Audience-to-action agent · Qloo taste data
Who else does your audience love?
Name your shop, brand or channel. An agent reads Qloo's taste data on the people who like you and comes back with partners to pitch, podcasts to sponsor, a playlist and content ideas — every pick traceable to the data.
Or open a finished run:
Partners to pitch
Brands your audience also loves — complementary, not competitors. Each comes with a draft you edit and send yourself.
Neighbours to team up with
Places nearby that the same people love.
Podcasts to sponsor
Shows this audience listens to, screened automatically for brand safety — the screen can miss things, so listen before you buy.
Playlist
Artists this audience plays — for the shop floor or your stream.
Content ideas
Hooks built on things they already love.
Every Qloo result the agent saw
How it works
- FindThe agent works out what you are — brand, venue, creator or podcast — and resolves you to a Qloo entity.
- ListenIt asks Qloo what your audience also loves: podcasts, brands, artists, films, and nearby places for venues.
- ScreenExplicit, partisan or extremist results are held back from ad and partner picks — and counted, never hidden. The screen is automatic and can miss things.
- ActA writer model turns the data into a plan. It may only cite Qloo results by id; anything it invents is removed in code.
The AI guess tab is the control: the same model, asked the same questions without data. Where the two lists differ, the plan is coming from your audience, not from stereotypes.
Use it from your own agent
The same tools are an MCP server (Streamable HTTP): /mcp — find_entity, audience_affinities, audience_action_plan.