by Steve Offsey

The debate on the importance of customer experience is over. In fact, a Forrester study already showed that “CX leaders grow revenue faster than CX laggards.” Nevertheless, most companies are still struggling to manage and improve customer journeys and experiences and measure it in a meaningful way. Even CX leaders are finding it difficult to make the quantitative link between customer behavior and business outcomes, so they can move beyond relying on gut feel and qualitative data to prioritize decisions.

In this post, I’ll describe how customer journey analytics makes CX actionable by directly tying customer experiences to revenue, profitability and other hard metrics on which executives are measured.

Why Quantifying CX is a Challenge

According to a Harvard Business Review Analytic Services Study, nearly half of all companies surveyed identified tying customer experience to business outcomes as very or extremely challenging. Even leading-edge companies face difficulties in this endeavor.

how customer journey analytics can help improve customer experience

From leaders to laggards, all companies find it challenging to tie customer experience to business outcomes. [Source: Lessons from the Leading Edge of Customer Experience Management]

Providing an exceptional customer experience is hard and tying it to tangible business outcomes is even more difficult. In order to quantify customer experience, you first need to create a single view of the customer as she interacts with your brand across channels and over time.

To achieve this unified view and deliver personalized customer experiences, analytics must evolve from retrospective reporting to real-time, behavior driven engagement. However, data overload and integration issues thwart a lot of these efforts.

Many companies are now collecting feedback from customer experience surveys, Net Promoter Scores® (NPS) and call center reports. When an individual metric like NPS improves, it is feted as a success and perhaps accepted without too many questions. But correlation does not equal causality, meaning that you are not controlling for other factors that could have caused an improvement in a specific metric, nor can you simply assume an exact relationship with hard metrics, like revenue or churn.

Measure effectiveness of customer service self-help

Customer Journey Analytics is the Bridge Between Customer Behaviors and Business Outcomes

Companies have traditionally looked to improve customer experience by focusing on particular touch points. This often leads to misleading results as customers could rate an individual interaction highly yet be unhappy over the course of an entire journey.

Customer journeys are at the core of customer experience, as customers engage with enterprises across touchpoints, channels and over time. Only by looking at a customer journey in its entirety across channels and over time can real pain points—and therefore opportunities for positive change—become visible.

How customer journey analytics can help improve customer experience

Looking at end-to-end customer journeys, and not individual touchpoints, is important

A recent McKinsey study found that “performance on journeys is substantially more strongly correlated with customer satisfaction than performance on touchpoints—and performance on journeys is significantly more strongly correlated with business outcomes such as revenue, churn, and repeat purchase.” Customer journey analytics is therefore essential to understand, prioritize, improve and measure customer experience and show its impact on revenue.

How Customer Journey Analytics Provides the Quantitative Information You Need to Improve Customer Experience

Here are four examples of how journey analytics enables enterprise teams to monitor, measure and quantify CX initiatives.

Quantify What Matters Most to Your Customers

Customer journey analytics platforms help enterprise teams pinpoint the drivers of customer satisfaction in a way that traditional analytics can not. It can provide quantitative key performance indicators (KPIs) along the paths that your most satisfied customers take, as they interact with your organization across channels and over time.

Use Journey Analytics to Orchestrate Personalized Customer Journeys

A global financial services institution uses Pointillist to identify high-impact CX issues and orchestrate proactive cross-channel customer engagement to improve NPS.

A CX team at a leading bank uses Pointillist to find high-impact support issues and reduce their impact through pre-emptive communication. They identify that a high percentage of NPS® detractors were experiencing a particular support issue, which we’ll call ‘Z.’

This issue is taking an average of five days to resolve, and is likely a key driver of decreased NPS scores.

issue in customer journey

After finding a simple solution that would allow customers to quickly and easily resolve the issue themselves, the CX team uses Pointillist to orchestrate communications to each customer across multiple channels, just seconds after they experience the issue.

As a result, 65% of the customers that receive the outreach campaign are able to resolve the issue in less than a day, which leads to a 5 point increase in NPS.

Identify and Measure the Impact of Customer Experience Obstacles

Businesses regularly lose money due to customer experiences that don’t live up to expectations, such as a failed onboarding experience. Even a few minutes of downtime for a website or an app in certain industries may mean a loss of millions of dollars. Yet companies are not successful in quantifying the impact of these experiences. Customer journey analytics can be used to understand the quantitative impact of a poor experience at every step of the customer journey.

