Contentsquare is a capable platform, and it has added AI features this year too. But the ground moved this fall. If your site sells anything, these are the four places a second look at Fullstory pays for itself.
Agentic commerce
See Muse and other AI agents as their own audience
Fullstory’s MetaMuse segment and dashboard template flag agent sessions from behavior and technical fingerprints: no pointer curve, cloud Linux desktops, Chrome 153+, Cloudflare and Fastly origins. Then it shows orders, revenue, AOV, entry pages, errors and friction for that segment alone.
It catches the hand-off. When a shopper takes over from the agent to finish checkout, highlight, copy and paste signals show up. You see pure human, pure agent, and everything in between.
Fullcapture
Sampling makes real problems look like noise
Every session, every click, every error, with no tagging plan. Agent traffic is new and spiky, which is exactly what a sample misses.
695 → ~8,000 users a day. A consumer subscription brand saw the same error page jump 11x the week it switched to full capture. The bug didn’t get worse. They stopped sampling.
Friction in dollars
Insights sized in revenue, backed by replays
Every finding pairs affected users with an observed conversion or retention lift, a dollar figure, and the sessions that prove it.
~$15.3M in annual revenue at risk found in 30 days at a subscription brand. $180M checkout opportunity tied to one iOS crash spike at a global retailer.
Open AI stack
Behavioral data your own AI tools can use
StoryAI agents investigate drops and spiking errors around the clock. The Fullstory MCP puts session data inside Claude and Cursor, next to GitHub and Snowflake, so engineers go from friction to root cause to fix in one prompt.
15+ critical bugs surfaced in initial MCP sweeps at a delivery marketplace, including a checkout blocker fixed in 45 minutes.