A/B testing is a fabulous technique for figuring out the best online promotional and marketing strategies for our business. We can use it for testing everything from website copy to sales emails for searching ads. And the advantages provided by the A/B testing automation guide are sufficient for off-setting the additional time it takes.
Well-planned A/B testing automation could make a large difference in the ineffectiveness of our marketing efforts. Narrowing down the most powerful elements like promotion and then joining them could make our marketing efforts much more profitable and successful.
Guide to A/B Testing
The first thing we should do while planning an evil test is figuring out what we want to test. Are we running an onsite or an oxide test? If we are running an onsite test, we should show relating all the sales-related pieces of our website and then figure out which elements we want to test.
We are probably testing with an ad or a sales email with an oxide test. Testing and AD copy for saying which ad brings in more converting visitors could help us focus on our advertising efforts. Once we know our address is converting and possible, it will be easier for us to justify spending more money on it. The same works for emails. If we send out two versions to our list, then tracking which one converts better will help us send only that version the next time.
Once we know what we will be testing, we should list all the variables we will be testing. For example, if we have decided on testing our call-to-action, we should test:
- Location of the call to action
- The exact test used.
- The button color or surrounding space.
It is a procedure, and it is common for multiple A/B tests to be conducted, and we should have a clear idea of the results we are searching for. We should now know our baseline result, which is the results we are obtaining currently. We surely want to test options A and b against each other, but we may also want to know that whichever one is performing better in the test is also performing better than our current results. Alternatively, we can use our control and leave it whatever we are currently using and then use something new for B.
Tests are required to be run concurrently for accounting for any variations in timing. We cannot test one variation today and the other tomorrow as it would be difficult to factor in any variables that you may have changed between today and tomorrow. Alternatively, we will be required to split the traffic viewing our variations at the same time.
A/B testing could improve our bottom line
Accurate A/B tests could make a huge difference in our bottom line. Using controlled tests and accumulating experimental data, we will be figuring out what marketing strategy is working best for our company and product. When we figure out that one modification might work two, three, even four times better than the other one, the idea that we should conduct promotions without testing begins to seem a little bit ridiculous.
If A/B testing automation is done consistently, it can improve our bottom line considerably. If we know what works and what doesn’t and have evidence for backing it up, it is easier for us to make decisions, and we can often craft more effective marketing materials from the outset. All we have to do is remember to test as the effectiveness of anything regularly could change over time.
Things to test
We can test virtually anything in our marketing materials from headlines, call to action, body copy, images, etc. We can test it if we can change it. But that doesn’t mean we should spend months testing every little thing. Instead of focusing on the things that are most likely will have a very big impact.
These things likely include on our website:
- The headline
- Any call to action
- Any graphic we use in direct correlation with our sales efforts.
- Sales copy or product descriptions.
Probably the same is included in an email. In an ad, particularly a text ad, we have fewer things to be changed, and so likely, we will test whether the main headline for the offer itself.
Testing various offers is also essential as we should make sure that we have methods for ensuring that each person is always offered the same promotion. For example, if a gift is offered to group A and the discount is offered to group B, we should make sure that group A always contains the same visit so does the group. We could also test things in conjunction with each other.
Devoting time to testing
A/B testing is not an overnight project. We would want to test anywhere from a few days to a few weeks depending on the traffic we receive. And if we want to do the most precise outcomes on one test at a time. Test time cannot imply distorted outcomes because there is not enough time to objectively accurately a wide number of visitors. If a test is run for too long, though, there are more factors that we cannot monitor for a longer period.
Ensure we are aware of something that could affect our findings to ensure that our results are checked for any statistical deviations. We should be sure that our test reports are kept informed and that any statistical irregularities should be reported as we check our results. It is completely fair to retest if we are in question. However, it’s worth taking a few weeks to perform research, given the effect the A/B testing automation guide may have on our bottom line. Test one variable at a time and allow enough time for running each test.
Can we test more than one thing at a time?
This issue could be addressed in two ways. First of all, let’s say that we want to test our title, but we have three potential differences. In that case, it is fair to do one test and break the guests (or email recipients) into three classes instead of two and will probably also be considered as an A/B test.
It is more than three individual evaluations (A vs. B, B vs. C, and A vs. C). We may need to perform an additional few days to run the test to have sufficient evidence for concluding. A multidimensional test of more than one thing at a time, such as a headline and an active call,
Testing more than one thing simultaneously, like a headline and call to action, is a multivariate test and is more complex to run. There are still plenty of options available for testing multiples, so we’re not going to worry about A/B tests until it comes to that.