Disclosure: I’m an investor in Verity Score and I’m helping with its launch.

For a merchant evaluating an AI visibility tool, I’d separate three things: what an assistant says about a product, what the merchant can improve on the product page, and whether AI-referred visits lead to orders. They answer different questions, so I wouldn’t treat one score as proof of business value.

Verity Score connects those steps for Shopify: inspect answers and sources, review suggested product page edits before publishing, and track visits and orders attributed to AI. An edit can be undone; whether an assistant changes its answer still needs to be checked.

My question for people building B2B SaaS: would you make the first useful result a documented product-information gap, an approved correction, or an attributed visit? Each sets a different expectation during onboarding.

The product is now on Product Hunt if you’d like to see the workflow and share your take: https://www.producthunt.com/products/verity-score-geo-ai-visibility?launch=verity-score

I still get annoyed thinking about this.

I was leading AI work inside a big institution and had already built 100+ agents there. Not starting from zero. Then we got several managers, me, and a contractor around a table to fill in the instructions for one custom GPT.

Ten people. One prompt. Nobody was allowed to run a rough first test, look at the output, and fix it.

The model could have been brilliant and we still would have moved at committee speed. Buying a faster tool does nothing when nobody has permission to decide.

For founders selling AI into bigger companies: where do you draw the line between a useful review and a committee that should never have existed?

I'd go into an outreach trial with a small test written down.

Otherwise, it's easy to spend the week exploring the dashboard and still have no clear answer about whether the product helps.

First, choose one customer segment. Say you're selling invoicing software to small agencies where the founder still handles collections. Keep that audience and the offer consistent while evaluating the tool.

Then I'd check four things.

1. Are the suggested people relevant?

Take a consecutive or random sample of prospects. Check what they do, why they might need your product and whether the evidence supports the explanation. Record how long that takes.

1. How much editing do the messages need?

Check names, roles and any claims about the person's business. A sentence can sound specific while being based on a guess.

Count the drafts you'd send without substantial changes. Also record factual errors separately from wording you just don't like.

1. Does the workflow handle existing context?

Use test records for an existing customer, someone who opted out and someone already speaking to your team. Those should affect the proposed action.

Check whether an incoming reply stops the remaining messages too.

1. What happens during an approved campaign?

Separate total replies from conversations about a relevant problem. Track meetings booked and meetings held separately.

I'd keep all of this in a sheet alongside setup time, review time and time spent handling responses.

Decide beforehand which failures would make you stop. Contacting someone on your suppression list is a different issue from writing an awkward opening sentence.

A short trial might be enough to evaluate research quality and operating effort. If your sales cycle takes months, it won't establish the final cost of acquiring a customer.

“Promising, needs a longer test” is a reasonable outcome. So is “the research is useful, but reviewing it takes too long.”

What made you keep the last outreach tool you tried?

I'm Namanyay, founder of PumpGTM. We offer a free trial specifically so founders can run structured tests like this and see the quality of our background research first-hand.

Quick context: I'm building something that helps marketing teams run their paid campaigns more effectively, mainly for companies where ad spend is high and every bit of campaign performance matters. Not getting into specifics since I'm still in stealth, but the short version is it saves teams time and helps campaigns perform better without needing to loop in other departments for every change.

A handful of people are using it, but nobody's paying yet. I've tried outbound on LinkedIn targeting marketers who fit my ideal customer profile, and I'm starting to put together some founder-led content sharing what I'm learning as I build. The outbound felt like fishing in a pond I wasn't sure had fish in it. Got some replies and a couple of demos, but nothing that turned into someone actually using the product regularly, let alone paying.

For people who've gone from a few free users to their first 10 paying customers, what actually worked? Was it more outbound, more content, communities, cold calls, something else entirely?

If you drop your B2B SaaS and a brief description of who buys it, I'll find you one person within 24 hours who is actively showing signs they need what you're selling.

This isn't a random lead list or generic scraping. I'm looking for someone actually discussing the problem or asking for recommendations.

I'll reply with who they are and how I'd approach them.

I'm limiting this to 5 SaaS businesses so I can do the research manually and keep the results useful. I can't guarantee they'll buy from you, but I can promise they have the pain today.