SponserdIQ

Chat

Chat is the simplest way to use SponserdIQ: just ask a question in plain English and get an answer drawn from the live sponsorship database. No filters to set, no columns to learn — type the way you'd ask a colleague.

It's the first thing you see when you sign in — and for almost everything you'll want to do, it's the only screen you need.

Just ask

Try things like:

  • "Which beverage brands sponsor MLS teams?"
  • "Who are Gatorade's biggest sponsorship properties?"
  • "Show me healthcare sponsors that look like they're about to lapse."
  • "What industries are most active in women's soccer?"
  • "Find brands similar to Allianz that I could pitch."

Ask a follow-up and it remembers the thread, so you can drill in conversationally: "Now just the ones in the Southeast."

How it actually works (the short version)

Behind Chat is an LLM — a large language model, the same kind of AI that powers assistants like Claude. On its own, an LLM is a brilliant writer but it doesn't know your data and can sometimes guess. So we don't let it guess.

Instead, we give the AI a set of tools (live lookups into the database) and skills (prepackaged analyses, like "find lookalike brands" or "spot the white space"). When you ask a question, the AI picks the right tool, runs a real query against the real data, and answers from the result — and tags the reply with how many sources it drew on, so the answer is grounded in the live data rather than guesswork. You get the ease of conversation with the reliability of a database.

In short: the AI does the typing and the reasoning; SponserdIQ supplies the facts.

Take it to the next level: connect your own AI

The in-app Chat is great for quick questions. But the same data can plug straight into your own AI assistant — and that's where it gets powerful.

What's MCP? (the one term worth knowing)

MCP — the Model Context Protocol — is like a USB-C port for AI. It's an open standard that lets any AI assistant plug into any tool or data source through one common connector. Before MCP, every AI-to-tool connection was a custom integration. With MCP, you just "plug in."

SponserdIQ speaks MCP. That means you can connect it to your own Claude (the desktop app, the web app, or Claude Code) and ask it sponsorship questions right inside your own AI workspace — no copy-paste, no exporting spreadsheets. (The Getting Started page walks through the one-time setup.)

The real magic: chaining SponserdIQ with your other tools

Here's the part that changes how you work. Your AI assistant can connect to many MCP tools at once — and then orchestrate them together in a single conversation. SponserdIQ becomes one skill your AI can combine with everything else you use.

Picture a prospecting workflow, start to finish, in one chat:

  1. SponserdIQ finds the targets — "Find 20 beverage brands that don't sponsor any MLS team yet, ranked by how active they are elsewhere."
  2. A contact-data tool fills in the people — if you've also connected something like a ZoomInfo MCP, follow up with "pull the head of partnerships and the CMO for each of those brands."
  3. Your CRM creates the leads — if you've connected a CRM MCP (Salesforce, HubSpot, etc.), finish with "create a lead for each one with a note on the open MLS opportunity."

Three different systems, one plain-English conversation, zero manual busywork. The AI is the conductor; each MCP tool is an instrument.

And it doesn't stop there. With other connectors in the mix, the same thread could:

  • Draft the outreach — "write a short, personalized intro email to each brand" (an email/Gmail connector).
  • Schedule the follow-ups — "put a reminder on my calendar to check back in two weeks" (a calendar connector).
  • Brief your team — "post a summary of these 20 opportunities to our #partnerships Slack channel" (a Slack connector).
  • Build the one-pager — "turn this into a pitch doc" (a docs/Notion connector).

You assemble the toolkit; the AI does the running around. SponserdIQ's job is to be the trustworthy sponsorship-intelligence piece of that puzzle — the part that knows who sponsors whom, what's lapsing, and where the open space is.

Why this matters: the future of this kind of work isn't one app that does everything — it's your AI assistant stitching together the best tools for each step. SponserdIQ is built to be one of those tools, ready the moment you plug it in.

See the answer, don't just read it

Chat doesn't only describe the data. When a question is about relationships or market structure, it can draw the answer right in the conversation — a relationship map around a brand or property, a market breakdown, or a quick table — so you get the picture without leaving the thread.