AI Meets Customer Experience: Mapping Journeys with Machine Learning

In this article, I‘ll walk you through everything I’ve learned about AI and customer journey mapping. You‘ll see how you can use machine learning to process large amounts of customer data, uncover hidden patterns, and predict future behaviors with uncanny accuracy. Whether you’re a solopreneur like me or leading a fast-growing tech startup, you'll find learnings and tips you can apply to your business.

Note: You’ll see references to both Claude and ChatGPT throughout the article. I tested both throughout the writing process — and you can apply the prompts to whichever tool you prefer.

Table of Contents

• What is AI-powered customer journey mapping?
• How to Create a Customer Journey Map With AI
• ChatGPT Prompts for Customer Journey Mapping
• Testing It Out: How I Created a Customer Journey Map With AI
• Helpful AI Tools for Customer Journey Mapping

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What is AI-powered customer journey mapping?

AI is transforming the way businesses understand and map their customers' journeys. By leveraging machine learning algorithms and big data analytics, AI can process vast amounts of customer data to identify patterns, anticipate customer behaviors, and uncover insights that might be missed by human analysis alone.

For example, a traditional customer journey map visualizes how customers move from awareness to acquisition and, ideally, to becoming loyal customers. AI enhances this process by:

• Processing large volumes of data from multiple touchpoints.
• Identifying hidden patterns and correlations.
• Predicting future customer behaviors.
• Personalizing the journey in real-time.
• Providing actionable insights for optimization.

How can AI improve the customer journey mapping process?

To understand how valuable AI can be, you should be familiar with the pain points (pun intended!) of the journey mapping process. Two of the biggest ones are:

1. The time it takes to build out, and
2. The vast amount of data needed to process.

Think about all the customer touchpoints you might have as an ecommerce startup, for example.

According to a Nielsen Norman Group survey, completing a traditional customer journey map could take days or even weeks. That's not including the time it takes to collect and synthesize customer feedback.

The process is time-consuming thanks to four main factors:

1. Quantitative data — website analytics, social media, customer service logs, sales data, etc.
2. Qualitative data — insights from different departments, customer interviews, survey feedback, etc.
3. Data analysis — identifying patterns and insights is often a manual, time-intensive task.
4. Visualization — it takes significant effort and skill to create a visually appealing and easy-to-understand map.

Here are some other use cases for AI in the customer journey mapping process, according to the experts I spoke with:

• Designing marketing/sales/CS processes for engagement along the customer journey.
• Architecting workflows/automation for data management and outreach campaigns.
• Analyzing customer sentiment across multiple touchpoints.
• Personalizing customer experiences in real-time.
• Predicting future customer behavior and needs.
• Defining and outlining the customer journey.

Statistic: 50% of surveyed sales professionals believed that AI would enable scalability in ways that would otherwise be impossible.

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• Exclusive insights from worldwide CRM leaders
• Analysis of modern customer behaviors
• Closer look at the AI opportunity in CRM
• Strategies for staying agile in 2024 and beyond

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What are the limitations of using AI to create a customer journey map?

It‘s easy to get crazed over the potential of AI in business, but it’s worth remembering that it‘s still relatively new. Keeping this in mind, I always recommend trying any new AI tool with a healthy dose of skepticism. (After all, I’m a journalist at heart!)

Erik Karofsky, CEO of VectorHX, has used AI to develop journey maps and feels it's not quite ready for prime time yet.

A big challenge with creating a journey map using AI is that “it doesn't serve any user well,” he says. “AI can produce overly complex maps cluttered with unnecessary information or may generate overly simplistic, generic maps that fail to provide valuable insights. These journey maps frequently require extensive revision, and during this process, gaps in the journey become apparent.”

However, where AI can be useful (with some caveats) is in providing insights that contribute to a better journey or influence the journey itself (though a UX professional is still essential to the creation process), he explains.

Here are some real-life examples he shared with me to illustrate:

• Summarizing qualitative insights to highlight key steps and pain points can be helpful, but the data must be rich and well-curated.
• Segmenting audiences based on specific criteria and analyzing their behavior has improved, but it still largely remains within the realm of analytics rather than journey mapping.
• Offering personalization suggestions is valuable, yet it's merely one component of a broader journey.
• Engagement across touchpoints can influence outcomes within a journey, but it doesn't define the journey itself.

