Artificial intelligence
that leads to real profit
SalesVu systems run 7 unique algorithms to help your
employees increase sales - there's nothing else like it.
SalesVu's AI technology is part of our full software
suite to increase your profits and decrease costs.
Increase your sales
  • Upselling shouldn't be a shot in the dark. Use
    powerful analytics to make better recommendations.
  • Improve customer experience by better meeting
    their needs and build loyalty.
  • Uncover hidden customer patterns to capitalize on
    them and maximize profits.
Decrease your costs
  • It's easier and cheaper to retain a customer than win
    a new one. Add value to your existing customers with
    better recommendations.
  • Combing through data yourself is tedious, time
    consuming, and expensive Let your computers do
    the work.
  • Personalized recommendations don't work if they
    are presented badly or if they interrupt the natural
    sales flow. SalesVu's AI recommendations are built
    seamlessly into the order experience.
AI in Action
AI - How it works on iPad
New Additions - All your newly added items will automatically appear in the "New" product category so your customers can easily discover new items. Items added to the "New" category will remain in this category for 7 days by default, or you can set up a custom time limit. New items will also be available in its original category that was assigned.
Best Sellers - This automatically populated category showcases your most in-demand products to your customers right when they begin ordering. Our software constantly accumulates and analyzes your sales data to determine which products sell the best. The first 5 all-time best-selling products will automatically appear in the Best Sellers category. You can set up custom parameters such as the maximum number of products in this category (the default is 5) and the minimum number of sales the product needs to have to qualify for this category (the default is 10).
Past Purchases - This product recommendation is populated automatically based on the customer's purchase history from the last 30 days. Our system will scan the purchased products and will suggest products that are frequently bought with the products that the customer has recently purchased.
Frequently Bought Together - Our system keeps track of the combinations of products in your customers' orders and analyzes which products are often purchased together. When a product is added to the order, the system will offer additional products to purchase in the modifier flow (a popup window) based on what other customers have frequently purchased with this product.
You might also Like - The algorithm behind this product recommendation will find all products that are Frequently Bought Together with all the items in the order and determine if there is one product, or products, that are Frequently Bought Together with all the items in the order. It will then select a single product, out of the "Frequently Bought Together" pool, that the products in the order have in common, that the customer is most likely to add to their order, and recommend it as the "You Might Also Like" suggestion.
Similar Products - This product recommendation group will show up on the bottom of the screen when a particular product is being viewed by the customer. It will show the customer additional products that they might be interested in, that are sharing the same attributes as the product that is being viewed. The similarities between products are determined by 'tags' that are attributed to each product. Products with the same tags will be considered "similar products".
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