The Essential Guide to Customer Journey Mapping for Data Analysts

Rishikesh Ranjan
September 28, 2023


As the architects of information and the engineers of insight, we, the data analysts, are typically submerged in figures and charts, tasked with extracting meaningful stories from a sea of numbers. However, to truly use the power of data, we need to step beyond the limits of quantitative analyses and get into a more holistic, human-centric approach. Enter: Customer Journey Mapping.

Customer Journey Mapping is not a new concept, but its critical role in optimizing customer experiences and brand interactions is more relevant now than ever. 

Customer Journey Mapping allows us to visualize and empathize with our customers’ experiences, decipher their motivations and expectations, and ultimately, unearth the 'whys' behind the 'whats' in their interactions with our brand. 

This blog is designed to be your guide on this exploration, a guide that will light the path from data to Insight, number-crunching to narrative-building.

Too long to read? -> Do it yourself. Click here to duplicate the template and get started. 

Why is “Customer Journey Mapping” important?

As a data analyst, you're often neck-deep in numbers, charts, and tables. Now is the time to put some life into those digits! 

Dive into Customer Journey Mapping. It is a storyboard where each frame captures a customer's interaction with your brand. Now, why's that cool and essential for a data maverick like you? Let's dive into it:

Humanize the Data:

Data's not just numbers; it's a story. Journey mapping lets you paint a picture, giving color to those rows and columns. It’s a Blend of Art and Science. For example: Instead of just seeing a spike in website traffic, mapping will reveal that visitors drop off after visiting a product page. They aren't just numbers; they're potential customers you are losing!

Spot Patterns and Gaps:

While crunching numbers shows results, journey mapping showcases the process. You will easily spot where customers waltz smoothly and where they stumble. Hypothetically, Say, 70% of customers abandon their carts. The map might reveal they do so after seeing shipping fees. Aha! Time to reconsider the shipping strategies.

Collaborative Catalyst:

Bridging Departments: Presenting findings with a customer journey map unites marketing, sales, customer support and product, sometimes even Finance. By having everyone share their thoughts and perspective, you get a more complete picture and a lot of praise, and may be promoted.

Scenario: Marketing drives traffic, but sales don't see conversions. With a map, they collaboratively identify bottlenecks and brainstorm solutions. Teamwork for the win!

Empathy-Driven Analysis:

With so many 1s and 0s, it's easy to forget that behind every click, scroll, and interaction is a human being. Empathy-driven analysis anchors the data in human emotions and motivations. By understanding not just the 'what' but the 'why' behind user actions, you will uncover deeper insights that pure data might miss. 

For instance, if customers consistently drop out after a signup page, maybe it's not just a UX issue. Could it be that they're overwhelmed or skeptical? Time to probe!

Predictive Power-Up:

Integrating customer journey mapping into predictive analysis offers a more refined approach to foreseeing future trends. It enables you and your team to anticipate customer needs based on patterns from the past. For example, if users who engage with a tutorial tend to make a purchase, then creating more such content will be a strategic move. Predictive insights from journey mapping also allow for tailored marketing campaigns, proactively addressing potential issues, and optimizing resource allocation based on forecasted demands.

End-to-End Insights:

Customer journey mapping provides a detailed overview of a customer's entire interaction with a brand, from the initial discovery to post-purchase actions. This full-scale view is very valuable in identifying key engagement points and potential drop-offs. Also, it sheds light on post-purchase behaviors, helping your customer success team in fostering long-term relationships. The insights gathered also ensure that strategies address the entirety of the customer experience, including interactions across various channels.

Fuel for Innovation:

Every interaction point in a customer's journey serves as an idea for business innovations. Addressing consistent challenges or issues faced by customers leads to the development of new product features or services. Moreover, any gaps in meeting customer needs signal opportunities for product or service expansion. Feedback, both positive and negative, is instrumental in driving innovation. Continuous insights from the customer journey support an iterative approach, allowing businesses to make regular refinements and improvements.

Customer Journey Mapping isn't just some fancy diagram. For a data analyst, it's a treasure that breathes life into numbers, fosters collaboration, fuels predictions, and is the mother of innovation. So, the next time you’re lost in a sea of data, draft a map, and explore the world from the customer's viewpoint.

What is “Customer Journey Mapping”?

Customer Journey Mapping is fundamentally illustrating and understanding the various stages and touchpoints a customer encounters with a brand or a service. It’s creating a vivid storyboard where each frame represents a unique interaction between the customer and the brand, letting you peek into the customer’s thoughts, feelings, and actions at every stage.

Basics of Customer Journey Mapping:

It is a visualization technique, often portrayed through graphs, flow charts, or diagrams, that narrates the whole story of a customer’s experience from the initial contact to a long-term relationship. It’s centered around the customer’s perspective, highlighting their expectations, experiences, and reflections at each interaction point.

