Customer experience is a strategic growth engine when successful and the most significant source of risk when failing. Data analysis is one of the most critical methods for enhancing customer experience. AI uses natural data to analyze each customer’s actions and purchasing habits to conduct predictive research to maximize interaction in the right place and time. If the market environment is connected to the AI, you can define touchpoints and develop CX-shaping tactics.
Personalized to Predictive
Businesses have access to more data about their customers than ever before, are effectively managing and analyzing that data can be vital to their success. The application of AI is helping businesses provide customers with personalized experiences and effectively predict customer needs. Whether it’s analyzing buying habits to offer customers deals on similar products in the future, or understanding online users’ favorite channels of interaction to serve them preferable content, AI is increasingly helping companies improve customer experiences.
Industry leaders are betting heavily on AI to drive customer experience
Netflix is perhaps the best example to highlight how AI is continuously improving the experiences of its customers, mainly by successfully predicting what its customers will want to watch next. As a result, 80% of shows watched on Netflix are due to recommendations, saving $1 billion a year in customer retention.
Amazon is another player that uses AI-fueled algorithms to improve customer experiences by providing personalized product recommendations. Imagine the future where your smart washing machine is linked to your Amazon account and it orders detergent when you’re running low. That future might be here sooner than you think.
The need for AI and Predictive Analytics is going to increase vastly
According to Gartner’s prediction, by the year 2020, customers will manage 85% of their interactions with businesses without interacting with a human. McKinsey recently reported that 70% of companies would likely implement at least one type of AI technology by 2030. That same report states that Artificial Intelligence could generate a global economic activity of around $13 trillion by 2030.
The sooner businesses adopt AI technology, the better prepared they will be for the customer experience-driven future.
Cutting-edge businesses turn to Artificial Intelligence and Machine Learning to change how they communicate with consumers, reinforce those relationships, differentiate themselves from competitors, and increase revenue.
Technologies such as chatbots, recommendation engines, personalized messaging, smart ad targeting, and image recognition are essential to this change.
How can TVS Next help you achieve your AI goals?
TVS Next has partnered with clients to create best-in-class AI solutions across industries. Through our unique approach, we enable clients to extract unrealized value from their organization’s existing data, optimize business processes, improve customer experience, and provide predictive analytics:
Exploratory analysis – In most cases, the business has an answer to ‘what’ is the issue that needs to be addressed. However, getting an answer to ‘how’ and ‘why’ that addresses a problem optimally and provides economies of scale, exceptionally large enterprises, becomes a challenge. TVS Next with its engineering consultants helps solve the problem, even before an actual engagement begins. We call it the ‘Design Sprint’ – which includes not only design but also the steps to be taken to get the solution right.
Effectivity analysis – Every plan may or may not reap into the right results, depending on the real-life metrics and parameters involved. We at TVS Next, take the ‘Effectivity analysis’ as serious as the ‘design sprint’. Analyzing and understanding the results concerning the plan and providing feedback to the ‘design sprint’ for the alternate phase becomes critical for a successful implementation.
To find out more about how TVS Next can help your business make the most of Artificial Intelligence technology, click here.