Customer Journey Analytics
Learn the difference between real customer journeys and post-it versions
This publication is broken up into three sections:
TL;DR - For those wanting a quick take
Summary - For those wanting a bit more context and high level points
Article - Main body of work containing fully detailed article and explanations that you might want to consume over several readings
TL;DR
Customer Journey Management (CJM) is required to deal with the increasing complexity of interactions between ‘customer segments’, devices, channels and capabilities offered on a specific channel.
Customer Journey Analytics (CJA) which is a part of the broader CJM realm. CJM is a fundamental shift in how organizations can approach their Customer Experience (CX) Management.
CJA uses data from multiple sources including web logs, surveys, customer service logs, and Customer Relationship Manager (CRM) systems to develop more personalized and tailored customer experiences with a unified customer experience across channels and devices.
CJA enables organizations to analyze customer behavior, identify trends, patterns, and opportunities to identify areas of improvement and opportunities for growth so they can make more informed decisions by understanding how your customers interact with your products, services, and content across multiple touchpoints.
CJA helps to identify and target customers who are most likely to convert, and those who need further nurturing through insights into customer preferences, behaviours, and needs that can be used to inform decisions and optimise customer experiences to improve customer engagement, loyalty, and satisfaction.
There are a few limitations to CJA such as data quality problems, data governance issues, data ownership barriers, customer identity matching and data schema incompatibilities, and the duplication of data across sources.
Summary
Customer Journey Management (CJM) is required to deal with the increasing complexity of interactions between ‘customer segments’, devices, channels and capabilities offered on a specific channel.
CJM consists of the following areas:
Journey Mapping - is a way to visualize and communicate your customer’s experience across touchpoints over time as they seek to achieve a specific goal.
Journey Visualisation or Discovery - is a way to analyse customer behavior data across touchpoints and over time to measure the impact of customer behavior on business outcomes.
Journey Orchestration - is a way to use each customer’s entire experience to inform and personalize interactions that will improve customer experience and drive desirable outcomes.
CJA is a type of data analytics that focuses on understanding how customers interact with a business’s products and services, across touchpoints over time.
CJA goes beyond web and product analytics tooling in that you are able to stitch together various touchpoints a customer or stakeholder could be using to interact with your organisation.
Instead of focusing on a theoretical customer journey you can deploy CJA tooling to understand the actual customer journeys your customers are taking to complete tasks and not the idealised or idolised version you crafted in a workshop using physical or digital sticky notes.
CJA provides insights into how customers interact with a company in order to improve their experience, increase conversions, and reduce customer churn across your touchpoints over time.
CJA platforms allow you to quantify customer experience with journey-based metrics and KPIs, so you can measure CX metrics like NPS, CSAT, and FCR at various points in the customer journey, and understand the kinds of behaviour that drive changes in each metric.
There are a few limitations to CJA such as data quality problems, data governance issues, data ownership barriers, customer identity matching and data schema incompatibilities, and the duplication of data across sources.
Article
My previous data related articles have covered the following areas: Data Data Data, Data Analytics, Web Analytics and Product Analytics. In this article I will continue exploring the analytics theme.
This article will cover an important analytics area referred to as Customer Journey Analytics (CJA) which is a part of the broader Customer Journey Management (CJM) realm. CJM is a fundamental shift in how organizations can approach their Customer Experience (CX) Management.
I share my perspective on how CX relates to UX and UI below.
Customer journey management
CJM is required to deal with the increasing complexity of interactions between ‘customer segments’ (e.g., stakeholder groups that need products, services, information, or have structured interactions with your organisation like regulators, suppliers etc.), devices, channels and capabilities offered on a channel. Unlike say web analytics and product analytics, CJA can handle integrating operational data from both online (web, smartphone app, email, kiosk etc.) and offline (retail store, contact center etc.) channels.
The framework I will use to frame CJM is inspired by Forrester where CJM is defined as Journey Mapping, Journey Visioning or Visualisation (aka Journey Discovery as referenced by vendor Pointillist), and Journey Orchestration which includes key functionality like Real-time Interaction Management (RTIM).
