Two big trends in the customer interaction and engagement space make Robotic Automation very relevant. First, the imperative to better enable agents. In the past years, customer service departments have invested in self-service. The second trend is to improve the customer experience. It entails streamlining and digitizing customer-facing processes.
Assistants and bots have reached a new adoption high. However, many businesses are finding their projects harder to scale than they expected. The disappointment with some deployments triggered controversy whether to use Artificial Intelligence (AI)-powered assistants or to stick with rule-based bots. Assistants and bots are relatively easy to set-up. Companies can start rapidly but are finding it more difficult to scale and can become disappointed. Challenges maximizing conversational AI should not be construed as the technology not being ready for large deployments. Let’s explore what needs to be done to get the most out of conversational AI.
Artificial Intelligence (AI) is finally making headways in the broader Customer Interaction Management space. Customer service departments have a lot of technology options to choose from to better their productivity and the customer experience. It incentivizes them to invest in software allowing incremental improvement of performance indicators. This has led to a conservative approach with breakthrough technologies such as AI. This is changing through the state of AI adoption.
Enterprises are looking at how they interact with customers in a more holistic way. It includes the resolution of the issues that triggered customers reaching out in the first place as well as providing proactive service. The transition to the cloud of contact centers has created a “gold rush” in a market where incumbent vendors had traditionally a leg up.
This article is the second of a two-part series on Robotic Automation for customer engagement. Part one provides an overview of the technology. It explains how it can be used to assist customer service representatives and automate tasks of customer-facing processes. Part two explores the art of the possible and dig into the three most common models for leveraging this style of automation. But first, we need to do away with two misconceptions.
A lot has happened in the sales tech space. The major change of this landscape iteration is the restructuring of the Sales Intelligence layer. The new layer features list providers regardless of their data collection method. Differentiate between vendors offering data augmentation services. Eventually, add call and web intelligence solutions, growingly used in sales organizations. Besides understanding how the category shapes up, follow steps for your vendor selection. Keep in mind this explosion of players brought a lot of variability in data quality.
We continue our exploration of the key trends shaping up the customer interaction management market. In the first part of this article, we looked at the accelerating transition to the cloud and the impact of digital transformation initiatives. In this second part, I would like to explore four other driving forces. The coming of age of Artificial Intelligence (AI) and the viral adoption of messaging apps are enabling conversational experiences. Self-service has become an investment priority for enterprises and the number of virtual customer assistant providers has surged to a whopping 80.