The travel sector is one of the most competitive verticals when it comes to organic search, with relatively low barriers to entry for most business models and an ever growing and varying consumer base, it’s an appealing market to be a part of.
We took 1000 of the most searched for travel queries in the UK from the past 3 years (to try and take into account changes in the vertical over the past 8 months). These keywords are a combination of:
- [country] holidays
- car hire [location]
- cheap [location] city breaks
- cheap flights [location]
- cheap holidays [location]
- cheap hotels [location]
- flights to [location]
And other more general phrases relating to month, trip duration, and level of boarding.
We then took these keywords and exported the 98,863 search results for them and using a combination of tools, scripts, and manual analysis looked for patterns and potential learnings that could benefit other websites within the travel sector (if not further afield).
Featured Snippets & Zero-Click Searches In Travel
Based on this data, what can we infer that a modern day travel SERP looks like?
We’ve known, and experienced, for a long time now that Google isn’t a linear positions one through ten, and produces results and special content result blocks based on matching multiple multiple user intents.
Based on this analysis, the below indicates what a modern travel SERP will look like, based on probability of both the type of search result (commercial/non-commercial) and the frequency of Google special content result blocks, this way we can take into account the varied search intent of the queries that generated the 98,863 search results.
Across the keyword sample, a total of 10 different special content result blocks were surfaced (not including Google features such as Flights and Hotels).
The below table details how often these elements surfaced within the search results pages:
|SERP Feature||Chance Of Appearing|
Consolidating the Video and Video Carousel special content result blocks, it’s likely that video content will surface in three quarters of searches made for travel queries, with one in three returning related questions.
The data also shows the need for utilizing reviews (and potentially review schema) with two in three keywords surfacing review elements.