If you’ve done a few hikes in your time, you’ve probably come across AllTrails.
If not, it’s essentially the app for finding nearby hiking trails. It gives you estimated times, photos, reviews, and maps – not just to get you to the start, but to finish the trail too.
It’s built out incredibly well from a user side. But they’ve also nailed the SEO side.
Let’s dive into what they’ve done right, how they’ve structured the site, what content they’ve built out, and how it all comes together to drive traffic.
Overall Performance
Taking a look at the SEO performance of Alltrails.com across the site, we see;
Pretty nice.
A slow and steady growth curve across the years – the kind of graph every SEO would be proud to show a client.
They’re not smashing out huge spikes, but it’s consistent. Very consistent.
Which is a direct result of their structured, scalable content strategy.
Site Sections
They’ve got a clear split in their site structure, and each piece plays a role:
Trails
Parks
Points of Interest
Location aggregations
User-generated Lists
Let’s break each down.
Trails
This is their bread and butter. It’s the absolute core of the site.
Everything else revolves around this content.
URLs look like this:alltrails.com/trail/us/washington/bridal-veil-falls-trail
alltrails.com/trail/*
These pages are where most of the SEO performance comes from.
The keywords tend to be exact trail names or destination-based (e.g. “bridal veil falls hike”), with some modifiers thrown in like “elevation gain” or “loop”.
All trails have a base-level generated description that takes in the available variables.
This isn’t just a base-level generation and would have taken some time to map everything out.
Would involve quite a bit of spintax and dynamic templates that take in the key variables like Distance, Location, Simplicity, Activities, and Opening/Seasonality.
It’s followed by what appears to be a manual description depending on the popularity of the trail. Assume they have used a system that identifies as much information about the route as possible to then be able to quickly spin up some text – a great way to extend the generated content.
The next core part here of the text-based content are the reviews;
The fact that these are constantly updated with new reviews being shared almost daily, gives Alltrails a significant edge above competitors.
These make it extremely difficult for a new player to enter the market.
On top of this text content, the interactive gallery, map and weather widgets offer a UX that locks users into a higher time on site, and lower bounce rate.
You can tell that these trail pages are doing the heavy lifting, and everything else is there to support or aggregate these.
Parks
Their first layer of aggregation.
Each park (like Yosemite) has its own landing page:
alltrails.com/parks/us/california/yosemite-national-park
These pages group trail content within a specific park, so they can also go after more generic park queries, not just “hiking in Yosemite” but “Yosemite map”, “Yosemite reviews”, and even “Yosemite photos”.
The real trick here?
They’re getting traffic for the park names without modifiers like “trail” or “hike”.
That’s huge.
This allows them to take their trail content, and then sidestep into non-trail keywords.
Many of the lower-volume terms will also be related to the parks and won’t include the filtered ‘trails’ or ‘hiking’ keywords.
We can see they have 23,500 keywords on the board with an estimated traffic of 1 or greater;
If we then exclude keywords containing things like ‘trails’ and ‘hikes’ (plus more similar words), we’re left with 14,200 keywords;
So only ~40% of the keywords are related to the trails, giving them a much larger exposure to people not searching directly for trails.
There are two pieces of core content on these pages.
The top list of trails, and the aggregated reviews.
The top trail widget heavily leverages the content of the individual trails, appearing to pull from what I believed to be the “manual” element of the trail description;
This is then followed by an aggregated view of reviews of all trails in the park;
A perfect way to ensure a constant rotation of fresh content, that won’t directly mimic the entire content of an individual review page.
This is all then wrapped up with a dynamic FAQ widget, which includes the brand name when answering some questions – a recommendation I have started including for AI crawlers.
They’ve also got some basic park details, like opening hours and contact info on the page, but it’s hidden behind a modal and only available in the <script> source;
Appears they use to expose this by default, based on wayback machine here;
I’d prefer to expose this by default, both on page & in the non-script HTML for simplicity, especially now with AI crawlers. Google appears to be indexing it fine at the moment, though, unsure of others.
