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Average rating based on reviews
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The total ranking of a product, represented by the bar length, is based on a weighted aggregate score. The score is calculated as follows: The product with the highest count in each area gets the highest available score. (20 points for Reviews; 16 points for Views, Comparisons, and Followers.) Every other product gets assigned points based on its total in proportion to the #1 product in that area. For example, if a product has 80% of the number of reviews compared to the product with the most reviews then the product's score for reviews would be 20% (weighting factor) * 80% = 16. For Average Rating, the maximum score is 32 points awarded linearly based on our rating scale of 1-10. If a product has fewer than ten reviews, the point contribution for Average Rating is reduced (one-third reduction in points for products with 5-9 reviews; two-thirds reduction for products with fewer than five reviews). Reviews that are more than 24 months old, as well as those written by resellers, are completely excluded from the ranking algorithm.

Customer Data Analysis Reviews

Read top reviews of Customer Data Analysis solutions from the IT Central Station community:
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‎IT Director with 1-10 employees
Apr 18 2018

What do you think of IBM Watson Commerce Insights?

Primary Use Case We needed a new, innovative solution for a standard scenario in the education sector. We are still progressing down this path. However, if we have an answer which is fresh and innovative, it will change education forever. • Improvements to My Organization Using Watson APIs has been extremely helpful, as it means we can get to our endgame faster. • Valuable Features Speech to Text NLU Cognitive AI Watson Discovery Elasticsearch Knowledge analysis These are all valuable to the end solution. • Room for Improvement It is constantly being improved upon. However, if we could get a marked improvement in the Speech to Text API, that would be great. • Use of Solution Still implementing.

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