If you can remember back to Dreamforce 2018, (here’s a blog post of the best features to help remind you) there were talks about new features that could come to light in the near and distant future. One of the few already here, as of the new Pardot spring release, is Pardot’s Einstein behaviour scoring to identify buying intent.
Scoring and grading is already a feature used by many Pardot customers, however with the help of Einstein this can be taken further to predict prospects to be passed straight to sales teams as they are deemed ready to buy.
Using previous sales data, Einstein is able to match current prospect patterns to those of your most valuable customers. This would allow companies to try to recreate previous successes by following the same patterns.
By defining a customer’s buying intent based on their actions and engagement patterns over a yearly time frame, Einstein is able to display a score out of 100 to assess how ready a prospect is and how urgently they should be pursued.
By this logic if a customer has previously purchased a product, and then begin to interact with other marketing materials or webpages for another, they would be scored high and be deemed relevant for future purchases. Equally if a customer shows signs of buying intent behaviour, such as adding items to the basket or even viewing reviews based on those products, they would also receive a high score as these could be signs of a customer with a view to buy.
Einstein behaviour scoring will improve the methods of analysing customer patterns and allow for clearer buying signs to follow. Identifying those eager to buy will speed up processes and allow for more accurate sales response times. It should also prove useful for cross selling tactics as users are able to identify previous customers with further interests.