Whether you want to leverage Facebook Advertising for audience growth, content promotion, or lead generation/customer acquisition, the key to success is isolating the audiences and messaging that produce conversions. And the best way to do that is through extensive Facebook ad testing.
It’s best to start with at least 5 diverse variations of each option – audiences, ad copy, and ad creative. However from there, the inclination for most marketers is to test all of these variables at once, creating a total of 125 different ad variations (5 x 5 x 5). Since the average ad requires spending at least $150 in order to get enough data that will allow you to make a decision on whether or not it is successful, this method dictates a total minimum ad testing budget of $18,750. While the insight you’ll gain is certainly invaluable, that’s a lot of money to spend on just testing, especially for a small business or startup.
Cheaper Facebook Ad Testing
The good news? There’s a way to save thousands of dollars (88% to be exact) on the typical Facebook ad testing process while still achieving the same results. Simply switch to testing one variable at a time.
Start by isolating one audience, and one version of your ad copy. Then create 5 different ads with that same audience and ad copy version, but test a different image in each. Five ads with a $150 ad test budget for each = $750. And boom, you’ll have your winning image.
Then you’ll want to repeat this process again. Set up another 5 ads, all with the winning creative and one of your audiences. This time around, your variable will be ad copy, and with another $750 spend, you’ll know which messaging resonates best.
Lastly, you’ll need to test your different audience variations by setting up 5 more ads with your best-performing copy and creative.
Three ad tests at $750 each brings your total Facebook ad testing budget to $2,250, and the results will be knowing exactly what your ads should look like and exactly who to target in order to run a successful Facebook Advertising campaign. Compared to the cost of testing all variations and variables at once, you’ll save $16,500.