Lead scoring: How to Prioritize and Segment Your Prospects Based on Their Interest and Fit

1. Introduction to Lead Scoring

lead scoring is a method of ranking your prospects based on their level of interest and fit for your product or service. It helps you to prioritize and segment your leads, so that you can focus your time and resources on the most qualified ones and increase your conversion rates. Lead scoring can also help you to align your sales and marketing teams, as they can agree on a common definition of a qualified lead and a consistent process of nurturing and following up with them.

There are different ways to approach lead scoring, but the most common one is to assign points to your leads based on two main criteria: explicit and implicit. Explicit criteria are the information that your leads provide you through forms, surveys, or conversations, such as their name, company, industry, role, budget, etc. Implicit criteria are the information that you infer from their behavior, such as their website visits, email opens, clicks, downloads, social media engagement, etc. By combining these two types of criteria, you can create a comprehensive profile of your leads and score them accordingly.

Here are some steps that you can follow to create and implement a lead scoring system for your business:

1. define your ideal customer profile (ICP) and buyer personas. Your ICP is a description of the type of company that is most likely to buy from you, based on factors such as size, revenue, location, industry, etc. Your buyer personas are the representations of the individuals who are involved in the buying decision, based on factors such as role, goals, challenges, pain points, etc. These will help you to identify the explicit criteria that are most relevant for your lead scoring.

2. Identify the key indicators of interest and engagement. These are the implicit criteria that show how your leads interact with your brand, content, and offers. You can use tools such as Google analytics, email marketing software, CRM, etc. To track and measure these indicators. Some examples of indicators are: number of website visits, pages viewed, time spent, bounce rate, email opens, clicks, replies, downloads, registrations, etc.

3. Assign points to each criterion based on its importance and impact. You can use a scale of 1 to 10, or any other range that suits your needs. The higher the points, the more valuable the criterion is for your lead scoring. For example, you can assign 10 points to a lead who fills out a contact form, 5 points to a lead who downloads a white paper, and 1 point to a lead who views your homepage. You can also use negative points to deduct points from leads who are not a good fit or show low interest, such as unsubscribing from your email list, visiting your competitors' websites, etc.

4. Set a threshold for qualifying leads. This is the minimum number of points that a lead needs to have in order to be considered as a qualified lead and ready to be passed on to the sales team. You can use a simple formula such as: threshold = average lead score + standard deviation. Alternatively, you can use your historical data and conversion rates to determine the optimal threshold for your business.

5. test and refine your lead scoring model. Once you have your lead scoring system in place, you need to monitor its performance and effectiveness. You can use metrics such as lead quality, lead quantity, conversion rates, sales cycle length, etc. To evaluate your lead scoring model. You can also get feedback from your sales and marketing teams to identify any gaps or issues. Based on your findings, you can adjust your points, criteria, and threshold as needed to improve your lead scoring accuracy and alignment.

2. Understanding the Importance of Prioritizing Prospects

One of the most important aspects of lead scoring is understanding how to prioritize your prospects based on their interest and fit. Prioritizing prospects means ranking them according to their likelihood of becoming customers and their potential value to your business. By doing so, you can focus your time and resources on the most promising leads and avoid wasting effort on those who are not ready or suitable for your offer. In this section, we will explore the benefits of prioritizing prospects, the criteria for doing so, and some best practices for implementing a lead scoring system.

Some of the benefits of prioritizing prospects are:

- increased conversion rates: By targeting the prospects who are most interested and qualified for your product or service, you can increase the chances of converting them into customers. You can also tailor your marketing messages and sales pitches to their specific needs and pain points, making them more relevant and persuasive.

- Improved efficiency and productivity: By focusing on the prospects who are most likely to buy, you can save time and money that would otherwise be spent on chasing low-quality leads. You can also allocate your resources more effectively and optimize your marketing and sales processes.

- enhanced customer satisfaction and loyalty: By delivering value and solving problems for your prospects, you can build trust and rapport with them. You can also nurture them with relevant and timely content and offers, keeping them engaged and loyal to your brand.

To prioritize your prospects, you need to establish some criteria for measuring their interest and fit. Interest refers to how engaged and responsive a prospect is with your marketing and sales activities, such as opening emails, visiting your website, downloading your content, requesting a demo, etc. Fit refers to how well a prospect matches your ideal customer profile, such as their industry, company size, budget, location, etc.

