B2B lead scoring: decide which enquiries to handle first
Build a readable grid with your sales team, keep profile and intent apart and check the enquiries you set aside before you automate anything.
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- Conversion
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- SBSébastien BalieuFounder of Numinam
A salesperson should be able to explain why one enquiry comes before another. Lead scoring makes that priority visible, based on criteria agreed with marketing. Qualifying the actual need still happens in the first conversation.
Start with a handful of deals you won, lost and turned down. Which profiles can you serve? Which signals came before a real sales conversation? Keep the good clients who did not look like the expected profile too.
How does lead scoring work?
Each contact gets a priority calculated from criteria decided in advance. The priority takes the form of a number of points, a letter or a category, and it triggers a specific action: assign the enquiry to a salesperson, send a useful reply, or keep the contact in follow-up.
The criteria fall into two families. Profile information comes from the form, the conversation or your CRM: sector, area, job title, type of project. Intent signals come from what the person does: a quote request, a reply to an email, a visit to the pricing page.
A scoring grid is a working hypothesis. It sums up what your salespeople have learned from their best clients, and you correct it when sales contradict the ranking.
Keep profile and intent apart
Profile describes how well the contact fits your offer: a need you cover, an area you serve, a type of company or a project constraint. Intent shows what the person wants to do now: ask for a quote, compare solutions or prepare a future project.
A very active contact outside your scope will never become a good prospect by reading more pages. A well-matched client who sends an explicit request should get an answer without first downloading several documents.
| Profile | Intent | Next step to consider |
|---|---|---|
| Need covered | Explicit sales request | Assign to a salesperson |
| Need covered | Still researching in general | Useful reply and suitable follow-up |
| Information missing | Explicit request | Human check before ranking |
| Need outside scope | Any intent | Point elsewhere or decline with a reason |
Keep these two dimensions in two separate fields, like the score and letter grade in Salesforce. A single number blends them: a contact with the ideal profile but little activity ends up with an average total and disappears into the list among lukewarm contacts. With two ratings, the salesperson can adjust the approach, following up gently with a good profile who is not yet engaged and calling straight away when an acceptable profile sends an explicit request.
Which criteria belong in the first grid?
Choose the ones that change what the team does next. If company size changes neither your ability to serve the client nor the next step, it does not need much weight.
On the profile side, the most useful criteria concern your ability to deliver. Does the need fall within your offer? Is the client in an area you serve? The contact’s job title counts too, with one caveat: in some purchases, the technical person who prepares the choice carries as much weight as the person who signs.
On the intent side, favour actions that take effort or commit the person. A meeting request, a precise question about lead times or a look at a case study close to their project says more than reading an article. Downloading a detailed comparison points to a more advanced project than downloading a list of general tips.
Start with few criteria, for example three for profile and three for intent. Add more when a real case shows that one is missing.
An example grid to adapt, with no benchmark value:
| Dimension | Signal | Suggested reading |
|---|---|---|
| Profile | Project within your scope | Good fit |
| Profile | Outside the area you actually serve | Out of scope, to confirm |
| Intent | Quote or meeting request | Strong |
| Intent | Project announced for later | Follow up according to the timeline |
| Data | Budget or role not given | Unknown, ask if needed |
If your CRM requires points, translate this grid into a simple scale. Check the threshold against real enquiries before you use it to assign them. Name the deciding signals, so that a pile of small interactions can never override a mismatch.
Turn the grid into points
Here is one possible translation of the previous table. The values are illustrations and only mean something once you compare them with your own sales.
| Signal | Points (example) |
|---|---|
| Project within your scope | +30 |
| Role that decides or prepares the purchase | +15 |
| Quote or meeting request | +40 |
| Reply to a sales email | +10 |
| Visit to the pricing page in the past month | +5 |
| Visit to the careers page | −20 |
| Outside the area you serve | Blocking, whatever the total |
To set the threshold, take your most recent enquiries. First rank them by hand with a salesperson, then calculate their scores, then look for the total that best separates the enquiries you would have wanted to handle quickly from the rest. If no threshold separates them, the grid is measuring the wrong signals.
Be wary of plain addition. A contact who is average on ten criteria can reach the same total as a contact who is excellent on the three deciding criteria and absent everywhere else, yet the second deserves a call and the first a simple reply. A trigger rule solves this case: good profile plus explicit request means immediate assignment, whatever the score.
A grid that is too fine creates another problem. With thirty criteria weighted to the exact point, nobody can explain why one contact gets 67 points and another 52. Salespeople then stop looking at the score and go back to their gut feeling.
