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Everything You Need to Know About

Customer Journey Analytics

and How It Differs From Customer Journey Mapping

Think about the last time you had a great customer experience. Now take yourself back to the last poor experience you had with a brand. Chances are, both encounters have influenced how you view the brand overall. But, which had the greater impact?

 

54% of customers say they have higher expectations for customer service today compared to one year ago, with 91% saying a poor customer experience means they likely won't do business with a company again. Conversely,  65% of buyers find a positive experience with a brand to be more influential than great advertising.

 

Keeping a continuous finger on the pulse of how your organization’s customer experience is perceived, customer journey analytics is critical. By creating a holistic view of the customer experience and monitoring it, you can take informed action to improve customer experience, products, and sales in real-time.

 

Read on to get everything you need to know about customer journey analytics, and how it can positively impact your business.

What is customer journey analytics?

Customer journey analytics is the process of continuously collecting and analyzing behavioral data about consumers, and across all touchpoints of their journey with your brand. 

 

Ideally, customer journey analytics involves connecting data across multiple channels to create a holistic view of your customer. Touchpoints along a single path to purchase may include your website, mobile app, in-store, social media, and more. Therefore, collecting data from only a few sources means you’re not getting the full picture. 

 

Customer journey analytics combines machine learning and predictive analytics, real-time data pipelines, behavioral segmentation, and more to provide companies with the information they can use to:

 

  • Streamline and improve the customer journey
  • Increase customer lifetime value
  • Create and nurture brand advocates
  • Catch and remedy friction with experiences faster

Leaders in CX like Sephora and Slack use customer journey analytics and other data to answer key customer experience questions like: 

  • Why/where are people dropping off?
  • Which marketing channels bring in the most leads?
  • Which messages convert the most leads to sales?
  • What are the most common paths to purchase and in what order do the steps occur?

All of this leads to a better and improved customer experience overall, which in turn means more revenue for your company. As research has shown, brands with superior CX take in as much as 5.7 times more revenue than those whose customer experience is just OK.

What is behavioral analytics?

Behavioral data refers to information that’s generated each time a customer interacts with your brand. Behavioral data may include small actions or “events” such as:

 

In addition, events have “properties” that further qualify or describe the events, such as device type or time of day. Whether your customers are business entities or individuals, behavioral data can always be tied back to a single end-user - which is crucial for personalization & segmentation within target demographics.

 

Observing customer behavior is not new, of course. Marketers, researchers, and product developers have been using behavioral data for years via call centers, help desks, surveys, and other qualitative research techniques. In the digital age, however, we leave behind a great deal more data that can be tracked and learned from by using behavioral analytics software.

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Why is customer journey analytics important?

Every day, brands lose customers without knowing why. Customer feedback surveys can only tell you so much, and dissatisfaction with a brand isn’t always after a purchase. In fact, issues can pop up at any point within a customer’s journey, be it during their research phase, free trial, point-of-sale, customer service interactions, or billing. 

 

Without connecting all the touchpoints for a complete picture, companies will never understand where customers are getting stuck and what’s keeping them from moving forward. 

 

Customer journey analytics allows you to see every interaction in a single view and answer questions such as:

 

  • Do more customers stay when we do X instead of Y?
  • Will they leave if we don’t do X?
  • Will we win more customers faster if I make this choice?
  • What can we do to encourage more of X behavior?
  • Where are customers churning and what are the potential reasons behind the dropoff?
  • Where can we improve?
  • What marketing messaging is resonating the best?
  • Which marketing channels lead to more loyal customers?

 

This information helps companies tackle problems effectively and identify wins, so they can put resources where they matter most. The overarching goal of customer journey analytics is to optimize and improve customer experience, leading to: 

 

  • Increased customer lifetime value
  • Happier customers (aka higher CX survey scores)
  • Higher customer retention
  • Better brand reputation
  • Increased revenue

What's the difference between customer journey mapping and customer journey analytics?

