Today, lead scoring is the key ingredient that helps salespeople determine which leads are worth their time and effort. But here's the catch - when it comes to lead scoring, you need reliable and accurate data points to ensure your sales reps are going after leads that are most likely to convert.

That's where first-party data enters the picture. If used correctly, first-party data can be a goldmine for sales reps. It is the information that is collected directly from your users or leads. Since the data comes straight from your target user base, it can help you successfully uncover and convert the best leads.

However, you have many data points at your disposal when it comes to first-party data. From behavioral to billing data, you can use many sets of data to achieve your sales goals and improve your strategies. So, how do you decide the data points you should use for your lead-scoring efforts?

This article outlines the top five first-party data your sales team should use for lead scoring. Read on.

What Exactly is Lead Scoring?

Before we mention the top five first-party data points for scoring leads, we must understand the basics of lead scoring. Lead scoring is the method of figuring out which potential leads are more likely to be converted into paying users and prioritizing them accordingly.

The rule-based lead scoring process involves assigning a score or numerical value to each lead based on their behaviors and other factors. Based on these scores, sales reps can segment leads into different categories or levels, like cold, warm, and hot leads.

These scoring criteria help them focus company resources and their efforts on leads that are more likely to convert. It helps save time, improves the conversion rate, and boosts sales revenue.

Predictive lead scoring is an algorithm-based machine learning segmentation strategy that uses all historical customer data to continuously calculate a score for each lead in real-time.

Tools like Toplyne, continuously segment and score your leads to surface conversion and expansion pipeline in your CRM for your sales teams to go after. This helps your reps prioritize the right leads and save dozens of hours every sales cycle. The key difference between predictive lead scoring and other manual methods is that it can be automated.

Its fast-paced, self-learning algorithm is the basis for predictive segmentation’s speed and accuracy making it ideal for B2B companies. Read more about predictive lead scoring here.

Five KeyFirst-Party Data Points You Should Use in Lead Scoring

Let's look at the top five first-party data points that should be part of your lead-scoring strategy.

1. Product Usage Data

The data about how users use your product is a key first-party data point that should be a part of your lead scoring process. Analyzing product usage data helps companies determine which aspects of a product are most engaging to different segments of their audience. This also provides an insight into which steps are providing friction in the product flow.

By analyzing product usage data points like usage frequency, the amount of time a user spends on your product, etc., your sales teams can develop highly-tailored messaging and lead targeting strategies. By breaking down, how your free users interact with your platform, understanding when they typically need more advanced features, and which paid features appeal most to them, you can leverage strategies that increase conversions.

Product usage data is also precious when it comes to segmentation. By categorizing leads based on their level of engagement, you can provide them with relevant content and marketing materials. Doing so will help strengthen your connection with them and improve your chances of converting them successfully.

2. CRM Data

Your CRM system is a single source of truth for your sales reps, holding key information about qualified leads. It tracks their journey, from initial contact to post-purchase interactions and other touchpoints. By incorporating this CRM data into your lead scoring process, you can comprehensively understand each lead's journey and assess what your closed wons journeys look like.

CRM data also helps in identifying opportunities to upsell and cross-sell. By analyzing past purchases, subscribing and unsubscribing information, and recognizing patterns, your team can chart product flows and map out sequences to build an expansion pipeline.

3. Billing Data

While billing data may not be the most conventional method for lead scoring, it can significantly impact your understanding of potential users. This type of data provides valuable insights into a lead's ability to make purchases, their financial reliability, and their level of commitment to your product or service.

By examining the payment history, you can differentiate between high-value leads who consistently make timely payments and those who may be less likely to become long-term users. This information will enable your sales and marketing teams to focus on suitable leads and improve the sales process.

You can also enhance your pricing strategies by incorporating billing data into your lead-scoring process. You can tailor offers according to a lead's budget and financial capacity, making your offerings more attractive and improving the chances of converting leads successfully.

4. Demographic Data

Understanding your target users is essential for successful lead scoring, and demographic data is vital in making this happen. By leveraging demographic information collected through form fills on the website or through lead-magnets, like names, roles, job titles, etc., you can better understand different types of leads and tailor your messaging and offers to fit their requirements perfectly. This helps you ensure your interactions are as targeted to your ideal customer profiles (ICP) as possible.

Demographic data helps in effective user segmentation. By tapping into demographic data, you open yourself to a world of possibilities. You can design marketing strategies tailored to specific segments and buyer persona and provide them with content that speaks to them.

Not only this but demographic data also helps you interact with your prospects through the channels that are best suited for them. For example, it can inform you whether your leads prefer to be contacted on social media platforms like LinkedIn or by email. The more you know about your prospects, the more successful you can be at prioritizing the right ones, moving them through your sales funnel, and boosting conversions.

5. Firmographic Data

Firmographic data offers valuable insights about the companies your leads belong to, including their company name, company size, industry, location, and annual revenue. By analyzing firmographic data, you can pinpoint leads from industries that match your target market and products/services. This way, you can focus your sales efforts on high-quality leads. Not only this, but firmographic data also plays a vital role in B2B lead scoring campaigns.

By comprehending the traits of your target audience's company, your sales team can customize their pitch to tackle their industry's specific challenges and objectives. This personalized approach showcases an in-depth understanding of their requirements, priorities, and pain points establishing your brand as a reliable partner and enhancing the chances of a fruitful conversion.

Moreover, using firmographic data is highly beneficial in developing tailored and effective lead-nurturing strategies. By tailoring your message to match the specific attributes of a potential customer’s organization, you can enhance engagement and cultivate long-lasting relationships with your prospects.

Analyze Your Lead Scoring Models for Continued Success

Effective lead scoring doesn't have to be a guessing game anymore. With the help of first-party data, you can turn your strategy into a powerhouse of conversions. Data is your friend, and the five first-party data points mentioned above will give you the information you need to make intelligent decisions, target high-value leads, and enhance your customer’s journey. It goes a long way in improving your lead generation, lead nurturing, and marketing efforts.

Finally, the design and calibration of your lead scoring models are also pivotal to your success. Incorporate the five first-party data points mentioned above into your lead scoring system, and you will have an efficient, accurate setup that reflects your outreach and sales goals. While traditional lead-scoring is great at eliminating bad leads, it is terrible at finding good leads. Predictive lead scoring is what you need to smash that sweet, sweet quota.