Components of a Journey Map:

  • Stages of the Journey: Outlining each phase a customer goes through, like awareness, consideration, purchase, and retention.
  • Customer Interactions & Touchpoints: Detailing every point where the customer interacts with the brand, such as browsing a website, receiving an email, or contacting customer support.
  • Customer Emotions: Capturing the highs and lows of a customer’s feelings at different stages, identifying their satisfaction or frustration levels.
  • Metrics & KPIs: Combining satisfaction scores, NPS, and other key performance indicators to quantify the customer experience.

Let’s take a hypothetical example to understand better. Imagine a coffee lover, John, deciding to try out a new coffee shop. His journey mapping will include:

  • Awareness: Seeing an ad or hearing about the shop from a friend.
  • Consideration: Browsing the shop’s menu online and reading reviews.
  • Decision/Purchase: Visiting the shop and buying a coffee.
  • Post-Purchase Experience: Reflecting on the coffee taste, shop ambiance, and service quality.
  • Retention/Loyalty: Deciding whether to revisit and recommend the coffee shop based on his overall experience.

Each of the above steps have unique touchpoints, like online ads, websites, the actual store, and word of mouth, and each interaction evokes different emotions and thoughts in John, which the map will visualize.

For data analysts, a customer journey map isn’t just a visual aid; it’s a treasure of data. It provides granular insights into customer behaviors, preferences, pain points, and satisfactions at each step. Analyzing this data helps in uncovering patterns, predicting behaviors, and formulating data-driven strategies to enhance customer experience and brand engagement.

Remember, it's about putting yourselves in the customer’s shoes and viewing the experience through their eyes, blending analytical insights with empathetic understanding like watching a movie where the customer is the protagonist, and every scene is a new interaction with your brand.

How to do Customer Journey Mapping?

To understand “how to do Customer Journey Mapping” using SQL, we have created a template in Airbook which you can duplicate and get started easily. 

Here we are going into the methodology of Customer Journey Mapping with SQL and sourcing data from tables centered around leads, opportunity, usage, and billing. This dynamic process is key to optimizing customer journeys and fostering higher retention rates by providing a comprehensive analysis of qualified leads, active pipeline statuses, product utilization by free users, and more.


Here we use lead, opportunity, usage, and billing tables to meticulously dissect how customers navigate through our sales funnel. This pragmatic approach sheds light on:

📌 Which marketing sources are getting us more qualified leads?

📌 The number and value of opportunities at each stage in our pipeline.

📌 The behavioral patterns of our free users, emphasizing product interaction and points of disengagement.

Lead Analysis:

We kick off by inspecting all qualified leads and their origins using SQL queries, isolating those that align with our Ideal Customer Profile (ICP) from diverse sources. 

An insightful group-by operation on lead sources reveals the supremacy of website and paid ad campaigns over other channels, prompting a recommendation to amplify efforts in these domains. (check the template below to understand better)

Pipeline Inspection:

To understand our active pipeline, we check the number and stages of the qualified opportunities generated. The analysis unveils $800,000 of ARR stagnating in the Contract Stage, necessitating a closer inspection of the responsible opportunity owners and a strategic push towards deal closure.

Usage Pattern of Free Users:

A pivotal segment of our study revolves around deciphering the product interaction of our free users, focusing on daily usage trends, the popularity of features, and identifying the most active users. 

An examination of average API calls per day unveils usage trends, while a meticulous analysis of product features unveils the popularity of specific plans, with the “Team Plan” demonstrating superior engagement over the “Starter Plan”.

Identification of Active Users:

Finally, we categorize opportunities based on product usage, spotlighting those with the highest interaction levels. This opens up options for tailored outreach to transition active users from free to paid plans and optimizing revenue streams.

Strategic Action Points:

Based on the details above, the data analyst might note the following action points:

🌟 Intensify focus on high-performing marketing channels which are websites and paid ad campaigns.

🌟 Review and accelerate opportunities in the Contract Stage valued at $800,000 of ARR.

🌟 Strategize outreach to active users, encouraging transitions from free to premium plans.

Conclusion & Next Steps:

This Airbook, infused with rich, actionable insights, serves as a pivotal resource for companies looking to navigate the customer journeys, pinpointing optimal marketing strategies, unearthing potential revenue opportunities, and enhancing customer interaction with products.

For a more thorough understanding, I strongly encourage you to watch the embedded video, which outlines each step of the process with better clarity. 

And you feel a surge of inspiration? Duplicate the template and dive right in to start your own customer journey mapping and optimization.

Remember, every customer interaction is a stepping stone to building stronger, more fruitful relationships, and using data efficiently is the key to unlocking a treasure of opportunities. So, let’s roll up our sleeves and dive into the Customer Journey Mapping with SQL on Airbook!


Duplicate and get started


Why is Customer Journey Mapping important for a Data Analyst?
Can Customer Journey Mapping predict future trends?
Can I create a Customer Journey Map using SQL?
What are the key components of a Customer Journey Map?
How does mapping help in understanding customer emotions and expectations?
What insights can be drawn from the Customer Journey Map regarding marketing strategies?
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