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State of support chatbot

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Chella Kumar

Date posted: July 15, 2019

Artificial Intelligence is the buzzword of the century and one of the avatars it has taken in the hands of consumers and businesses is Chatbot. While the technology to make chatbots independently intelligen t is still at its grassroots level, the concept itself has already brought in several chatbot solutions to the table. These solutions require extensive training, maintenance, and feedback and the level of effort (LOE) varies depending on the complexity of the questions it needs to answer. Many support organizations experience this bitter reality during their assessment of the solution or within months of implementing a solution. That said, one can safely conclude that the success of a chatbot has a non-linear correlation to the effort invested in training. It is non-linear as the LOE could reduce post the initial setup.

As per 2018 Technology Adoption And Spending: Support Services by TSIA only 15% of their member organizations have adopted Chatbot and it is the least adopted technology out of the 23 categories.

To push adoption, chatbot solution vendors like IBM Watson, Dialogueflow, LogMeIn …etc have come up with innovative approaches and tools to enable Ease of training and Maximize ROI

Based on the approaches taken, most solutions in the market can be broadly classified into the following three categories,

  1. Leverage existing content : Focus on indexing existing content where there is an ongoing investment like Support Knowledge Base. These offer the least customization capability and requires very less effort in training and maintenance. They have no or minimal conversational capability.
  2. Highly customizable: Focus on facilitating a solid platform where any simple or complex use cases can be solved with advanced integration capabilities. Implementing such platforms require a sophisticated team of Chatbot Architects and Software Developers.
  3. Centered around live chat: Focus on providing chatbot as an extension to the Live chat capability and highly rely on live chat responses to train itself.

There are solutions like LogMeIn Bold360 that offer key elements of all of the above yet has limitations across all of the capabilities. On the other hand solutions like IBM Watson limits to chatbot only, however, offers solid integration with SalesForce LiveAgent.

Before you start your pursuit for the perfect chatbot solution, conduct a thorough assessment of your organizational strength, need and capabilities and then pick an intersection from the Venn Diagram where you want your ideal solution to be and then invite vendor for demos.

Here is a list of areas I started my assessment with. At the end of this assessment, you will clearly know the type of solution you will need and if your bot will find a product-market fit (among your support customer).

  1. Type of Issues reported by customers.
  2. The complexity of your Products.
  3. Current methodology used to generate help content.
  4. Support channel preference.
  5. Live chat need/presence.
  6. Team skills and capability.
  7. Current support platform landscape.
  8. Leadership and customer expectation.

In the coming weeks, I plan to deep-dive into each of the assessment areas. Post which I will cover chatbot implementation and content best practices

At the end of this series, you as a Support leader or practitioner should be able to answer the following questions,

  • Is chatbot required for my support organization?
  • What type of solution should I pick?
  • How do I implement my chatbot to achieve the highest ROI?
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