That being said, let's explore how you can create a customer journey map with AI — with a focus on using it as a partner in the process instead of an overall replacement.

How to Create a Customer Journey Map With AI

This is where the fun begins (though, be warned: there is a learning curve). My biggest pro tip when incorporating AI into any aspect of your business is to take the time just to experiment without putting pressure on the outcome. New tools are being released every day (or at least it feels that way): try different tools and prompts to see what's possible.

See the example below of how one tool, Journey AI, helps synthesize customer data to create a personalized journey in a matter of seconds.

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This is a sneak peek of what‘s possible — we’ll dive deeper into the tools shortly. But before we get there, let's cover the basics. Here are the first steps you should take to create a customer journey map with the help of AI.

Step 1: Define your objectives.

Start by clearly outlining what you want to achieve with your customer journey map. For example, you could focus on any of the following:

• Identifying and addressing customer pain points.
• Enhancing overall customer satisfaction.
• Identifying new upsell opportunities.
• Boosting customer retention.
• Increase conversions.

According to a study by Gartner, companies that prioritize and effectively manage customer journeys are twice as likely to significantly outperform their competitors in revenue growth. This underscores the importance of setting clear objectives for your journey mapping process.

As I walked through these steps for my own business, I really wanted to find opportunities to increase conversions among my potential customers. This helped me keep a narrow focus as I built out a customer journey map.

If you're at a larger organization, John Suarez, director of client services at SmartBug Media, first recommends interviewing marketing/sales/customer service to understand their customer and ideal journey. From there, you can be laser-focused on gathering the specific data you need.

How to implement AI at this stage: Test out different ChatGPT prompts to uncover your objectives and find ways to narrow down your customer journey map. Here's an example prompt below I tried with Claude.

Step 2: Gather customer data.

Gather all relevant customer data from various touchpoints. This will depend on your specific business, of course, but it can include:

• Customer service data — help tickets, chat logs, knowledge base usage, etc.
• Purchase history — purchased orders, abandoned carts, returned items, etc.
• Email marketing data — emails opened, links clicked, unsubscribe rates, etc.
• Social media interactions — direct messages, mentions, engagement, etc.
• Direct feedback — surveys, customer satisfaction, product reviews, etc.
• Website analytics — page views, heat maps, session duration, etc.
• Referral data — organic search, paid ads, direct referrals, etc.

Warning: AI tools are only as useful as the data you feed them. Using poor or dated data sources can be very destructive in this process. AI is like baking — a quality cake comes from quality ingredients. The data you're pulling needs to be as recent and thorough as possible.

For my business, my main touchpoints are my business website and my social media profile. From there, I'm able to pull reports using tools like Google Analytics to learn more about my website visitors. I can learn more about what links they click on, how often they return to my website, and where they drop off in the user journey.

If you're a startup or small organization, gathering customer data is crucial but can be challenging due to limited resources and a potentially small initial customer base. A lean approach might involve leveraging a combination of free and low-cost tools to collect data across various touchpoints, like your CRM.

How to implement AI at this stage: Once you‘ve gathered all of the data you’ll need, you can dump it into Claude or ChatGPT and try something like the prompt below. By asking specific questions in your prompt, you can tailor the responses and data analysis to your needs.

Use AI-powered tools to integrate this data into a cohesive dataset.

In the era of big data, consolidating information from various sources into a unified, actionable dataset is a major challenge for businesses of all sizes. But this is an important step creating accurate and comprehensive customer journey maps — so you'll want to get it right.

A survey by Forrester found that 80% of companies struggle with data silos, which can lead to incomplete or inaccurate customer journey maps. Thankfully, AI-powered data integration tools can help overcome this challenge by automatically consolidating data from multiple sources.

Step 3: Analyze the data with machine learning.

Apply machine learning algorithms to your integrated dataset. These algorithms can identify patterns, segment customers, and highlight key touchpoints in the customer journey.

Here is an example prompt you can try. Just make sure to tweak your own data points.

There are also more advanced tools you can use — especially if you're a developed business with a massive quantity of data to analyze.

Step 4: Use NLP to analyze customer feedback.

Next in your process, you can use natural language processing (NLP) to analyze customer feedback and communications. This helps in understanding customer emotions and sentiments at different stages of their journey.

