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Shopping Behavior Data Catapults The Video Ad Targeting Formula

Catapult

Modern day shopping, whether it be online or in-person, creates a data stream that follows those purchases. It should be no surprise that this data matters. When you properly ingest shopping behaviors and leverage the right technology to empower your media buys, video ad performance will realize a measurable impact and sales lift. 

Which data sets are we actually talking about? 

Data points such as: what products are being searched for, in which geographies and at what times of the day; the frequency in which a particular product is searched for; and the categories of products that are often searched for together, can all be added into a bigger dataset, leveraged in a machine learning model and then utilized to predict the likelihood of sales conversions for strategically placed video ads. 

This combination of data-informed contextually relevant placements is the future of performance video advertising. Content, the datasets you utilize and providers you choose will be the difference between simply surviving or thriving in this ever-changing market. 

Individual data streams provide good insight, while more complex data streams and combinations help support the creation of sophisticated machine learning models to more accurately inform AI-driven media buying decisions. 

So, what sorts of datasets and methods are viable to future proof your media buying operation while improving performance?

Shopping behavior data is critical 

One way Precise TV helps businesses execute sale-securing media buys is through exclusive access to global Amazon shopping behavior data, such as product browsing, in-cart activities, review posting, and of course purchase data. The inputs are all provided by consumers, but the data itself is all 100% privacy compliant, non-PII (non-personally identifiable information).  

To that non-PII point, accessing privacy-compliant data that defines and pinpoints purchase intent behavior is key as the world collectively moves away from the use of cookie data. This approach is the best way for advertisers to securely pivot into modern “cookie-less” marketing methods, gain the trust of consumers and rid themselves of compliancy concerns.

When this Amazon purchase journey data is combined with Precise TV’s contextual machine learning models, we’re realizing tremendous increases driving sales results for our brand customers. We can now pinpoint which specific video placements hold the highest propensity for conversions and weight bidding based upon that probability score. In essence, reaching the highest valued consumers while they are consuming the highest valued (or most relevant) video, rather than just generalizing video ads to an overall channel. Early results show using Amazon’s behavioral consumption data drives a 43% higher chance of conversion. 

It’s worth noting that other retail data (Target, Walmart, etc), in addition to first party shopping behavior data from direct to consumer brands (via their own sites or Shopify), is all similarly viable to supporting machine learning models that can help inform business outcomes-focused media buys. 

Elvie: helping a challenger brand outflank the competition 

Precise TV is seeing great success leveraging our exclusive access to Amazon shopping behavior data for Elvie, a femtech company that produces breast pumps. Check out our Elvie case study which shows we’ve driven more than 3x ROAS (return on ad spend). Understanding what the shopper is consuming for education and entertainment video-wise greatly helps advertisers place an ad about breast pumps on the videos that are most relevant to the shopper, allowing them to engage in a purchase that actually helps them, rather than displaying an irrelevant ad that they might skip past.

Further, Precise TV was able to pinpoint specific videos where breast pumps were the focus – pre-birth preparation, the different week stages of birth, what to do with newborn babies, etc. Inserting Elvie adds against those video impressions, and consequently boosting Elvie’s search popularity by +44.7%. 

In summary, targeting specific video-level moments with contextually relevant ads and augmenting the targeting with the help of retailer shopping behavior data will dramatically increases product searches and subsequent sales. 

Please reach out to discuss how contextually targeting video at the placement level minimizes wastage and how adding exclusive shopping behavior data can help maximize your video ad performance.  

Topics: youtube, Google, privacy, advertising, contextual targeting, tiktok, CTV, facebook