From 13 months to 5 years! Amazon advertising has undergone a major upgrade!

Amazon is about to launch another big move!

Not long ago, Amazon dropped a bombshell announcement at the CES show in Las Vegas – advertisers can query up to five years of shopping data through AMC (Amazon Marketing Cloud) !

Let me give you a brief introduction. AMC stands for Amazon Marketing Cloud. With the help of AMC, advertisers can easily obtain customer behavioral event data on Amazon, perform model analysis and generate aggregate reports.

In the past, AMC could only query 13 months of historical data . When formulating marketing strategies, advertisers were often limited by the short-term and fragmented nature of the data, making it difficult to fully present the long-term impact of some advertising campaigns .

Now after the upgrade, you can directly query up to five years of shopping data , which means that advertisers can track the entire shopping process of consumers in detail and conduct a comprehensive review of different advertising strategies implemented over the years .

Especially for seasonal sellers , unlocking five years of shopping data is a boon. Seasonal product sellers can find out the specific time preferences of consumers when purchasing products, and can also clearly see the sales start time of products related to specific seasons or festivals, the duration of sales peaks , etc.

Data transparency has multiple impacts on advertisers:

Gaining a deeper understanding of consumers’ long-term purchasing patterns, preference changes, etc. A longer time span can help more accurately capture the consumption cycle characteristics of various commodities.

For example, in the consumer electronics category , advertisers can see how long it takes consumers to consider replacing accessories after purchasing a mobile phone, or which groups of people respond first when the next generation of products is launched.

For household items , it is possible to know how often consumers replace bedding, furniture, etc., whether they make bulk purchases every two to three years, or whether they have different purchasing rhythms depending on the seasons and life scenarios.

Taking seasonal products such as ski equipment as an example, 5 years of data can clearly show the specific time points when consumers in different regions begin to pay attention to and purchase them each year, as well as the fluctuations in purchasing enthusiasm.

Five years of data provide advertisers with more sufficient materials to build detailed and accurate consumer portraits. Starting from multi-dimensional information such as the product categories, brand preferences, price ranges, purchase frequency, and repurchase status purchased by consumers, the huge consumer group can be segmented into sub-groups with different characteristics.

For example, for sports enthusiasts , it is possible to further distinguish whether they prefer outdoor sports or indoor fitness, whether they prefer high-end professional equipment or cost-effective basic products, etc. For beauty products , five years of data can show consumers' attempts at and changes in loyalty to skin care products with different functions and brands.

Data transparency has directly promoted the advancement of advertising strategies. Advertisers no longer need to blindly try different advertising combinations, but can lock in the most valuable target audience, delivery time period and advertising format based on accurate analysis of five years of data.

In addition, DSP advertising will also add the [ AMC crowd function] . The new function allows sellers to manage advertising more accurately, especially in DSP advertising. Through the AMC custom crowd function, sellers can use AMC to deeply analyze consumer behavior data and achieve more accurate advertising targeting.

In other words, the greatest value of the AMC population is to segment the different needs of customer search terms and deliver them precisely.

With the help of five years of data, we compared key indicators such as conversion rate, click-through rate, etc. under different advertising forms (such as display ads, search ads, etc.), different delivery channels (various sections within the site, off-site cooperation platforms, etc.), and different delivery budgets , in order to find the most cost-effective and highest return advertising model .

In addition, by digging deep into consumers' response patterns to new products, promotions, etc. over a five-year shopping history, advertisers can also uncover more potential marketing opportunities and plan more innovative marketing campaigns.

For example, if you find that certain niche but distinctive products have achieved explosive growth through specific marketing methods in a particular year, you can learn from this model and carry out targeted promotions for similar potential products to open up new marketing growth points.

It should be noted that this function is currently only available to some merchants.

[Query 5-year historical data function ] is currently in the testing phase, and only a small number of merchants can experience it first;

[ AMC crowd function] is also in the official internal testing stage. Currently, the only way to enable it is to cooperate with an advertising agency. You need to activate Amazon DSP advertising and meet certain conditions to use AMC. Interested sellers can contact the investment manager for more information.