What is lead scoring?

Lead scoring is a method used by companies to rate prospects (leads). Leads are assigned a score based on various criteria. The aim is to prioritize leads so that the sales team knows which prospects are most likely to convert into customers.

This upstream lead scoring system enables the sales team to concentrate on quality leads, and therefore not waste time on leads with a low probability of conversion, thus increasing the overall conversion rate.

Similarly, lead scoring enables better communication between marketing and sales teams by establishing common lead evaluation criteria.

What data are used in lead scoring?

Global lead scoring includes demographic data such as age, gender, job title, industry, company size, etc., firmographic data such as company sector, company size, growth…) as well as information on lead behavior, such as website interactions, e-mail opens, content downloads and webinar participation.

Similarly, this system takes into account leads' engagement with the company's social networks (shares, comments, etc.).

Finally, BANT data is also contemplated, concerning budget, authority, need, and temporality (or timing) relative to the purchase.

Prerequisites for using lead scoring

Companies using or wishing to use lead scoring need to demonstrate a number of prerequisites, such as a complete and up-to-date database of lead information :

• They must also have effective marketing automation tools, and have established a list of criteria for a “good” lead.

• Lead scoring mobilizes both marketing and sales teams. But it may be necessary to involve data analysts as well as management. Each team plays a different role.

• As a general rule, the marketing team is in charge of setting up and managing the lead scoring system.

• The sales team is responsible for feedback on lead quality and the effectiveness of the scoring system itself.

Manual Lead Scoring

Manual prospect scoring is based on the evaluation of prospects by individuals, according to criteria pre-established by marketing.

These criteria are generally derived from persona data and customer behavior. Depending on the number of points awarded to each prospect on the basis of these criteria, a “score” is established. When scores exceed a certain threshold, leads are forwarded to sales via a personalized CRM field or alerts.

✅ Benefits of manual lead scoring

This traditional approach to lead scoring allows a certain degree of flexibility in terms of customization, since it's up to the marketers to establish all the scoring criteria. They can adapt them to the needs and particularities of their company.

❌ Disadvantages of manual lead scoring

The main problem with this system is that this manual rating, which is therefore carried out by human beings, is subject to their judgment(s) or bias, and therefore loses objectivity. This is because each individual understands, appreciates and prioritizes the criteria for comparing prospects differently.

Another point to bear in mind is that this approach can mobilize significant resources for companies, due to the often increasing number of prospects (in particular, the need for skilled labor).

The time it takes to set up manual lead scoring will vary according to various factors, such as the complexity of the criteria, the availability of data and the size of the team responsible for implementing it. In general, it can take from a few weeks to a few months, depending on the sophistication of the system and the availability of resources.

The time required for monthly updates also depends on the volume of data collected, the way it is processed, and the frequency with which scoring criteria need to be adjusted . A manual lead scoring system will take a few hours a month to a full day to update, depending on the complexity of the process and the volume of data to be processed.

AI Lead Scoring

AI lead scoring uses machine learning algorithms to analyze large quantities of lead data, such as historical data, online behavior, reactions and interactions with the company.

✅ Benefits of AI lead scoring

Unlike manual lead scoring, this system tends to reduce the risk of bias and subjectivity, as it is based on data rather than human judgment.

What's more, AI lead scoring enables large volumes of leads to be processed efficiently and in a short space of time, making it more compatible with companies with extensive lead generation activities.

Another advantage of AI lead scoring is that it can be adapted and improved by processing an increasing amount of data, enabling the system to be optimized on an ongoing basis.

Finally, AI can be added to existing CRM systems used by companies to better automate the evaluation process and streamline lead management.

❌ Disadvantages of AI lead scoring

AI lead scoring is a recent development, but it is not without its advantages, and there is a risk of bias in certain cases, for example if the algorithm has been trained on data that is not representative of the diversity of potential customers (unintentional discrimination).

In conclusion, while manual lead scoring offers both flexibility and personalization of the process, AI lead scoring offers objectivity combined with the possibility of continuous process improvement. Today, many companies actually use the two processes in a complementary way, using AI, for example, to perfect the results provided by the manual system.

Conclusion

In conclusion, the choice between manual lead scoring and AI lead scoring depends on the company's needs. Manual lead scoring offers flexibility and personalization, but can be biased and resource-intensive. AI lead scoring, on the other hand, is more objective and efficient, able to process large amounts of data quickly, although it can be biased if the training data is not representative (garbage in -> garge out).