There are different ways to assign scores to your prospects based on these criteria, such as:

- Explicit scoring: This involves assigning points to your prospects based on the information they provide or you collect about them, such as their job title, company name, revenue, etc. For example, you can give more points to a prospect who is a decision-maker in a large enterprise than to a prospect who is an individual contributor in a small business.

- Implicit scoring: This involves assigning points to your prospects based on their behavior and interactions with your marketing and sales channels, such as their email open rate, website visit frequency, content consumption, etc. For example, you can give more points to a prospect who has visited your pricing page multiple times than to a prospect who has only viewed your homepage once.

- Predictive scoring: This involves using advanced algorithms and data analysis to predict the likelihood and value of a prospect becoming a customer, based on their demographic and behavioral attributes and historical data from your existing customers. For example, you can use machine learning to identify patterns and correlations between your prospects' characteristics and their conversion rates, and assign scores accordingly.

Some best practices for implementing a lead scoring system are:

- Define your goals and objectives: Before you start scoring your prospects, you need to have a clear idea of what you want to achieve and how you will measure your success. For example, you can set goals such as increasing your conversion rate by X%, reducing your sales cycle by Y days, or generating Z% more revenue from your leads.

- Segment your prospects: Not all prospects are the same, and you need to account for the differences in their needs, preferences, and behaviors. You can segment your prospects based on various criteria, such as their industry, persona, stage in the buyer's journey, etc. And assign different scores and weights to each segment. For example, you can give more weight to the fit score for a prospect who is in the awareness stage than to a prospect who is in the decision stage, as the latter is more likely to be interested in your offer regardless of their fit.

- Test and refine your scoring model: Lead scoring is not a one-time activity, but a continuous process of improvement and optimization. You need to test your scoring model regularly and compare it with your actual results, such as your conversion rates, sales revenue, customer retention, etc. You also need to update your scoring model as your market, product, and customer base change, and as you learn more about your prospects and their behavior. For example, you can use A/B testing to compare different scoring methods and see which one performs better, or you can use feedback from your sales team to adjust your scoring criteria and thresholds.

3. Defining Interest and Fit in Lead Scoring

One of the key challenges in lead generation is how to identify and prioritize the most qualified prospects for your business. lead scoring is a method of assigning numerical values to each lead based on their level of interest and fit for your product or service. By using lead scoring, you can segment your leads into different categories, such as hot, warm, or cold, and focus your marketing and sales efforts on the ones that are most likely to convert. In this section, we will explain how to define interest and fit in lead scoring, and why they are both important factors to consider.

Interest and fit are two dimensions of lead quality that measure how well a prospect matches your ideal customer profile and how engaged they are with your brand. Interest refers to the degree of interaction and responsiveness that a lead has shown towards your marketing campaigns, content, or website. Fit refers to how closely a lead matches your target market, buyer persona, or industry. Both interest and fit can be measured using various criteria, such as:

1. Demographic data: This includes information such as age, gender, location, income, education, job title, company size, industry, etc. Demographic data can help you determine if a lead fits your target market and buyer persona, and how likely they are to afford and use your product or service. For example, if you sell a B2B software solution for small businesses, you might assign a higher fit score to leads who work in small companies in your industry, and a lower fit score to leads who work in large corporations or unrelated sectors.

2. Behavioral data: This includes information such as website visits, email opens, clicks, downloads, form submissions, social media engagement, webinar attendance, etc. Behavioral data can help you determine how interested and active a lead is in your marketing activities and content, and how far they are along the buyer's journey. For example, if you offer a free trial of your product, you might assign a higher interest score to leads who have signed up for the trial and used it frequently, and a lower interest score to leads who have not taken any action after receiving your email invitation.

3. Psychographic data: This includes information such as pain points, challenges, goals, motivations, preferences, values, etc. Psychographic data can help you understand the needs and wants of your leads, and how your product or service can solve their problems or fulfill their desires. For example, if you sell a fitness app, you might assign a higher fit score to leads who have expressed a clear goal of losing weight or improving their health, and a lower fit score to leads who have not indicated any specific fitness objectives.

By combining interest and fit scores, you can create a lead scoring matrix that ranks your leads into different categories, such as:

- A-Leads: These are your ideal prospects who have a high interest and a high fit for your product or service. They are ready to buy and should be contacted by your sales team as soon as possible.

