What is AI-powered campaign automation and optimization?
Anusha | March 23, 2022
Artificial intelligence (AI), machine learning (ML), and data-driven automation and optimization pop up in marketing materials for ad tech partners a lot, often promising outsized returns on investment. But what exactly do these words mean for Amazon sellers, especially in relation to their advertising campaigns?
In this post, we’ll go into more depth about what we mean when we say our platform uses AI, ML, and data-driven automation and optimization, and how it can power your Amazon ad campaigns to grow sales and revenue.
How are artificial intelligence and machine learning used in advertising?
In advertising, artificial intelligence and machine learning are powerful computer algorithms that optimize campaigns with data derived from trillions of combinations of ad attributes like product listings (ASINs), ad types, keywords, bid amounts, and more to reach goals like increasing sales, maintaining total advertising cost of sale (TACoS), hitting share of voice and more.
Why are artificial intelligence and machine learning important?
These are the core technologies powering the world’s best platforms, from media (e.g., Netflix), information discovery (e.g., Google Search), and e-commerce (e.g., Amazon) that require massive amounts of data to make almost divination-like recommendations to users. Sellers must keep in mind that platforms are not neutral arbiters; they are businesses that are working to increase their own revenues, and none more so (and with more data) than Amazon.
Often, the platforms do align with your goals (e.g., if you’re a credible source you will rank highly on Google, or if your products are of quality, drive high sales, and collect amazing reviews, Amazon may place you higher in organic results), but they’re never completely aligned. Amazon, for instance, experienced more advertising revenue growth in Q2 2021 than growth in retail sales. This is indicative of a shift in priorities to services rather than owned e-commerce and sales…services that are sold to sellers like you.
How does Quartile’s AI-powered platform work for sellers?
Quartile’s core AI and machine learning are purpose-built to drive more sales, but also deploy algorithms that optimize sales within constraints like budget, total advertising cost of sale (TACoS), the share of voice, and more (including a soon to be released margin-based optimization). These algorithms work similarly to those of the tech titans mentioned earlier and rebuild campaigns based on your products and historical sales data in your Amazon seller accounts or other retail sites, like Instacart.
A key difference between human-built and AI-built Amazon campaigns is the decisioning power. Decisioning power is the capacity of a person to manage and optimize campaigns. When any seller starts on Amazon, with a couple dozen products, campaign management and the decisions necessary to optimize them and get a return on investment seem almost easy. As sellers grow their product catalogues and scale campaigns/ad spend to maintain sales growth, these campaigns become unwieldly, requiring extra help or an outside agency to manage. Quartile’s AI-built and optimized campaigns do not have constraints on decisioning power, enabling one-to-one campaigns to ASIN structures that target individual keywords more effectively, increasing sales, and lowering TACoS as the system learns and continues to optimize.
As illustrated above, Quartile’s AI-powered platform automates and multiplies the number of campaigns without any limit to its decisioning power, freeing up sellers to focus on creating more granular goals and expanding their product catalogue. This exponentially increases the data points that feed into the platform, adding to a flywheel effect of more data to optimize campaigns.
That last sentence is an extremely important part of how and why so many clients see success with our platform. While we only highlight twelve ASINs above, the same structure can be built for thousands, or millions, of product variations (e.g., color, size, price). Every variation leads to more campaigns, leading to more data, and every data point adds to the optimization power of our platform. While some clients see success in as little as a week, most, especially those with less money to spend on ads, fewer organic sales, or a limited number of products, need around 3 months to accumulate enough data for the algorithm to work, which we’ll explore in our next post.
Ready to check out the power of our platform for yourself? Schedule a demo today and get a custom walkthrough of your Amazon Sellers account!
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