Overlap Analysis

Author: Robin Jia，Tommy Lin

Last Update：2024/06/14

 

1. Model Introduction

The Overlap Analysis model is mainly used to quantitatively analyze the audience coverage and conversion of different ads. By calculating the audience overlap of different ads, the uniqueness and complementarity of ads can be examined. At the same time, by comparing indicators such as the audience scale and conversion contribution of each ad, the delivery efficiency of different ads can be evaluated. This model supports customizing ad sets at different granularities and flexibly adjusting the conversion type and time window for analysis, meeting the needs of ad strategy optimization in different business scenarios.

Through this model, the following business questions can be analyzed:

• Is there significant overlap in the audiences covered by various ads? What is the independent contribution of each ad?
• Which ad combinations have the best synergy and can bring the highest conversion benefits for my brand?

 

2. Model Interpretation

This model mainly consists of three parts. The data cards at the top represent the overview of the current ad data being viewed and the totals of various data. The collection graph section uses the area of circles to represent the size of each ad's data under the currently selected data metric and the size of the data overlap relationship between them. This section mainly focuses on absolute value-related metrics. The bar chart section represents the data performance of ads independently or in intersection. This section mainly focuses on calculated metrics.

In the model's top menu, the predefined model is for fixed Amazon users and all ASINs under the store. The time range selector can select data by month for viewing.

The number of cards in the model's upper section is determined by the number of selected collection dimensions. When one collection dimension is selected, there is 1 card; when two collection dimensions are selected, there are 4 cards; when three collection dimensions are selected, there are 8 cards. The download button in the upper right corner of the data cards can download the data table of the model.

The default data metric for the data cards and collection graph is the number of users. Click the edit button to expand the sidebar. Here you can replace the metrics in the data cards and collection graph. You can also select the ad collections currently displayed, supporting the selection of 1-3.

The collection graph shows the distribution of independent covered users and jointly covered users of each ad from different perspectives. By observing the size of the areas in different regions, you can discover the differences in the independent reach ability of each ad, as well as the degree of overlap between ads in terms of audience coverage.

The filtering condition section further filters the selected ad collections. When choosing to exclude a certain ad, all data related to that ad will be excluded, including the part that overlaps with other ads. If you want to see users who are only reached by a single ad and not reached by other ads, you can use this filtering function.

In the collection graph below, when hovering the mouse, the corresponding data will be highlighted in the cards above and the bar chart on the right. This function can be used to see the magnitude and metric performance of the selected area.

The bar chart further compares the effect performance of different ads (combinations) from the conversion perspective. Among them, the conversion contribution of a single ad represents its marginal contribution ability to the overall, while the conversion contribution of ad combinations reflects the combination effect. Through cross-comparison, the most valuable ad combination forms can be found. More data performance metrics can be switched above the bar chart.

 

3. Model Customization

The custom model conditions of this model provide the function of filtering by ad account and support Amazon Purchase Data Insights. The ad section below can customize ad groupings. By default, it counts separately by ad type (DSP, SP, SB, SD). Custom sets can also be selected, with a maximum of 5 different groupings defined.

Click the edit icon to select the ad campaigns included in the ad grouping. Note that a single ad grouping can only include ad campaigns under the same ad type.

 

4. Model Data

This model is based on Amazon's attribution mechanism and defines different reach conditions for different ad types. Users who do not meet the reach conditions will not be counted in the data dimension. DSP-type ads use exposure as the reach condition, while SP, SD, and SB-type ads use clicks as the reach condition.

Based on advertising delivery and user behavior data, in specific analysis, different businesses can utilize the rich configuration items provided by the model to customize analysis plans according to actual focus points. For example:

• You can choose to focus on the exposure overlap or click overlap of users between different ads. The former can examine the overall reach range, while the latter can focus on high-intent audiences.
• You can adjust the number of ads included in the analysis. You can compare different ad types (SP, DSP, etc.) at a macro level, or focus on analyzing strategy combinations (Video, Display, etc.) under specific ad types.
• You can switch between different conversion goals (overall conversion, new customer conversion, etc.) to examine the effect differences of ad combinations in different conversion scenarios.
• You can select different time windows to evaluate the stability of combination effects from short-term and long-term perspectives.

Glossary

Type	Term	Description
Dimension	Group	Overlap Ads collection.
	Ads Account	Advertiser of DSP or entity of Sponsored Ads.
Metrics	UV	Unique Viewer
	Group UV	Deduplicated number of grouped users.
	Total Cost	Total Cost of ads
	Total NTB Product Sales	Total New-to-Brand Product Sales
	Total NTB Purchase	Total New-to-Brand Purchase
	Total NTB Purchase UV	Deduplicated number of new-to-brand purchase users
	Total Product Sales	Total Product Sales
	Total Purchase	Total Purchase
	Total Purchase UV	Deduplicated number of purchase users
	Total ATV	Total Average Transaction Value (Total Product Sales/Total Purchase UV)
	Total CPP	Total Cost per Purchase (Total Cost/Total Purchase)
	Total CPP UV	Total Cost per Unique Viewer Purchase (Total Cost/Total Purchase UV)
	Total NTB CPP	Total Cost per New-to-Brand Purchase (Total Cost/Total NTB Purchase)
	Total NTB CPP UV	Total Cost per Unique Viewer New-to-Brand Purchase (Total Cost/Total NTB Purchase UV)
	Total NTB PR UV	Total Unique Viewer New-to-Brand Purchase Rate (Total NTB Purchase UV/Reach UV)
	Total NTB ROAS	Total New-to-Brand Return on Ad Spend (Total NTB Product Sales/Total Cost)
	Total PR UV	Total Unique Viewer Purchase Rate (Total Purchase UV/Reach UV)
	Total ROAS	Total Return on Ad Spend (Total Product Sales/Total Cost)