Location aggregation pages
The hierarchy here is strong.
They go:
Country:
alltrails.com/usState:
alltrails.com/us/utahCity:
alltrails.com/us/utah/bryce
From here, it filters further by:
Activity:
alltrails.com/us/utah/bryce/walkingAttractions:
alltrails.com/us/utah/bryce/hardSuitability:
alltrails.com/us/utah/bryce/dogs-leash
With a linking widget above the footer to these pages;
These are mostly just aggregation pages that pull in relevant trail pages with dynamic text. But they do the job well.
It allows for structured internal linking and some smart long-tail targeting.
Points Of Interest
Looks like a newer rollout.
Example:alltrails.com/poi/us/utah/the-cathedral
Pages built for landmarks or notable places that aren’t trails or parks.
Still relatively small, but this section is likely aimed at future-proofing. More generic visibility. More long tail.
Give it another 6-12 months, and I’d expect it to contribute a measurable slice of their overall SEO pie.
Lists
This is their most flexible section – user-generated lists.
Example:alltrails.com/lists/14ers-in-colorado
These let users compile their favourite hikes into custom pages, write their own descriptions, and pull in trails + reviews.
Not only can users suggest new trails, but they can then aggregate those, and existing, trails into lists. Double-sided targeting.
It’s a clever move. It sidesteps templated structure limits and opens up targeting to all kinds of specific queries – regional, themed, or even niche.
But…
There’s a downside.
A Bit Of A Mess: Adult Keywords & Spam
There are over 500 pages ranking with adult-related keywords.
Likely due to spammy lists or users playing games with the UGC.
It’s not affecting the site too negatively yet, but it’s not great for the brand image – and it’s likely attracting backlinks from some pretty dodgy corners of the web.
This is something I’d clean up sooner rather than later.
A mass delete of lists containing flagged keywords + a ban on future creation of those keywords in titles or descriptions
A Missed Opportunity: Review Extraction
AllTrails already pulls a little review snippet per trail:
But that’s only scratching the surface.
I ran a few trails through a model and got summaries like:
“Consider detours, additional viewpoints available.”
“Great views, a bit steep in places.”
“Go clockwise, harder sections first.”
This is perfect info for hikers – and it’s already on the site. It’s just buried in the reviews.
They could extract recurring themes and surface them at the top of trail pages, like:
🔥 Steep sections ahead
🐶 Dogs allowed (leash required)
☀️ No shade – bring water
🚻 Bathrooms at start point
With a full breakdown from a handful of reviews via ChatGPT;
That’s real value. And it’s scalable.
Key Takeaways
Here’s what stands out the most from the AllTrails setup:
1. Leverage your core content as support content
Even though trails are the core, they use them everywhere – in parks, locations, lists, and even POIs.
That reuse allows a single piece of content to fuel dozens of pages.
2. Structure wins
From clean URLs to smart foldering, their hierarchy gives Google a clear view of how it all fits together.
Each level of aggregation gives them more reach – and more relevance.
3. Let your users work for you
Lists are user-created, and yet power long-tail keyword targeting. That’s smart.
If you’re not ready for that, just start by mining your internal search data. What are people trying to find, but you’re not offering yet?
4. Clean up before it becomes a problem
With UGC, comes great responsibility.
Those UGC lists with dodgy keywords? Might not be hurting rankings yet, but they will attract bad backlinks and lower trust.
Nip it in the bud
5. Mine your own reviews
They’re already on the page. Extract the value and turn it into usable, scannable info.
Real users write the best guides – use their words to make your content more valuable (and more structured).
Final Thoughts
AllTrails is a great example of a product that feels like it’s just for users, but behind the scenes is one of the cleanest SEO-first builds I’ve seen in this space.
Their growth reflects it.
The core content’s nailed, the structure’s clean, and the aggregation logic is simple yet powerful.
Overall, a strong example of SEO strategy done right.
Want me to break down another site like this? Or think your setup could be doing a little more with your content?
Get in touch, and we’ll dive in.