You’re likely familiar with customer journey mapping, but you may be wondering, “what exactly is customer journey analytics” and “how is it different from customer journey mapping?

 

The two concepts complement one another. A customer journey map can take many forms, but is essentially just what it sounds like–a visual map of the customer’s experience with your business. 

 

In practice, this often takes the form of a diagram or image dreamed up by marketing and brand teams. While these models are helpful, traditional customer journey maps fall short in that they:

  • Only cover the journey from a high-level perspective (or zoom in on one to two sub-journeys)
  • Don’t account for differences in individual customer journeys
  • Often portray an ideal picture, thus missing critical opportunities for change

Customer journey analytics augments the journey mapping concept by using data to capture each detailed step along the path, with all its twists and turns. With real-time data gathered from multiple sources across your brand (social, mobile, desktop, CRM, etc.), you can honestly assess the current state of your discovery and purchasing processes and improve on them for more impact.

 

 

customer-satisfaction-graphic

Who can benefit from customer journey analytics?

Customer journey analytics benefits teams across your entire organization, in a number of ways.

Marketing & Sales

Most organizations struggle to align marketing and sales departments due to a lack of visibility into what each department is currently doing, and what they can do better to support one another. 

 

A comprehensive customer experience analytics tool can make it easy to break down these silos and provide visibility into efforts on both sides that can help influence each department. 

 

For example, marketers use customer journey analytics for a number of actions, including:

  • Quickly seeing which marketing channels offer the lowest customer acquisition costs
  • Understanding which marketing campaigns are most effective in generating new leads
  • Quickly segmenting audiences to know which personas are most likely to convert or churn

Sales teams use customer journey analytics for a bird’s eye view of individual prospects as they move through the sales funnel. For example, understanding how seamless the handoff between marketing qualified leads and sales qualified leads are. Ideally, they’ll be able to spot any potential trip-ups that might be causing them to lose prospects.

 

Here’s an example of what a sales and marketing dashboard could look like, using customer journey analytics:

 

CX Scuba

Product Management

Product teams use customer journey analytics to understand how people interact with product features, packaging, messaging, and more. For example: by seeing the exact steps a prospect goes through when viewing a product demo, product managers can learn whether the process is too drawn out, confusing, or whether an area of the product itself doesn’t work as planned. In addition, product managers may be able to anticipate what new features are needed based on trends shown in customer behavior within the product.

 

For example:

 

Scubs Product CX

Customer Service

Customer journey analytics tools provide data that frontline teams can use to increase efficiency and reduce the cost of doing business. By examining the chain of events that led up to a service call, and paired with data across multiple touchpoints and journeys, service teams can uncover the root cause of customer issues.

 

Scuba CX Customer Service

Customer Experience

Finally, customer experience teams can use customer journey analytics to elevate the entire customer experience by stitching together insights from each department’s dashboards. A 360-degree view into customer behavior helps quickly underline friction points and inefficiencies. Then, they can gauge what level of activity or key touchpoints are needed--and when--to retain top customers. Eventually, understanding how customers behave empowers companies to anticipate customer needs, and provide the kind of top-notch customer service that keeps people coming back for more.

 

Having broad insights into customer interactions allows organizations to approach customer journey analytics from an industry-wide perspective as well. 

Retail

Customer journey analytics in retail is perfect for understanding how effective existing cross-selling workflows are, learning friction points in order to reduce cart abandonment, and building customer loyalty through a better customer experience.

 

Additionally, customer journey data empowers retailers to spot behavioral patterns that lead to repeat or higher-value purchases and see which acquisition channels lead to the quickest conversions. For example, if someone buys a new pillow, an analytics tool can capture that action and trigger a recommendation for a pillowcase at checkout.  