Take points away: negative scoring
Some signals should lower the priority. A visit to the careers page may signal a job application. A competitor or supplier who fills in your contact form has no reason to jump ahead of your prospects.
Inactivity is part of scoring too. Set how long signals stay valid. An old request may deserve a lower priority today. An unsubscribe must stop the emails it covers, and the person may still have other commercial needs.
Keep a record of why points were removed. A salesperson must be able to rescue a contact downgraded by mistake, with the correction noted in the CRM.
Signals that can mislead you
A visit to the pricing page can mean a comparison, competitive research or a real need. An email open proves no buying intent. With Apple’s Mail Privacy Protection, an open can even be counted when the person never read the message. Give more weight to an explicit reply than to a series of behaviours you have to interpret.
A personal email address is no reason on its own to disqualify a freelancer. A technical role can influence the purchase without signing the contract. Treat missing information as unknown: it tells you nothing about the profile.
Who does what after the ranking?
Write a working agreement between marketing and sales: handover criteria, owner, response time and reasons for rejection. Define “qualified enquiry” and “opportunity” in your context, and write down a definition for MQL or SQL if you use them.
These two acronyms refer to two lifecycle stages of a contact. An MQL (marketing qualified lead) is a contact that marketing considers far enough along to hand over. An SQL (sales qualified lead) is a contact a salesperson has reviewed and accepted as an opportunity to work on. The gap between the two measures the quality of the handover.
The salesperson must see the information that produced the priority and be able to correct it. Plan for absences and for enquiries left without a status. The marketing automation guide covers this assignment in detail.
Set up lead scoring in five steps
- Bring marketing and sales together around real enquiries. Review deals you won, lost and turned down together. Note the signals that came before each signature, and write down the definition of a qualified enquiry.
- Choose between five and ten criteria. Keep the ones that change what happens to the enquiry next, and sort them into profile and intent.
- Rank by hand for a few weeks. A spreadsheet is enough. The salesperson notes whether the ranking matches their judgement after the call.
- Move the grid into the CRM. Show the score on the contact record and in the sales views, along with the signals that explain it.
- Review the grid after one sales cycle. Compare the priorities with the opportunities and signed clients, then adjust the criteria.
Predictive lead scoring: useful for a small business?
Some CRMs offer a score calculated automatically from the history of won and lost deals. The model looks for the characteristics signed clients have in common.
That calculation needs a large, steady history. The minimum volume depends on the tool, the quality of the records and the variety of your clients. Dynamics 365, for example, requires at least 40 qualified and 40 disqualified leads, closed during the model’s training period. With a few dozen deals a year, a manual grid is easier to explain and correct. The same precautions apply to chatbots that qualify enquiries: the tool applies criteria, and you still have to define them.
How do you know whether scoring helps?
Compare the ranked enquiries with the opportunities and clients after a relevant sales cycle. Analyse the rejections and reread a sample of the low-priority contacts. Without that second check, you will miss the good prospects you set aside.
If a salesperson is short of opportunities, check the traffic, the follow-up, the offer and the criteria before you touch the threshold. If the prospects ranked as priorities do not sign, the problem may also lie after qualification.
Before you build scoring into your tools, run the grid by hand on your most recent enquiries. Only collect in your forms the data that serves the next decision. The CRO guide covers measuring the rest of the journey.
If the site gets too few enquiries for the ranking to change anything, look first at the journey that leads to the form. The free audit starts there.
Frequently asked questions
What is the difference between an MQL and an SQL?
An MQL is a contact that marketing hands over because it meets the agreed criteria. An SQL is the same contact once a salesperson has reviewed and accepted it. Write both definitions into the agreement between your teams, along with the possible reasons for rejection.
How many criteria should a grid have?
Five to ten is enough to start. Beyond that, salespeople struggle to understand a score and stop trusting it. Add a criterion when a badly ranked enquiry shows that one was missing.
Do I need software for lead scoring?
No. A spreadsheet is enough to test the grid on your most recent enquiries. A CRM becomes useful when the volume makes manual ranking too slow, or when several people need to see the same priority.
How often should I review the grid?
After each sales cycle, and as soon as your offer, your area or your client base changes. Each time, reread a sample of the contacts ranked as low priority.
Does lead scoring make sense with few enquiries?
Yes, in a light form. With a few enquiries a week, a written definition of a qualified enquiry and one owner per contact cover the essentials. Points become useful when sorting by hand takes too long.
