eCommerce is Dead! Long live iCommerce!
My new column article on how to take advantage of AI and MachineLearning in eCommerce is live on CustomerThink. It gives you background and actionable information, answering pressing questions like ‘Where does AI come into the picture’? Not wanting to spoil, here a little hint: There is far more than merely product recommendations. But read for...
Tenacity – Improving Customer Experience by bettering Employee Experience
Following some of my posts on AI in customer service environments I got contacted by Daniel Doctor from Tenacity who invited me for a chat with Ron Davis, the founder and CEO of the company. Which I had. And it was an interesting conversation. In my articles I spent a lot of time focusing on how AI, machine learning and chatbots can help improving both, the customers’ and the service agents’ experiences by making sure that all relevant data is collated and available, reducing wait times for customers, being able to already suggest good solutions to both, customers and agents, and so on. The objective is at all times to have the customer get a good solution as frictionless as possible and to enable the service agent to concentrate on the hard jobs. The idea behind this approach is that it reduces customer irritation by having the answer faster and improves the agent situation by making the work more attractive. After all, who of us loves dull, boring and repetitive work. Not many, I bet – certainly not I. Of course, this is only half of the truth. Service agents, like all employees also react strongly on who they work with, who they work for, whether they have the right tools at hand to get their job done, how their stress levels are, whether their private lives are untroubled, whether they have enough sleep, and so on. Additionally, the more interesting situation of the dull jobs being taken care of by the machine creates stress, as the customers tend to already have an elevated level of frustration that was...
Content Management Systems – The Secret of Great CustServ
Today’s customer service requirements are getting ever more complicated for businesses. Customers encountering problems increasingly rely on self-help. Customers may start looking for solutions by searching on Google, on community sites, or inside a mobile app. A logical starting point depends on the device and application, as well as personal preferences. The bottom line is: customers want to get to their solution as quickly and easily as possible, and they do not want to change their habits and preferences in order to reach support. Many companies run several customer service applications that support different channels, each with a separate knowledge base (KB) subsystem. These may include a support application for an ecommerce site, some general help pages on the company web site, and FAQs on a mobile application. For internal purposes, there might even be an Enterprise Content Management (ECM) system with information for contact agents to use but that are not published externally. Of course the normal situation for a service agent is to work on more than one channel. This means that depending on the nature of the inquiry, agents need to use and update multiple knowledge bases. This results in additional, redundant work and information. Furthermore, information gets easily out of sync—resulting in confusion. Similarly, customers need to navigate through different knowledge bases and FAQs. Apart from being highly inefficient and ineffective, this has an impact on both employee satisfaction and customer satisfaction. It leads to frustration because customers who do not find their solution need to relay the same information multiple times, and they could be put on hold while the agents research different databases,...