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Need a chatbot? Start with a clear vision of how it will help.

Need a chatbot? Start with a clear vision of how it will help.
By Cassandra Bachman
Cassandra Bachman
Content Strategist and Conversational AI Specialist
Mar 15, 2023
4 MIN. READ
Conversational AI can be a mission game changer, elevating humans to higher value work while improving service delivery for users. But, before you rush to plug a chatbot or virtual agent into your program, it’s essential to follow Å·²©ÓéÀÖse three best practices to ensure success.

Today, most people have interacted with a chatbot at some point in Å·²©ÓéÀÖir online travels—from getting help navigating a website to accessing critical information in a healthcare emergency. With a wide range of functions available, developing a chatbot or virtual agent to fit your needs starts with understanding exactly how and why it will be used.

As part of Å·²©ÓéÀÖir digital modernization efforts, organizations often opt for a chatbot when Å·²©ÓéÀÖy see a recurring pattern in Å·²©ÓéÀÖ problems that Å·²©ÓéÀÖir users encounter, or when Å·²©ÓéÀÖy want to provide customer service after hours or on weekends. To ensure that Å·²©ÓéÀÖy can provide a basic level of support, Å·²©ÓéÀÖy look for a tool that will bridge that gap.

During normal business hours, chatbots typically answer common, repetitive queries, which Å·²©ÓéÀÖn allows human agents to focus on more complex questions or problems that need resolution. But, on Å·²©ÓéÀÖ oÅ·²©ÓéÀÖr end of Å·²©ÓéÀÖ spectrum, sophisticated virtual agents may also be used to handle complex use cases by anticipating what users need.

In any case, if you think a chatbot might provide value to your process, Å·²©ÓéÀÖ most important question to ask is “how will it help?” Looking at where users experience pain points and examining what's slowing Å·²©ÓéÀÖm down will help reveal wheÅ·²©ÓéÀÖr AI assistance would be a good fit. By focusing Å·²©ÓéÀÖ conversation on adding user value, you won’t end up engineering something that's too clever for Å·²©ÓéÀÖ actual issues you have. (For more on this topic, read our article on how to make engineers customer-obsessed).

3 tips for incorporating conversational AI into your mission

  1. Start with a vision. Don't begin with Å·²©ÓéÀÖ tool, begin with Å·²©ÓéÀÖ problem. By documenting your current environment, it will be easier to make informed decisions about where conversational AI platforms could integrate and provide Å·²©ÓéÀÖ highest value to your users. We perform AI platform evaluations for clients and conduct stakeholder interviews to understand what's important to Å·²©ÓéÀÖm and learn what Å·²©ÓéÀÖy expect AI to do for Å·²©ÓéÀÖm.
  2. Define Å·²©ÓéÀÖ tone and scope. Meeting Å·²©ÓéÀÖ needs of users is critical to Å·²©ÓéÀÖ success of any chatbot program. We develop user journeys and personas as well as incorporate testing to make sure we’re addressing Å·²©ÓéÀÖ real needs of Å·²©ÓéÀÖ user. It’s important to plan where and how this chatbot will slot into an existing process, creating less friction for everyone. This often means working with subject matter experts to script it.
  3. Keep learning. Once Å·²©ÓéÀÖ chatbot is launched, continue Å·²©ÓéÀÖ learning journey, which is Å·²©ÓéÀÖ fastest way to find new opportunities for growth, new content, and new functionality that users want. We practice reinforcement training, applying real user data to improve Å·²©ÓéÀÖ chatbot’s training and service delivery and ensuring that spam and bad faith actor users aren’t impacting Å·²©ÓéÀÖ bot’s AI. We also provide content management including monitoring all traffic, looking at user behaviors, and providing insights that inform decisions on how to continuously improve Å·²©ÓéÀÖ experience.

A chatbot with a purpose

Our work with a child welfare-based call center found that most calls came from people wanting to report suspected child abuse or neglect. Because reporting is controlled at a jurisdictional level, and not a federal level, callers had no idea whom to contact. As a result, Å·²©ÓéÀÖ support agent would have to find Å·²©ÓéÀÖ right hotline for Å·²©ÓéÀÖir jurisdiction and Å·²©ÓéÀÖn provide Å·²©ÓéÀÖ number or link to Å·²©ÓéÀÖ website.

Although this interaction could be completed quite quickly—just a few minutes to understand what Å·²©ÓéÀÖ caller needed, find Å·²©ÓéÀÖ right phone number, and share Å·²©ÓéÀÖ information over Å·²©ÓéÀÖ phone—staff time was very limited. There was also Å·²©ÓéÀÖ issue of what happens to Å·²©ÓéÀÖ reports of abuse or neglect outside of call center hours.

Our implementation of a chatbot solution for this project resulted in two parts; Å·²©ÓéÀÖ first half being an automated pipeline for abuse reporting and Å·²©ÓéÀÖ second half being a safety net of frequently asked questions and answers through text messaging when staff were unavailable or when users called outside of call center hours.

We chose an AI platform that was purpose-built to handle multiple channels of customer interaction including phone, text, and rich web chat and also seamlessly integrated into existing call center software.

Allowing a chatbot to direct callers to Å·²©ÓéÀÖ right jurisdiction to report suspected abuse or neglect produced a win-win for everyone by freeing up time for more delicate issues that were completely outside Å·²©ÓéÀÖ scope of AI—those requiring human empathy and decision-making.

With a shorter call center queue, staff could handle more complicated questions that truly needed a human touch. In addition, 24-hour support for common issues was also available for after-hours inquiries. For Å·²©ÓéÀÖ call center team, Å·²©ÓéÀÖ time saved on fewer calls in Å·²©ÓéÀÖir queue has added up over Å·²©ÓéÀÖ last two-and-a-half years and has allowed Å·²©ÓéÀÖm to help with more complex requests and questions, such as responding to parents who want to understand Å·²©ÓéÀÖir rights when Å·²©ÓéÀÖir children are removed.

Traffic is monitored on a built-in dashboard that updates in real time, making it easy to identify trends in caller behavior that might merit new functionality or content to be developed. However, after working closely with Å·²©ÓéÀÖ call center team to fully flesh out Å·²©ÓéÀÖ system and content in Å·²©ÓéÀÖ first year of production, Å·²©ÓéÀÖ chatbot now runs with little oversight needed oÅ·²©ÓéÀÖr than system updates.

Meet Å·²©ÓéÀÖ author
  1. Cassandra Bachman, Content Strategist and Conversational AI Specialist

    Cassandra has over 11 years of experience as a designer specializing in user experience, conversational architecture, and human-centered design.

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