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The average number of days required to secure the Technical Win, from the day an opportunity is first assigned to a Sales Engineer.

Buyers are more informed and no longer need generic product education, they want to meet with technical experts who will grasp their specific requirements faster and align tailored solutions to drive value more effectively. As a result, early sales stages are shortened, leading to a more significant portion of the sales cycle spent achieving the technical win. In addition, vendors with Generative AI capabilities undergo additional scrutiny to secure the technical win.

This metric measures the efficiency of the technical sales process, as it reflects how fast buyers (prospects and customers) agree that your product meets their technical requirements. A shorter duration indicates a more streamlined and effective pre-sales process, which is essential for maintaining customer satisfaction and competitive advantage.  *YoY is the variance between the last two 12 month periods.

*YoY is the variance between the last two 12 month periods.

Of the opportunities that reach Tech Win, the percentage that also reach Close Won.

Technical wins aren’t actual wins, but virtually no wins happen without technical fit. Fewer Technical Wins converting to closed-won opportunities suggests that the increased presence of corporate finance is dragging down win rates through reduced technology purchases. Sales Engineers can be of value here, as they can correlate the outcomes and financial impact of their solutions.

This metric evaluates the effectiveness of the Technical Win in progressing towards the final closure of deals. A high Technical Win Close Rate indicates a strong correlation between technical wins and successful closures, reflecting the alignment between customer needs and the solution provided.
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*YoY is the variance between the last two 12 month periods.

The percentage of revenue closed by AE’s that are supported by the PreSales team.

SEs do more than demos, and the increase in lift reflects the value add of the function, where SEs can frame the value of holistic solutions to problems, as opposed to selling a single product. As this also leads to more licenses and/or higher usage, understanding optimal levels of technical expertise required to support sales cycles can increase average deal size significantly.

This metric quantifies the impact of PreSales support on revenue generation. It highlights the contribution of the PreSales team in facilitating successful sales outcomes and emphasizes the importance of collaboration between sales representatives and technical experts.
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*YoY is the variance between the last two 12 month periods.

The percentage of pipeline with any technical fit risks flagged.

Opportunities in Q4 have aggressive close dates leading to higher levels of technical risk. This results in deals slipping into the next quarter, which carry the same dynamic. Identifying technical risks early puts the organization in the best position to improve forecast accuracy and achieve attainment goals.

This metric assesses the quality of opportunities in the sales pipeline by identifying potential technical challenges or mismatches early in the sales process. It enables proactive mitigation of risks and ensures that resources are allocated effectively to opportunities with higher chances of success.
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*YoY is the variance between the last two 12 month periods.