What is Lead Scoring? | Best Lead Scoring Solutions

Traditional Lead Scoring

Traditional or static lead scoring is the foundational approach to lead qualification. In this straightforward approach, points are assigned to the leads based on a predefined set of rules. It primarily uses data such as job title, industry, location, etc., and lead behavior such as website visits, email opens, form submissions, etc.

Behavioral Lead Scoring

This scoring approach focuses on analyzing the lead’s interaction and actions with the company’s marketing materials and digital channels, such as website visits, content downloads, webinar attendance, email engagement, and other touchpoints. Behavioral lead scoring gives valuable insights into lead interest, allowing dynamic lead prioritization and effective lead nurturing for those with low behavioral scores.

Purchase-Intent Lead Scoring

By utilizing the purchase-intent lead scoring method, businesses can evaluate and prioritize leads based on their intent to make a purchase. This approach goes beyond mere demographics and behavioral lead scoring to identify leads who actively consider or research the company’s products or services and are most likely to convert in the near future.

Predictive Lead Scoring

Predictive lead scoring, the modern alternative to traditional lead scoring, is a more dynamic and data-driven approach. It utilizes advanced analytics, historical data, customer behavior, and machine-learning algorithms to assign scores that are more accurate and dynamic. Compared to traditional lead scoring, this approach predicts the lead conversion probability with greater precision.

Account-Based Lead Scoring

It is a tailored approach, especially for businesses that target specific accounts or companies instead of individual leads. Account-based lead scoring assigns scores to the entire account on the basis of company size, industry, revenue, etc., and aligns with account-based marketing (ABM) strategies, allowing prioritization of high-value accounts for personalized outreach.

Hybrid Lead Scoring

The hybrid lead scoring model is a combination of multiple models or techniques. It overcomes the limitations of each model by leveraging their respective strength, resulting in more accurate lead qualification and improved targeting. This approach of lead scoring enables businesses to customize their scoring approach according to their specific business needs and objectives.

STEP 1 ➧

For new customers, a rule-based system prioritization starts after 2 sales cycles, but for existing use cases, it starts from day 3 itself. This helps us determine which leads to contact first.

STEP 2➧

After achieving 500 sales, the system transitions to a machine learning (ML) model for lead prioritization. The ML model requires historical data to function accurately and become effective.

STEP 3 ➧

Our lead prioritization model is re-evaluated and updated every 2 sales cycles or once every month, whichever comes first. This ensures the model stays relevant and adapts to changing customer needs.

Align Sales & Marketing

It provides a common ground for both sales and marketing teams to understand and prioritize leads. This collaboration fosters better communication, smoother handoffs, and improved overall performance.

Prioritize Sales Efforts

Lead scoring helps save time and resources by eliminating wasted efforts on unqualified prospects. Additionally, it enables the sales team to focus on customers with the highest lead scores.

Improve Sales Forecasting

By utilizing lead scores, businesses can predict their future sales performance. Scores are used to estimate the number of lead conversions in a given timeframe, allowing better budget planning and resource allocation.

Boost Marketing ROI & Conversion Rates

It allows the marketing team to identify and nurture leads with high potential, enabling them to target these leads by sending personalized content and offers, leading to improved ROI and conversion rates. 

Enhance Customer Experience

Lead scoring fosters personalized and relevant interactions with the customer based on their behavior. This boosts positive customer experience as it creates a sense of loyalty and trust among the leads.

Access to Data-Driven Insights

Lead scoring gives businesses the liberty to generate and analyze valuable data about the leads, which allows them to understand their target audience, identify trends, and refine their lead scoring models if required. 

STEP 1 ➧ Define Lead Attributes

• Identify the characteristics of your leads using demographics and firmographics.

STEP 2 ➧ Assign Point Values

• Assign point values to each lead attribute based on its significance in determining a lead’s score.

STEP 3 ➧ Capture Lead Data

• Utilize various sources like CRM and marketing automation to collect data on your leads.

STEP 4 ➧ Calculate Lead Scores

• Tally the points for each lead based on their attributes and recorded actions.

STEP 5 ➧ Set Lead Score Range

• Define a lead score range to categorize leads based on their scores.

STEP 6 ➧ Prioritize Lead Nurturing

• Prioritize and reach out to the leads with high scores.
• Nurture the leads with a lower score.

Define Your Goals and Ideal Customer Profile

Start with clear objectives for your lead scoring program, as it helps guide your scoring strategy. Additionally, knowing your ideal customer profile is crucial in understanding which data points are most relevant for scoring.

Choose the Right Scoring Model

There are different lead scoring models, such as demographic, behavioral, predictive, and others. You must consider your resources and data availability when choosing a model. You can also implement a hybrid model that combines elements from different approaches for a more comprehensive evaluation.

Start Simple & Scale Gradually

Don't try to create an overly complex scoring system right away. Begin with a basic model and gradually add complexity as you gather more data and refine your understanding of your leads.

Focus on Data Quality

Ensure that your data sources, such as CRM, marketing automation, and web analytics, are seamlessly integrated and the information is up-to-date. This benefits in two ways: accurate scores and an automated lead scoring process. 

Assign Weights to Scoring Criteria

Not all data points are equally important. Assign weights to different criteria based on their significance in determining a lead's value. For example, a demo request might hold more weight than a blog post download.

Use Negative Scoring

Don't just reward positive actions. Include negative scoring for actions that indicate low interest, such as unsubscribing from emails or abandoning shopping carts.

Monitor & Refine Your Model Regularly 

Your scoring models need to be modified as well in order to remain effective in this ever-evolving business structure and changing market conditions. You must regularly review and refine your scoring criteria based on performance metrics.

Align Sales & Marketing

Ensure both teams understand the scoring system and how it's used. This fosters collaboration and helps them work together more effectively towards shared goals.

Respect User Privacy

Be transparent about how you collect and use data for lead scoring. You must ensure adherence to the relevant privacy regulations to ensure effective data security. 

Use Lead Scoring for Lead Nurturing

Leverage lead scores to personalize your marketing efforts. Send targeted content, offers, and campaigns based on a lead's score and interests.