Chatbots Will Be A Primary Customer Service Channel By 2027

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Within five years, chatbots will become the primary customer service channel for roughly a quarter of all organizations, Gartner predicts in a new report.

The research firm found that 54 percent of organizations today use some form of a chatbot, virtual customer assistant, or conversational artificial intelligence platform for customer-facing applications. In the next two years, it expects chatbots to have the greatest rise in value and level of deployment across organizations and half of all companies will spend more per fiscal year on bot and chatbot creation than traditional mobile app development.

“Chatbots and virtual customer assistants (VCAs) have evolved over the past decade to become a critical technology component of a service organization’s strategy,” said Uma Challa, senior director analyst in the Gartner Customer Service & Support practice. “When designed correctly, chatbots can improve customer experience and drive positive customer emotion at a lower cost than live interactions.”

And while the overall outlook for the technology is great, current chatbot deployments continue to fall short due to a lack of actionable metrics and the maturity of chatbot infrastructure, Gartner also found.

“[Customer service] leaders have a positive future outlook for chatbots but struggle to identify actionable metrics, minimizing their ability to drive chatbot evolution and expansion and limiting their ROI,” Challa said. “Benchmarking chatbot performance metrics at one organization against that of its peers is ineffective and can be misleading because chatbot type, design, and complexity vary widely by organization.”

To combat this, Gartner recommends that customer service leaders seeking to effectively deploy and measure chatbot performance as part of their channel strategies should do the following:

  • Create an appropriate chatbot deployment strategy based on use cases and the complexity of service interactions. Plan early and consider all dependencies to ensure the necessary resources are available.
  • Enhance customer containment and reduce customer effort by improving chatbot usability.
  • Identify the most relevant chatbot metrics, such as goal completion rate, abandonment rate, conversation steps, handle time, etc.) based on the organization’s unique context.
  • Adapt the metrics to their desired chatbot metric performance level, or baseline, by considering the chatbot design and complexity.
  • Set up a cadence to review the chatbot metrics against the established baseline to gain insights into strengths and prioritize opportunities.