First, what is lead scoring? It is a method to score leads based on general criteria and criteria specific to your business, often requiring a thorough analysis. Each criterion is associated with a certain weight; you get your lead scoring model from that. The main goal is to help prioritize potential leads based on their likelihood to convert and generate revenue.

In this playbook, we’ll focus mostly on B2B lead scoring, why it is important, how to leverage data enrichment as a key part of your lead scoring model, and share lead scoring best practices.

Why is lead scoring important to increase your deal closing rates?

Lead scoring can be relevant at almost every stage of the funnel.

First, it can help you generate more leads to contact. Whether you call them Marketing Qualified Leads or just MQLs, a lead scoring model will help you detect from a list of contacts who should be contacted even if they haven’t explicitly asked to be reached out to. This means that you don’t have to rely solely on demo requests and sign-ups, any lead you have with a high score can be worth a shot. This is especially true depending on the content that they see.

Any lead in the “to be contacted” pool doesn’t have the same value. Signs that usually lead to implementing a lead scoring model can be:

• Too many leads to handle for the number of sales reps - usually a good problem to have
• Hiring more people on the team but not seeing an increase in revenue
• Sales team complaining about the quality of the leads
• Lack of focus
• Discrepancy in conversion rates between reps
• Low conversion rates

That’s exactly what a lead scoring model will prevent. You will improve your team’s efficiency and focus.

Lead scoring best practices involve reaching out to everyone, but giving a different level of service. While an automated email sequence might do the job for low-quality leads, top leads are more likely to convert with multi-channel outreach including manual tasks. The higher the quality, the higher the personalization.

Your lead scoring software or homemade tool helps level the knowledge among the team. Indeed, your top sales reps might not see the value of a lead-scoring tool right away because they already know which profiles are a good fit for the company but it’s harder for newcomers. Moreover, lead scoring is not just about the lead’s profile and company, it should also consider the lead’s behaviors and patterns.

Scoring and prioritizing leads requires internal alignment, with at least sales and marketing.

A good way to start the conversation would be to look at data. Here are some questions to guide you:

• How many deals signed in the past six months fit our buyer persona and ideal customer profile?
• Are the deal values typically higher when we have an ICP fit?
• What is the journey for the deals we sign today? Spoiler - there is usually more than one but try to categorize as much as possible.
• Does it differ based on the deal value?
• Do we have content at each stage of the funnel?
• Did our last 10 customers consume any content?
• How many of our top 10 content consumers are clients?
• What is the probability that they become a client?
• What is the typical deal win rate?
• Does it differ based on the channel?

Don’t be afraid to dig deeper.

Maybe your attribution reports show that you have more leads coming from demo requests in terms of the number of deals won. However, looking at the annual contract value, you might find that deals closed after events usually have 50% higher ACV so any event-related action from prospects needs to have a lot more weight.

You will need to have input from your internal teams as well as customers and even prospects if you can to make sure you understand what leads to conversion and revenue.

Keep in mind that you have to start somewhere, you will need to do a lot of testing and adapt your lead scoring model along the way.

Maximize lead scoring with data enrichment

We’ll get straight into it and give some indications on the main groups of criteria for a lead scoring model: demographic, firmographic, psychographic, and behavioral.

The main demographic trait is the lead’s job title. Depending on your buyer persona, it can also involve the lead’s location, seniority, time in position or even age, gender, level of education, and income.

Firmographic means any data you can have on the company. It usually involves the company’s:

• Industry
• Type i.e. Public, NGO or Private
• Headquarters location
• Number of locations
• Number of employees
• Annual revenue
• Founding date
• Growth rate - general or within a specific department

Psychographic criteria are usually the hardest to find. They include anything related to the person’s beliefs, interests, lifestyle, brand loyalties… The most important part if you want to sell to them is related to their pain points and motivations. To get that information, you can rely on behavioral criteria that we will explain in a minute or you can also ask them directly in your demo form for example. 