CJM consists of the following areas:
Journey Mapping - is a way to visualize and communicate your customer’s experience across touchpoints over time as they seek to achieve a specific goal.
Journey Visualisation or Discovery - is a way to analyse customer behavior data across touchpoints and over time to measure the impact of customer behavior on business outcomes.
Journey Orchestration - is a way to use each customer’s entire experience to inform and personalize interactions that will improve customer experience and drive desirable outcomes.
To execute on CJM effectively the following capabilities are required:
Customer Journey Data Management – integrated time-series data repository of customer behaviour journey data across device and channel touchpoints.
Customer Journey Analytics - measurement, monitoring and optimization of customer experience, by aligning the organization with the customer’s goals.
Customer Journey Orchestration - use each customer’s entire experience to inform and personalize interactions that will improve customer experience and drive desirable outcomes.
NB., The key to getting operational impact and business outcomes is to leverage a tool that has journey orchestration tooling and real-time interaction management which can enable dynamic experience use cases to be developed that use event-driven architectures e.g., imagine purchasing the latest MacBook Pro from your favourite online retailer and paying using a direct deposit EFT payment method which kicks-off a high value payment alert at your bank (who happens to provide you with P&C insurance cover) which is used to trigger a message informing you that your bank is willing and able to offer you device cover under your existing P&C cover and all you have to do is accept the new pricing in the banks in-app authentication center. This is what real-time interaction management and orchestration could enable.
Usage areas for CJM in your organisation
Journey Design is the process of defining the experience a customer has as they seek to achieve a goal or task and the actions the company will take at each step to promote progress towards the goal or task completion.
Journey Insights are the quantitative and qualitative information that helps you understand the behavior of your customers as they seek to achieve a goal or complete a task.
Journey Optimization is a closed loop approach that uses AI or machine learning to improve the experience of each customer, so they can achieve their goal or tasks more efficiently.
Background on customer feedback programs
Before we get into what CJA is, which forms a part of Journey Visioning or Visualisation we need to review some background context.
Prior to the emergence of CJM as a concept and approach, there were customer feedback programs that were created to capture and understand how well an organisation was performing in meeting customer needs. One of the most well-known of these customer feedback programs was Voice of the Customer (VoC).
The concepts and methodologies of VoC were first outlined in a Marketing Science paper published by Griffin and Hauser in 1993. The VoC paper built upon work by Hauser and Clausing in 1988 titled The House of Quality in Harvard Business Review. VoC is described in that paper as "...a product-development technique that produces a detailed set of customer wants and needs, which are organized into a hierarchical structure, and then prioritized in terms of relative importance and satisfaction with current alternatives."
Extract from Abstract for Voice of Customer (VoC):
“The Voice of the Customer (VOC) is a process for capturing customers’ requirements. It produces a detailed set of customer wants and needs which are organized into a hierarchical structure, and then prioritized in terms of relative importance and satisfaction with current alternatives. There are four aspects of the VOC – customer needs, a hierarchical structure, priorities, and customer perceptions of performance. Voice of the Customer studies typically consist of both qualitative and quantitative market research steps. They are generally conducted at the start (or “Fuzzy Front End”) of any new product, process, or service design initiative in order to understand better the customer’s wants and needs (see WIEM05-022). The VOC can be also be a key input for new product definition, Quality Function Deployment (QFD) (see WIEM05-023), or the setting of detailed design specifications (see WIEM05-049). The Voice of the Customer process has important outputs and benefits for product developers. It provides a detailed understanding of the customer’s requirements, a common language for the team going forward in the product development process, key input for the setting of appropriate design specifications for the new product or service, and a highly useful springboard for product innovation. As may be seen in the examples presented, gathering the Voice of the Customer is an extremely important part of the new product development process. It forms a solid basis for design and marketing decisions from concept development through product launch.”