Using predictive analytics and machine learning algorithms, journey analytics can help identify which customers are most likely to churn, thus providing you with valuable data to turn the situation around. Moreover, by employing customer journey analytics your efforts to woo back your former customer are significantly more likely to succeed, as you reach out to them with the right message through their preferred channel within the right timeframe. Even if you fail at winning back that customer, the information you gather will help you take proactive steps before customer churn becomes a problem.

Customer journey analytics helps customer experience teams by identifying the key customer experience obstacles along a customer journey. It also provides important quantitative data to determine the impact of these CX obstacles on business objectives, as well as the effectiveness of any remediations.

Prioritize and Act Upon Customer Experience Issues Based on Their Revenue Impact

As customer experience has risen in prominence, investments in this area have also increased. But it is important to strike a balance between rising customer expectations and the financial value attached to it.

According to KPMG, the relationship between customer experience and financial return is complex and delighting customers can reach a point of diminishing returns quickly, the costs often exceeding the value generated.

Moreover, customer experience investment returns are not consistent across industries. McKinsey finds that in the healthcare industry, marginal improvements in customer experience for dissatisfied customers have a better return than delighting the customers to become advocates. In contrast, retail banking has found that every customer matters and moving customers from 80th percentile to 90th percentile of satisfaction provides significant returns.

Use NPS to Prioritize Initiatives to Improve Customer Experience

A retail bank uses the Pointillist Customer Journey Analytics platform to measure NPS for specific customer journeys, so they can identify and prioritize areas for CX improvement.

The bank’s CX team knows that customers who miss a payment often ask for a late payment fee waiver.

So, they want to evaluate and compare the customer experience for three different channels customers can use to resolve a late payment fee: the mobile app, web chat and the call center.

By conducting a simple analysis in Pointillist, they find that not only did the highest volume of customers make an inbound call to request a fee waiver, but those that did had a lower NPS score than those that resolved the payment fee through the mobile app or web chat.

nps in customer journey

In contrast, the mobile app journey had the highest average NPS score. As a result, the CX team chooses to launch an initiative to guide more customers who missed a payment to the app, so they can increase overall customer satisfaction, while simultaneously reducing cost to serve.

Use Customer Experience to Differentiate From the Competition

Customer journey analytics can be used to glean quantitative insights that can improve customer experience and turn it into a point of differentiation. In a recent McKinsey article, the authors state that customer journeys which result in more than six calls per customer are ripe for innovation. Making transformative changes in those pain points not only lowers cost to serve, but can also be used to differentiate yourself from your competition.

Customer Journey Analytics Helps a Major Retail Bank Increase Credit Card Conversions

A retail bank leverages customer journey analytics to discover the most effective message and channel to drive conversions.

The credit card team at a major retail bank is tasked with improving credit card opening rates among millennials. To understand the role that different channels play in credit card offers and their respective efficiencies, the bank uses the Pointillist Customer Journey Analytics platform.

They uncover a variety of customer journeys across online and offline channels—such as branch visits, website browsing, mobile data, email data and in-app interactions—that lead customers to view a credit card offer.

Within minutes, they discover how many customers go on to apply for a card online versus how many reject or ignore the offer. With one click, they are able to see how many customers move forward at each step, how many drop out and how many are still present at that step.

Using Pointillist, the bank determines that the offer converts better for people who see it as an email than as a text message or within the bank’s mobile app. Based on this information, they decide to send a personalized email offer to those who view the credit card offer and then abandon their journey.

credit card offer journey

A few days later, the credit card team reviews the results and are delighted to see a large number of the email offers have been converted into new credit card applications. Since Pointillist is already integrated with their email platform, they decide to set up an automated trigger to add anyone abandoning this journey in the future to the new email campaign.

This multichannel analysis would have taken days and consumed high-level data science resources to accomplish using traditional analytics approaches. Using Pointillist, the credit card team is able to quickly find, deploy and analyze a solution themselves with minimal outside support.

credit card offer customer analysis

Looking Ahead

Customer journey analytics is fast becoming the preferred approach for marketers and customer experience professionals looking to improve customer experience. By linking customer experience to quantitative metrics, customer journey analytics enables you to focus on implementing changes that truly matter. It directly ties customer experiences to business outcomes, so you can deliver on revenue, profitability and other hard metrics on which your company’s executives are measured.