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What Are Customer Journey Analytics (And Why You Need a CJA Strategy)

Megan Wells

If you’ve seen or heard the term and you’re wondering “what is customer journey analytics” you’re not alone. Customer journey analytics is gaining in popularity for its ability to weave together every touch-point between brand and buyer, no matter where it occurs. By using existing data to map out the various behavioral scenarios of your customers and prospects, you achieve a deeper understanding of them.

 

From the awareness stage to the delight stage, a customer may make contact with your brand across multiple channels: 

 

  • Browsing items or researching on a website
  • Watching a video about your product on Youtube 
  • Reading reviews on social media 
  • Touching a product in-store
  • Talking to customer service 
  • Meeting with a representative for an in-person consultation 

 

The concept of customer journey analytics is to bring all these touch points together for a unified, 360-degree view. 

 

Customer journey analytics combines data with continuous intelligence to build a story that’s grounded in reality, not guesswork. And it operates hand-in-hand with behavioral analytics to dive deep into individual pathways, motivations, and purchasing habits.

 

Collecting and analyzing data from end to end helps you answer questions like: 

 

  • Which entry points lead to a purchase most often?
  • Which path or paths lead most directly to a purchase?
  • What efforts translate into the most amount of conversions?
  • Where steps can we simplify or remove?
  • At what point do users churn or bounce?
  • What times of day, week, month, or year do users engage or purchase most?
  • What free product features bring in the most paid users? 

Why do brands use customer journey analytics?

Companies use customer journey analytics for its ability to improve customer experience, increase customer retention and lifetime value, and grow revenue. With a clearer picture of the customer story backed by real-time data, you can see exactly how someone behaves on your website or any other platform. You can visualize how they get from A to Z, and see any snags or friction points along the way. 

Customer journey analytics powers your CX strategy

Whether it’s streamlining the customer experience, adding requested features, or curating personalized recommendations, it’s no secret that a customer-focused approach pays off. It’s how megabrands like Netflix and Spotify have become leaders in their markets. And Forrester’s most recent large-scale CX consumer survey found customers are: 

 

  • 2.4x more likely to stay with a company when they resolve customer issues quickly
  • 2.7x more likely to spend more when companies communicate clearly 
  • 10x more likely to recommend when employees in physical stores can answer all questions

 

The bar for customer satisfaction is high, and there’s nowhere to go but up. 75% of customers are willing to spend more to buy from companies with a good customer experience, and 50% say they’ll switch to a competitor after just one bad experience.

 

Yet customers provide only so much feedback, and what they do share is often skewed. Thus, analyzing customer journey data is the best way to find out where your marketing messages might be confusing, identify the most common issues or questions, and train employees on how to resolve them.

Rising customer expectations are driving the growing importance of CX for brands

With customer experience rapidly becoming a key differentiator, companies are ramping up their focus on customer experience efforts. At the same time, marketers are seeing the drawbacks of traditional journey maps, which are often dreamt up in conference rooms or based on scant data. 

 

Customer journey analytics paints a more dynamic, complete, and actionable picture of the customer within the journey. With millions of data points being interpreted immediately in real time, teams can quickly find and root out the cause of pain points.

Challenges in mapping the customer journey

While the concept may have emerged to improve on static journey mapping, the process of developing customer journey analytics comes with its own challenges. Especially if you’re not using the right tools.

 

Some customer journey analytics technologies on the market have limitations and challenges that hinder business objectives, including:

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, customer journey analytics tools can’t always keep up with the pace of customer demand. 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 touch points or platforms are more data rich than others, or produce data that’s 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 scientists 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.

A unified solution for effective customer journey mapping

In order to be useful, you need a customer journey analytics software that brings everything together under one roof. Additionally, time-stamped event data is critical to knowing exactly when and in what sequence actions occur. 

 

Scuba can process both structured and unstructured data, which means nothing gets left behind. No complicated ETL process required on your part, meaning you can get to work fast. And you can create new queries on the fly, without help from data scientists. Visualizations of the complete customer journey unlock ideas for improvement as well as sales driving opportunities.


See how Scuba’s continuous intelligence platform unifies customer journey maps and empowers your team to make real-time business decisions. Request a demo.