How the lead interacts with your company is key. Below are some examples of behavioral criteria:

Website

• How often do they visit your website?
• How long do they stay on the website?
• Which pages do they see? Is it more awareness, consideration, or decision content?
• Have they downloaded any content?

Social media

• Do they follow your company page?
• Do they often like or comment on your company’s posts?

Event registration

• How many webinars have they attended?
• Have they attended any physical events?
• Purchase history: have they ever bought anything from you?
• Source of the lead: for example, a lead who requested a demo shows more intent than a lead who signed up for a webinar

Something to keep in mind when building your lead scoring model is that the lead’s score can also go down if they have red flags. Examples of negative scoring include:

• Far outside your target audience or industry
• Unsubscribed from your newsletter
• Negative review
• Multiple previous deals
• No shows on previous interactions

Once you’ve determined all the criteria that translate how a lead could convert for your funnel, you need to decide on a total score - 100 is a good one - and the weight associated with each criterion.

Not all of the data can be found online and sometimes even if it is online you cannot get it automatically in a non-expensive way so think about what you need to ask your prospect and leverage your forms. 

No matter your lead scoring model, you must test and iterate.

To test your model you can try calculating the score for your:

• Top 20 customers
• Last 20 customers
• Last 10 customers from each acquisition channel
• Top 20 content downloaders
• Top 20 event attendees

Guide to automate the lead scoring process with Captain Data

There are several steps along your funnel where Captain Data will be useful to score leads, especially when:

1. You’re analyzing all your data to build your model, you might find that your CRM is not that enriched. 
2. You’re applying your model to go from leads to qualified leads and realize you don’t have all the data
3. You’re scoring your incoming leads, from all acquisition channels and only have very limited information.

No matter the use case, you can see here that the key lies in the data.

Captain Data is integrated with Hubspot and Salesforce to get the data points you have, enrich the profiles and companies, and then push the data back to your CRM.

You can also use Make, Zapier, n8n, or our API directly if you have a different CRM or use a lead-scoring tool outside your CRM.

Below are useful workflows to help you get as much data as possible on your leads based on what you’re starting with.

• If you have nothing other than their full name and company name, you can Enrich leads from full name & company name
• If you have their email address, you can Enrich Email with Outlook & LinkedIn (People & Company)
• If you have their LinkedIn information, you can extract their profile with Extract LinkedIn People Profile or if you don’t have an email address for these leads yet, you can Enrich leads with email from LinkedIn profile

The same logic applies when enriching companies, you can start from the company’s:

• name only with Enrich a list of company names with LinkedIn
• Domain with Enrich a list of domains with LinkedIn
• LinkedIn page with Extract LinkedIn Company Profile

We’re releasing a new feature to have workflows triggered automatically within Captain Data thanks to Hubspot lists, please request a demo with us if you’re interested in getting all the details!

Le Wagon's case study

Le Wagon is a growing B2C coding school whose challenge was to expand with a new B2B offer. Having had already quite a lot of batches, they were sitting on a pile of gold that was gathering dust.

Captain Data helped Le Wagon reclaim power over its CRM by enriching and qualifying more than 20,000 contacts for GDPR-compliant B2B outbound.

Jean Mennesson, Business Outbound Growth Manager, states that:

“It’s turned our alumni list into an actual sales tool. Before we really weren’t able to use one of our biggest potential sources of positive leads. Now we actually have the info we need to start effective sales conversations with the right people.”

Discover the details of their success story here.

Wrapping-up

Implementing a lead scoring model is a critical first step in prioritizing leads and enhancing your sales process. However, it's not enough on its own. While high-scoring leads should be your primary focus, don't neglect the colder leads; they still hold potential opportunities. Furthermore, predictive lead scoring relies on historical data and may not reflect changes in your strategy or market conditions.

A robust lead scoring model saves time, reduces lead generation costs, and improves alignment between your sales and marketing teams. By lowering your Customer Acquisition Cost (CAC) and boosting productivity, you ensure better use of resources and more effective sales efforts. Remember, continuous testing and iteration are essential to adapt your model and stay ahead of changes in your business environment!

Start enhancing your leads with Captain Data today.