Unveiling the Value Behind Amazon Marketing Cloud (AMC)

2021-10-25 08:01

Nowadays, big data can help us analyze the marketing results of different media channels and the moment ads make contact with target audiences, helping us understand the habits of different users and interpret the same data through various dimensions to produce different insights.

Chinese companies and sellers going overseas are becoming increasingly keen in using big data modeling to accurately monitor the effects of different forms of advertising and understand the preferences and behavior habits of overseas consumers, especially for complex advertising attribution problems. For example, within the Amazon ecosystem, if consumers see an SP search ad, then a DSP display ad and finally place an order in search ads, how should this conversion be counted?

Amazon launched the Amazon Marketing Cloud (AMC), a solution for overall measurement and analysis with the intention of helping sellers and marketers measure the effectiveness of different media channels such as search advertising, display advertising, video advertising, and OTT TV advertising through dimensional and granular data analysis. Unlike data that sellers see from Amazon Advertising or the DSP backend, AMC data can be refined to the user level (User ID) and log-level.

Built on Amazon Web Services (AWS), AMC provides advertisers with flexible and transparent cross-channel data for more precise marketing decisions. In other words, AMC relies on AWS cloud computing services, whose security, compliance, big data analysis and management capabilities ensure the efficient operations of AMC. In the secure and privacy-protected cloud environment, advertisers can easily analyze multiple anonymous data sets and generate summary reports. Although the data granularity of the AMC platform is specific to each user, all information in the AMC is processed in strict accordance with Amazon's privacy policy where the anonymous summary report can only be accessed from the Amazon Marketing Cloud (AWS) and is unable to provide any personal user data.

AMC's analytical capabilities help sellers and advertisers conduct in-depth analysis of required information, provide a comprehensive view of campaign performance, evaluate complex attribution problems and the advertising effects of various media channels. What is more, AMC provides users with open APIs and UIs to complete data collection and analysis. Apart from Amazon Advertising campaign metrics such as displays, clicks and conversions, an advertiser’s own data sets can also be inputted. This way, the AMC report can further analyze the performance of advertising data and help sellers make wiser decisions for each cross-channel marketing placement.

AMC’s primary advantage lies in its ability to perform customized data analysis based on advertising goals, strategies and channels; including the strategy adjustment of advertising operations within each channel, conversion path and window analysis. It is also possible to develop custom attribution models to clearly understand which channels or ad formats have had the most influence on target audiences. Let’s explore some actual cases to better understand the significance of data analysis:


Optimal Frequency Analysis Module
We analyze the relationship between advertising frequency and click-through rate, and adjust advertising settings at any time according to the performance of different products at different stages to optimize the overall performance.

The above figure shows the performance of a customer at the conversion stage. The conversion rate is at the highest after the first ad exposure. As exposures increase, the conversion rate decreases accordingly and sees a steep decline after the fifth exposure. In other words, at the conversion stage, six exposures will achieve a desirable conversion effect.

Since the consideration stage is mainly used to attract potential consumers to learn about the product and brand, we take DPVR (the conversion rate to DPV) as the main assessment goal. The data analysis in the above figure also shows that the highest DPVR was obtained in the first exposure, and the conversion rate gradually weakened as the number of times increased. We can conclude that during the consideration stage, the advertising efficiency is higher when the number of audience contacts is less than 3 or 4.

User Path to Conversion
The analysis of conversion paths is mainly used to observe the actions consumers take from the first time they’re exposed to an advertisement to completing a purchase. This also helps us gain an in depth understanding of consumer preferences and behavior habits at different stages and channels to further analyze the impact of these on the conversion at different points in time.

As shown in the figure above, the left side is the channel for first touch, and the right side is the channel in which users place orders. Let’s take placing an order on Amazon as an example. With the help of AMC’s conversion path analysis, we can see from right to left that consumers who place an order on Amazon often visit news and email pages as well as entertainment websites along with other apps. This means that when launching advertisement campaigns, we implement channels on and off the Amazon ecosystem to cover a wider range of target audiences and expand the upper level of the marketing funnel to obtain more traffic.

In daily operations, we find that brands tend to pay more attention to the retargeting stage than the traffic penetration of the whole path to purchase. The case analysis in the image above also showcases how covering all stages of the funnel from initial touch point to consideration to conversion will yield much higher conversion rates in the long run compared with focusing on the first two stages only.

By analyzing the full path of conversion via AMC, we can also adjust the budget ratio in time for more consumer-focused paths. Allowing for continuous analysis of different audience groups and advertising spaces as well as data tracking throughout the entire process to attribute the conversion effect and improve advertising accuracy.

Conversion Time Window Analysis
By analyzing the full path of conversion via AMC, we can also adjust the budget ratio in time for more consumer-focused paths. Allowing for continuous analysis of different audience groups and advertising spaces as well as data tracking throughout the entire process to attribute the conversion effect and improve advertising accuracy.

Analyzing the conversion window helps us understand when consumers convert after first exposure to the advertisement. As shown in the figure above, after the user is touched by the advertisement, its effect and impact on the user diminishes. This requires timely, daily adjustment of price settings for specific audience groups to maximize exposure probability and improve conversions.

Cross-channel Analysis
As mentioned earlier, many sellers encounter budget allocation, media channel and advertising efficacy questions. In response to these challenges, AMC's cross-channel advertising data analysis can help us allocate budget based on data driven decisions.

From AMC log-level data to data science modeling to the best budget combination, we are able to understand the impact of different advertising channels and formats on business growth and implement algorithms to effectively allocate the proportion of different channels to maximize growth opportunities.

All in all, AMC can deliver unique data reports and marketing results based on the customized needs of different sellers and advertisers, differentiated audience classification, diversified channel selection and complex attribution models. AMC can provide a comprehensive reporting guide for the analysis of advertising effects on and off the Amazon site.

At the moment, Xtream Marketing’s self-developed SaaS system, Xplatform is complemented with AMC capabilities. We help some of our leading clients carry out data analysis and refined operational management through AMC. While ensuring data security and user privacy, we hope to further unleash the power of data groups in the Amazon ecosystem and continue to empower advertisers' digital strategies to promote the long-term growth of brands.