How do you handle and nurture leads that are not ready to buy or do not fit your ideal customer profile?

1 Why validate and test your lead scoring model?

Your lead scoring model is not static and must be validated and tested regularly to ensure it reflects current goals, market conditions, and customer preferences. Doing so can help you identify any errors, inconsistencies, or gaps in your data and scoring criteria. It will also help you evaluate the accuracy and effectiveness of your model in predicting and influencing lead conversion rates and sales performance. Additionally, validating and testing your lead scoring model can enable you to optimize and refine it to align with buyer personas, buyer journey stages, and sales funnel stages. Ultimately, this will increase marketing and sales efficiency, productivity, and ROI by focusing on the most qualified leads.

2 How to validate your lead scoring model?

Validating your lead scoring model is essential to ensure it is based on reliable and relevant data, and that it matches your expectations and assumptions. To do this, you must audit your data sources and quality, making sure there is enough data to score your leads and that it is accurate and up-to-date. Additionally, you should review your scoring criteria and weights, defining clear criteria for scoring leads based on their demographic, firmographic, behavioral, and contextual attributes. Assigning appropriate weights to each criterion is also important. Finally, compare your scored leads with actual results to make sure they match the predefined stages and categories. Analyzing the correlation between lead scores and lead conversion rates, sales cycle length, deal size, and customer lifetime value can also help you validate your model.

3 How to test your lead scoring model?

Testing your lead scoring model requires experimenting with different scenarios and variables to determine how they affect your scoring outcomes and performance metrics. Start by splitting your leads into test groups, using methods such as random sampling or A/B testing. Then, apply different scoring models to each group, modifying criteria, weights, thresholds, or formulas to see how they change lead scores and rankings. Additionally, use different scoring models such as predictive scoring, account-based scoring, or behavioral scoring to compare their results. Lastly, measure and compare the results of each group by tracking their impact on key performance indicators like lead quality, lead quantity, lead conversion rate, sales cycle length, deal size, customer lifetime value and ROI. This will help you identify the best-performing scoring model for each group and the factors that contribute to its success.

4 How to optimize your lead scoring model?

Optimizing your lead scoring model requires fine-tuning and updating it based on validation, testing results, feedback, and insights. To do this, you should implement the best-performing scoring model for each group, adjusting it as needed. You can also use a hybrid or multi-dimensional scoring model that combines different scoring models or criteria for different groups or stages of your leads. Additionally, it is important to communicate and align your scoring model with your team. Make sure your marketing and sales teams understand and agree on your scoring model, its logic, its benefits, and its limitations. Establish clear and consistent definitions and processes for managing and nurturing your scored leads to ensure a smooth handoff and collaboration between your teams.

5 How to get started with validating and testing your lead scoring model?

Validating and testing your lead scoring model is not a one-time or optional task; it is an ongoing and essential practice. Doing so can help you improve your lead generation, qualification, and conversion strategies, and ultimately grow your business. To get started, you should define goals and metrics that are aligned with your overall marketing and sales strategy. Additionally, you should collect and analyze data from various sources, such as your CRM or website. Then, you can build and launch your initial lead scoring model based on the data, criteria, weights, thresholds, and formulas. Finally, you should validate and test your lead scoring model to check, experiment, measure, compare, and optimize it. This process should be repeated regularly to keep the model up to date and effective.