How Goodwill uses AdTheorent to drive visits to stores

When Goodwill wished to drive foot visitors to their stores in addition to create consciousness about their bigger mission of offering job coaching and assist to native communities, they turned to AdTheorent, a number one supplier of predictive digital advert know-how.

Formed in 2011, AdTheorent is a machine learning-powered, focused promoting supplier. Their know-how uses numerous information alerts that exist within the digital ecosystem to successfully and effectively goal digital adverts to customers based mostly on their shoppers’ targets.

ClickZ spoke with Jim Lawson, the CEO of AdTheorent, to focus on Goodwill’s latest cellular marketing campaign, together with gaining a greater understanding of the Cost Per Incremental Visit (CPIV) mannequin which requires that advertisers solely pay for incremental retailer visits (e.g., “visitations”).

example of Goodwill recent mobile campaignGoodwill banner proven through the AdTheorent marketing campaign

Goodwill’s aim in launching a marketing campaign with AdTheorent was to drive visits to their brick-and-mortar stores as effectively as potential. They realized about AdTheorent via a partnership with Ad Council.

Ryan Kuhn, Goodwill’s Interim CMO, writes, “Goodwill Industries International is very focused on finding the most efficient and effective means to reach targeted consumers with our message, and have been focused on the advances in geotargeted and tracked advertising technologies. When Ad Council approached us with this opportunity, and we saw AdTheorent’s proposed capabilities, we knew it was something we wanted to explore.”

AdTheorent’s Jim Lawson defined that they’re plugged into an unlimited quantity of advert stock by way of advert exchanges which facilitate the shopping for and promoting of stock throughout a number of advert networks.

“What the ad exchanges allow us to do is hyper target users on an impression-level basis using non-sensitive personal information from the bid stream and other sources,” explains Lawson. “We leverage data such as operating system, phone type, time of day, publication type, weather patterns, geographic location, and other signals. Our system then correlates variables that existed when conversions occurred and determines what variables yield visits to Goodwill stores so it can optimize delivery of ads to those people more likely to convert.”

Typically, advert concentrating on is predicated on retargeting or audience-based concentrating on and never based mostly on data-driven, real-time alerts. But AdTheorent’s know-how makes this potential by tying advert variables to customers’ cellular information. For instance, if there are individuals standing inside a mile radius of Goodwill and somebody is on the NYTimes app, AdTheorent should buy the out there advert house in real-time by way of the change market and serve up the advert to the one that is inside a sure radius of the shop.

What real-time cellular advert supply regarded like for Goodwill

For Goodwill, the advert unit itself was a show advert that linked to the Goodwill web site. The adverts appeared on cellular apps with out there stock out there all through the size of the marketing campaign. Once an AdTheorent marketing campaign is launched, it takes just a few weeks for the know-how to be taught what works finest based mostly on the marketing campaign targets (on this case, retailer visits or “visitations.”)

Says Lawson, “In Goodwill’s case, the system optimized ad delivery towards the best performing creative sizes with the 320 x 50 having the highest percentage of visitations. The machine learning model optimized toward that creative type.”

The system additionally acknowledged that customers related by way of wifi have been extra possible to convert, Verizon customers have been extra possible to convert, and customers at residence versus these at work have been more likely to convert to a visitation. They additionally discovered that Monday and Tuesday have been the most effective changing days.

“These are things you can’t anticipate in advance and plan for,” says Lawson. “Our system is about using big data and the vastness of the data and letting the system tell you what drives conversions and then optimizing towards those variables.”

The value per incremental go to (CPIV) mannequin

AdTheorent utilized its value per incremental go to (CPIV) advert pricing mannequin for the Goodwill marketing campaign. The CPIV pricing mannequin ensures that manufacturers solely pay for incremental foot visitors ensuing from advert publicity. AdTheorent works with a third-party measurement companion that uses know-how which allows them to decide whether or not an advert drove somebody to go to a retailer.

“There are digital IDs that were exposed to the ad and we share that with our partner,” explains Lawson. “Our partner has a very large panel and when there’s overlap they can determine the visitation of their panel and extrapolate the conversions of the exposed panelists to the broader audience to determine the incremental lift caused by seeing the ad.”

AdTheorent is paid per incremental go to based mostly on the third-party report. “If we don’t drive visits, we don’t get paid,” says Lawson. “The key to being able to do this is in making sure you have enough scale and enough data, so you can be confident that the models will determine or detect correlations that will drive performance.”

AdTheorent has guidelines round which sorts of campaigns are eligible for CPIV pricing. They get reporting all through the marketing campaign from their visitation companion and supply a wrap-up report to the shopper on the finish of the marketing campaign which breaks down issues like day of week, time of day, high performing segments and demographics.

adtheorent sample report, product screenshot

Sample AdTheorent Report

Lawson defined that they negotiate the CPIV prematurely with every shopper and advocate a minimal six-week period for each marketing campaign, so the software program has time to be taught what works.

“Models, by their very nature, need to learn,” Says Lawson. “Oftentimes in our campaigns, the first couple of weeks are the learning period though this could be a shorter or longer period of time.”

Goodwill’s optimistic outcomes

In Goodwill’s case, the mixture of machine studying and a hyper-targeted geofencing strategy drove good outcomes when it comes to getting individuals into their native Goodwill retailer.

As talked about above, one of many key targets of the marketing campaign was to generate consciousness about Goodwill’s mission. Goodwill did this by way of the marketing campaign artistic items utilizing the message “Shop Goodwill, Bring Good Home.”

The adverts linked to the Bring Good Home web page on the place customers may examine Goodwill’s mission and think about a wide range of content material together with a video and a graphic.

Goodwill was proud of the outcomes of this marketing campaign which far exceeded their expectations. AdTheorent delivered a 470% raise in incremental visitation at almost 80% lower than the contracted CPIV. While these outcomes have been greater than passable, additionally they realized so much from AdTheorent’s data-driven, machine studying strategy to serving adverts.

“The learnings will inform how we continue to advance our outreach beyond this single campaign,” explains Kuhn. “This marketing campaign is refining the expectations we set for all of our geotargeted efforts. We noticed intel that was counter-intuitive from what we all know. That is that the information confirmed a rise in guests on Monday and Tuesdays versus weekends when extra opportunistic consumers go to Goodwill stores.

We realized the true value and influence variations between an ordinary geotargeted “store visit” and those who symbolize an ordinary raise in addition to a behavioral raise. These insights are extraordinarily useful in attribution of our advertising and marketing efforts, which we now have not had beforehand, and we plan to discover in rather more depth.”

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