A/B testing for even better beauty sampling campaigns
In marketing, we are constantly testing everything, from brand messaging, to email copy, to ads and website design elements.
The data we gain from testing allows us to make data-driven decisions and constantly improve our campaigns and strategies based on the facts of what works.
So how does this apply to product sampling campaigns?
What is A/B testing?
An A/B test is a randomised experiment which involves changing one variable (eg. an email subject line) to create two (or more) variants of an asset and comparing performance (eg. open rates of the email).
Benefits of testing in your sampling campaigns
Products sampling campaigns have evolved a long way since brands first started giving out small cosmetic samples in supermarkets several decades ago.
In digital sampling campaigns, A/B testing can be carried out just like any other digital campaigns. Meaning you can test, learn and optimise your way to higher engagement, lead generation and sales conversions from sampling.
Increased performance
A/B testing helps increase campaign performance by demonstrating - with data - the marketing strategies and products consumers prefer. Applying the learnings from your tests to future campaigns will make them more successful.
You can test to optimise for whatever metric is important for your current strategy.
Some examples:
Reduce costs / better campaign efficiency
A/B testing is ultimately an exercise in campaign efficiency.
You can hone in on the most compelling style and content of marketing and product sampling campaigns.
This can reduce future campaign costs by only running campaigns that you know are effective and that yield a good return on investment.
Things to test in a sampling campaign
Channels
Running your sampling campaigns across different channels (probably something you’re already doing!) can quickly give you insight into where your ideal customers are the most engaged.
Bear in mind that which channels come out on top could be different for different campaigns types/audiences.
Ad creative and messaging
Imagery, copy, colours, video etc. Do your customers respond more to science-backed product claims, or influencer testimonials of your product? Test it! Bright eye-catching ads or a more modern muted palette? Test it!
Different products
Offering multiple products in a sample campaign is a great way to test what is resonating more with your customers.
Be prepared to manage the fulfilment discrepancy this may create if one option is the clear winner.
Launch time
Often forgotten, the time a campaign launches can have a huge impact on performance, and is a really crucial learning for future campaign efficiency.
Personalisation
Personalisation is a standard practice for marketers now, and tried and tested, we know it works. But the extent of your campaign personalisation should be carefully tested, in a world where consumers are increasingly more concerned about data protection.
It can be a fine line between personalising an email, and your message seeming ‘creepy’.
Things to remember
- Only change 1 thing. Each test should have a specific variable linked to a specific outcome so you can clearly see what has impacted performance.
- Be clear on exactly what you’re testing and how you will measure which variant wins the test.
- Be open minded. We don’t always get the results that we expect. But this is exactly why we test - because we learn!
In marketing, we are constantly testing everything, from brand messaging, to email copy, to ads and website design elements.
The data we gain from testing allows us to make data-driven decisions and constantly improve our campaigns and strategies based on the facts of what works.
So how does this apply to product sampling campaigns?
What is A/B testing?
An A/B test is a randomised experiment which involves changing one variable (eg. an email subject line) to create two (or more) variants of an asset and comparing performance (eg. open rates of the email).
Benefits of testing in your sampling campaigns
Products sampling campaigns have evolved a long way since brands first started giving out small cosmetic samples in supermarkets several decades ago.
In digital sampling campaigns, A/B testing can be carried out just like any other digital campaigns. Meaning you can test, learn and optimise your way to higher engagement, lead generation and sales conversions from sampling.
Increased performance
A/B testing helps increase campaign performance by demonstrating - with data - the marketing strategies and products consumers prefer. Applying the learnings from your tests to future campaigns will make them more successful.
You can test to optimise for whatever metric is important for your current strategy.
Some examples:
Reduce costs / better campaign efficiency
A/B testing is ultimately an exercise in campaign efficiency.
You can hone in on the most compelling style and content of marketing and product sampling campaigns.
This can reduce future campaign costs by only running campaigns that you know are effective and that yield a good return on investment.
Things to test in a sampling campaign
Channels
Running your sampling campaigns across different channels (probably something you’re already doing!) can quickly give you insight into where your ideal customers are the most engaged.
Bear in mind that which channels come out on top could be different for different campaigns types/audiences.
Ad creative and messaging
Imagery, copy, colours, video etc. Do your customers respond more to science-backed product claims, or influencer testimonials of your product? Test it! Bright eye-catching ads or a more modern muted palette? Test it!
Different products
Offering multiple products in a sample campaign is a great way to test what is resonating more with your customers.
Be prepared to manage the fulfilment discrepancy this may create if one option is the clear winner.
Launch time
Often forgotten, the time a campaign launches can have a huge impact on performance, and is a really crucial learning for future campaign efficiency.
Personalisation
Personalisation is a standard practice for marketers now, and tried and tested, we know it works. But the extent of your campaign personalisation should be carefully tested, in a world where consumers are increasingly more concerned about data protection.
It can be a fine line between personalising an email, and your message seeming ‘creepy’.
Things to remember
- Only change 1 thing. Each test should have a specific variable linked to a specific outcome so you can clearly see what has impacted performance.
- Be clear on exactly what you’re testing and how you will measure which variant wins the test.
- Be open minded. We don’t always get the results that we expect. But this is exactly why we test - because we learn!
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