pinpoint your number and paths to target

Analyzing a vast array of success indicators for each opportunity and benchmarking them against historical data, revealing patterns that might be missed without such detailed analysis. This is akin to having a team of expert statisticians evaluating every transaction to predict outcomes more precisely using data-driven insights.

Discover how RevOps leaders use Gong’s AI to analyze every interaction across sales and customer success teams, so they have the critical insights needed to call forecasts with superhuman ability.

AI offers enhanced visibility by detecting potential risks and opportunities within the sales pipeline that might otherwise remain unnoticed. It also provides scalability, offering comprehensive insights across all deals in the pipeline, enabling a more holistic view.

Moreover, AI contributes to increased efficiency by automating routine tasks, freeing up time for sales managers and teams to concentrate on engaging customers and converting pipeline, ultimately improving sales productivity.

Interested in learning how Gong customers use AI in sales forecasting? Read this case study on Crayon, a Boston-based company, that leveraged AI to boost forecast accuracy while reducing the time spent on forecasting calls by 66%. 

One of the biggest challenges of sales forecasting is subjectivity. Human biases can lead to overly optimistic or pessimistic forecasts. Additionally, the absence of AI can lead to incomplete data, as manual CRM entries might not be updated or adequately capture prospect needs, creating ‘ghost pipeline’ within the system.

Second, data overload is a challenge. When handling a substantial amount of data, it’s difficult to distill it into actionable insights for your sales team. 

Lastly, without AI, manual sales forecasting demands labor-intensive efforts, detracting from valuable time that could be better spent on closing deals.

Explore our “Reality of Forecasting Report” to uncover common factors contributing to inaccurate forecasts and learn how to achieve precision, efficiency, and confidence when making projections.

AI-driven sales forecasting solutions integrate with existing CRM systems through API integrations or plugins. The AI software pulls data from the CRM, processes it using predictive algorithms, and then provides insights and predictions back into the CRM interface for sales teams to use to make real-time decisions.

The ROI of AI-powered sales forecasting stems from multiple enhancements in the realm of forecasting and pipeline management. These improvements include shortened sales cycles resulting from AI-driven execution enhancements, leading to more efficient processes.

Additionally, AI-generated guidance contributes to higher conversion rates, assisting sales teams in navigating deals more effectively. The increased accuracy in forecasts facilitated by AI allows for improved resource allocation, optimizing the allocation of resources.

Lastly, the time-saving aspect is significant as AI takes on the task of forecast compilation, freeing up the sales team to concentrate more on deal closure, thereby maximizing productivity and efficiency.

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