amazon affliate

So, Amazon DSP allows brands to leverage Amazon’s data intelligence to reach audiences off Amazon, and the potential to reach users on Amazon-owned properties. We already talked a bit about targeting, but why is Amazon so good at it? Amazon was an early adopter to Big Data. They have been refining their data analysis methods since as early as 2003 and show no signs of stopping. What makes this data especially valuable is that it is about purchasing behaviour. ‘Google knows what you search, Facebook knows what you like, but Amazon knows what you buy.’ Amazon has made a business of knowing the who, what, when, why (or why not) and at what price of e-commerce. Well enough to both predict and influence shopping behaviour. Specifically, Amazon uses Pixel Based targeting which is behaviour tracking triggered by visiting a website (or specific pages) or performing certain actions online. As important as the quantity and quality of data is the ability to interpret it in meaningful – and marketable – ways. Like creating lifestyle groups such as vegans, foodies, or fishermen. Part of how Amazon manages to interpret this data is through a Collaborative Filtering Engine which groups activities and data points into sets. A super simple example: If Tom and Jerry both demonstrate an interest in luxury cat toys and premium yoga mats, then Tom also expresses interest in a reusable bamboo coffee cup, it is possible – even likely – that Jerry will too. This targeting method is called ‘Audience Lookalike’. Now apply this logic with the knowledge that Amazon has hundreds of data points for millions of people. With a constellation of different online activities combined with the predictive power of collaborative filtering, Amazon is able to create detailed consumer profiles. With these insights, brands can avoid making (potentially false) assumptions about their prospective customers. The same logic is behind Netflix’s recommendation algorithm: Netflix uses your past browsing and watching behaviour in combination with others’ to predict what you would like to watch next. The more you watch, the more informed (and more accurate) the algorithm becomes. The same is true for Amazon, except that there are many activities that may feed the algorithm. Remember that Amazon is way more than a selling platform. Of course, Amazon’s extensive reach, on and off the marketplace itself, is as much of a boon to ad distribution. Who can you reach with Amazon DSP Ads? Lifestyle, Contextual, Remarketing, Behavioural, Advertiser Audience, Audience Lookalike Amazon offers targeting based on a combination of the following factors: Imagined Product: Sally’s Avocado Slicer Targeting Type Description Individual Example Behavioural Groups who have displayed specific behaviours, such as buying or browsing similar items recently. A user who visited the sub-category ‘Graters, Peelers, & Slicers’ on Amazon last week. Lifestyle Groups who have displayed behaviours that, when understood as a whole, suggest a certain (common) lifestyle. Vegans, vegetarians, foodies. Contextual Groups who demonstrate an interest in your product by visiting websites thematically related to your product. A user browsing a guacamole recipe. Remarketing Groups who have come close to buying your product or a competitive product, a.k.a. ‘in market’ audiences. Users who added your competitor product ‘multi-fruit slicer’ to their shopping cart without buying. Audience Lookalike Groups of customers who behave similarly to selected groups. Such as a brand’s customers or competitor’s customers. Users who are similar to people who like Sally’s Avocado Slicer on Facebook. Advertiser Audiences Relevant groups (customers or prospective customers) provided by the brand. Visitors to Sally’s A