Banking

By connecting customer feedback with operational, financial, and behavioral data for an individual user, banks can begin to understand and even predict customer behaviors, preferences, and motivations. For example:

  • Identifying points that drive the highest traffic
  • Pinpointing bottlenecks
  • Discovering which ad or distribution platforms attract the most conversions
  • Recommending ideal-fit products based on previous journeys
  • Personalizing and optimizing marketing messages

Technology

Tech enterprises thrive on using the customer journey to improve outcomes for their brand and product. SaaS companies like Dropbox and others use customer journey analytics to move customers faster from a freemium model to a paid subscription. Customer journey analytics can help determine what actions or recommendations will garner more account registrations--for example, a landing page or a pop-up. 

SaaS companies will also benefit by being able to see where and why customers give up in the middle of a signup process. When customer journey mapping is supported by live data, they can also see the effect of removing or adding an additional step at any point in the process.

How to analyze the customer journey

While customer journey maps may be created once and then revisited quarterly or yearly, customer journey analysis is an iterative process. Consolidating multiple live data pipelines means you’re continually gathering new data and insights that can inform teams across your organization. A simple customer journey analysis might involve the following steps:

  1. 1. Create a customer journey map first by using real-time data from a variety of sources: Connect desktop, web, mobile, social, point-of-sale, and other interactions for a 360-degree view of your customer as they connect with your brand.
  2. 2. Visualize the journey for each of your key audience segments: Tracking multiple journeys for key segments helps you get a clearer picture of who they are and helps identify trends across customer groups.
  3. 3. Evaluate your journey maps: Look for problem areas, things to improve, and patterns that could be simplified or eliminated.
  4. 4. Test your theories: Based on your analysis, you can make adjustments and then measure the impact on customer satisfaction, sales, or other KPIs.
  5. 5. Reiterate: Repeat the process continuously as you improve customer retention and boost sales along the way.

 

Scuba Analytics CX

Challenges in customer journey analytics

Even large brands struggle to make sense of all the data available to them. When it comes to executing a successful CJA strategy, the most common challenges cited are:

  • Too much data to be useful: The growing volume of data available to brands can be overwhelming. It’s easy to miss something among the millions of disparate data points.  Often, teams fail to access the insights they need to take data-informed action.
  • Customer journeys are constantly changing: Some customer journey analytics tools struggle to update fast enough, or can’t keep up with the continuous stream of information coming in. The resulting analysis is an outdated journey map that may provide a skewed perspective. If there’s a gap in your analytics, the actions you take may not have the effect you want. In other words, if you only make a change on one platform, you may “break” other aspects of the customer experience without realizing it.
  • Requires too many technical resources: Heavy data processing and ETL requirements often means bringing in data scientists to get the data into a format where it can be queried. Many organizations either don’t have enough data experts on their team, or they can’t spare those resources for data prepping projects.
  • Data integration is complex and time-consuming: Data in organizations is often siloed. Bringing those disparate sources together under one roof presents challenges in preparing the data for analysis. The process opens up your data to errors and mismatches, not to mention it’s extremely time-consuming.

 

Watch this video where CloudBees merges customer data from multiple data sources, and then starts to perform deep analysis with Scuba in under an hour.

 

Scuba Analytics Makes Customer Journey Analytics Easy

Choosing the right customer analytics tool can enable your business to succeed in new and unprecedented ways. Scuba allows you to move past these obstacles to achieve complex analysis, faster and efficiently. Scuba brings in data from multiple sources and can store both structured and unstructured data, so you don’t have to leave anything out. You can dynamically visualize customer journey maps and analyze new patterns as they emerge, thanks to continuous live data.

 

Scuba offers flexibility and insight for the entire company–and it doesn’t require extensive ETL to get started, and you can run no-code queries, which means anyone in your enterprise can use it. If you want to beat the competition, win (and keep) more customers, and provide a top-notch customer experience, you need a customer journey analytics tool that encompasses every aspect of how people interact with your product.

 

Learn more about Scuba for customer journey analytics today. Request a demo.

 

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