How Visme Builds Brand Visibility in AI Search

Visme operates in one of the most competitive categories in software. Anyone building a presentation, an infographic, a social graphic, a video, or a one-off web page already has at least three brand-name tools in mind. Visme handles all five surfaces in one product, but breadth alone doesn't win the consideration set. Buyers have to actually see Visme in the same breath as the giants when they're picking what to try.

That decision used to happen in a comparison post or a review site. It now happens upstream of both: in ChatGPT, in Google AI Mode, in whatever AI surface a buyer asks for a shortlist.

Visme knew they belonged on those shortlists. They needed to see whether they were actually showing up there, who they were showing up alongside, and which sources were making the recommendations stick.

The Challenge

Most teams reach for an AI search problem with the SEO playbook and end up confused. The signals don't line up. A page can drive almost no organic traffic and still be the source AI engines cite when answering a category-defining question. A page can rank first on Google and never get cited at all. Without a map of which third-party sources AI engines lean on, every campaign is a guess.

Visme wanted that map. Which review sites, listicles, social platforms, and community discussions were shaping recommendations in visual content? Once they had the picture, they could decide where to invest in outreach, where to push UGC, and where their own content needed to do more lifting.

The hardest part wasn't knowing AI search mattered. It was getting a clear view of how Visme actually shows up: which sources shape the recommendations, where we're getting outweighed, and what we can do about it.
— Chelse Hensley, Social Media Strategist at Visme

Why They Chose Qvery

Visme didn't need a dashboard that tracked a number. Plenty of those existed. They needed something that took measurement and connected it to a campaign on the other end.

Qvery is built to be that loop. AI Engine Researcher captures what's happening in the data daily. Qvery Assistant turns each finding into a workflow that produces an outcome. The pieces aren't separate tools the team has to stitch together. They sit inside one command center.

How They Use Qvery

The work starts in Qvery Assistant with a Citation Gap Analysis. The template pulls together the third-party sources fueling AI recommendations in visual content, scores them by influence, and shows where Visme's own footprint is thin compared to where the conversation actually lives. That single view replaces a folder full of disconnected spreadsheets.

From the gap analysis, Visme's team pulls two work streams:

• The first is outreach: getting Visme into the high-influence sources where competitors are already getting cited.

• The second is UGC: seeding genuine user content on the platforms AI engines actually pull from. Both workflows live inside Qvery Assistant, so the team isn't context-switching between research and execution.

Results

Visme now has a working read on their AI search position and a system for moving it. They know which conversations matter, which sources to invest in next, and which campaigns are actually shifting the citation footprint. AI search stopped being a black box and became a managed channel.

The bigger shift is internal. The team isn't waiting for a quarterly report to know whether their work landed. They run AI search the way they run every other channel they own: measure, act, measure again. Qvery is the operating layer underneath.

If you want to see how your brand shows up in AI search, sign up for Qvery or reach out for a demo.