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How to Choose the Best Customer Journey Analytics Tool for Better CX

Camila Martinez-Granata

Customer experience (CX) professionals and marketers are increasingly relying on the use of customer journey analytics to learn more about their customers. Through real-time insights about individual touchpoints and interactive views of the journey as a whole, customer journey analytics software helps create better experiences on a large scale. More specifically, enterprises can visualize the various paths that users take and prioritize the ones that impact business goals (like sales, revenue, churn, and repeat purchases).

 

If research is any indication, enterprises are doubling down on CX and digital experience efforts. According to recent Voice of the Enterprise survey reports from 451 Research:

 

  • 50 percent of respondents were increasing overall budgets to improve online experiences in the wake of COVID-19
  • 68 percent of digitally driven businesses already have advanced customer experience management tools in place
  • Another 15 percent of those businesses were already in the discovery or proof of concept phase

 

As organizations expand their CX budget and more enterprises add customer journey analysis tools to their technology stacks, what does it take to meet the needs of you and your team? 

 

Read to learn how to select the best customer journey analytics tool for elevated customer experience. 

What is customer journey analytics and how does it help CX professionals?

Customer journey analytics is the process of continuously collecting and analyzing behavioral data about consumers across all touchpoints of their journey with your brand. This approach emerged to help brands succeed in today’s CX landscape. Customer experience is the driving force behind retention and profits, leading companies to compete more on service than on quality or price. While there is plenty of available data--it’s scattered across a web of touchpoints, channels, and internal silos. 

 

Right now, CX teams might have a “Frankenstack” of insights technologies. Many are using a mix of traditional website and behavioral analytics tools like Google Analytics, voice of customer (VoC) platforms, and basic data visualization software. Chances are you’ve found that while one tool is strong on visualization, it doesn’t drill down deep enough into customer segments and behaviors. Another tool may be great for tracking user flows across your website, but doesn’t tell the story of what happens elsewhere. 

 

The new generation of tools was purpose-built to meet these challenges. Customer journey analytics helps CX teams become more customer-focused and promotes: 

 

  • Better alignment across business teams
  • Stronger customer relationships 
  • Agile response to changing customer needs  
  • Business decision-making based on real data 
  • Improved customer acquisition and retention
  • Increased revenue and CLV

7 capabilities of a strong customer journey analytics platform

If you want to understand your customers, make better use of your data, and get answers quickly, customer journey analytics can help. But finding the right tool can be a daunting task. 

 

There are many customer journey analytics tools on the market, each with different strengths and capabilities. As always, the best solution depends on your own business needs and objectives. At a minimum, though, an enterprise-level customer journey analytics solution should offer the following capabilities:

 

  1. 1. Real-time data

Given the speed at which digital interactions occur, real-time data is not a nice-to-have, it’s a must-have. Today’s definition of great CX is proactive--it’s being in the right place at the right moment to provide personalized recommendations, solve problems, or remove roadblocks.

 

To do this, a customer journey analytics tool has to integrate large quantities of qualitative and quantitative data in real or near real-time via live data pipelines. 

 

  1. 2. Predictive analytics

Artificial intelligence is impacting the future of virtually every industry, and customer experience is no exception. Predictive analytics elevates customer journey analytics by utilizing AI, machine learning, and historical data to predict future patterns in customer behavior. 

 

The ability to anticipate a prospect or customer’s next move in real-time enables companies to quickly help a customer reach their goals faster. For example, offering a well-timed discount, a product nudge, or sending hyper-relevant content based on the user’s industry, interests, or geographic location. Over time, you can predict and encourage a customer’s interactions that have the highest likelihood to convert.  

 

Companies like Netflix, Spotify, and Amazon have made their fortunes with the help of predictive recommendations. Research indicates that customers prefer personalization, with 66 percent of consumers expecting brands to understand their individual needs. 

  1.  
  2. 3. Robust data visualization 

The core of customer journey analytics is to visualize the customer experience. This means robust visualization must be a key component of any journey analytics tool worth its salt. Basic journey analytics tools can show you where a customer goes on your website, and how they got there. But they don't paint a very rich picture of the journey as a whole, with its splintered touchpoints and timelines. Robust data visualization can solve this problem.

 

The right customer journey analytics platform will enable you to zoom in on specific behaviors like channel switches, skipped steps, misordered or repeated steps, and drop-offs. A strong platform will have the capacity to switch quickly between charts, graphs, and diagrams, and visualize the customer journey as a whole. 

 

  1. 4. Behavioral segmentation 

Customers prefer personalization. Behavioral segmentation plays a significant role in making that happen. A significant advantage of customer journey analytics software is that you can visualize the journey as a whole. But every individual’s experience is unique, and you should optimize CX for different personas and segments. Common types of behavioral segmentation to look out for in a premium customer journey analytics tool include: 

 

  • Purchasing behavior
  • Occasion or timing
  • Benefits sought
  • Customer loyalty
  • User status (ie first time customer, return customer, brand evangelist)
  • Stage of the buyer journey
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  2. 5. Data integration across channels 

Your customers are interacting with you via websites, mobile apps, email, social, and more. For a comprehensive view of customer journeys across channels, you need to be able to aggregate multiple data sources, without losing fidelity. Proper integrations allow you to collect both quantitative and qualitative insights from all data sources and formats. Cross-channel data integration is the future of customer journey orchestration, as it’s the only way to identify key CX opportunities across silos and move toward an omnichannel experience for customers.

 

  1. 6. Customized alerts based on customer events

Customized alerts allow brands to track and engage with specific events as they happen based on parameters that they set. When an important milestone occurs within data, you’ll be notified and can act on it immediately. 

 

Here’s how it works: You create custom queries based on the conditions you want to measure. Then the tool runs them in the background and alerts you when the condition is met. You can configure alerts based on events like advancing to a new step, filling out a support form, or changes in numerical values or percentages. Automation is critical for time-strapped teams, and alerts are a key feature for top analytics tools.

 

  1. 7. Measurement of KPIs that matter to your business

Working in CX means businesses rely on measuring KPIs to gauge how well their CX is performing, especially in regards to ROI. Yet, quantifying the impact of CX efforts remains a top challenge in the industry. The new flock of customer journey analytics tools eases this challenge by enabling you to track the impact of key CX metrics such as churn rate, retention rate, customer lifetime value (CLV), cost to serve, and revenue. Since they’re calculated using all data from integrated sources, you won’t miss cross-channel marketing touches or referrals.

How Scuba can elevate your CX analytics

Leaders in enterprises are refocusing on the customer and using vast sources of real-time data to shape and improve experiences. Customer journey analytics empowers CX professionals--and business teams across organizations--to align on customer strategy and provide a better overall brand experience. In order to meet the needs and challenges of today’s CX, a customer journey analytics tool should be able to: 

 

  • Visualize customer journeys in real-time
  • Aggregate multiple disparate data sources
  • Segment audiences based on behaviors
  • Predict behavioral patterns and trends
  • Measure the impact of CX efforts
  • Provide automated alerts based on significant events within the data


Scuba is a comprehensive customer journey analytics platform that connects customer journeys and digital interactions in real-time for a 360-degree view.

 

Learn how Scuba provides everything you need and more for self-service customer experience management. Explore a quick demo now!