Use Customer Journey Analytics to Improve the Customer Experience
Sr. Content Marketing Manager, Sigma
Today’s global marketplace is more competitive than ever. Companies across industries have discovered that product-market fit isn’t enough. To get ahead, they must deliver an exceptional customer experience at every touchpoint. Customer journey analytics empower organizations to do just that.
By analyzing millions of data points in real-time, it’s possible to identify sources of friction and the various factors affecting the customer experience. Armed with this information, you can then take the actions needed to improve the experience, ultimately increasing revenue, reducing churn, and optimizing profitability. In this post, we explore how to use customer journey analytics, business intelligence related to the customer journey, and how to craft a customer 360.
What is Customer Journey Analytics?
Customer journey analytics is a data-driven approach to streamlining the customer experience. It involves tracking and analyzing customer behaviors at every stage of the funnel and how customers use the full spectrum of channels to interact with an organization. Customer journey analytics, also called Big Data customer analytics, can help answer questions like these:
- What’s the customer trying to accomplish?
- How do the customers’ goals align with the company’s goals?
- What’s causing customers to behave in this particular way?
- What series of customer actions have led to this issue/challenge/result?
- What are the various paths that customers take in their journeys? Do these paths share similarities by segment?
- How can we streamline the path to purchase?
- How can we deliver more value to customers at particular challenge points?
How to Use Customer Journey Analytics
When you have a clear picture of the journey for each customer segment, you can more clearly see how to reduce friction, increase lead volume, boost conversions, close deals faster, and see where opportunities lie for upsells, cross-sells, and additional purchases.
Mining customer journey data is one of the most effective ways to increase customer lifetime value, improve customer loyalty, and drive revenue growth. Specifically, customer journey analytics allows you to:
- Pinpoint where and how customers interact with your business to personalize their journey for their next visit
- Help identify if the current stages in the journey are optimal or even in the correct order
- Create an outside-in look at existing marketing and sales processes
- Identify gaps and opportunities to drive conversion
Let’s take a look at some examples.
Finance — A finance team might use customer journey analytics to identify the common causes of overdue payments. They might look at shared traits or behaviors among accounts typically delinquent by 30 days or more and then implement strategies to prevent underlying causes, such as making it easier to pay online.
Sales — A sales team might see that people are engaging with new account promotions online but aren’t actually opening new accounts. They could identify the most common drop-off point and test new strategies or even create new journey paths based on insights gained.
Marketing — A marketing team might track individual customers’ past purchases and then recommend specific products based on those previous purchases when the customers next visit the website.
Customer Journey Stages
Before you can improve the customer journey, you’ll need to get a thorough understanding of your customer journey stages and what they look like for your customer segments. There are five main stages: awareness, education, evaluation, purchase, and advocacy, which typically correspond with certain touchpoints, as illustrated below.
In the awareness stage, the customer may not even realize they need your product. Social media ads, display ads, and other types of advertising serve to build awareness of your brand and trigger a realization that a need exists.
During the education phase, the customer has realized that they have a need and is exploring a solution for their problem. They may ask friends or colleagues for information or conduct a Google search to find educational content such as blogs, e-guides, and videos.
Once the customer has identified a solution to their need, they begin evaluating different products and providers. They start looking at case studies and testimonials, and they may explore a demo of the product.
In the purchase stage, the customer does final research on the products and providers under consideration, looking at sales sheets, pricing pages, sales proposals, etc.
ADOPTION AND ADVOCACY
Once the customer has made a purchase, they begin implementing the product and (if they’re happy) spreading the word to their friends and colleagues. They engage with email nurture campaigns, customer success content, and office hours.
How Business Intelligence Fits in
Customer journey analytics is a particularly challenging form of business intelligence due to the massive amounts of data needed and the disparate sources the data is coming from. Research by Deloitte revealed that companies have, on average, 16 different technology applications leveraging customer data, with an average of 25 different data sources for generating customer insights and engagement. This data is typically siloed, and the sheer volume of data is difficult to wrangle with traditional data warehouses and analytics tools.
However, with the Snowflake Data Cloud and cloud data platforms like Amazon RedShift and Google’s BigQuery, big data sets can be loaded and prepared for analysis within seconds. Customer journey analytics software like Sigma enables business teams see the full spectrum of front-end interactions like pageviews and product usage to back-end data. This means that you can connect the dots between your BI solutions and other software from from CRMs like Salesforce – no coding knowledge required!
How to Build a Customer Journey 360
360 customer analytics give you a complete view of your company’s entire relationship cycle with a single customer across every interaction they have with your brand. Building a customer journey 360 based on data will help you better understand your customers’ paths and allow you to generate more accurate insights. Here’s how to do it.
IDENTIFY TOUCHPOINTS IN EACH STAGE OF THE JOURNEY
Before you can measure and optimize the effectiveness of your customer journey, you need a clear picture of your current customer touchpoints. The simplest way to do this is to map each potential interaction to a specific stage in the customer journey. Start broad to get a lay of the land (for example, “blog posts” would be listed under the Education stage) and then drill deeper (such as specific blog posts) as you get further into the process.
IDENTIFY SOURCES FOR CUSTOMER DATA
Next, identify all sources of customer data. Look at sources for each stage of the customer journey, from awareness to sales to repeat purchase to churn. Consider the following:
- What platforms are prospective customers using to discover your brand?
- Where does a prospective customer first engage with your business?
- What tools do they use, and for how long?
- What are their behaviors on your website and/or app? How long do they typically stay in a session, what pages do they view, etc.?
- Where is your company storing data related to each type of marketing effort? Sales? Customer service?
INTEGRATE DATA ACROSS SOURCES IN A SINGLE PLACE
You can only build a customer 360 if you integrate your data sources so you can work with all the data together in one place. Cloud data warehouses make it easy to store, manage, and analyze massive volumes of live data from across sources in a centralized, fully-governed repository. Be sure that all your data sources are connected to your CDW. Pre-built data connectors like Fivetran can help with this process.
Once you have a 360 view of the customer journey, you have a firm foundation for customer journey analytics. Choosing a cloud-native data analytics tool like Sigma that can handle the millions of data points you’re generating and allows non-technical users to conduct their own analysis will give your team the insights they need when they need them.
Drive Revenue Growth with Big Data Customer Analytics
Generating customer journey data insights is one of the most effective ways to increase customer lifetime value, improve customer loyalty, and drive revenue growth for your organization. Big data customer analytics is the field where companies will compete in the modern marketplace.
Read “Build a Customer Journey 360 to Deliver Personalized and Seamless Experiences” to learn more about developing your customer journeys.