- B-Leads: These are your qualified prospects who have a high interest or a high fit for your product or service, but not both. They are interested in your offer, but may need some more nurturing or education before they are ready to buy.

- C-Leads: These are your unqualified prospects who have a low interest and a low fit for your product or service. They are not likely to buy from you and should be removed from your database or transferred to a different marketing campaign.

- D-Leads: These are your dormant prospects who have a low interest or a low fit for your product or service, but not both. They are not engaged with your brand, but may have some potential to become qualified leads in the future. They should be re-engaged with relevant and personalized content or offers.

By defining interest and fit in lead scoring, you can prioritize and segment your prospects based on their quality and readiness to buy, and optimize your marketing and sales strategies accordingly. Lead scoring can help you increase your conversion rates, revenue, and customer satisfaction, and reduce your cost per lead, sales cycle, and churn rate.

4. Key Factors to Consider in Lead Scoring

lead scoring is a process of assigning numerical values to your prospects based on their interactions with your brand, their profile information, and their stage in the buyer's journey. By doing so, you can prioritize and segment your prospects based on their interest and fit for your product or service. Lead scoring helps you to focus your marketing and sales efforts on the most qualified leads, increase your conversion rates, and optimize your resources. But how do you decide what factors to consider in lead scoring? Here are some key factors that you should take into account:

1. Behavioral factors: These are the actions that your prospects take on your website, social media, email, or other channels. They indicate the level of interest and engagement that your prospects have with your brand and your offer. Some examples of behavioral factors are:

- Visiting your pricing page

- Downloading your e-book or whitepaper

- Signing up for a free trial or a demo

- Opening or clicking your email

- Following or mentioning you on social media

- Filling out a contact form or a survey

- Watching your webinar or video

- Reading your blog posts or case studies

- Requesting a quote or a proposal

- Referring a friend or a colleague

- You can assign different scores to different behaviors based on their relevance and importance. For instance, requesting a quote might have a higher score than opening an email, as it shows a higher intent to buy.

2. Demographic factors: These are the personal and professional attributes of your prospects, such as their name, age, gender, location, industry, job title, company size, revenue, etc. They indicate the level of fit and alignment that your prospects have with your ideal customer profile. Some examples of demographic factors are:

- Working in your target industry or niche

- Having a decision-making role or authority

- Having a budget or a need for your solution

- Matching your buyer persona or customer segment

- Being located in your target geographic area or market

- Having a similar or complementary use case or problem

- You can assign different scores to different demographics based on their relevance and importance. For example, working in your target industry might have a higher score than being located in your target area, as it shows a higher alignment with your value proposition.

3. Temporal factors: These are the timing and frequency of your prospects' interactions with your brand, such as their recency, duration, and cadence. They indicate the level of urgency and readiness that your prospects have to move forward in the sales cycle. Some examples of temporal factors are:

- Visiting your website or landing page recently

- Spending a long time or a short time on your website or landing page

- Interacting with your brand or offer frequently or infrequently

- Responding to your email or call quickly or slowly

- moving through your sales funnel or stages rapidly or slowly

- You can assign different scores to different temporal factors based on their relevance and importance. For example, visiting your website recently might have a higher score than visiting your website frequently, as it shows a higher urgency to buy.

These are some of the key factors that you should consider in lead scoring. However, you should also keep in mind that lead scoring is not a one-size-fits-all approach. You should customize your lead scoring model based on your business goals, your industry, your product or service, your buyer's journey, and your data. You should also test and optimize your lead scoring model regularly to ensure its accuracy and effectiveness. By doing so, you can leverage lead scoring to prioritize and segment your prospects based on their interest and fit, and increase your chances of closing more deals.

5. Implementing a Lead Scoring System

One of the most important steps in any lead generation strategy is to implement a lead scoring system. Lead scoring is a method of assigning numerical values to each lead based on their interest and fit for your product or service. By scoring your leads, you can prioritize and segment them according to their readiness to buy, their potential value, and their likelihood to convert. This way, you can focus your marketing and sales efforts on the most qualified and profitable leads, and avoid wasting time and resources on the ones that are not.

