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It is a known fact for anyone that has been keeping up with the trade media that artificial intelligence is moving to transforming various digital sectors. 80% of US online marketers believe that customers are ready to embrace this new technology.

There are huge improvements that have been brought about by the AI; from use of tools such as chatbots for automation of customer’s interaction to assisting marketers make constant improvements to meet desired target through utilization of user’s patterns. This cuts a lot of cost and improves efficiency because they are basically faster and sometimes more accurate than humans.

Individuals are demanding for advertisements that are more targeted and this is possible because of the proliferation of artificial intelligence. Based on a study carried out by Accenture, about 70% of customers said that most advertisements are short of standards while about 50% of individuals are more concerned with advertisements that suit their personal interest.

How will these demands be met? One best way the approach this lies in AI driven multivariate testing.

The Multivariate Testing

The multivariate testing is a tool that is only talked about at times but often ignored. It is the processes of breaking down a particular campaign into smaller units to assist marketers comprehend the various factors concerned. Most advertisers ignore the full potential of optimization even though, it has been around for a long time now.

To begin, most advertisers combine their targeting dimensions all in one place and then forget it once it is set and goes online. This not only results to the disadvantage of poor performance and higher prices, but often concludes with providing any real insights to the audience.

In reality, it will be impractical or rather impossible to analyze the various elements of a campaign that is modular in order to know what brought about its success or failure. All these should have been taken into consideration from the front end.

Multivariate testing has become both practical and possible through the AI technology. With the help of AI, marketers can now fragment a particular campaign into numerous of micro-campaigns while taking a lot of factors including audience targeting, device, location, gender and age into consideration. Performances can now be compared for a particular group by advertisers. For instance, males of ages between 35 to 40 years using laptop who are generally interested in sports or females between the ages of 18 to 24 using tablet and they are generally interested in fashion.

This is impractical for an average human media to do but these activities can be carried out by AI using multivariate testing through the huge amount of data accumulated about users.

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