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Opportunity Scores

Abstract

Analyze past wins and losses to determine factors contributing to the likelihood of an opportunity being won or lost so you can influence change.

By determining how likely each opportunity is to be won, you can focus your energy and attention on those that require it most. Symon.AI can analyze past wins and losses, and provide you with all the factors contributing to the likelihood of an opportunity being won or lost so that you can influence change. Using historical CRM snapshot data, Symon.AI can identify patterns in openings and closings. This data is fed in through the Build tab. Once Symon.AI has trained a model based on your unique organizational data patterns, you can start feeding open opportunity CRM data in the Run tab for Symon.AI to predict open opportunities.

How to train Symon.AI to predict the outcome of opportunities?
  1. Bring in the historical CRM data through Opportunities (Data).

  2. Use the Adapt tool to improve the labels and account for any columns that may have the wrong data type.

  3. Update the Classifier and can see what the baseline accuracy score is.

  4. Optionally, add in other data or create new columns in Symon.AI, then re-update the Classifier to try to achieve a higher accuracy score.

From the output of our final step, we can see that each opportunity has been assigned a probability of success. We can then investigate what factors contributed to Symon.AI's prediction using the Explain feature.

How to know which opportunities to focus on?
  1. After building a Classifier, move to the Run tab.

  2. Type a descriptive name in the Run name text box.

  3. Selecting the current open CRM data in the Opportunities drop-down menu. You can import the data in the Data tab on the Symon.AI home page.

  4. Click Make runs. Symon.AI will make predictions on these open opportunities.

  5. Once Symon.AI is done, download Classifier Export on the run results page. This contains our original data set, with two columns added. One contains Symon.AI prediction (Won", or "Lost"), and the other the probability assigned to that outcome.