Case Study: Optimising Amazon Advertising Performance with Dayparting Strategy

This case study explores the impact of a dayparting strategy on Amazon advertising campaigns for a retail client. Dayparting involves adjusting ad budgets based on performance metrics throughout different times of the day and specific days of the week to maximize efficiency and returns.

Background:

Upon analyzing historical campaign data, it was observed that the Advertising Cost of Sale (ACOS) was unfavorably high during the early hours of the day (12:00 AM to 08:00 AM) and on certain days of the week (Mondays and Thursdays). The objective was to optimize ad spend to improve conversion rates and lower ACOS.

1. Strategy Implementation:

Hourly Budget Adjustment

Budgets were restricted from 12:00 AM to 08:00 AM, reallocating funds to higher-performing hours of the day.

Daily Budget Allocation

The daily budget was scaled down to $200 on these lower-performing days. Conversely, on days with higher conversions and lower ACoS, the budget was increased to $400, above the average daily budget of $300.

2. Results:

Following is the comparison data before (1-15 Feb) and after (15-29 Feb) the implementation of the strategy:

                       Impressions   Clicks  CTR     Spend          CPC    Orders    Sales         ACOS

01 - 15 Feb      3,064,977    11,129 0.36%    $3,748.70    $0.34    320      $14,039        26.70%

15 - 29 Feb     3,153,309     12,717 0.40%   $3,988.30    $0.31    483     $21,496.16    18.55%

Key Wins

Enhanced Efficiency: The budget reallocation to more optimal times and days resulted in an improved click-through rate (CTR), from 0.36% to 0.40%.

Cost Savings: The average cost per click (CPC) decreased from $0.34 to $0.31, indicating a more cost-efficient use of the advertising budget.

Sales Increase: Total sales surged by over 50%, indicating a direct correlation between the dayparting strategy and the conversion rate.

ACOS Improvement: A significant reduction in ACOS was observed, dropping from 26.70% to 18.55%, reflecting a more profitable advertising approach.

Following are the screenshots of the advertisement page for reference:

Sales Before implementing the Strategy

Sales After implementing the Strategy

3. Flow of the Strategy: 

Data Analysis Phase: 

Campaign data was meticulously reviewed on an hourly basis and daily basis to identify performance trends throughout the day.

Insight Generation:

Identification of Low-Performance Intervals and Day-Specific Patterns:

Budget Reallocation:

The budget was cut during the early morning hours and on specific low-performance days. Conversely, the budget was increased during the peak performance hours and on days with higher conversion rates.

Monitoring Changes: 

After the implementation, the campaigns were closely monitored to ensure that changes were taking effect as expected.

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