Customer journey analytics built for modern digital experiences.

Customer journey analytics (CJA) is the process of understanding how customers interact with an organization across multiple channels over time. The goal is to deliver optimal customer experiences across touchpoints by providing cross-functional teams with a 360-degree view of the customer.

CJA identifies key moments when customers choose to proceed with a purchase or drop out of a certain path. This allows organizations to steer away from negative paths to improve the customer experience.

A practical example of customer journey analytics is the ability to track and visualize total visits that started on the website, reached out to the contact center, visited a retail store, and then either abandoned or completed a transaction on the native app.

• CX teams use Quantum Metric customer journey analytics to measure and validate optimal iterations in the customer journey across mobile app, web, contact center, physical stores and beyond, enabling more timely improvements and faster resolution to issue escalations. 
• Product teams can understand how customers interact with features, pages, messaging, and determine why they’re dropping off. By visualizing the exact steps a customer takes to a specific experience, product managers can learn if there are too many steps, or if it’s confusing or not working as expected.
• UX/Design teams can get data on how people navigate feature sets, see what’s popular (and what’s confusing) in the design, identify roadblocks, and pinpoint key moments of abandonment.
• Marketing teams can use journey analytics to see where customers are entering and abandoning to stop “leaky” ad spend, and understand which aspects of the experience drive conversions. 
• Analytics teams can get a complete view of how customers traverse channels and recommend stakeholder action.
• Customer service & support teams can diagnose issues in the customer journey in real-time to answer customer questions, resolve concerns more quickly, and reduce call volumes.

Customer journey analytics and customer journey mapping are distinct but interconnected aspects of understanding the customer experience. Customer journey analytics involves tracking and measuring customer behavior and interactions across the various channels of your business. Customer journey mapping, on the other hand, is a collaborative process (often involving workshops between internal researchers and customers) of gathering qualitative and quantitative data about customer expectations, perceptions, and realities across the customer journey.

The goal is to understand the gaps between what customers desire and expect from an experience vs. how they perceive the experience vs. how they actually behave during the experience at each step of the journey across various channels.

In other words, customer journey analytics can be used as a behavioral data input into the overall customer journey mapping process.

Customer journey analytics can vastly improve the customer experience by helping businesses better understand and empathize with their customers. The insights derived from customer journey analytics tools like Quantum Metric Journeys help CX, digital, and support teams drive improved ROI and overall customer satisfaction by identifying, optimizing, and/or personalizing customer journeys.

Quantum Metric collects all of your customer journey data together in one place to not only understand the paths your customers are taking through your website, mobile app, and even contact center or store, but also why they have taken that path or abandoned it.

Using a combination of Sankey charts, sunburst diagrams, session replay, and omnichannel insights, Quantum Metric helps teams across the organization improve KPIs related to engagement, conversion, and drop-off. For example:

• Engagement across channels
• • • How are customers navigating and where is friction that might be navigating them away unnecessarily from more efficient, self-service channels (like digital) to higher cost channels, impacting their satisfaction? Top KPIs: sessions, bounce rates, time spent on page, rage clicks, possible frustration, back buttons used, rapid scrolling and slow APIs.
• Conversions and drop off
• • • Where and why are customers entering and abandoning at various stages across web sites and native apps, and what drives them to convert? Top KPIs: account creations, bill pay completions, credit card applications completed, product demos, sales conversions
• Customer feedback, sentiment, retention and operational efficiency
• • How can we gain deeper context and reasoning behind the feedback and NPS scores we receive at various stages of the customer journey? And how can we make it easier for customers to complete tasks and resolve issues, improve customer retention, reduce churn rate? Top KPIs: Customer Effort Score (CES), Customer Satisfaction (CSAT), Net Promoter Score (NPS), Customer Retention Rate, Customer Churn Rate, Average Resolution Time

Quantum Metric stands out for its ability to easily pivot from journey visualizations to contextual session replays and to easily enrich any offline data source with actionable omnichannel insights. For example, by linking call center data to digital session data, you can diagnose the events that lead to calls. Or by uploading offline purchase data, you can optimize digital experiences for offline conversions.

While most customer journey analytics tools show the various paths and drop-offs of users, Quantum Metric helps teams understand why customers struggle and how those struggles impact business outcomes.

Other journey analytics tools include visually appealing Sankey charts, but the insights they provide can feel a bit limited and static. Quantum Metric’s real-time quantification plus visualization helps your brand understand the “why” behind customer paths and the steps you need to take in response – whether it’s fixing a specific error or capitalizing on a revenue opportunity.

Plus, with Quantum Metric’s autocapture, you get hundreds of out-of-the-box behavioral indicators and automated step analysis, allowing you to quickly prioritize the most important business opportunities and take action.

Yes, Quantum Metric customer behavioral data and technical data populate in real time across the platform. This means that if you release a feature, you can automatically visualize how customers use different channels throughout the journey, so you can proactively address fixes or enhancements.

Customer journey analytics can provide answers to a wide range of business questions that help you improve customer experiences, product development, and marketing strategies. A few examples:

• How do customers engage with our brand across different channels?
• What are the common paths or sequences customers take before making a purchase?
• Where do customers experience friction or drop off in the customer journey?
• What are the key drivers of customer satisfaction or dissatisfaction?
• How can we personalize customer experiences at different stages of the journey?
• What is the impact of marketing campaigns on customer acquisition and retention?
• Are there any patterns or trends in customer behavior?
• How can we optimize cross-channel customer journeys?
• What is the lifetime value of different customer segments?
• How can we improve customer loyalty and advocacy?