This analysis paints a picture of what a modern travel sector SERP looks like – with correlative data to measure against.

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.

Earlier this year I wrote a post looking at how travel brands can be competitive this year, and then the world went into lockdown.

That being said, the three points I raised in this post are for me now even more important than ever.

In the new landscape travel brands need to be:

• Engaging with influencers on new mediums.
• Being open to new audiences and markets.
• Leveraging micro-moments.

It’s also important to understand the current search landscape, take any learnings, and identify any correlations between the websites ranking well on search engines versus those ranking beyond Page 2.

Methodology

We took 1,000 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.

Using a combination of tools, scripts, and manual analysis, we looked for patterns and potential learnings that could benefit other websites within the travel sector (if not further afield).

From this analysis, we can then paint a picture of what a modern travel sector SERP looks like, with correlative data to measure against.

Competitive Spread

Given the breadth of keywords, and the diversified product portfolios of a large number of travel websites, I first wanted to look at the competitive spread at how often the same websites ranked for a variety of search phrases.

In total 11,373 unique domains ranked within the sample of 98,863 results.

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On average, each domain appeared 11 times within the total sample of search results, with the top three appearing 1,092 times, 1,024 times, and 958 times respectively.

#marketing analytics #seo #analyzing #machine learning