Einstein Case Classification

In recent times Salesforce has added many capabilities to Service Cloud Einstein. One of them is Einstein Case Classification or simply Einstein Classification. In my future blogs, I will be talking more about those new features.

Let's start by knowing what is Einstein Case Classification: Salesforce's Einstein Case Classification is a tool that utilizes machine learning to suggest or automatically populate Case record fields. Einstein Case Classification always uses an organization's last six months of closed cases to recommend or populate picklist or checkbox field values. In short, it removes the guesswork in completing case fields so that agents can resolve cases quickly, accurately, and consistently.

Great now we know what it is so let's start configuring it.

Step 1: The most important thing here is to have the relevant license you will need. The paid version of Einstein Case Classification and Case Wrap-Up is available with the Service Cloud Einstein add-on license. This license allows for five models per app. Einstein Case Classification also includes automatic field updates and Einstein Case Routing. To upgrade, talk to your Salesforce Account Executive.

But don't worry if you just want to try you can create a scratch org using this link. Do select Classify Citizen Requests option.

Step 2: Now we have all we need to start. From Setup, in the Quick Find box, enter Einstein Classification, and then select Einstein Classification. Next Click the toggle to turn on Einstein Classification Apps. This can take a few minutes.

Step 3: Click on Get Started on the Einstein Classification setup page.

Step 4: On the next screen select Case Classification, enter the name for your model and click next.

Step 5: This is one of the important steps to understand here we need to tell the system for which Cases the values should be predicted. This means you can ask the model to consider all the new Cases or Cases specific to a business unit or a category.

Step 6: Now we have decided which new Cases to have predictions, but from where does this prediction originates? The model considers the existing Closed Cases to build the prediction model. You have the flexibility to either use all the recent(up to six months) or specific Cases.

Step 7: Next identify which field values you need to set the prediction on.

Step 8: When you click next on the screen you will see something like a summary of what we have done. The table at the bottom shows which fields will be predicted. An important factor to note fields should contain diversity in values it will fail if the values are almost similar e.g. if there are 10000 records where the Priority is all Medium or Low this will fail. Also, your org should have plenty of data to build the model minimum is 400 which is not effective enough.

A common error you will see, it is important to have different values.

Step 9: Finally click finish, but wait it is still half job done.

Step 10: It's time to build your Classification Predictive Model. Once again go to the Einstein Classification Setup page and select the model name. Click on the Setup tab. You can also remove a field from the model and select Remove from the Action menu. To add fields, select Edit under Configure Data. At last, you can now click Build to generate the model.

This will take a few hours totally depending upon the amount of data your org holds. Salesforce will send you an email once the build is finished.

Step 11: We are inching towards the end, now we need to Configure Field Prediction Settings. What we are doing here is that we are asking the model that is built to decide the level of prediction automation. With the lowest level of automation, Einstein recommends the top three field values for each field in your model. Or you can have Einstein select and save the best value automatically. 

You can do this by clicking edit under Configure Predictions and selecting a field. Alternatively, select edit next to a field in the list.

Below you are telling the model to show the top values for those fields which need to be predicted. The model will show the values but will not set or select for you. Here you will also need to set the prediction confidence threshold, which is your minimum required confidence level for selecting the best value. A prediction’s confidence level represents the likelihood that the recommendation for the field value is correct.

We can also ask the model to prepopulate the fields with the best values determined by the model. You can click on the Automate value tab and turn on the Automate value. The field will show the best value already selected with the BEST label next to the value. Again you will need to set the prediction confidence threshold.

Step 12: Select Save & Close. Your changes take effect immediately, and the prediction settings appear in the field list. You can now click on the Activate button.

Step 13: Grant Users access to Einstein Classification. New permission set Einstein Case Classification is already created as soon as you did the second step. Manage Assignments and assign users to the permission set.

Step 14: Add Classification Apps to the Case layout. Drag the Einstein Field Recommendations component onto the page. Select Case Classification and relevant Update Action. Save your changes.

Note: You will need to update Action’s layout to determine which fields appear in the component. You will also need to add your prediction fields if not already exposed.

Step 15: Now this is ultimately what the user will see when they create a Case.

You will see Einstein Recommendations Available clickable link. If you click on the link you will see your selected fields to be predicted highlighted with a green dot.

If you click on any prediction-enabled field you will see the Einstein Recommended Values.

Step 16: If you want to see the performance of the model you can again go back to the Einstein Classification and click on your model name.

You will see the performance tab click on it, here you can see how the model is performing and helps you to decide which field values to automate.

The Top 3 Recommendations chart indicates how often one of the top three recommended values matches the final field value at the time the case is closed.

The Top Recommendation chart shows how often the top-recommended value matches the final field value when the case is closed.

When a case with field predictions is closed, the dashboard refreshes.

Summary(exactly what Salesforce has mentioned)

• At a minimum, Einstein recommends the top three values for picklist and lookup fields on new cases, and the top value for checkboxes (enabled or disabled). Agents can click into a picklist or lookup field to see which values Einstein recommends.
• For both classification apps, if you enabled Select Best Value for a field and the prediction confidence is above your threshold, Einstein shows the field with the best value already selected next to the word BEST.
• For Einstein Case Classification, if you enabled Automate Value for a field and the prediction confidence is above your threshold, Einstein saves the best field value automatically and triggers any case routing or assignment rules that you've put in place.

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