How We Got to BoothIQ

BoothIQ started with a simple question: “How do I get this CSV into Salesforce?”

Emily asked me this when we first met over Zoom earlier this year. I didn’t know it yet, but she would soon become my cofounder.

She’d just come back from a conference with a CSV full of leads she needed to get into Salesforce. She was talking about how she has to do this for every event. There’s no standard format. It’s super tedious and annoying. From the time the post-event CSV gets delivered to finding the time to actually sit down and enter the leads one by one, it takes about a week, if not more. She needed to change the column headers and make sure all the data was formatted correctly to get the leads into Salesforce.

I threw together a quick workflow using a no-code drag-and-drop tool to clean the spreadsheet and map it into Salesforce. Took about an hour, and it did its job well enough. It wasn’t very sophisticated, but it did what we needed it to.

That got us talking about what else we could automate. Emily was already recording her booth conversations to remember what people said. She started asking if certain features were possible. Could AI transcribe those voice notes? Could it summarize them? Could it automatically populate contacts in the CRM?

Yes. Yes. Yes.

But before we built anything serious, we wanted to make sure this was actually a problem worth solving. We talked to people: event marketers, field marketers, event managers. They all said the same thing: the current landscape of lead capture, event follow-up, and ROI tracking sucks.

After our user interviews validated the idea, we decided to take a swing at it and see if we could build a solution for this problem that people would actually use.

I built a quick web app to test it out. Record a conversation, let AI transcribe and summarize it, see what happens. It wasn’t much more than a glorified note taker at that point, of which dozens already exist. But we wanted to see if it actually worked for our use case.

We used it on some meetings we had. The summaries came back with details, names, action items. Actual useful stuff.

But we quickly realized a problem with recording on the web. It doesn’t work well when the phone is locked. You have to keep tapping the screen to keep it awake during a conversation, which is really annoying. If people were going to use this for real, background recording was table stakes.

So we needed a mobile app.

React Native seemed like the fastest way to get on the App Store, so we built it and shipped it. It worked.

Then a framework update broke certain features. I wasn’t able to easily fix the issues. At that point, I started thinking about alternatives.

Normally, app rewrites are a bad idea. But the app was young and wasn’t too terribly feature heavy. If we were ever going to rewrite in full native, now was the time.

I decided to experiment with AI to see if I could get a native app up and running. It worked better than I expected. AI did a great job, and it was better at writing native code than it was at writing React Native, at least anecdotally. I found that surprising.

I made the call to go full native. The look, feel, and performance are all leagues better than the React Native version was. We’re very happy with that decision.

Normally, a full software rewrite kills momentum for months, but AI tools changed that. What should have been a project-ending rewrite was just another iteration. We built it, shipped it, and it’s live on the App Store now.

All of this (quick workflow, web app, React Native, native iOS) happened since June 1st.

We’re still early. Working with our first customers, learning what works, iterating fast. Our initial customers love it, and the feedback keeps getting better. We want to make not only the day-to-day booth experience better, but events as a whole, from pre-event all the way to tracking closed deals and how the events tied in. We’re just getting started.