For decades, marketers and advertisers relied almost exclusively on audience targeting data to help them make decisions about which ads to run and where. It made building ad creative and buying ad space very easy.
If you knew the previous purchases and user behavior of someone who looked like your customers demographically, you could predict with near certainty the chances of them buying your product or service. All you had to do was serve those who were most likely to convert the right ad at the right time — all information marketers had at their disposal, thanks to audience targeting.
But in recent years, the importance of user privacy has rightfully started to outweigh the needs of marketers. Companies and governments have implemented mandates, preventing invasive audience targeting. The introduction of Apple’s tracking opt-in inside iOS 14, the California Consumer Privacy Act (CCPA), and the General Data Protection Regulation (GDPR) are all a direct result of this shift away from mining user data for commercial use.
Creative intelligence, on the other hand, has always been more of a nice-to-have, rather than an innovative decision-driving tool.
But now, two factors are turning creative intelligence into the new must-have for marketers:
This isn’t to say that the art of crafting ad creative is dead. There will always be a need for brilliant art directors and copywriters to develop the concept and design the execution. But to build better creative you need deep, solid creative intelligence.
The creatives behind our favorite ad campaigns are beginning to look more like scientists and engineers than ever before. And they’re backing their art with science; not just by testing one ad concept against another.
Using an ad creative testing approach called multivariate testing (MVT), today’s most innovative marketers test ad creative at scale and get insights into what’s working — and what’s not — right down to the headlines, images, and background colors.
Multivariate testing measures the performance of every possible combination of creative variables. Variables are any single element within an ad — images, headlines, logo variations, calls to action, etc.
For example, let’s say while concepting an ad campaign, your creative team came up with the following:
4 headlines
3 images
2 background colors
3 calls to action
To run a multivariate test against these assets, you’d build an ad for every possible combination — all 72 of them (4x3x2x3) — and test them against each other.
There are insights you can only learn from testing in this way. From the test above, for example, you might learn things like:
Test ad creative against other ad creative
Measure how well ad creative performs against a goal (conversions, engagement, etc.)
The number of ads typically run in each test
The state of the variables in each test
The granularity of the results of each test
Number of ads per test
2-3
Tens or hundreds
State of variables in each test
Very few or zero variables are controlled
Example: Two distinct ad concepts, each with different image styles, typography, headlines, and color palettes.
All variables are controlled
Example: 12 ad designs featuring every possible combination of two headlines, three images, and two background colors.
Granularity of results
Macro: solely measures the performance of ad against ad
Tells you which ad won but cannot reveal why
Micro: measures the performance of every ad against every other ad and every element within each ad against every other version of that element
Tells you how each ad, and each element of each ad, performed
Best for
Understanding which overall ad concept performs best
Understanding which ads and which elements within your ads perform best
whether or not a variant group has reached high confidence
if further testing for a certain variant group is necessary
whether repeating the test again would result in a similar distribution of data
when you have enough information to move on to your next test
one variant or variant group is the all-time best (or worst)
a variant group will always (or never) impact your KPIs
there’s no need to challenge winners in subsequent tests
0–55% confidence; fluctuations in performance are likely due to chance
further testing for this variant group is necessary
you do not have enough information to move on to your next test
try testing variants with more substantial differences between them
56–79% confidence; fluctuations in performance might be due to chance
further testing for this variant group is necessary
you do not have enough information to identify a definitive winning or losing ad or creative element
try looking at another KPI or continue to put spend behind this test to reach high confidence
80–100% confidence; fluctuations in performance are not due to chance
further testing for this variant group is not necessary
if enough variant groups are green, you have enough information to move on to your next test
continue to challenge winning elements and drop low performers in future tests
Winning headlines can be applied to your home page and landing pages
Winning images can be used to inform future photoshoots
Winning colors can be incorporated into your packaging
Product in packaging
Product in packaging with props
Product in packaging on white
Product in packaging on black
Product out of packaging
Product out of packaging with props
Outdoors
Indoors
Model applying product
Model holding packaging
Model w/ face cropped from image
Model with face in view
Smiling models
Serious models
Facial close-ups
Hand close-ups
Smiling models
Serious models
Variable elements are ones you want to test.
Fixed elements are ones you want to keep the same across every ad variant.
Typical cadence
Weekly (though some Marpipe customers with larger testing budgets run two 7-day tests per week)
Bi-weekly
Budget
Smaller (typically 1/52 of your overall ad creative testing budget)
Larger (typically 1/26 of your overall ad creative testing budget)
Volume of variants
Fewer variables and ad variants (smaller budget = fewer variables)
More variables and variants (larger budget = more variables)
Best for
Collecting quick creative intelligence on incremental changes
Finding the best version of an ad that’s already working
Testing net-new creative ideas
Testing ad creative that must perform during a finite window of time (product launch, holiday ads, etc.)
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