For example, you can use AI to analyze the sentiment of customer feedback, categorize feedback into themes, discern customer intentions, and predict future customer behaviors. All of these tasks can give you invaluable learnings about the customer journey.

Step 5: Visualize the data with AI tools.

Use AI visualization tools to create a dynamic, data-driven representation of the customer journey. This visual map should highlight key touchpoints, pain points, and opportunities.

Suarez recommends using a tool like Whimsical Diagrams' Custom GPT for Flow Mapping at this stage. I was fascinated with how quickly this tool created a simple customer journey map flow chart.

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Step 6: Validate with human insight.

As with any AI tool, you'll want to approach it with a hefty amount of skepticism and validate your findings with human expertise. Even in this process, I sometimes had ChatGPT recommend studies that simply didn't exist.

While that‘s especially not ideal for writing an article — it can be harmful if you’re relying on this to build your business and boost your bottom line. By combining the AI-driven insight with feedback from your customer-facing teams and actual customers, you'll get the highest quality output possible.

Pro tip: If you want help getting started with your own customer journey map, check out our templates here.

Don't forget that the customer journey continues post-purchase. Check out our Post-Sale Playbook for more insights and strategies.

ChatGPT Prompts for Customer Journey Mapping

To see how I could use AI to learn about customer journey mapping, I first turned to ChatGPT to brainstorm some helpful prompts. I think of this step of the process as tapping into a research assistant where I'm simply experimenting with ways to improve the customer journey process.

You can see an example prompt and ChatGPT response here:

Here are some top prompts I've discovered that will save you a ton of time:

1. Identify the key stages in a typical customer journey for [your industry].
2. What are common pain points customers face when interacting with [your product/service]?
3. What objections do my customers have before buying?
4. List potential touchpoints between a customer and [your brand] throughout their journey.
5. How can we measure customer satisfaction at each stage of the journey?
6. What metrics should we track to evaluate the effectiveness of our customer journey?
7. Suggest ways to personalize the customer experience at different touchpoints.
8. How can we use customer feedback to improve our journey map?
9. What are potential obstacles that might cause a customer to abandon their journey?
10. Identify opportunities for upselling or cross-selling in the customer journey.
11. How can we streamline the onboarding process for new customers?
12. Suggest ways to personalize my post-purchase onboarding and support.
13. What post-purchase customer interactions can we implement to increase customer loyalty?
14. How might customer needs and customer expectations change throughout their journey?
15. What are effective ways to gather customer feedback at different stages?
16. How can we use AI to predict potential customer churn points?
17. What are the key differences in the journey between new and returning customers?
18. How can we create a more emotionally engaging experience throughout the journey?
19. How can we drive customer loyalty? List points for improvement in our process.
20. What are potential triggers that move a customer from one stage to the next?
21. How can we better align our marketing efforts with the customer journey?
22. What role does customer support play in the overall journey, and how can it be improved?
23. How can we use AI to create more accurate customer personas for our journey map?
24. What external factors, such as economic fluctuation and seasonality, will influence my customers' buying decisions?
25. What are the most common drop-off points in our [email nurture sequence, website, etc.], and how can we address them?
26. Where is automation least effective in my customer journey — where do our customers need the most one-on-one contact?
27. What data should we start collecting now to get actionable and accurate predictive analytics on our customers later?
28. What trends are going to influence our customers' needs and buying decisions?
29. Which of our customer segments are underserved, and what are suggestions for filling the holes?
30. What data should we be collecting now to accurately analyze our customer journey 6 months from now?

Pro tip: When using AI, remember your outputs will only be as good as your inputs. The more details you can give about your business, your objectives, your data points, etc., the more tailored your responses will be.

You can save time in this process by creating a custom GPT with a ChatGPT plus membership. This personalized chat will be trained on your business data and act as a tailored AI knowledge base for your business.

Testing It Out: How I Created a Customer Journey Map With AI

To learn how to build a customer journey map with AI, I wanted to try it out myself.

Here's a simple prompt that I tested out. Keep in mind that I added some background information about what services I offer, who my customers are, etc., so that I would get a more tailored response.

The response? I was able to turn the initial results into a simple chart with the help of Claude. You‘ll see that it covers touchpoints, client actions, opportunities, and metrics at each stage of my buyer’s journey. Not a bad start if you ask me!

