Oct 13

Reasons Why Your A/B Testing Results Are Not Doing Enough For Your Business Organization

6 errors to avoid while performing A/b Testing | Mockingfish

6 Errors to Avoid While Performing A/B Testing

In this jet age, every business organizations is running behind instant coffee results which are not only impractical but are also too risky in terms of long term business planning. In this mad race for achieving non feasible results, we are often ignoring the ground realities and end up with our efforts going in vain. No business organization would want their efforts, money and time go unproductive for the success and growth of their organization.

However, unfortunately this is a common scenario for numerous companies when it comes to making use of A/B testing results. They are often making false assumptions and are running behind hypothetical goals which are difficult to be accomplished in a given time frame. Let us now examine the various factors that are contributing behind the failure of your A/B testing results for your business organization.

Wrong considerations of the goals for your test- Before implementing split testing for your business organization, you need to have a thorough understanding of your current business scenario. Don’t make any vague considerations for your organization that are too impractical to be achieved. Discuss your goals, challenges and business potential of your organization with your concerned authorities so that you can set the right feasible goals for your business organization.

Giving importance to too many variables at a time- If you are a novice in the field of testing, it would be ideal to test one variable at a time so that you can get a clear picture about what is actually driving your conversion rates. Don’t get lured to test multiple variables at a time or go for multi- variate testing if you are not familiar with the basics of the web testing.

Further, testing multiple variables at a given instance will make you confuse as to what is actually the prime reason behind the recent surges in your conversion rates and sales volume. If you are an old player in this field of testing, you can effortlessly go for multi- variate testing but till then restrain yourself from the temptation of testing multiple variables at a time and go with A/B testing only. If you are too adamant about trying your hand on multi- variate testing, you can happily go with our Mocking Fish tool.

Expecting major gains from the minor changes- Always, remember that split testing is not some magic wand that can resolve your every issue related to your website and can turbo boost your conversion rates and sales volume. Instead, you need to make significant efforts in other areas of your site like website design, loading time, mobile optimization, easy navigation facility and other such factors.

By making required efforts in these areas along with the right implementation of the A/B testing results, you can easily go for the big kill. But, do make sure that A/B testing is just one of the strategy to make your intended changes more acceptable to your targeted customers without actually hampering your current business interests and conversion rates to a great extent. There may be other players apart from the ineffective web testing results that may be spoiling your game, so better watch those culprits.

Unequal distribution of the website traffic on your different site versions- For measuring the accurate results of your split testing, you need to divide your site traffic equally between your two site versions so that there may not be biased results based on the website traffic directed to your each version. Make a 50- 50 diversion of your traffic so that you can clearly infer that the increased conversions on your site version is actually due to the response of your customers and not because of your uneven traffic distribution.

Although, you can make your traffic distribution like 60- 40 or 70- 30 if you are too sure about the impact of your test results, otherwise a 50- 50 approach would be a more sane idea.

Imperfect selection of the testing tool- It is rightly said that “You can’t cut vegetables with a blunt knife” so is the case with A/B testing tool. Check properly that your testing tool doesn’t have a wide unacceptable testing error which could drastically affect the whole outcome of your results.

It would be better to check the reliability of your tool by undertaking an A/B test so as to determine if the errors are too major to be ignored or it can be accommodated. In terms of reliability, you can bank upon our reliable and multi feature A/B testing and heat map tool known as Mocking Fish. It is further known for its simple user friendly dashboard design, easy implementation, low cost and reliable test results.  Reliability is one of the important aspect of A/B testing, so don’t ignore it for a more acceptable test results.

Non completion of the testing time interval- Business organization should foresee that the testing results undertaken by them are actually feasible within the scheduled time interval or not. This is because the complete execution of the test results will let you understand the changing dynamics of the test results on each day and will make you realize whether test results are going to stand relevant even after the stipulated time period or not.

Further, it will provide insight about how your conversion rates are changing over a period of time and whether it will be beneficial to implement your test results for your business organization in the long run. So, don’t make haste in arriving at a conclusion of your test results but give more time for the maturity of your test results.

These are some of the tips that can help you rectify the possible flaws in your testing results so as to achieve the desired test outcomes. Take a careful look at each of the points mentioned above so as to avoid the backfiring of your A/B test results. Remember that “A stitch in time, saves nine” so don’t shy away from making necessary changes or corrections in your test results so as to avoid disappointment later on.