Helpful Ads Compliment a User’s Journey

When people think of the word “ad”, it often triggers assumptions about poor user experiences. Especially on the web, the past decade has seen the rise of the truly annoying advertisement. From overwhelming animations to non-dismissable interstitials (the screen that forces a count-down before loading your content) that block your journey, we’ve seen ads go to some dark places.

But advertisements, when designed well, can serve a real user need. When combined with the principles of the Better Ads Standards, they can complement the functionality of a publisher’s. Here at <intent>, our design team is dedicated to finding that area of usefulness for users looking to book travel – providing a win-win-win scenario for travel shoppers, publishers, and advertisers.

Our design team has helped OTAs, meta sites, and other companies in travel vastly improve their user’s journey experience with user-centered-design (UCD) that facilitates good ads

Focusing on the early stages of the user journey with qualitative research

Online travel shopping is constantly getting better at providing value to bookers. But design teams at these travel websites need to have a focus, and can’t optimize for every part of the user journey. Despite the growing inventory that individual brands offer to shoppers, the reality is that users are going to visit several sites to see all their options because no site can truly offer everything

Some sites have access to different types of lodging inventory, especially when comparing rental properties to hotel options. Different flight OTA’s have access to different airlines, and some of the top travel sites don’t offer flights at all. 

That’s where <intent> can help. We focus on the very early stages of trip research when the user is still narrowing things down. We offer experiences that help them carry their search across multiple sites and product types without replicating the features that OTA’s and meta sites do so well.

Conducting user interviews to create personas

usability testing example

Usability testing one of our placements

To target this specific part of a travel user’s journey, we have interviewed hundreds of travelers in person across three continents, observing carefully how people shop for travel. We’ve consolidated all these observations into our own user personas which represent common needs and behaviors of the early travel shopper who likes to compare.

Our personas are used in every ideation session, while designing every screen, and considered while evaluating test results and iterating on design concepts.

We have our developers and product managers on regular rotation to sit in on these sessions and take notes – that way everyone involved in building a specific product is exposed to the user, which allows for empathy in a way that just isn’t possible when only sharing highlight reels or research updates. They also join us during our design sprints, bringing unique and innovative perspectives!

Product Managers, Engineers & Account Managers in a Design Sprint

Product Managers, Engineers & Account Managers in a Design Sprint

Strengthening the story with quantitative research

This covers the qualitative research needed to create useful ads, but to really get to solutions that matter, we also need to conduct quantitative research. 

Once we have live ad placements collecting real data, we start A/B testing various design directions. Designers, developers and PM’s review the data at our weekly planning meetings and iterate designs based on the most successful variant. 

It’s not uncommon for us to test a couple dozen variants in a few weeks, quickly leading to experiences that are not only more effective at generating revenue, but are more useful to users. An ad with high interaction rates and solid feedback in usability tests becomes more than just an ad, it becomes a tool.

Tying everything together with machine learning

Of course, all of this is contingent on being able to identify and target users who look like the personas we design for. Luckily the geniuses on our data science team have that figured out. By using our <intent> Scores to separate the users who are in comparison shopping mode from those who intend to book soon (even if they are first-time visitors), we are able to ensure we’re applying the exact right experience to the right user.

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