We will probably see AI help drive specialisation and advanced staffing models, such as that customer wait time becomes a thing of the past. – thinks Thomas REBY about the role of AI in contact centres in the future.
What will be the role of AI and technology in general in contact centres in the future?
Technology will play an ever-increasing role in complementing human ability. Technology provides solutions to aspects of service that are repeatable and where rapid, error-free operation is paramount. Areas such as identity/address verification, scheduling and status reporting are all examples in which technology can free up human resource and allow companies to re-deploy time and energy in to service that requires empathy, evaluation and non-standard solutions. Humans will be augmented, not replaced by technology, and my hope is that we will start seeing more focus on service and relationships, since the parts of customer service that are “script-prone” get automated. In addition, AI will help us build connections and relations between events that we would not be able to identify with our limited cognitive ability. We are already seeing many examples of this across industries and in contact centres I believe predictive service intervention and proactive, outbound contacts will be fuelled by AI. We will probably see AI help drive specialisation and advanced staffing models, such as that customer wait time becomes a thing of the past. Likewise, AI-driven coaching will help train agents much more specifically in the areas needed. Far too often operations managers are relying on simple analysis of operational data to make contact centre decisions and I anticipate with AI that we will increase the depth of understanding dramatically. We will gain a new level of knowledge behind Customer Satisfaction increases (and decreases) as well as much better understanding of why individual performance varies in contact centres.
What are the advantages and disadvantages of self-service?
Self-service carries the obvious examples of rapid, on-demand help at low cost. Effective self-service allows for the customer to gather the knowledge needed, when convenient and without human interaction, it creates very little overhead. A less obvious benefit is meta-data capturing. As self-service journeys are logged or journaled, meta-data is created which helps feed process improvement initiatives, all the way back to product design and serviceability. This is very powerful, and coupled with AI, the meta-data will be able to provide unexpected insight leading to improved customer experience.
How to boost agent performance and productivity?
In my experience, agent performance and productivity is driven through instilling a sense of ownership and self-direction. Too much focus on metric optimisation and coaching towards metrics, leads to disenfranchised employees who think with a transactional, sub-optimising mind-set. The key to boost agent performance lies in making sure that they place a part in developing the business. Here are some tips:
- Make sure coaching is targeting their growth and goals and the performance will follow
- Take their feedback seriously and improve process and product accordingly to gain their trust
- Allow them to help set targets and own their business reviews as a team. Hand over accountability and after a transition period you will see a level of commitment you would not have imagined
A lot of literature exists on self-managed and self-directed teams and I would strongly suggest anyone looking to improve team performance to look into bringing in a degree of self-managed teams as a start!
Thomas REBY is a Senior Strategy Manager at Google with extensive experience from technology companies, including Google, YouTube, eBay, Dell and Electronic Arts. During his career he has managed global operations in e-commerce, technical support, content management and digital advertising, as well as held key leadership positions developing strategies for customer experience, revenue generation and knowledge management. He has advanced CX research methodology by shifting traditional survey processes towards progressive action-oriented insights, centring on pre-empting failure and knowing when to deviate from standards. In addition, he introduced a fusion of sales and services, delivering customer success through machine learning models that drive product adoption and revenue growth as a byproduct of customer goal attainment. Through seven years of dedicated Knowledge Management experience he has transformed KM capabilities of two Fortune 500 companies. This includes establishing knowledge sharing culture, implementing KM systems and tools, as well as tracking and optimising the value of knowledge and knowledge contributors across global teams. Currently, Thomas is a Strategy Manager at Google, supporting consumer operations in areas such as Gmail, Google Maps and Pixel hardware. He is a father of two and currently lives in Dublin, Ireland.