How to use Metadata in Grip

Grip's AI-powered matchmaking engine is a self-learning system that will continually deliver more intelligent recommendations to users, the more they engage with the platform.

In order to deliver the best possible recommendations, high-quality data is essential. 

Well-thought-out data strategies will improve the recommendations our matchmaking engine delivers to your users.

3 metadata strategies to consider

  1. "Supply & Demand": The AI will use "Supply" and "Demand" metadata types to learn more about a user's true interests and to match against the same value in the complementary category.
  2. "Matching Facts": The AI will use "Matching Facts" to learn more about users true interests and to match against the same values selected by users.
  3. "Facts" about a user: The AI will use "Facts" to learn more about users true interests.

All of these categories can be learnt from. For example, our AI can see from a users swipes that they are interested in Gin and Rum regardless if a user has pre-selected that they are interested in Gin and Rum.

The "supply and demand" and "matching facts" categories can be matched.

Matching happens immediately, learning requires swipes to be made.

How are these strategies used?

Each of these strategies are categories of metadata that will have values that sit underneath them. Users will have provided their "answers" to these categories a) when they register for a ticket to your event, b) through onboarding questions when they first log into Grip, or c) by updating their networking preferences at any point while using the tool.

Supply & Demand

We have created a dedicated article on this as these can be used to create an interest match. Click here to learn how to create an interest match.

Matching Facts

Matching Facts act as both supply and demand and will be used to make immediate matches. The matchmaking engine will also use the values that sit underneath these categories to learn more about users true interests.

Please see below for example categories for the "Matching Facts" strategy:

  • Category
  • Sector
  • Subject Interested
  • Language Spoken
  • Workshops Interested
  • Mentorship Opportunities
  • Objective

This is useful if you would like to help connect German-speaking individuals or perhaps users who share an interest in Artificial Intelligence workshops.


Facts are used by our AI for learning purposes only.

Please see below for example categories for the "Facts" strategy:

  • Purchase Decision Maker
  • Challenges
  • Company Size
  • Country of Origin
  • Decision Maker
  • Purchase Influencer
  • Job Level
  • Number of Stores
  • Primary Role in Purchasing
  • Skills
  • Years of Experience
  • Currently Raising Funding
  • Industry
  • Job Functions
  • Continent
  • Industry Interested
  • Employment Status
  • Hiring
  • Sponsors of Interest
  • Speciality

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