Criteria for implementing
a lead scoring strategy
Criteria for implementing a lead scoring strategy
For any business, establishing an inbound marketing strategy essentially results from the need to attract as many leads as possible into the sales funnel. Mainly through the distribution of relevant and, above all, attractive content. Once this objective is achieved, it is all the more necessary to distinguish between leads already ready to purchase your product and those still in the solution research and comparison phase . Hence the favorable intervention of lead scoring.
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How to define lead scoring?
Lead scoring is generally defined as a marketing process, allowing each lead of a company to a quantitative value: that is to say a point or at least a score. In other words, a lead notation system, but how is it possible? This is carried out on the basis of different award criteria, such as the professional data of the prospect and especially its online behavior vis-à-vis the company. It is a whole system helping marketers and commercial in the management of prospects , particularly being able to meet their needs in a relevant way in order to make qualified leads.
Several lead scoring marketing strategies are implemented by online sales companies, but the most famous is this one, which is based on information from already existing customers to establish this lead scoring system. The principle would be to identify the common characteristics of these then isolate them from new leads. This will allow you to clearly determine which attribute to prioritize in your inbound marketing conversion process.
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What are the lead scoring criteria?
As previously stated, lead scoring is carried out on the basis of certain criteria specific to the main “buyer persona” profile established by the company. These criteria essentially revolve around the information you collect from leads. We include in particular:
- Company information (B2B marketing);
- Prospect demographics;
- The lead's online attitude;
- His commitment by email;
- The interest that the lead has in the company on social networks;
- Spam detection.
For a score between 0 and 100, each of these criteria must guarantee an irrefutable probability of purchase on the part of the prospect.
Socio-demographic data
When we talk about socio-demographic data, we mainly refer to age, sex, the region, the profession, the matrimonial situation of a person. In our case, it is information on your leads that you collect through the various forms present on your website. If this information allows you to determine your target and personalize your marketing campaign for sale, it must above all serve you in the segmentation of your CRM base.
Assuming that each of your products is geared towards a specific demographic segment, it is all the more important that you rule out any prospect who does not meet this target profile with a negative score. If, on the other hand, the information collected on a lead matches, rate it with positive points. You can even award extra points to prospects who fill out optional form fields.
Firmographic data
If your sales activity is categorized as b2b marketing, your target is undoubtedly a company like yours. Firmographic data can then be considered as the equivalent of socio-demographic data in b2c marketing. In order to qualify your target as a potential customer or not and to help you in your lead scoring process, you can include questions in your forms to collect as much information as possible. Whether in terms of size, type of activity, turnover, location... Enough to allow you to award points to leads who correspond to your target and exclude those who do not. not.
The behavior of the online lead scoring
It has been proven more than once that the attitude of a prospect on a site is very significant in terms of his purchasing decision. It would therefore be ideal to study the behavioral history of former prospects who became customers, that is to say how they behaved when faced with the different content on the site. For example, the offers that may have interested them, those they downloaded, the type and number of pages they visited or even the type of form filled out. All of this could help you in lead scoring. It would indeed be wise to award more points to prospects visiting high-yield pages and forms (price page, demo request, etc.). The same as for leads who visit your website 15 times while others 5 times in the same time.
However, for a lead who ceases all activity on your platform for a certain period of time, you should possibly consider deducting points from them. This behavior could be defined as a sudden disinterest of the prospect in your company.
The interest of the lead scoring for your business through email
Just like your content, email is a crucial point of your inbound marketing strategy; the interest your leads have in it is significant. However, simply subscribing to your newsletter is also not conclusive on the part of the lead in terms of purchase. It is above all through the email opening and click rate that one’s intentions become clear. Knowing who opens and reads the contents of each email and then clicks on the offer links should make it easier for all of your salespeople to choose qualified leads. They certainly won't have to waste time on false lead nurturing leads. This commitment is therefore a valid pretext for assigning prospects a positive rating score.
