Pointhound.com
Award flight search - book flights with points
How Pointhound used Sitefire to grow site visits from AI Search by 300%
More people ask an AI model how to book flights with points than ever before. Using Sitefire, Pointhound identified which of those questions it could win and created AI-optimized content for them. Within three months that content went from zero to nearly half of all AI bot traffic to the site, and Pointhound began appearing in AI answers where it had been absent. Every headline number comes from Pointhound’s own server logs and analytics.
+300%
more site visits from AI Search
People clicking from an AI answer onto pointhound.com, since the new content went live. Measured in Pointhound's GA4.
+294%
more AI models reading Pointhound's pages
Real-time fetches by AI models reading a page to answer a live question, since the new content went live. From Pointhound's CDN server logs.
~45%
of all AI bot traffic is the new content
Up from zero. The content Pointhound created with Sitefire is now the most-fetched on the whole site.
0 → 1.0%
Citation Share, from a standing start
Pointhound now appears in AI answers to the tracked award-travel questions. Measured in Sitefire.
The work
Using Sitefire, Pointhound found where it could win and created the content
Award travel is confusing, and more of the people trying to figure it out now start with ChatGPT instead of Google. Pointhound is best positioned to be the answer those AI models give.
Using Sitefire, Pointhound ran multiple GEO optimization loops. At each turn, Sitefire agents identified where award-travel questions were being answered across ChatGPT and other AI models, and in which topics Pointhound had the strongest claim to win. Pointhound then turned those insights into SEO and GEO optimized articles.
Across the spring, Pointhound shipped three waves of content this way.
The loop
1
Identify
Sitefire’s agents map which award-travel questions AI models answer, and which of them Pointhound is best placed to win.
2
Create
Using Sitefire, Pointhound turns those insights into SEO and GEO optimized articles, built on its own brand voice.
3
Publish
Pointhound ships the wave, measures what the models read, and the loop starts again.
“With Sitefire, we ship articles we're actually proud to publish. No other tool got us there.”
Jay Reno
Pointhound
The results
Every signal up since the content went live
Four signals, week by week, from late February to the end of June. The dashed vertical lines mark the three waves of content Pointhound published; the first went live on March 14. The first two charts come from Pointhound’s own systems: CDN server logs and GA4 analytics. The other two come from Sitefire. Visibility Score is the share of AI answers on a tracked set of award-travel questions that mention pointhound.com. Citation Share is pointhound.com’s citations as a share of all citations in those answers.
Site visits from AI Search+300%
per week, against the pre-launch week
AI bot traffic+294%
per week, against the pre-launch week
Visibility Score0 → 1.0%
share of tracked answers
Citation Share0 → 1.0%
pointhound.com's share of cited sources
The control
The new content against the rest of the site
The content Pointhound created with Sitefire now accounts for nearly half of its AI bot traffic, up from zero. The single most-fetched page on the whole site is now one of those articles.
AI bot traffic by page group
per week, against the pre-launch week
Content that did not exist in March is now nearly half of what AI models read on the site.
The rest of the site did not have to shrink for that to happen - the new content grew the total.
Find the questions your buyers ask AI models
Sitefire runs the same diagnosis Pointhound used - and turns it into content built to win those answers.
In short
In short
Using Sitefire, Pointhound identified the award-travel questions it could win in AI answers and created AI-optimized content for them. That content now accounts for nearly half of the site’s AI bot traffic, site visits from AI Search grew 300%, and Pointhound now appears in AI answers where it had been absent - all measured in Pointhound’s own logs and analytics.
If your buyers are asking AI models about your category, the answers are already being written from someone’s content. Sitefire shows you which questions you can win, and turns them into the content that wins them.
What comes next
Using Sitefire, Pointhound continues to identify new questions its customers ask and turn them into content, further growing its traffic from AI Search.
“We're not slowing down. This is where our customers are searching now.”
Jay Reno
Pointhound
See your brand’s AI visibility
We’ll show you which questions your buyers ask AI models - and which of them you can win.
Methodology
- Windows. Weekly charts run February 23 to June 29, 2026. The first content went live March 14, with further waves in April and June. Headline changes compare the last full week before that first content went live with the most recent week, for every metric.
- AI bot traffic comes from Pointhound’s own CDN server logs and counts the agents that read pages to answer live questions (ChatGPT-User, Perplexity-User, Claude-User). Indexing and training crawlers are excluded. Shown as change against the pre-launch week.
- Site visits from AI Search (AI referral traffic) come from Pointhound’s GA4 and are a floor: most AI-influenced readers research inside the model and then navigate directly, and clicks from Google’s AI Mode arrive with a plain google.com referrer.
- Sitefire metrics. Visibility Score and Citation Share come from Sitefire’s tracked question set: award-travel prompts fixed at onboarding, evaluated on the same models throughout (definitions at sitefire.ai/docs/kpis).
Get started with Sitefire
Take action to win customers in AI Search
