How to effectively analyze Amazon advertising placement?
Analyze Amazon advertising placement effectively
As a seasoned operator in the cross-border e-commerce industry, it is said that it is not only necessary to accurately and efficiently place Amazon ads, but also to have an important skill, which is to effectively analyze the placement and see the results through data.
The significance of analyzing the effectiveness of ad placement is to better understand the entire ad placement cycle and assist operations in adjusting placement strategies. By using data analysis to solve the problem of “coarse placement” and promote the process of refined operation. Therefore, it is necessary to merge the data of all Amazon ad types, calculate advertising operating indicators in different dimensions, and observe the changing trends of various indicators on the timeline, so as to judge the effectiveness of advertising placement and improvement, and form warnings for abnormal indicators in a timely manner.
1. Data Cleaning and Analysis The main thing in analyzing the effectiveness of ad placement is to measure various dimensional indicators, such as:
1. Aggregate display volume, click volume, cost, order volume, sales volume, etc. according to ad campaigns, and use the aggregated data to calculate multiple indicators such as CTR, CR, ACOS, ROSA, etc.
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2. Conduct year-on-year and month-on-month calculations. 2. Data visualization for easy real-time monitoring
After analyzing the data, through the configuration of the dashboard and filter, data viewing dimensions can be flexibly switched, and key indicators and changing trends are clear at a glance, which provides a lot of convenience for subsequent judgment work.
3. Optimize ad placement strategies According to multi-dimensional measurement and analysis of various indicators, viewing the interactive dashboard can grasp the current status of ad placement in real time. With the reminder of data warning, the next step of optimizing ad placement strategy can be carried out. (1) Some key indicators:
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Ad data: Focus on analyzing the exposure volume, click-through rate, conversion rate, CPC price changes, and changes in the proportion of ad orders to the overall situation.
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Exposure volume: Exposure is the basis of our clicks and conversions, which is also a key indicator we focus on.
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Click-through volume and rate (CTR): Click-through volume is closely related to our orders. Assuming that our product conversion rate is 10%, then 10 clicks lead to one order. We need sufficient click-through volume to achieve our target ad order volume.
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Click-through rate: Click-through rate is one of the most important indicators of our ads. The click-through rate of most products needs to be above 0.4%. If our product click-through rate cannot reach this level, it is unqualified.
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Conversion rate: Conversion rate is our ultimate goal, which is to serve the conversion rate through category analysis, observation of QA to increase our influence, and optimization of exposure volume and conversion rate.
(2) Abnormal Data Warning and Strategy Adjustment It is also important to support setting data warnings according to indicators and changes calculated by various dimensions, which can remind us to optimize promotion strategies in a timely manner. Here are two examples that require setting warning values:
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When the conversion rate drops by a certain percentage or the advertising cost increases by a certain percentage, data warnings need to be set.
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In terms of keyword targeting, select keywords that have not yet been targeted but have reached a certain number of orders, supplement them with targeting, and observe their targeting effect in a targeted manner.
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