Lead scoring commitment to your social media strategy
If a lead has the habit of liking and then sharing your tweet and Facebook post content, it means that they are really interested in your brand on social networks. This is obviously a huge commitment to your business. Quantitative metrics (number of positive reactions from the prospect, shares, comments, etc.) above all represent good indicators for lead scoring. The score would be relatively higher for a qualified prospect who also has a strong influence on social networks. He could even later become an ambassador for your brand.
Scoring leads in the spam category
To top it all off, watch out for leads classified as “spam”. Makes you wonder how this is possible. There are indeed these prospects to whom you will systematically have to give a negative score. Those whose responses to forms do not fit with the established convention are the typical example. Prospect's first and last names without capital letters, the same for company names or other fields containing a succession of at least 4 letters according to the AZERTY provision.
The newly informed email addresses are also to be compared to those of your customers. For example, if your Inbound strategy targets a company as a prospect, it is obvious to expect a professional address like moc.esirpertne@elpmexe . When you are faced with Gmail and Yahoo addresses, it will suffice to reduce the number of score points compared to that of others.
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How to identify the right data for your lead nurturing marketing strategy?
Being given that you collect a fairly large amount of information, it remains to be seen how to assess their relevance in relation to your inbound marketing. The best would probably be to refer to your team of salespeople, to chat with your customers or to rest on analytics reports.
For sure, the solution would be ideally to combine these three possibilities. You will thus have all the necessary data in order to better capture the philosophy of each lead, from the content to the offers they consider attractive.
Consult the existing sales team
Depending on your inbound marketing tactic, your sales agents, namely your sales team, are those who are directly in contact with prospects, whether they become customers or not. They are therefore the best able to see the results of your inbound marketing. Thus, they can precisely inform you about the type of marketing content to put in place to facilitate your lead scoring.
In addition to the type of content or the type of offers likely to interest prospects, salespeople are able to inform you about the number of points to attribute to each type of content.
Talk to customers
Despite the fact that your sales agents know enough about the type of content favorable for converting prospects, customer opinions would also be welcome. Since they have experienced this during the sales cycle, their point of view is all the more useful. You may see a difference with the information from your sales agents.
Take into account data analysis reports
To support the information obtained so far from customers and salespeople, you can trust the test reports from analytics marketing. These thanks to marketing tools such as CRM HubSpot software allow you to concretely know which actions generate the most conversions during the sales cycle. It should be recalled that the content disseminated, even relevant, are not the only elements to take into account in your lead scoring process.
These reports can provide you far beyond the kind of relevant content, the most consulted pages for example.
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How to Determine Lead Score
There are several marketing methods dedicated to calculating prospect scores, but if you are just getting started with lead scoring, you might as well rely on the simplest one. This is essentially carried out step by step depending on other elements, we invite you to proceed as follows.
Calculate the conversion percentage of prospects into customers
Having its place above all in the reference in lead marketing, this rate represents the quotient of the total number of new customers by the total number of prospects generated.
Choose the attributes linked to your qualified lead profile
As already mentioned, you will need to rate your prospects in relation to the attributes that you consider subjective to the expected commercial result. It is therefore appropriate for you to choose these elements based on the information you may have received from your salespeople, your customers or the results of marketing analytics.
Calculate the individual conclusion rate of each chosen attribute
Especially since it influences your inbound marketing actions, it is absolutely essential to calculate the individual conclusion rate of the attributes selected and identified in each lead. Start by evaluating the number of prospects who become qualified leads and then customers based on the elements highlighted.
Compare the previous result to your overall conclusion percentage then finally award the points accordingly
The goal is to find the attributes whose individual conclusion rate is significantly higher than your overall conclusion rate and then award them points. Certainly, the values will be chosen on the fly, but make sure that there is some consistency. Let's take the example of an attribute worth a conclusion rate of 40% compared to your overall rate of 15%, you can rate each lead demonstrating this attribute by 25 points.
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More lead scoring methods
Apart from the basic marketing method of lead scoring previously highlighted, there are others which are based on very in-depth exploitation of data. Among others, logistic regression and predictive scoring.
Logistic regression in marketing
Since marketing data mining methods are more delicate, these require you to get to grips with Excel workbooks. Logistic regression indeed involves the creation of a formula (solution) aimed at precisely determining the possibility of any conversion of lead into customer. Taking into account all possible attribution elements, this method has the advantage of presenting real conclusion rates in a much more intuitive manner.
