Influence Over Impressions: Ranking Publishers By Time To Purchase
Content matters. Period. It drives purchase consideration and purchase. And the impact of the content brand recommending what you buy matters too. But none of that is accounted for in an advertising economy that believes that volume matters more than influence.
Programmatic advertising is gross. It rewards impressions, which leads to terrible content. It follows you around the internet whether you want the product or not, increasing consumer distrust and privacy concerns. It’s meant to commoditize content rather than value it. And you know that whole fake news thing.
But most importantly it gets credit for the last click before purchase rather than the long line of content providers who helped influence that purchase path.
Our goal at OpenUp is to disrupt that model. We are purposely engaging consumers to share their data with us because we know that only their data can truly reveal the factors that influenced them to purchase. We track every click on the journey to purchase and through that are helping content brands prove that they are a critical part of the purchase journey. (Just ask our clients.)
As part of that route to disruption, we ranked publishers by impact on purchase for beauty content by tying the content they read with the time it took to make a purchase. The list below shows a ranking of the publishers with the shortest purchase window for reading beauty content and then making a beauty purchase.
To understand this better imagine if every time someone went on best-televisions.com and then immediately afterwards bought a television set. Their time to purchase would be close to 0 minutes.
With a single purchase, this approach doesn’t make much sense: Just because someone went to Google.com before buying toilet paper doesn’t mean the two things were related. However, when averaging over thousands of purchases, as we have here, we can sift through the noise to see if a consistent pattern emerges of what websites lead to what types of purchases.
Narrowing in on a specific vertical — beauty — we tracked 5K purchases over 5 months across several hundred publishers that had beauty content. For each user in our sample, we calculated the average time between when they last saw beauty-related content on a specific publisher, and when they made a beauty-related purchase. We then averaged across all users and all domains to come up with the top publishers.
These publishers are ranked in terms of how soon, on average, users made a beauty purchase after seeing beauty content on these pages. We have also included how popular these sites are among our user base, defined as the % of users that have seen the site at some point. Notably, besides Refinery29, there isn’t a clear case of popularity of a site leading to a shorter time to purchase.
Over the next few months we will work to build a brand drill down so we can see the attribution for Chanel lipstick or Tide detergent. We will also link the big publishers and small blogs that together influence the purchase path. The goal is to have a clear and simple way to understand how what we read is impacting what we buy.
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Methodology: OpenUp incentivizes consumers to share their browsing, social and opinion data via the OpenUp Browser Extension. The data for this analysis was done with a sample of 1000+ women between the ages of 18 to 34 recruited from both panels and publishers. Five months of behavioral data was used.
Written by Aswini Anburajan
