Journey mapping is not just about the destination—but the journey itself—and all the moving parts that make it a memorable ride.
Over the past 10-plus years, I’ve built dozens of journey maps—and have always approached each one a little differently. My favorite go-to journey research method is diary studies as they allow me to observe people completing their actions in real-time and over multiple touchpoints.
“[Diary studies are] a way of capturing rich, qualitative data about people’s behaviors, experiences, and attitudes over time.”Indi Young
My diary tools have run the gamut from no-cost to high-tech/higher-cost like dscout and Indeemo—and have experimented with all formats: mobile, written, and video. (See below for a complete list of what I’ve tried.)
In my most recent journey mapping project, I leveled up my research approach by incorporating text analytics for the first time—and found this new perspective to be incredibly valuable for me professionally and to the overall effectiveness of the journey map.
Case Study: University Admissions Journey Mapping
For this project, I leveraged a variety of research methods—video diaries, surveys, projectives—to inform the journey that prospective students go through to apply to college and finance their degree.
But this time, I added one new research tool: text analytics.
To give you an example of how I did this… In one diary entry, I asked research participants to tell me all about their admissions counselor—what were their first impressions of them, what did they talk about, in what ways were they helpful, in what ways were they not helpful, etc.
After reading their diary entries, next, I looked up every phone call between the research participant and their admissions officer using a text analytics platform. Now, I could literally see both perspectives of the same experience: the customer’s perceptions of what happened and what actually happened!
The additional insights gleaned from text analytics allowed me to add a layer of richness to my storytelling approach. As nice side effects, it also increased the credibility of the map and deepened stakeholders’ emotional connections to my research findings.
5 Ways to Leverage Text Analytics When Building Journey Maps
If you have access to text analytics at your organization, here are some ways you could use it to flesh out your journey maps.
1) Sentiment Analysis
Use sentiment analysis analyzed in customer feedback, reviews, and comments at different touchpoints of the customer journey. Identify the emotional highs and lows of customers in each part of the journey and gain insights into the factors driving positive or negative experiences.
2) Topic Modeling
Create topic models for:
- Customer issues: Identify common themes in customer feedback, such as issues with a particular product feature or concerns about customer service.
- Journey stages: Segment customer feedback by customer journey stages, such as pre-purchase, purchase, and post-purchase.
- Unmet needs: Uncover hidden customer needs and preferences that may not be explicitly stated in customer feedback data.
Identify different customer personas that emerge from the data in order to create more targeted and effective journey maps.
4) Network Analysis
Visualize the relationships and connections between different touchpoints of the customer journey. Use this information to identify the critical paths that customers take and optimize those paths for a better overall experience.
5) Predictive Analytics
Build predictive models that identify the factors driving customer behavior and predict future outcomes that lead to higher customer satisfaction, loyalty, and advocacy.
Other Research Methods for Journey Mapping
Here are the different methods and tools I’ve used to conduct journey research over the years:
- Box (video diaries)
- dScout (written & video diaries)
- Focus groups
- Google Docs (written diaries)
- Google Form (written diaries)
- HatchTank (written & video diaries)
- Indeemo (video diaries)
- Projectives (e.g., drawing exercises, scavenger hunts)
- Text analytics
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