Kumo AI Wins 2024 A.I. Award for Most Innovative AI Technology
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Solutions
Personalization
With the same data integration and just a few predictive queries, ensure that every touchpoint with your customer is as delightful as possible and drives long-term engagement while improving product sales.
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Read case studyWithout any ML expertise required
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Flexibly predict any measure of affinity between user and item:
- Probability of click, purchase, return, or any other kind of interaction event
- At the level of an individual item or any higher-level item attribute (category, brand, price band, etc.)
- Over the timeframe of your choice–from days to quarters
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Run a wide variety of analyses of your choice:
- Affinity between any arbitrary user or item
- Top K users likely to buy a target item or top K items to show a target user
- Top K Items similar to a target item or top K users similar to a target user
- …and more!
Downstream workflows turbocharged
- Curate customer experiences across web/mobile app/etc. that look and feel unique to each user and address their individual needs
- Anticipate growing trends in the marketplace to establish yourself as a trail-blazer among competitors
- Leverage user preferences to advise new product designs and make your business more customer-focused
- Programming chatbots that are capable of accommodating customer needs on an individual basis
- Enhancing product catalogue or enterprise search systems
- Enriching the content of any organic outreach (emails, notifications, sales calls, etc.) to drive higher customer engagement
- Choosing which specific users to target with a new event, major upcoming product launch, thematic promotion, etc.
- …and more!
Representative workflow
Define the ML Problem
Kumo makes it easy to define the ML task using a simple, declarative language, and then uses AutoML to execute a highly optimized and fully tuned model. Build the query and predict the future!
Structure your problem using a simple query to predict affinity to categories, brands, and products.
Predict 7-day category-specific purchase affinity:
PREDICT LIST_DISTINCT(Orders.Store_ID -> Stores.category,0, 7
FOR EACH Users.ID
Predict 7-day brand-specific purchase affinity:
PREDICT LIST_DISTINCT(Orders.Store_ID -> Stores.brand,0, 7)
FOR EACH Users.ID
Predict user will return a product they purchased within 30 days:
PREDICT EXIST(Returns.itemID, 0, 30)
ASSUMING EXIST(Orders.itemID, 0, -30)
FOR EACH Users.ID