We are currently in the midst of a true customer experience (CX) revolution. Research from Gartner predicts that AI bots will power 85 percent of all customer service interactions by the year 2020, but implementing the technology is just the first step toward finding success.
To make the most of a customer experience strategy that is augmented by artificial intelligence (AI) and chatbots, companies need to identify and then track metrics to ensure their technology is paying dividends.
By proving its value, companies can justify the investment, highlight trends and find areas where virtual agent performance can be improved. For each organisation the metrics to measure value will differ dependent on its goals, but, there are some overarching things that most organisations should monitor.
Here are five key performance indicators (KPIs) to keep in mind while working to automate and enhance overall customer experience:
- Customer engagement: The intention of AI-augmented CX is to help find answers to customers’ questions and address their needs more quickly and easily. Tracking engagement KPIs can help organisations to understand the success of the interactions their customers have with chatbots. Now as some have pointed out, what constitutes a successful engagement to each company needs to be determined in order to produce a meaningful metric. For example, rather than tracking purely the number of chatbot interactions per conversation, measuring engagement could entail tracking clicks on links to resources provided by the AI agent or monitoring whether customer issues are resolved without human involvement.
- Satisfaction rates: User feedback can be required as sometimes KPIs are misleading. For example, longer interaction times with a virtual agent may lead to the belief that customers are highly engaged, when in fact it’s taking too long for them to find a solution. This is where satisfaction rates come in. By letting customers rate their experience with the chatbot a more accurate picture of the success can be achieved. The system can be purely a star rating or entail more involved questions. To encourage this, many companies offer a small incentive to customers for providing feedback, such as a gift card or discount.
- Confusion triggers: While in an ideal world the chatbot would provide the right answers to customers every time, it is likely they will occasionally get confused by what customers are requesting. In this scenario, the inquiry will likely be routed to the customer service team. Tracking when and how often the chatbot responds with “I don’t know” or “I don’t understand” can help to improve the technology to reduce confusion. This will then save staff time in the future and enables a better interaction overall.
- Conversions: Chatbots can do more than answer questions; they can help convert enquiries into purchases. Facebook’s branded messenger bots provide a great example. The longstanding flower company 1-800 Flowers was successful in utilising this tool to make it easier for customers to order flowers via the social media platform. This led to 70 percent of its orders coming from new customers, who connected with the bot and then bought flowers. Tracking the conversion rate enables companies to analyse the effectiveness of virtual agents—and perhaps even find new opportunities for more sales.
- Cost efficiencies: While implementing a virtual agent can make CX more efficient, it is also able to help companies better manage costs. Frost & Sullivan reports that chatbots typically “…deliver significant cost reductions, with ROI associated with some providers typically in less than twelve months.” These cost savings can come from reducing staff time spent on redundant and easily automated tasks, to increasing customer contacts without hiring new employees.
Virtual agents are becoming a necessary part of the customer experience equation. Developing a plan for analysing, measuring and improving on chatbot experiences can verify that an organisation is making the most of this technology.
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