets reviewed periodically.
What happens if the model ranks a lead badly?
The team still sees every lead, ranked but never hidden, so nothing gets lost to a wrong score. When we detect that the model is systematically undervaluing a type of lead — say, a sector that actually converts well but scores low — we adjust the model's variables or weights using the real data that shows it. It's not about getting it right the first time, it's about correcting quickly when the data says to.
Which of my lead data gets used for scoring?
We use the data you already have in your CRM and on your website: contact source, pages viewed, forms filled in, and business details the lead themselves provided. No external databases are bought or cross-referenced to fill out the profile. We configure the model inside your own account, with your own access, respecting the legal basis and the processing notice that should already exist on your contact forms under GDPR.
What do I need to get started?
You need a CRM with some lead history and, ideally, some past closed deals: the more real cases there are, the better the model calibrates from the start. If you don't have history, it can still be built using fit criteria and refined later with the first closed deals. The first step is a one-hour working session to define with you what makes a lead good for your business.
NEXT STEP
Show us your lead list.
We’ll hand it back sorted.
We look at your CRM and the data you already have, and tell you which variables are worth scoring before touching anything.
I want to try my scoring The initial review is free, with no obligation.