What if you are asked to keep burning cash on multiple ads recommending a product and never able to know which ad is performing worst or bringing you the highest revenue?
In marketing, we call that the Attribution problem.
When running ad campaigns on Google and Facebook, it's possible that Google Analytics or Facebook Reports may not be able to accurately assign conversion credit.
Because both platforms don't own the transaction data and they have to rely on referrer URLs or third-party data to categorize a conversion.
It's a major headache for eCommerce marketers to run cost-efficient and targeted marketing campaigns as the increasing restrictions on accessing third-party data is creating more ambiguity for them to understand customer behavior and create specific buyer personas as they will never be 100% sure which ad triggered the click and resulted in a purchase.
That's where Amazon literally kills Google and Facebook.
Because Amazon owns the customer data for the end-to-end marketing funnel from product search (advertising data) to purchase (transaction data) as it is the cash register.
So, when marketers run an ad on the Amazon marketplace, AI and machine learning algorithms can accurately track shoppers' activity on the site, recommend a product, and tag it as a conversion if it results in a purchase.
Further, after every transaction, Amazon's AI collects a series of data and utilizes that knowledge to help retail marketers target and sell to the next consumer.
Also, Amazon's AI can optimize each marketing campaign in real-time to maximize the likelihood of a customer buying a product recommended to them.
That's how Amazon creates a win-win situation for marketers by optimizing every dollar spent on marketing.
Divyesh is a senior copywriter at ewiz commerce, responsible for creating original content and distribution strategies for website, social, and paid marketing channels. He keeps track of hot digital trends and latest technology stuff and likes writing digestible stories around AI and eCommerce space.