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    Home»News»Chatbots to become a premier customer channel by 2027 – Gartner
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    Chatbots to become a premier customer channel by 2027 – Gartner

    CXFocus EditorBy CXFocus EditorAugust 2, 2022Updated:August 2, 2022No Comments2 Mins Read0 Views
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    Despite low ROI and a range of other challenges, investment in chatbots, conversational AI platforms and virtual customer assistants is expected to grow. By 2027, chatbots will become the primary customer service channel for roughly a quarter of organisations, according to Gartner.

    “Chatbots and virtual customer assistants (VCAs) have evolved over the past decade to become a critical technology component of a service organisation’s strategy,” said Uma Challa, Sr 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.”

    A Gartner customer service and support (CSS) survey of 50 respondents conducted online in January and February 2022 revealed 54% of respondents are using some form of chatbot, VCA or other conversational AI platform for customer-facing applications.

    “CSS 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,” said Challa. “Benchmarking chatbot performance metrics at one organization against that of its peers is not effective and can be misleading because chatbot type, design and complexity vary widely by organisation.”

    CSS leaders seeking to effectively deploy and measure chatbot performance as part of their service and support channel strategies should:

    • 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 (e.g., goal completion rate, abandonment rate, conversation steps, handle time, etc.) based on the organisation’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 prioritise opportunities.
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