To take it one step further, I took this data and added it to a Whimsical Diagrams GPT to create a visual chart. There were still some kinks to work out with the prompting, but I eventually got to a basic version that I'm pleased with.

Source

Going through this process, I discovered that I had two problems (read: areas of improvement) on my hands. The first is that I lacked a lot of customer data that I needed to input into the AI — so this was a good nudge for me to find better ways to monitor my customers' journey. The metrics column here offers a great starting point for KPIs I can track — and ideally improve.

I also found that there was a pretty big gap for buyers at the consideration stage. I don't always make it clear why they should hire me instead of my competitors. Luckily, this chart is actionable for me. I'm able to focus on creating more diverse writing samples and client success stories — and will be tracking this through my site metrics.

Pro tip: Once AI has helped you identify the holes in your customer journey, use it to help you make a plan to fix it. Try customizing this prompt:

I'm making a customer journey map for my [freelance writing] business, and I have gaps in the [consideration stage]. What are ways for me to fill this stage of my customer journey map?

ChatGPT had great suggestions for me, like strengthening my portfolio, gathering more social proof, and developing low-commitment offers for new clients.

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Helpful AI Tools for Customer Journey Mapping

Of course, there are so many incredible AI tools on the market that go beyond ChatGPT. If you're serious about incorporating more AI into your process, I highly recommend checking these out. Again, I tested each of these out for my own business to see first-hand what the experience is like as a user.

1. Taskade

You might already be familiar with the AI tool Taskade. It offers a ton of helpful work management features, like managing tasks and team collaboration. But I found their User Journey Map Generator (powered by AI) to be a really helpful tool in both brainstorming and visualizing the customer journey map.

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Key features:

• Integration with other project management tools.
• Real-time collaboration capabilities.
• AI-driven journey map creation.
• Customizable templates.

Pro tip: Taskade's AI can help generate journey maps based on your input, making it an excellent starting point for beginners new to journey mapping (aka me!). What I really liked is that you can use their AI agent at various points of the process, which will help you research specific bullet points, develop an outline, and even spell-check.

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2. Twilio Segment

Twilio Segment is a powerful customer data platform that can help make your journey mapping a breeze. While not exclusively a journey mapping tool, it has strong capabilities for data collection and analysis that can help you create a more detailed customer journey.

For example, you can visualize the journey a specific customer might take who hasn't purchased from you in three months but has visited your site in the past month. Without using AI, think how much time you could spend trying to track, identify, and tell a story from these data points.

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Key features:

• Integration with over 300 tools and platforms.
• AI-powered customer segmentation.
• Unified customer data collection.
• Real-time data analysis.

Pro tip: This also helps CX teams increase their personalization — which is a top priority according to our State of Customer Service report.

3. Journey AI

Although last on this list of tools, Journey AI is one of the most fascinating tools I discovered during my research process. Created by TheyDo, Journey AI instantly converts customer research into journey maps packed with actionable insights — and saves you hours worth of manual work.

For example, you can input your text-based research (think everything from sticky notes to surveys) to create a customer journey map tailored to customer feedback.

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Key features:

• Standardize and scale customer journey mapping and management.
• Creates customer journey maps in a matter of minutes.
• Intuitive, easy-to-use editor.

Personalize Your Customer Journey With AI

As I was researching and reviewing these AI tools, what I found most fascinating is all the ways you could personalize and improve customer journey maps with the click of a few buttons (plus some trial and error). Through this process, I was able to tweak my prompts and inputs throughout to tailor it for my specific business and needs. If you can apply the same lessons, the outcome is powerful.

AI can help transform a task that is arduous, time-consuming, and complex into one that is streamlined, driven by data, and easy to understand. This empowers me on my business journey to focus more on what I do best — while also ensuring that I keep a steady stream of happy customers. (A win-win!)

Of course, this is a great place to remind you that AI is not a magic solution. It‘s a powerful tool that works best when combined with human insight and expertise. As I continue to test new tools, I'm excited to see how AI will further help me improve my customer journey and build my business.

Editor's note: This post was originally published in October 2024 and has been updated for comprehensiveness.

The State of Customer Service Report

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• Exclusive insights from worldwide CRM leaders
• Analysis of modern customer behaviors
• Closer look at the AI opportunity in CRM
• Strategies for staying agile in 2024 and beyond

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