The context
As part of a branding campaign in autumn 2019, a few months after a change of name, the gas carrier and storage company Térega, advised by the Makheia agency, called on Qwarry to conduct part of a display and video display campaign, carried out in parallel on YouTube and programmatically with third-party cookies. This programmatic campaign - a first for the advertiser - started in September 2019 and is still ongoing.
Qwarry, a company co-founded by Julie Walther and Geoffrey Berthon in February 2019, uses natural language processing (NLP) to analyze the content of the pages of numerous sites, determine which contexts are most in line with the advertiser's campaign, and then bid on the advertising space via its DSP. “Our agency presented us with the Qwarry solution, and their ethical positioning without using user data was close to our company values”, justifies Dominique Boquillon, Téréga's communications director.
The device
Continuously, the deep learning algorithm based on NLP developed by Qwarry analyzes millions of URLs to determine a semantic and feeling scoring on each content and page. “We do this scoring work beforehand because our computing power does not allow us to carry out all the steps in real time and respond in less than 200 milliseconds to a bid request”, explains Julie Walther.Before launching the campaign, Qwarry analyzed Térega's semantic field and deduced similar semantic segments (on BtoB targets: industry, urban planning, agriculture for example) to link them to each target defined by Térega (consumers, businesses and institutional journalists). The start-up then operates via its own DSP to position the advertiser's formats on contexts (site pages) that it has “whitelisted” in these segments. Not using geolocation data, Qwarry targeted nationally, except on the target residents who were primarily targeted via regional news sites. On the investment side, no amount for this campaign was revealed. However, Qwarry specifies that it is paid with a percentage of the CPM (not communicated) and that it operates on campaigns at a minimum of 5,000 euros and 10,000 euros on average, to justify the time associated with the analysis phase of the advertiser's semantic field, and the creation of segments in the case of Térega. Julie Walther specifies that the added value of her solution is visible on campaigns with branding and “top of the funnel” objectives like this one, more than on performance-oriented operations: “On this type of campaign, we believe that we are complementary to other traditional solutions using user data” she adds.Read the full article on Mind News.
À lire aussi
How did Terega use Qwarry's cookie-less targeting solution?
Qwarry generated a 36% higher click rate than that obtained by other actors who used user data during the campaign.
How Térega used Qwarry's contextual targeting solution for its first programmatic campaign
The regulatory context and anti-tracking policies of browsers are leading more and more companies to position themselves on contextual targeting. To reach different audiences, the gas carrier and storage company Térega therefore called on Qwarry, a company that uses semantic analysis of the distribution context to guide programmatic campaigns. mind Media interviewed Qwarry and Térega, to assess the initial results of this campaign.
