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Of all the many businesses that participate in digital marketing, many are not following the basic process of testing advertising to see if any of it actually works. While "A/B testing" and "split testing" are nice buzzwords in the field, the actual process required with these often requires patience from the same companies that are expecting fast results from their marketing. If one masters the basic flow of confirming optimal marketing tactics with data, they should have no problem with testing advertising.
Step one is to form a hypothesis based on what is known already, and to test it on the least important part of a campaign that it applies to. That way, the rest of an account can remain unaffected while a specific campaign runs the new idea on a limited budget. Many companies falter here by applying a hypothesis on a widespread rollout, making it difficult to see if it actually works or not.
Step two is to evaluate those results. If the original test isn't successful, revisit the original idea and start over. Once there is some success in testing advertising ideas, those are the ideas that should be given more money. It's much easier to justify moving more budget when the data points in favor of the hypothesis.
While basic, many businesses are in such a hurry to drive immediate results, especially with mediums like pay-per-click, that they either skip testing or apply testing too broadly without confirming that it works. What are some other ways you all test when optimizing your marketing?