What are Customer Journey Maps?
Customer journey maps are a visualization method to investigate user experiences. They consist of user personas, user flows, and scenarios based on qualitative and quantitative data. This data can help stakeholders and conversation designers develop empathy for the virtual assistant’s end users.
The practice of mapping creates a deep insight into the industry, brand, competitors, services, products, and users. These dynamic documents need to be updated regularly by engaging stakeholders across the entire enterprise to provide many perspectives. The act of journey mapping demands a shift from multichannel to omnichannel in order for customers to move freely.
By leveraging these journey maps organizations can understand how customers interact with various touchpoints within their customer-facing channels, from websites to apps to conversational solutions. With better understanding comes opportunities to further optimize lead generation, sales funnels, and increased revenue and customer satisfaction. These documents become a prompt for designers to ensure that every step of a journey needs to flow in a natural, frictionless, and efficient way.
The Importance of Journey Mapping in Conversational AI
Customer journey mapping is critical when designing conversational AI experiences. When businesses invest in AI, it’s often added to new conversational channels, becoming the new, more efficient home for existing use cases that may currently require interactions with multiple websites or GUIs. These use cases need to go beyond reducing wait times and automating FAQs to providing adequate support to ensure convenience and meet customer needs. How can we make sure this new solution is better than the current state? By mapping out all steps that customers take along with identifying their goals, motivations, and challenges. This map will become the reference point a conversation designer will use to ensure that whatever they design for the new conversational experience must offer more value, efficiency, fewer steps, and a better customer experience than how users are completing tasks or converting today.
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Tips to Utilize When Building Out a Customer Journey Map
The following list is our recommended steps conversation designers should follow when building out your customer journey map:
- Align on project goals before map development.
- Interview a large, diverse set of customers (not just the loyal ones) to understand goals, motivations, pain points, and all steps within the journey.
- Involve internal and external stakeholders to drive changes from journey map analysis and promote buy-in from management.
- The mapping process should result in a list of actionable to drive accountability.
- Leverage collaborative customer journey mapping platforms or templates to add your qualitative and quantitative data. We like UXpressia and Miro.
- Use a prioritization matrix to distribute your resources smartly; start with the most problematic steps in the journey to reduce friction.
- Focus on all stages of interaction (awareness, comparison, purchase, etc.)
- Add key performance indicators to ease the process of decision-making that will inform a conversation designer’s design.
- If optimizing an existing conversational solution, showcase chatbot analytics such as the Net Promoter Score and Customer Satisfaction Scores to identify opportunities for optimization at different stages of each journey.
- Regularly update the journey map with new data.
Example of a customer’s journey ordering a burrito for lunch using an SMS chatbot.
Personalization in Conversational AI
Journey maps also lend themselves well as artifacts used to identify areas for additional personalization in a user experience. Customer data can be captured at different points including personal details, product preferences, questions asked, shopping behavior, and contextual cues from conversations. Everything from utilizing a customer’s name, relaying previous order information, giving real-time updates about account information, or presenting content based on past purchases are all areas where personalization can be leveraged and identified in developing a journey map.
Leveraging Data in Conversational AI
Qualitative research such as user interviews, diary studies, and usability testing deepen understanding of users whereas quantitative research such as data found in analytics and dashboards can help understand customer behavior on existing channels that can be used to inform the design of virtual assistants. Where customers spend their time, on what product or service pages, along with points of dropoff or exits can all inform a journey map and then be used to prioritize use cases for conversational flows. Once a conversational solution is launched, journey mapping must be continued to highlight optimization opportunities.
Conversational solutions offer intelligent, personalized, asynchronous experiences that are continuing to gain traction and popularity by consumers. In order for businesses to successfully invest, design, and develop conversational AI experiences, customer journey mapping must be part of the process. It is these artifacts that will ensure user needs are understood and their experiences are optimized and more efficient than how they interact with the brand today. Reach out to us about your project here.
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The Role of Customer Journey Mapping in Conversational AI was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.