Believe it or not, the main reason that Airbnb was ranking poorly was its lack of authority in comparison to its competitors. In other words, other vacation rental websites were getting more links than Airbnb when it came to the topic of vacation rentals. Thus, Cogney devised a linkbuilding strategy based on three types of analysis: What publishers linked to Airbnb and what kinds of content or enticements successfully induced publishers to link to Airbnb in the past? How did Airbnb’s competitors obtain links? What ingenious promotions, content, campaigns or news would be likely to result in links to Airbnb? In one case, we encouraged Airbnb to replicate the success of their Chicago campaign, “Spend the night in the Bulls stadium”, by creating similar listings in other territories. Sometimes, the content was already there, waiting to be plucked for a fruitful linkbuilding campaign. For example, we repurposed reports demonstrating economic and social benefit to specific geographical areas compiled by Airbnb in response to public concern about the existence of Airbnb operations in those areas to secure links from local newspapers and publications.
To improve Airbnb’s rank for specific locations when the number of vacation destinations (and web pages) was practically infinite, we conducted both technical and content audits, the findings of which fell under two major themes. First, it was crucial to leverage crawl budget so that Google could read as many of the most important pages on the site as possible on any single crawl. For example, Cogney modified the site architecture so Google could get from “Bismarck, North Dakota” to “Cincinnati, Ohio” in as few clicks as possible, a gain in efficiency that might have been invisible to a human being but which was indispensable to optimizing crawl budget. Second, content and nomenclature had to be adapted to the particularities of the reader for any given region or location, in order to boost relevancy and linkbuilding potential for that geographical area. Our content audit, essentially a “listening” exercise, revealed how and what people were searching for in a specific area. When someone searched for “Chicago vacation rentals”, their search queries tended to fall into a defined cluster which included queries such as “what to do in Chicago”, “best restaurants in Chicago”, etc. Based on these insights, we recommended the addition of new content or the optimization of existing content to better address these popular queries. A similar analytical process was applied to the terminology used on the site. For example, in French-speaking mountain areas, we recommended the introduction of listings for “chalets” to supplement the usual categories of homes and apartments. All this was done while avoiding cannibalization of content between pages, so that crawl budget wouldn’t be spent on processing duplicative pages.
Finally, we conducted A/B testing of different content on pages of the same class with similar traffic to optimize user efficiency and conversion. Due to the continual addition of pages from new listings, we emphasized that such testing must be conducted on a permanent, ongoing basis in order for Airbnb to maintain best-in-class SEO while constantly growing and changing its website.