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Opportunity Scoring For Improved Forecasting
Opportunity Scoring For Improved Forecasting

Predict those from your open opportunities with the likelihood to convert or at risk. Improve your close rates and forecasting accuracy.

Noa Lembersky avatar
Written by Noa Lembersky
Updated over 9 months ago

Let's explore a crucial Sales use case - leveraging Opportunity Scoring to enhance forecasting. Predict who from your open opportunities is likely to convert or at risk, ultimately improving your close rates and forecasting accuracy.

Identifying Sales-Ready Leads: The Foundation of Success

Successfully identifying sales-ready leads requires an effective lead-scoring system. However, lead scores can degrade as buyer behaviors change, leading to potential revenue leakage. Consistently monitoring changes in lead scores is critical to maintaining a healthy sales pipeline.

Spotting Degrading Lead Scores

Lead scores naturally fluctuate during the buyer's journey, but a sharp drop over an extended period may indicate low buyer intent or engagement. To identify such drops in time, analyze data points like increasing days between marketing touches, product usage, or low engagement with marketing or sales outreach. If observed, these signs suggest that lead scores should be degraded.

Smarter Way for Updating Lead Scoring Model

Rather than manually identifying trends, savvy marketing operations teams implement predictive lead scoring. Self-learning predictive models automatically surface leads trending down and notify sales reps instantly through familiar tools like Salesforce or Slack. These solutions continuously learn, improve scoring accuracy, detect changing lead behavior trends in real time, and require no manual model building or coding.

Beware of Bias in Outdated Scoring Methods

Outdated scoring methods, like rules-based systems bundled with HubSpot and Marketo, depend on human decisions, potentially introducing bias. Machine learning-based lead scoring can automatically eliminate bias, but achieving that manually for each scoring rule is challenging. If an AI-based solution isn't feasible, involving data scientists can help eliminate bias and human error, ensuring accurate prospect scoring.

Final Thoughts: Proactive Approach for Enhanced Forecasting

Degrading lead scores, if left unaddressed, can directly impact sales productivity and pipeline health. The key is a proactive approach through predictive scoring and consistent model optimization. This enables instant detection of deteriorating lead engagement, allowing sales teams to pivot resources accordingly and ensuring a robust forecasting process.

For further assistance or to explore how Forwrd.ai can enhance your Opportunity Scoring and forecasting, please get in touch with our support team. We're here to help you maximize the potential of your marketing operations with cutting-edge technology.


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