Case Studies
How Lean Layer Helped Our Client Improve Forecasting Accuracy by 65%
Learn how we transformed our client’s forecasting approach, resulting in a 65% increase in forecasting accuracy.
Case Studies
Brooke Hattie
Sep 23, 2024
MQL quality not what it used to be? See how we worked with this client to reduce low quality leads by 48%.
The Challenge
Our client was facing a dwindling MQL (Marketing Qualified Lead) to opportunity conversion rate, leading to significant friction between the sales and marketing teams. Although the marketing team was hitting their MQL targets, the quality of those leads was not translating into revenue.
This resulted in wasted efforts by SDRs, as they spent time pursuing low-quality leads that rarely converted into opportunities. The misalignment between sales and marketing became a key issue, with marketing’s budget being inefficiently spent on generating leads that didn’t contribute to the pipeline.
The client needed a new approach to redefine their MQL criteria and improve their overall lead quality and efficiency.
The Solution
We implemented a comprehensive strategy to enhance the client's lead generation and sales conversion process. We began by redefining their MQL criteria, focusing on high-quality leads such as hand raises and demo requests. This allowed us to eliminate unproductive leads and ensure that the sales development representatives (SDRs) were spending time on prospects most likely to convert.
Next, we introduced a warm outbound strategy, enabling proactive engagement with potential leads based on their level of interaction. This replaced the previous score-out method, which was less effective. We also retrained the SDRs to differentiate between engaging high-interest leads and nurturing leads requiring further development.
Through this data-driven approach, Lean Layer significantly reduced low-quality MQLs by 48%, doubled the MQL-to-opportunity conversion rate, and improved the overall alignment between marketing and sales efforts. This resulted in more accurate reporting and a more efficient, revenue-focused lead generation process.
The Approach
Learn more about our approach on how we solved this for our client below:
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Analysis of MQL Logic: We first conducted an in-depth analysis of the client’s existing MQL definitions. During this analysis, we discovered two distinct paths to MQL status—hand raises and score-outs—which were being treated equally, despite the significant difference in their conversion rates.
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Segmentation of MQL Buckets: Once we identified these two paths, we separated them into distinct buckets, allowing us to see the performance differences clearly. Hand raises had a far higher conversion rate compared to score-outs, providing a clear path forward.
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Client Enablement: We worked with the client to explain the benefits of focusing on hand raises as the primary MQL criterion. We equipped their team with data showing that while MQL volume might decrease, the quality and conversion rates would significantly improve. This higher-quality lead pool would give SDRs fewer but more valuable leads to work with, ultimately resulting in more opportunities and a more efficient workflow.
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Technical Adjustments: We migrated the MQL tracking from lead and contact logic to a campaign member format, ensuring accurate tracking of demo requests and engagement. We also introduced lead scoring decay mechanisms, ensuring that SDRs prioritized the most current and engaged leads.
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SDR Enablement and Reporting: To ensure SDRs were equipped to handle the changes, we provided them with new training materials and reporting tools. We introduced customized reports in Salesforce to help SDRs focus on the highest-scoring leads, allowing them to work their accounts more strategically.
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Historical Data Analysis and Goal Setting: We conducted a historical data analysis to help the client understand how the changes would affect their MQL numbers and targets. By applying the new definitions to past data, we showed that conversion rates would double, and helped the client confidently set new, realistic goals for the coming quarters.
The Impact
- 48% Reduction in Low-Quality MQLs: By eliminating low-quality MQLs, we significantly reduced the number of leads SDRs had to pursue, allowing them to focus on higher-value prospects.
- Doubled Conversion Rate: The client’s MQL-to-opportunity conversion rate doubled as a result of the focus on higher-quality leads and improved lead scoring.
- Improved Reporting: The changes also allowed the client to accurately report on 48 previously unreported demo requests, further improving the visibility into their marketing efforts.
- Strengthened Sales and Marketing Alignment: With clearer MQL criteria and higher-quality leads, the relationship between sales and marketing improved, leading to greater trust and collaboration.
- Increased Revenue Potential: The combined effect of better lead quality, enhanced reporting, and stronger alignment contributed to a more efficient pipeline, allowing the client to achieve greater revenue potential.
Request a free consultation to see how we can help you improve your MQL quality and drive more meaningful pipeline.