Some interesting questions to explore in future articles, how is VoC which was conceptualized for Product Development, Quality Function Deployment and Jobs to be Done Theory (ala Tony Ulwick) related given all three approaches reference needing to understand customer needs and determining relative importance and value of those needs to customers?
VoC programs were aimed at providing marketing and product teams with information to develop better products and services.
According to Gerald M. Katz (2001), VoC was initially used to improve Product Development, though eventually it became a technique referencing “any type of market research with customers”.
Nowadays the most common perception of VoC is for surveying customers on their experience with your organization. Typically, with VoC programs you’re only capturing feedback from a portion of your customers and tracking maybe 1 out of every 2500 interactions.
The way VoC is used today is not in line with its initial purpose as a new product development technique. I guess this is the main challenge with any framework or idea, it eventually gets corrupted or used in other ways not intended e.g., Business Model Canvas, Balanced Score Card, Design Sprints, OKRs etc.
Although many organizations have already adopted customer feedback management, 73% of companies failed to improve their CX scores in 2020 despite this investment.
The reason is simple, survey based VoC data is only measured in aggregate, by segment, or after isolated transactions within individual touchpoints. It doesn’t enable you to understand and optimize individual customer experiences or measure their impact on business outcomes and only a fraction of your customers are responding to your surveys.
The core motivation for CJA is the fact that you can now get actionable insights on real-world customer journeys.
What is customer journey analytics?
CJA is a type of data analytics that focuses on understanding how customers interact with a business’s products and services, across touchpoints over time.
CJA goes beyond web and product analytics tooling in that you are able to stitch together various touchpoints a customer or stakeholder could be using to interact with your organisation.
Touchpoints are combinations of device, channel and specific capabilities you interact with for a given interaction e.g., a customer interacting with a bot within in-app chat on a native smartphone application can be viewed as a touchpoint or someone interacting with a web application self-service capabilities on a desktop could be another touchpoint or a customer calling into the call center to complete a specific transaction is another touchpoint on a feature phone.
Instead of focusing on a theoretical customer journey you can deploy CJA tooling to understand the actual customer journeys your customers are taking to complete tasks and not the idealised or idolised version you crafted in a workshop using physical or digital sticky notes.
CJA provides insights into how customers interact with a company in order to improve their experience, increase conversions, and reduce customer churn across your touchpoints over time.
CJA, I believe will continue to gain momentum as enterprises recognize the value of customer journeys as a means to monitor customer experience performance and identify opportunities for improvement.
Measuring customer experience is still a struggle for many enterprises. One of the core challenges of CX has been quantifying the ROI of CX initiatives and investments. Without a sound theoretical model of change measuring impact of CX initiatives will continue to be a problem.
What can you measure with CJA?
CJA in the early 2000s was in it’s formative stage and began as a way to measure customer satisfaction and customer loyalty. Since then, the technology has evolved to include more sophisticated analytics capabilities, such as predictive and multi-touch attribution across multiple touchpoints.
With CJA, organisations can measure:
customer engagement
customer lifetime value
real customer journeys and drop-off or friction points
customer acquisition costs
cost to serve a customer across specific channels
customer behaviour, such as customer preferences, customer sentiment, and customer segmentation
CJA software helps you identify the costliest failure points in your customers’ journeys, so that you can allocate company resources based on what matters most to your customers and your organization.
CJA platforms allow you to quantify customer experience with journey-based metrics and KPIs, so you can measure CX metrics like NPS, CSAT, and FCR at various points in the customer journey, and understand the kinds of behaviour that drive changes in each metric.
You can pinpoint the drivers of customer satisfaction by understanding the journeys that influence your most—and least—satisfied customers. And you can determine the impact of a poor experience on business objectives like revenue, churn, or repeat purchase rate as well as the effectiveness of remediation that you may make.
CJA platforms can help you design personalized experiences by allowing you to create hypotheses and test them with new journeys and visualize their impact on the current experience.
