Lead scoring: 6 criteria to prioritise for your marketing automation

When setting up an inbound marketing strategy, the first concern is to generate enough leads in its funnel.

But once these leads are acquired, then you need to find out who is really interested in your product or services, and who is discovering it for the first time.

What is lead scoring?

Lead scoring assigns a score to each lead (a certain number of points) according to the information collected via the forms as well as their behaviour and degree of involvement on your website.

This practice of lead scoring allows your salespeople to prioritise the best leads to be treated first in order to maximise the conversion rate of leads into customer and therefore the performance of your company. Example: You are not going to treat in the same order of importance a lead who visited 5 times your page of “prices” that a lead who arrives the first time on your site and looks at the page “About”.

Each company applies a different method of awarding points, but the most common is to rely on old lead data to create the most appropriate scoring system.

How? Begin by determining what your contacts who have become customers have in common and define the attributes of those who have not become so. Once you have analysed all the data collected for these two groups, you will be able to establish the attributes to favour.

Sounds pretty simple, doesn’t it? However, depending on your business model and the leads in your database, things can get complicated quickly.


6 criteria to use for your lead scoring

To make it easier for you, we have identified the different stages of this process, the data to be analysed, the method to set up to define the best attributes and the formula for calculating a score for your leads.

1 – Socio-demographic data

Does your ideal customer target (or buyer persona) match a typical profile? In this case, enter questions related to socio-demographic attributes in the forms of your landing pages. You will be able to check the information provided by your prospects to make sure they match your target audience.

These answers will also allow you to assign a lower score to prospects that do not match your targets, by removing points from those who are not part of the segment you are addressing.

If, for example, your products are only available in a well-defined geographic area, you could assign a negative score to any prospect including city, region, postal code, country etc. that does not fit this area.

If, however, some fields, such as the phone number for example, are optional on your form, you could grant additional points to the prospects who will have filled them anyway.

2 – Company information

If you are a B2B company, do you determine which companies you are targeting based on their size, type or sector of activity? Do you have a preference for the B2B or B2C sector?

You can also ask these kinds of questions on landing page forms to give points to prospects who are part of your target audience and remove those who are not.

3 – Online behaviour

The behaviour of a prospect on your site can tell you a lot about their intentions to buy. Analyse the leads that have become your customers. What offers did they download? How many have they downloaded? On which pages – and how many pages – did they go before becoming one of your customers?

The number and type of forms and pages are as important as each other. Here, you could assign a higher score to your contacts when they go to high-value pages (like the prices page), or when filling out forms close to the final decision (such as a demo request).

In the same vein, you could also assign a higher score to your contacts when they visited your site 30 times rather than 3.

What if your prospects change their behaviour over time? When a prospect no longer visits your site or stops downloading your offers, it may mean that they have lost interest or have left the company.

You could then withdraw points from prospects who have stopped visiting your site after a certain period of time, the duration of which – 10, 30 or 90 days – will depend on your reference sales cycle.

4 – Engagement by e-mail

That a contact chooses to subscribe to your newsletter does not give you any certainty as to his intentions of purchase. The opening and click rates will allow you to know their intentions.

Your sales team needs to know who opens your tracking emails, or who clicks on the promotional offers in your emails so they can focus on the contacts that are most involved.

In this case, you could assign a higher score to prospects clicking on links in high-value e-mails, such as demo requests.

5 – Social commitment

A prospect’s interest in your brand on social media also indicates how interested he is with your company. How many times did he click on a Tweet or Facebook post published by your company? How many times has he retweeted or shared your posts?

If your target audience is active on social networks, you might consider giving extra points to prospects who post a certain number of articles, or a number of subscribers.

6 – Detection of detractors

Last, but not least, you can also consider assigning negative scores to prospects who do not complete the forms well. Their names and surnames and/or company name were written in capital letters? Is a prospect called Chuck Norris?