There are different ways to implement a lead scoring system, depending on your business goals, your industry, and your target audience. However, some common best practices and steps are:

1. Define your ideal customer profile (ICP). Your ICP is a description of the type of customer that is most likely to benefit from your solution, and that you want to attract and retain. Your ICP should include demographic, firmographic, behavioral, and psychographic characteristics, such as age, location, industry, company size, budget, pain points, goals, challenges, preferences, etc. You can use your existing customer data, market research, surveys, interviews, and other sources to create your ICP.

2. Identify the key indicators of interest and fit. Based on your ICP, you should determine the factors that indicate how interested and how fit a lead is for your product or service. These factors can be divided into two categories: explicit and implicit. Explicit factors are the ones that the lead directly provides, such as their name, email, job title, company, industry, etc. Implicit factors are the ones that you infer from the lead's behavior, such as their website visits, email opens, content downloads, webinar attendance, social media engagement, etc. You should assign different weights to each factor, depending on how important and relevant they are for your business.

3. Set up your scoring criteria and scale. Once you have identified the key indicators of interest and fit, you should define how to score each lead based on these factors. You should use a consistent and transparent scoring system, such as a numerical scale from 0 to 100, or a letter grade from A to F. You should also establish the thresholds and ranges for each score, such as 0-25 for cold leads, 26-50 for warm leads, 51-75 for hot leads, and 76-100 for sales-ready leads. You should also decide how to handle negative scores, such as deducting points for unsubscribing, bouncing, or being unresponsive.

4. Test and refine your scoring model. After setting up your scoring criteria and scale, you should test your scoring model on a sample of your leads, and compare the results with your actual sales outcomes. You should analyze how well your scoring model predicts the lead's stage in the buyer's journey, their likelihood to convert, and their lifetime value. You should also solicit feedback from your sales team, and see how they use and benefit from the scoring system. Based on your findings, you should adjust and optimize your scoring model, and repeat the testing process until you achieve the desired accuracy and performance.

5. Monitor and update your scoring system. Your lead scoring system is not a one-time project, but a dynamic and ongoing process. You should regularly monitor and evaluate your scoring system, and update it as needed. You should consider factors such as changes in your market, your product, your customer behavior, your competitors, your goals, and your data quality. You should also use tools and technologies, such as CRM, marketing automation, analytics, and AI, to automate and enhance your scoring system, and to integrate it with your other marketing and sales activities.

Implementing a lead scoring system can help you improve your lead generation strategy, and increase your conversion rates, revenue, and customer satisfaction. By following these steps and best practices, you can create a customized and effective scoring system for your business, and gain a competitive edge in your market.

6. Best Practices for Segmenting Prospects

Segmenting prospects is a crucial step in lead scoring, as it allows you to group your leads based on their characteristics, behaviors, and needs. By segmenting your prospects, you can tailor your marketing and sales strategies to each segment, increasing your chances of converting them into customers. Segmenting prospects also helps you prioritize your leads, as you can assign different scores to each segment based on their potential value and readiness to buy. In this section, we will discuss some of the best practices for segmenting prospects, and how they can help you improve your lead scoring process.

Some of the best practices for segmenting prospects are:

1. Use both demographic and behavioral data. Demographic data refers to the basic information about your prospects, such as their name, location, industry, company size, job title, etc. Behavioral data refers to the actions and interactions that your prospects have with your brand, such as their website visits, email clicks, content downloads, social media engagement, etc. By using both types of data, you can create more accurate and comprehensive segments that reflect your prospects' interests and fit.

2. Use dynamic segmentation. Dynamic segmentation means that your segments are updated automatically based on the changes in your prospects' data. For example, if a prospect downloads a white paper from your website, they can be moved from a cold segment to a warm segment, or if a prospect requests a demo, they can be moved from a warm segment to a hot segment. Dynamic segmentation helps you keep your segments relevant and responsive, and avoid missing out on any opportunities.

3. Use multiple criteria for segmentation. Depending on your business goals and target audience, you may want to use different criteria for segmenting your prospects. For example, you can segment your prospects by their industry, product interest, pain points, budget, purchase stage, etc. By using multiple criteria, you can create more specific and targeted segments that address your prospects' needs and challenges.

4. Use negative segmentation. Negative segmentation means that you exclude some prospects from your segments based on certain criteria. For example, you can exclude prospects who have unsubscribed from your emails, who have not opened your emails for a long time, who have expressed dissatisfaction with your brand, etc. By using negative segmentation, you can focus your efforts on the prospects who are more likely to buy from you, and avoid wasting time and resources on the prospects who are not.