Since there are a variety of real business problems that CJA can be used to solve, these platforms do not include identical capabilities, nor do they prioritize the capabilities they do include in the same way. This is an important consideration when evaluating options and solutions.
Fundamental CJA capabilities to consider when evaluating options
Unify customer data and match customer identities across touchpoints (i.e., logged-out and logged-in states)
Discover and visualize real customer journeys
Segment customers based on behaviour, demographics, and psychographics
Rapidly generate insights to understand the factors impacting key KPIs such as churn, revenue, acquisition, customer lifetime value, etc.
Orchestrate personalized, multi-channel customer experiences
What are the limitations of CJA?
To get the right CJA insights on customer journeys, you need a deep understanding of customer behavior so that you can provide your customers with a better experience.
To achieve the above requires: well-developed event data taxonomy, architecture and data quality practices.
As with most things in life there are limits on what a given technology can do. Below is a high-level view of the main limitations:
CJA is dependent on the accuracy of customer data provided by the business. If the data is incomplete or inaccurate, then the insights from CJA may be inaccurate.
CJA requires a significant amount of resources in order to be successful. Companies need to invest in the technology, data collection and analysis, personnel, culture and process engineering to ensure the accuracy of the data being collected and analysed.
CJA is limited by the amount of data that is available. If a company does not have access to a large amount of data, they may not be able to accurately measure customer journeys or accurately identify trends or patterns.
CJA relies heavily on up-to-date data, so if the data is not updated regularly, the insights gained may not be accurate.
Other impediments to CJA are data and organizational silos which are major barriers, particularly in banking, telecom and health insurance companies who have overwhelming amounts of data from millions of customers across touchpoints and business functions.
Typical challenges to implementing CJA
These range from data quality problems, data governance issues, data ownership barriers, customer identity matching and data schema incompatibilities, to the duplication of data across sources.
Even if you’ve overcome these challenges, getting your customer data analytics questions answered often requires dealing with a bottleneck with getting access to data science specialists.
Data aggregation
Customer data is often siloed among several channels--customer feedback surveys, CRM data, social media reviews, website analytics, purchase history, etc. Each source has a distinct data format, and combining them all for a complete picture isn’t always simple.
Timing
Customers want fast solutions to their problems, otherwise, you risk losing them to competitors. Unfortunately, CJA tools can’t always keep up with the pace of customer demand if new approaches like streaming are not included. Either the data is not updated in real-time, or the need for intensive data preparation (eg. ETL, data cleaning) results in long lag times before the data can be queried.
Missing the big picture
Some touchpoints or platforms are more data-rich than others or produce data that are easier to digest. When data is not equally distributed across the buyer journey, you may end up focusing on one touchpoint without looking at the entire journey. Thus it’s important to have a tool that can bring in data from all sources and data formats.
Complexity of data
Enterprise data is extremely complex, in many cases requiring help from data specialists in order to create and answer even basic queries. For more complex queries, you may wait weeks or months for insights. This is a huge impediment to both company objectives and efficient use of resources. Not to mention it makes solving customer problems on the fly virtually impossible.
What do you need to effectively implement CJA?
To get actionable customer insights from CJA tooling the following issues need to be addressed.
Organisational and Process Considerations:
Organisational discipline to keep data trustworthy is a Herculean task. When information is missing from manual instrumentation, agile PMs are forced to make gut decisions, or delay a release until they gather necessary data. These challenges increase as your company gets larger.
Collaborative workflows are possible with robust and customizable permissions. Ideally, individual users can go exploring in the data without affecting what other users are seeing. And teams should be free to access the data they want, analyze it with flexibility, and leverage it to build a powerful user experience.
Custom permissions give each user the right level of access and control. You can roll out data to everyone the whole company and empower each user to do the most with it.
Unified views keep everyone on the same page, reversing the usual trend towards entropy. When everyone is looking at the same data all the time, silos don’t get a chance to form.
Data Quality and Governance Considerations:
Clean data which maximizes opportunities for confident and accurate insights.