Remember to check the type of email address used by your prospects by comparing them to those of your customers. For example, if your target audience is business, you could withdraw points from prospects who use a Gmail, Hotmail, and other addresses.


How to define the most promising criteria for your lead nurturing?

So you’re in possession of a huge amount of data that you now have to determine the degree of relevance. Should you ask the question to your sales team? Talk to your customers? Or do you dive into analysis reports?

In fact, we recommend that you combine these three elements. In fact, they will allow you to define the content most likely to convert your prospects into customers and, consequently, to assign a certain number of points to certain offers, certain e-mails, etc.

Ask your sales team

Your sales people are in the field and they are the ones who are directly addressing both prospects who will become customers and those who will not become clients. They usually get a pretty good idea of ​​the type of marketing content that favours conversion.

What kind of articles or offers do they like to send to prospects? Some may say, “Whenever I send such content or offers, it’s much easier to close a sale.”

For you, this information has no price and it is essential to identify these contents and offers to assign them a number of points accordingly.

Talk to your customers

If your salespeople think that certain content helps convert prospects into customers, the opinion of prospects who have actually experienced the sales process may differ, and it does not matter. You need to know each other’s points of view.

Ask some of your customers what they think motivated their decision to buy one of your products or services. To avoid limiting the scope of your analysis, consider including customers with a long sales cycle and those who were short.


Immerse yourself in analysis reports

Do not forget to support this research with concrete data from the analysis of your online marketing.

Establish an attribution report to determine which marketing efforts are generating conversion throughout the funnel. Beyond the content that allows you to convert prospects into customers, consider those that your visitors see before they become prospects.

Here, you could assign a number of points to visitors who download content whose history shows that it generates leads, and an even higher number of points to those who download one whose history shows that it generates customers.

To help you find valuable content on your site, you can also report on contacts. It will tell you how many leads and how much revenue has generated a particular marketing effort.

Offer downloads or clicks on links in email campaigns are good examples. Note activities that generate fast, slow conversions, etc. and award them points accordingly.

How to calculate the score of a lead?

There are several methods but we chose to explain the simplest below.

1 – Calculate the conversion rate between lead and customer for all your prospects

To do this, divide the number of new customers acquired by the number of leads generated and then use this conversion rate as a reference.

2 – Choose different attributes of customers that you consider to be very qualified prospects

These could be customers who have sought a free trial offer, operate in the finance industry, or have 10 to 20 employees.

The choice of attributes to include in your formula is similar to an art form. Rely on the conversations you had with your sales team and the analysis reports you studied, but use your common sense above all.

If you assign five different people to this task, you will get five different results, which is not a problem as long as the development of your score is based on the data we have presented so far.

3 – Calculate the lead-to-client conversion rate for each attribute you have selected

Once you’ve made the criteria choices, calculate the lead-to-customer conversion rate to get a better idea of ​​your conversion rate and performance.

4 – Compare the customer conversion rates of these attributes to your conversion rate to a global customer and award them points accordingly

Find attributes whose conversion rate to customer is significantly higher than your overall conversion rate. Then choose the attributes to which you want to award points and, if applicable, the number of points you intend to give them.

You can determine this number based on the difference between the individual conversion rates of the attributes you selected.

The choice of the number of points will probably be a little arbitrary but you must strive to remain as consistent as possible.

For example, let’s say your overall conversion rate is 1% and the “Demo Request” rate is 20%. The latter being 20 times higher than the overall completion rate, you could award 20 points to prospects who have this attribute.

Data mining technique

Easy and simple to set up, the method we have just defined is an excellent starting point. However, the safest approach from a mathematical point of view is to use a data mining technique such as linear logistic regression.

Data mining techniques are relatively complex. Linear logistic regression involves creating a calculation formula in an Excel file that will determine the likelihood that a prospect will convert to a customer.

This method, which is more precise than the previous one, adopts a global approach that takes into account the interactions between all the attributes of a customer (his sector of activity, the size of his business, or the fact that a request for a test has been formulated).


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