5. Test and optimize your segments. Segmenting prospects is not a one-time activity, but an ongoing process that requires constant testing and optimization. You should monitor the performance of your segments, such as their conversion rates, revenue, retention, etc., and compare them with your benchmarks and goals. You should also experiment with different segmentation criteria, methods, and tools, and see what works best for your business. By testing and optimizing your segments, you can improve your lead scoring accuracy and effectiveness.

7. Analyzing and Adjusting Your Lead Scoring Model

Once you have set up your lead scoring model, you might think that your work is done. However, lead scoring is not a one-time activity, but a continuous process that requires regular analysis and adjustment. You need to monitor how your leads are progressing through the sales funnel, how your sales team is following up with them, and how your scoring criteria are aligned with your business goals. In this section, we will discuss some best practices for analyzing and adjusting your lead scoring model to optimize your lead generation and conversion.

Some of the steps you can take to analyze and adjust your lead scoring model are:

1. Review your lead scoring criteria and weights. You should periodically review your lead scoring criteria and weights to make sure they are still relevant and accurate. For example, you might want to add new criteria or remove outdated ones, adjust the weights based on the importance of each criterion, or change the scoring scale or threshold. You can use data and feedback from your sales and marketing teams, as well as industry benchmarks and best practices, to guide your decisions.

2. Segment your leads by score and behavior. You should also segment your leads by score and behavior to understand how they are distributed and how they are engaging with your brand. For example, you can use a histogram or a scatter plot to visualize the distribution of your lead scores, and identify any outliers or gaps. You can also use a heat map or a funnel chart to track the behavior of your leads, such as the pages they visit, the emails they open, the forms they fill out, or the actions they take. You can use these insights to identify any patterns or trends, and to spot any issues or opportunities for improvement.

3. Test and compare different lead scoring models. Another way to analyze and adjust your lead scoring model is to test and compare different versions of it. You can use a split test or an A/B test to run two or more lead scoring models simultaneously, and measure their performance based on key metrics, such as lead quality, conversion rate, sales cycle length, or revenue. You can then compare the results and determine which model is more effective and efficient. You can also use a control group or a baseline to measure the impact of your lead scoring model against a scenario without lead scoring.

4. collect and analyze feedback from your sales and marketing teams. Finally, you should collect and analyze feedback from your sales and marketing teams, as they are the ones who interact with your leads and use your lead scoring model. You can use surveys, interviews, focus groups, or other methods to gather their opinions and suggestions. You should ask them questions such as: How do they use the lead scores? How do they prioritize and follow up with the leads? How do they qualify and convert the leads? How satisfied are they with the lead scoring model? How can the lead scoring model be improved? You should use their feedback to identify any gaps or challenges, and to implement any changes or enhancements.

By following these steps, you can analyze and adjust your lead scoring model to ensure that it is always up to date and aligned with your business objectives. You can also improve your lead generation and conversion processes, and increase your sales and marketing efficiency and effectiveness. Lead scoring is not a static process, but a dynamic one that requires constant monitoring and optimization. By doing so, you can gain a competitive edge and grow your business.

8. Successful Lead Scoring Strategies

One of the best ways to learn about lead scoring is to look at how other companies have implemented it successfully. Lead scoring is a method of ranking leads based on their level of interest and fit for your product or service. By assigning scores to leads, you can prioritize and segment them according to their readiness to buy, their potential value, and their likelihood to convert. In this section, we will explore some case studies of successful lead scoring strategies from different industries and perspectives. We will see how lead scoring can help you improve your marketing and sales performance, increase your conversion rates, and grow your revenue.

Here are some examples of successful lead scoring strategies:

1. HubSpot: HubSpot is a leading provider of inbound marketing and sales software. HubSpot uses lead scoring to segment their leads into four categories: subscribers, leads, marketing qualified leads (MQLs), and sales qualified leads (SQLs). Subscribers are people who have signed up for their blog or newsletter, but have not shown much interest in their products. Leads are people who have downloaded a free offer, such as an ebook or a webinar, but have not requested a demo or a trial. MQLs are people who have shown a high level of interest and engagement with HubSpot's content and products, such as visiting their pricing page, viewing a case study, or filling out a form. SQLs are people who have expressed a clear intent to buy, such as requesting a consultation, a quote, or a proposal. HubSpot assigns scores to leads based on their demographic and behavioral data, such as their industry, company size, location, website activity, email opens, and clicks. HubSpot also uses negative scoring to deduct points from leads who are not a good fit, such as students, competitors, or people who have unsubscribed or bounced. HubSpot's lead scoring system helps them align their marketing and sales teams, nurture their leads effectively, and increase their sales efficiency and productivity.

