Coding creative memes

If an ad campaign ran, it’s because someone had an idea that they thought would work. Therefore most creative analysis is deductive: how did the thing I tested perform? If you’re smart you already tagged everything you care about in the campaign’s URL parameters. Understanding if ‘luxury’ outperforms ‘nightlife’ for your travel startup can be done with a find function and a pivot table.

However the most valuable insights often come from unstructured data — the patterns that emerge that weren’t on your radar, are the most important for you to see. If most of your best performing ads had ‘desks’ in them, you should cater more to business travellers. Inductive coding is a process for tagging unique ad creative with consistent labels that can be compared to find patterns.

Start by selecting a small sample (10%) of your campaigns and create codes (labels) that will cover the sample. Too many categories makes comparison impossible, so start broad (atmosphere, location, quality) and drill down deeper later. Select a new sample and apply the codes you created, adding new codes or consolidating where useful. Repeat, until you’ve coded all your campaigns.

This can be a lengthy and manual process, but it gives you an unfair advantage: the best creative performs 10x better, and this increases your odds of finding it. Once you’ve sorted your data into categories, combine it with performance data to start drawing conclusions. What labels appeared most and least often, and how did performance differ? Any key insights should inform future A/B tests, so you can validate your findings.

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