Experiment and channel count impact: Past 180 days channel and audience analysis

In our recent deep dive covering the last 6 months (December 2023 – June 2024) into the correlation between experiment count, channel count, and ROI, we’ve uncovered some compelling insights about optimizing marketing strategies. Here’s a breakdown of our top findings:

  1. Higher Experiment Count Boosts ROI: Companies running 1001-2000 experiments saw the highest ROI, especially when utilizing 2 channels – a whopping 17.57 average ROI!
  2. The Magic of Multiple Channels: Utilizing more channels generally increases ROI. For experiment counts of 500-1000, using 2 or 3 channels resulted in an average ROI of around 12
  3. Quality over Quantity: Surprisingly, companies with the highest number of experiments (5001-10000) did not necessarily see the highest ROI. It highlights the importance of a focused and optimized approach over mere volume.
  4. Optimal Channel and Experiment Count Combination: The data suggests that combining an experiment count of 101-500 with just 1 channel can yield an impressive average ROI of 9.47, indicating a sweet spot for ROI efficiency.
  5. Experiment and Channel Count Correlation: There is a positive correlation between the number of experiments and channels used, particularly in the mid-range of experiment counts (101-2000). This synergy appears to optimize ROI effectively.
🔍 Breakdown by Experiment Count Range:
Notes:
  1. Experiment refers to one unit of an ad (audience + creative + Offer).
  2. Channels included in this study were Linkedin, Facebook, Instagram and Google Ad words
Download the Past 180 days channel and audience analysis

More like this

Ad Benchmarks

Exploring the Impact of Ad Formats Across Different Channels at Metadata.io

At Metadata.io, we track and analyze the performance of various ad formats on different social platforms to optimize our marketing strategies.
Paid Ads

What We Learned From $130M in Spend in A Down Economy

Metadata customers have spent nearly $130M in advertising over the past year.
Ad Benchmarks

Audience types and channels

This analysis focuses on identifying the best combinations of audience types and channels for running advertising experiments in B2B marketing.