As a business leader, you want to have as much good information as possible before making important strategic decisions. Yet, many decisions that affect customers, employees, and products are made based on "common knowledge" handed down within the organization.
These seat-of-the-pants decisions often work out fine. But, sometimes, they blow up in your face. And we often need a complete picture of why they succeed or fail.
It's time to get organized and embrace a new approach to data-driven journey maps.
What is Journey Mapping?
You probably associate journey mapping with customer journeys. But journey mapping is a versatile tool beyond customer interactions, extending to any process within a company that unfolds over time.
Whether it's charting a product's lifecycle from conception to market, mapping an employee's progression from onboarding to advancement, or tracing the customer's experience from awareness to loyalty, journey mapping captures each step.
It is a visual narrative that highlights the sequence of events and interactions within these journeys, identifying key moments that matter. And it's all based on data.
This method enables businesses to dissect and understand the complexities of their operations, employee experiences, and customer engagements. By visualizing these paths, organizations can pinpoint opportunities for improvement, barriers to success, and moments of excellence.
Journey mapping is about finding a destination and optimizing the paths that lead there, ensuring a seamless, efficient, and engaging experience for products, employees, and customers alike.
The Rise of Knowledge Graphs
Knowledge graphs represent a paradigm shift in data analysis. They offer a dynamic and interconnected framework that can evolve with the customer journey, providing a comprehensive real-time view of customer interactions across various touchpoints.
Traditional relational databases—while helpful when applied to customer journeys—often fall short of capturing the dynamic nature of customer interactions.
They're structured with predefined schemas, making it difficult to adapt to the evolving nuances of customer behavior that journey mapping reveals. The better way to organize your data is with knowledge graphs.
Here are some examples of customer journeys:
Customer Experience
At its core, journey mapping starts with the customer experience. Businesses can design experiences tailored to their needs and desires by tracking each customer's step. For instance, if journey mapping reveals that customers often seek help after making a purchase, a company can proactively offer support immediately after the sale, enhancing satisfaction and loyalty.
Marketing Campaigns
In marketing, journey maps can illustrate how customers move from discovering a product to purchasing. This visibility enables marketers to craft targeted campaigns that speak directly to where the customers are in their journey, resulting in more effective marketing spending and better conversion rates.
Customer Segmentation
Customer segmentation based on behaviors is where journey mapping and knowledge graphs show their true power. By mapping customer behavior and preferences, businesses can create highly targeted segments. Knowledge graphs take this a step further by uncovering groupings, hidden relationships, and trends that can lead to discovering niche segments or predicting emerging customer needs.
A Perfect Pair: Knowledge Graphs and Journey Mapping
When combined with journey mapping, knowledge graphs illuminate the relationships between customer interactions, offering businesses a 360-degree view of the customer experience. This pairing highlights direct paths and reveals indirect routes customers may take, offering a depth of previously unattainable insight.
In essence, knowledge graphs offer a more nuanced, contextually rich, and scalable approach to data analysis than traditional relational databases. This approach makes them particularly well-suited for journey mapping, where understanding the complex web of customer experiences and operational processes is critical.
Further, once journey mapping is completed, the foundation has been set to apply machine learning for predicting actions and exploring what-if scenarios and causal relationships.
By leveraging the superior capabilities of knowledge graphs, businesses can achieve a more comprehensive and dynamic understanding of their data, leading to more intelligent, more informed decisions—and who wouldn't want that?
Want to learn more? Read Knowledge Graphs are Marketing's New Superpower.
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