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.
- 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.
- 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
- 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.
.svg)
.avif)
.svg)
