The Critical Importance Of A/B Testing For Sales And Consumer Satisfaction

AI, or artificial intelligence has had a major impact on business in all industries. The estimation is by 2020, 85 percent of all customer interactions will be through AI. The amount of data this encompasses has become too extensive to be handled by humans. This is where A/B testing becomes critical, due to the ability to use algorithms to analyze time consuming data. This eliminates time previously spent on repetitive and boring tasks. AI is dominating the automotive, stock and healthcare fields, and search engines are using AI to improve and refine their information.

Online chatbots are improving personal shopping, effectively using voice prompts, and becoming personal shopping assistants because of AI and A/B testing. Websites are using chatbots to replace employees because they are always available and provide an excellent customer service experience. The data analyzed allows consumers to have questions answered by chatbots, and receive personal recommendations. It has become difficult for consumers to be certain if they are speaking with a chatbot or an employee. This would not be possible without AI and A/B testing because it would be impossible to analyze the extent of data required.

A/B testing prevents retail data from becoming fragmented or out of date. It determines what colors, sizes and combinations will sell in any area. This technology is capable of learning from trial and error, and the behavior of the consumers. This leads to more intelligent solutions not available in the past. Retailers have turned to predictive analytics to personalize sales, and gain customer loyalty and satisfaction. Eighty percent of all online and physical store sales are now driven by AI.

An employee can make a recommendation based on what is available on the shelves. AI can identify the best items to offer based on the personal criteria of the consumer. This includes the potential profit for the retailer, real time availability, and the browsing history of the consumer. Items tried on in the past by the consumer are available through the RFID tags that have been imbedded directly into the garments. The recommendations are informed because social media along with other numerous factors like weather forecasts, fashion trends and consumer choices can be accessed. A/B testing looks for recurring patterns so unnecessary markdowns and out of stock items are avoided. This not only keeps the shelves fully stocked, it predicts what is going to happen. AI technology has become the driving force behind personalization and sales.

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