As competition for a finite universe of bookers intensifies, retargeting has emerged as an indispensable tool in a smart advertiser’s online toolkit. By using behaviourally targeted ads to reengage site abandoners, retargeting has seen huge success in the travel and hospitality industry.

The dirty secret at the heart of traveller retargeting, though, is that huge amounts spent on it are being wasted. We all know this is true from personal experience. I’m a longtime member of the highest tier of the loyalty club of a major British airline (some might even say the world’s favourite airline). I like the service, I like the rewards, I like the app, and I like the fact that the searches I do are stored in my loyalty profile. I would also estimate that over 90% of the time, I’ll later return to the site and book the flight for which I’ve been searching. So does it make sense that after every such search on their site, a retargeting ad follows me around the web?

It isn’t enough to simply retarget; we must also make the move to smart retargeting. The best approach is to combine core retargeting data (the data from the portion of your audience who were cookied as they browsed products or services) with other key data, such as product yield and availability, as well as loyalty status and past behaviour. Utilising this, together with data derived from outside your website (such as that generated as the same visitor browsed other sites) allows for your messaging to be based on their intent, other actions they may have undertaken and, critically, the ability to fulfill their desire. Advertisers need to, and now can, go beyond just the fact that someone has visited their site. Only with this model will the true value of retargeting and its place in the purchase funnel be realised.

Critically, we shouldn’t chase conversions that are going to happen on their own when we could be taking that money and generating new business instead. Hunt for incrementality. We recently conducted an A/B test lift study on prospecting and retargeting campaigns for a global hotel brand. Most targeted groups of the retargeting campaign were associated with a high volume of conversions. However, the study revealed that several of these groups were driving no incremental sales. The conclusion was that the high loyalty status individuals were booking regardless of whether or not they were shown an ad. Interestingly, this study also revealed that the prospecting campaign, despite lower volume conversions, had better ROI due to the greater incremental impact.

Wasted retargeting ads hurt the budget and don’t help the customer. If there is a high probability that someone will book regardless of your advertising, why waste impressions on him or her? Of course this doesn’t mean that all retargeting should be stopped. An overlay of the user loyalty status would ensure that the retargeting was focused on driving incremental sales. Furthermore, if your product or service has limited availability, such as in travel or hospitality, overlaying data from your product inventory or yield management system will help ensure money is not wasted. After all, it’s illogical for an airline to retarget me if the flight I searched for to New York is normally always full or overbooked.

Combining retargeting data with intent data derived from other sites adds an additional layer to the refinement of targeting. Travel intent data captured and aggregated from airlines and flight meta search sites can be used to prospect successfully. This same data can also add depth and granularity to a retargeting campaign. Utilising all these layers of data (someone who has visited your hotel site and also recently searched for a different destination on a meta search site) may now offer a more refined targeting opportunity

We need to truly understand our audience’s status and act on it. Plenty of money is being wasted in retargeting; it should all be about incrementality. Using other intent data can mean getting much more granular with users. We need to combine this with a deep knowledge of the space to understand which data aspects are going to optimise the campaign and messaging effectiveness. By utilising audience status and capacity to fill it, we can better determine where to spend money efficiently and change people’s behavior.