Customer satisfaction has never been more important. Competition lurks everywhere. Whether you run an old-world pizza parlor or a startup app promising to revolutionize an industry, satisfied customers make or break your enterprise. The pizza may taste great and the technology may be genius, but if customers have a miserable experience, they will go elsewhere.

Keeping customers happy must be the primary goal of business because that’s where the revenue comes from. With customers expecting on-demand service, savvy business owners realize that they must employ customer service technology effectively. Without the latest customer service tech, companies fall behind the competition. Tech allows for the company to distribute its resources efficiently. In the end, that means customers receive service faster and at higher quality.

In Forbes Magazine, Daniel Newman, CEO of Broadsite Media Group, explores the customer service tech no CEO or CIO can afford to ignore.


Newman is quick to point out that automation and robots are not synonymous. Automation, rather than being a robot that does work previously completed by humans, consists of processes more efficiently handled by machines, freeing employees for tasks beyond the capability of automation, such as those requiring creativity, empathy, and human ingenuity.

Phone system automation must increase customer satisfaction. Done right, it reduces hold times, provides rapid resolutions, and reduces stress. Most of us have suffered through bad automated phone systems. They seem to cause greater inconvenience and cost the customer additional time. Poor design and outdated systems are often to blame.

Chatbots can be employed to provide very efficient service on basic requests. Many customer service issues can be resolved in seconds, leaving human CSRs available for complex customer service issues. Effective chatbots have problem solving ability and demonstrate empathy. Because of this, they complete many calls without human intervention.

Machine learning and data

The rapid progress in machine learning has provided new ways to use data for creating positive customer experiences. Previously, determining what factors made the difference between positive and negative experiences required a certain amount of guesswork. There was no way to definitively analyze every single customer interaction and compare them.

Machine learning has advanced to the level where AI provides the capability to do just that. Armed with this granular view of customer interface, management can determine where negative experiences originate from and fix the difficulties before they result in irate customers. Furthermore, it can use its previous experience to judge when a particular interaction is turning negative and decide on the best next step. Another innovation involves using data to match customers with the customer service reps who are most suitable.

Marketing data

Marketing has always asked the question: why do customers buy? AI provides the data analytics to finally analyze customer behavior definitively, telling marketing departments the customer’s real feelings about the product, the price, and other key points. This then provides the opportunity to create ideal marketing content. To fine tune marketing messages even further, IoT tells companies about their customers in detail never before possible. By integrating this data, the picture of the ideal customer emerges, and a laser targeted marketing campaign is born.

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