Personalizing Customer Experiences with Data Analytics
Personalized experiences help companies grow in the market and increase their customer’s base. Accenture predicts that companies will have a $2.95 trillion business owing to personalized customer care. Moreover, 40 percent of U.S. customers admitted that they bought expensive products because of excellent customer service. A marketer’s primary aim should understand the customer and their needs. It is relatively easy nowadays because customers generate heaps of data every day. However, mining of available data is essential. To achieve this, smart data analysis and the right tools along with a correct approach is vital.
A marketer must get rid of the silos across departments, teams, and channels to comprehend data and understand customers better which leads to growth. An organization must approach this process by starting small and connecting their web and app analytics to its customer relationship management technology. Marketers can use customer call data and third-party demographics to optimize ads better. Using a CRM to push this data between departments and everyone receives the benefits. Business leaders regularly refresh their marketing metrics, dashboards and prioritize integrated technology platforms to help make timely customer connections.
The companies should consider merging app and mobile web teams. Customers perform extensive research before buying any product and switch between apps and mobile sites before making a decision. The customers end up making a phone call to a sales rep while taking a decision. This is challenging for a company because they have to connect their digital journey to a phone call. For a brand, an app is viewed as a platform for engaging customers. However, an app needs to earn its spot among customers. On average, a customer visits an app or a mobile website at least six times and shifts from a mobile site and an app. Users expect friction-free research experiences and seamless points of sale.
Present companies use smarter use of technological advances like machine learning (ML). Emerging technologies like built-in intelligence and machine learning bring insights so that the marketing team spends less time making decisions. Marketers can use ML to serve customized ads to different audiences. Additionally, an integrated platform can bring teams together and globally. Leading marketers have to extract the most out of the data to see growth and have to use analytics proficiently.
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