Standardized event naming with categories and annotations provides structure and context for events, actions, properties, and user segments. Together, these features eliminate confusion over what events refer to, making it easy for everyone on the team—and across the company—to find the data they’re looking for.
Data dictionary provides naming conventions and a single source for all product data, including events, properties, categories, and user segments. Newly-created definitions should automatically be submitted for verification, to give analysts confidence that they’re using the right information.
Event repair alerts admins about stale and/or duplicate event definitions, then guides them through the process of repairing or archiving. There’s no confusion about definitions and your dataset stays lean and mean.
Key take-aways on CJA
CJA uses data from multiple sources including web logs, surveys, customer service logs, and CRM systems to develop more personalized and tailored customer experiences with a unified customer experience across channels and devices.
CJA enables organizations to analyze customer behavior, identify trends, patterns, and opportunities to identify areas of improvement and opportunities for growth so they can make more informed decisions by understanding how your customers interact with your products, services, and content across multiple touchpoints.
CJA helps to identify and target customers who are most likely to convert, and those who need further nurturing through insights into customer preferences, behaviors, and needs that can be used to inform decisions and optimise customer experiences to improve customer engagement, loyalty, and satisfaction.
Postscript
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Basic overviews of some CJA vendors
CSG Kitewheel is a cloud-based customer journey orchestration platform designed to help organizations create personalized customer experiences.
It integrates with customer data, channels, and systems to manage and automate customer journeys.
It provides a visual journey designer that enables users to easily create, optimize, and analyze customer journeys.
It includes a journey analytics dashboard that provides insights into customer behavior and allows users to make data-driven decisions.
CSG Kitewheel enables users to create personalized experiences by leveraging customer data and insights.
It offers machine learning-based journey optimization capabilities that help to maximize customer engagement.
It integrates with customer relationship management (CRM) systems, marketing automation platforms, and customer engagement platforms.
CSG Kitewheel provides an API that can be used to integrate with third-party systems and applications.
It offers advanced segmentation capabilities that enable users to target customers based on their preferences and behavior.
CSG Kitewheel is available as a SaaS platform, and provides enterprise-grade security and scalability.
InQuba is a cloud-based customer data platform that helps companies get a 360-degree view of their customers across multiple channels.
InQuba helps businesses link and unify customer data from various sources including online and offline channels.
InQuba helps businesses track customer journeys and gain insights into customer behavior and preferences.
InQuba enables businesses to create personalized customer experiences based on data-driven insights.
InQuba helps businesses build relationships with customers by providing a unified customer profile across multiple channels.
InQuba offers a suite of tools to help businesses segment customers, measure customer loyalty, and analyze customer churn.
InQuba’s data platform provides advanced reporting and analytics capabilities to help businesses make better decisions.
InQuba provides APIs and SDKs to integrate with existing systems and processes.
InQuba also offers consulting services and professional support to help companies maximize the value of their customer data.
InQuba is GDPR compliant and provides secure data storage, access control, and data encryption.
Genesys Pointillist is a customer experience analytics platform designed to help organizations gain insights about their customers.
Pointillist provides real-time visibility into customer behavior, enabling organizations to make better decisions about customer interactions.
It uses AI and machine learning to monitor customer interactions and provide actionable insights.
Pointillist helps organizations measure customer satisfaction, track customer journeys, and identify areas of improvement.
It integrates with other customer experience solutions, such as Genesys PureEngage, to provide a unified view of customer data.
Pointillist can be used to gain insights into customer sentiment and sentiment trends, as well as monitor customer engagement with marketing campaigns.
It provides analytics dashboards and reports to help organizations better understand customer needs and preferences.
Pointillist supports data integration with popular business intelligence (BI) systems, such as Tableau, Power BI, and Qlik.
It also offers APIs for developers to access customer data and build custom applications.
Pointillist can be deployed on-premise or in the cloud.
Resources
PKwik Pro open Customer Journey Analytics