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KOL Marketing: How can the effectiveness of A/B testing be boosted?

A/B testing, in simple terms, is a performance comparison of two versions of some samples[1] leading to the same measurable goal. The result from the test will then indicate which version (or sample) performed better. Scientifically, this is known as a randomized controlled experiment, where a variable is changed and tested to observe which set-up leads to a more desirable outcome. A/B testing is widely employed in various types of research, and one field where A/B testing is heavily used is marketing.


In marketing contexts, A/B testing is often used to test out the conditions in which a marketing campaign or material generates better results. For example, one may design two versions of an ad for a credit-card and see which of them generates higher conversions. In practice, the variable tested may include versions of a marketing material, audience groups, locations in which a marketing material is placed, and the times in which a marketing material is published, and the metrics used in evaluating results may include conversion rates or click-through rates. For example, if we want to use A/B testing like finding the better location for a call-to-action button on a website, the process will be quite straight forward. On the other hand, A/B testing could be difficult to implement in some cases, especially for KOL marketing. In KOL marketing, A/B testing becomes very time-consuming, or in many cases, even not possible because it is very difficult to test with many KOLs at the same time, given the advertiser has to carefully select different KOLs to work with, undergo some tedious and lengthy negotiation process, and bear the high cost in terms of time and finance in doing the test. Therefore, the efficiency in conducting A/B testing in KOL marketing is usually not high.


However, with the emergence of Artificial intelligence (AI) based KOL Marketing, the efficiency of A/B testing can be optimized, making A/B testing in KOL marketing not only possible, but also very cost-efficient. With the aid of AI technology, brands can easily insert their ads into many different KOL videos across many different categories (e.g. lifestyle, beauty, workout, gadgets) at the same time to test out which KOL category, or even which KOL, works the best for their campaigns. They can then adjust their strategy accordingly and place ads on the videos of those KOL categories or KOLs that generate the best results. For multinational campaigns, they can also test with many different KOLs across different countries. Using this method, brands can significantly reduce the cost needed not only to do A/B testing in KOL marketing, but also the cost needed to do KOL marketing in general.


If you are in the search for an AI KOL Marketing platform who can do A/B testing for your KOL marketing campaigns, Zyviz.com might be your best choice. Zyviz.com is currently the leading AI-enabled MCN platform in the world, and our ground-breaking model of AI KOL marketing makes testing your advertising campaign in many KOL videos across many categories and countries easy. Visit www.zyviz.com or contact us through info@zyviz.com. We gladly await your enquiry.


[1] https://hbr.org/2017/06/a-refresher-on-ab-testing

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