2. Salesforce: Salesforce is a global leader in cloud-based crm and enterprise software. Salesforce uses lead scoring to rank their leads based on their propensity to buy, their fit for their products, and their engagement with their brand. Salesforce uses a combination of explicit and implicit scoring to evaluate their leads. Explicit scoring is based on the information that leads provide, such as their job title, role, industry, company size, and revenue. Implicit scoring is based on the actions that leads take, such as their website visits, email responses, social media interactions, and event attendance. Salesforce also uses predictive scoring to analyze the historical data of their customers and prospects, and identify the patterns and signals that indicate a high likelihood of conversion. Salesforce's lead scoring system helps them prioritize their leads, optimize their marketing campaigns, and accelerate their sales cycle.

3. Netflix: Netflix is a global streaming service that offers a wide variety of movies, TV shows, documentaries, and original content. Netflix uses lead scoring to segment their users based on their preferences, behavior, and loyalty. Netflix assigns scores to users based on their viewing history, ratings, reviews, searches, and recommendations. Netflix also uses machine learning and artificial intelligence to analyze the data of their users and create personalized profiles, suggestions, and offers. Netflix's lead scoring system helps them retain their users, increase their satisfaction, and grow their subscription revenue.

9. Maximizing Sales Efficiency with Lead Scoring

Lead scoring is a powerful technique that can help you optimize your sales process and increase your conversion rates. By assigning numerical values to your prospects based on their interest and fit, you can prioritize the most qualified leads and focus your efforts on them. Lead scoring can also help you segment your prospects into different categories, such as hot, warm, or cold, and tailor your communication and marketing strategies accordingly. In this section, we will conclude our blog by summarizing the main benefits of lead scoring and providing some best practices and tips to implement it effectively.

Some of the benefits of lead scoring are:

1. It improves your sales efficiency and productivity. Lead scoring can help you save time and resources by eliminating the need to chase unqualified or uninterested leads. You can also automate your lead nurturing and follow-up processes based on the lead score and trigger actions such as sending emails, making calls, or scheduling appointments. This way, you can ensure that your sales team is always working on the most promising opportunities and moving them along the sales funnel.

2. It enhances your customer experience and satisfaction. Lead scoring can help you understand your prospects better and deliver personalized and relevant messages that match their needs and preferences. You can also align your sales and marketing teams and ensure that they are sending consistent and coherent messages to your prospects. By providing value and building trust with your prospects, you can increase your chances of converting them into loyal customers.

3. It boosts your revenue and growth. Lead scoring can help you increase your sales performance and results by improving your conversion rates and reducing your sales cycle. You can also identify cross-selling and up-selling opportunities and maximize your customer lifetime value. By using lead scoring, you can optimize your return on investment and grow your business faster and smarter.

To implement lead scoring successfully, you need to follow some best practices and tips, such as:

- Define your ideal customer profile and buyer personas. Before you start scoring your leads, you need to have a clear picture of who your ideal customers are and what characteristics and behaviors they exhibit. You can use data from your existing customers, market research, and feedback to create your ideal customer profile and buyer personas. These will help you determine the criteria and factors that you will use to score your leads.

- Use both explicit and implicit data to score your leads. Explicit data refers to the information that your prospects provide to you, such as their name, email, company, industry, role, etc. Implicit data refers to the information that you infer from their online behavior, such as their website visits, email opens, clicks, downloads, etc. You should use both types of data to score your leads based on their interest and fit. You can also use negative scoring to deduct points from leads who show signs of disengagement or low interest.

- Test and refine your lead scoring model. Lead scoring is not a one-time activity, but a continuous process that requires constant monitoring and evaluation. You should test your lead scoring model and compare it with your actual sales results and feedback. You should also update your lead scoring model regularly to reflect any changes in your market, product, or customer behavior. You should aim to have a lead scoring model that is accurate, reliable, and scalable.