The forecast scoring leads
The advantages of the implementation of a lead scoring system are no longer refuted, even if it still remains a slight problem. Until then, we have erected a lead scoring notation system according to a manual approach. Which in the long run becomes weighing on marketing management because it remains a punctual and regular task.
The simple solution would then be to entrust this task to well advanced CRM software, such as Magileads. It is in this logic that the provisional lead scoring comes in. A simply automated system that saves you in time and efficiency. Magileads is therefore a CRM software by itself performing all the management functions of the lead scoring. Allowing your sales agents to focus only on leads likely to become customers.
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Criteria for implementing a lead scoring strategy
Expert references and credible studies of leads scoring
Recognized experts in leads scoring
David Raab (founder of Raab Associates): "Lead scoring must combine explicit data and implicit behavior for an optimal prediction" ( interview on Martech )
Trish Bertuzzi (author of "The Sales Development Playbook"): "A scoring leads cause 30% of commercial opportunities" ( Linkedin article )
Sammy Shreibati (Growth Manager at Gong.io): "AI now allows a dynamic scoring adjusted in real time" ( Podcast Revops )
Leads scoring case studies
Adobe : 27% increase in the conversion rate after revising scoring criteria ( Adobe Digital Insights study )
Forrester : 68% of B2B companies using the lead scoring see their marketing king increase ( report 2024 )
Direct testimonies
Marie Dupont, CMO at Scaleup Tech
“By integrating the commitment on webinars in our scoring, we identified 40% of additional qualified leads in 3 months. »»Ahmed Khan, dirty manager at SaaSfactory
“The scoring based on the pages visited has reduced our qualification time by 65%. »»Sophie Lambert, founder of Marketlead
“The addition of corporate size criteria boosted our conversion rate by 22%. »»Thomas Ruiz, Growth Hacker
“Our predictive model combines 12 criteria with variable weights - Result: +35% sales. »»Elodie Martin, VP Marketing B2B
“Behavioral scoring allowed us to eliminate 50% of false positives in our pipeline. »»
Stories and anecdotes of Leads scoring
The scoring error which cost $ 1M
A Scale-Up ignored the weak signals (repeated downloads of documentation) and missed a key account that signed in a competitor.
The case of the Dominant SCoring Leads, which has become a premium customer,
a contact noted "cold" for 8 months turned out to be a decision -maker after a change of position - saved by an automatic rescoring.
The unexpected impact of "careers" page visits
A company discovered that the leads consulting their job offers were 3x more likely to convert.
The startup which has too much automated
a too rigid scoring algorithm eliminated 70% of the good leads before a human sew them.
The turning point of the leads emotional scoring
The NLP analysis of emails allowed a company to identify the hidden frustration of leads ready to buy.
Approaches segmentation
Business type | Key criteria | Recommended tools |
---|---|---|
TPE | Contact frequency, Inteent Data | HubSpot, Mailchimp |
SME | Content commitment, | Pardot, ActiveCampaign |
Eti | CRM data, technologies | Marketo, Salesforce CDP |
Tech startup | Product Usage, API Calls | Intercom, Clearbit |
Diagram: ideal scoring lead process
[Data Collection] → [Criteria weighting] → [lead scoring] → [segmentation] → [action]
Questions/Answers on the SCORING leads
How to determine the right scoring criteria?
Analyze the common characteristics of your existing customers and test different models with cohorts.
Should we include demographic data?
Only if correlated with conversion - age matters less than the role in 80% of B2B cases.
What frequency to revise the model?
MINIMUM quarterly, or after any significant change in the offer or the market.
How to manage false positives?
Add negative criteria (eg "career" page visits) and minimum thresholds.
Should scoring be the same for all channels?
No - a lead from a webinar can have a threshold different from an organic lead.
Can we do without dedicated tools?
Possible for <100 leads/month, but automation becomes crucial beyond.
How to involve the sales teams?
Train them to interpret the scores and collect their feedback on the quality of the leads.
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