Originally published in Forbes
Written by Mark Smith
As companies strive to engage customers across the customer journey and shape the way these journeys unfold, they are faced with a vexing question: What’s working and what isn’t? The only way to answer that question consistently is with a rigorous and thoughtful approach to journey analytics.
Analytics are key to effective customer journey orchestration. Thankfully, rich, omni-channel journeys offer an array of data points to track, measure and analyze. Mapping the customer journey, for example, shows you how, when, and where people become customers and interact with your brand. Analyzing specific touch points or journey steps tell you what journeys are typical, where you’re getting things right and where things are breaking down.
When you look at customer journeys with the right level of detail, it can help you test marketing assumptions and guide the tactics you use to address customer needs and move them down the funnel, increase purchase frequency or achieve other business goals you are driving toward.
But while it can be relatively easy to measure the success of specific steps, channels or touch points, it can be exceedingly difficult to measure the success of your customer journey programs as a whole. To simplify that process, we recommend the following:
Measure Business Outcomes
In an ideal scenario, a customer interacting with your brand will go through three phases in their customer journey:
1. The journey of becoming a customer: A potential customer might begin with absolutely no knowledge of who you are, what you do and what you sell. The road to purchase can be long, but it includes some of the most important touch points of the customer journey: first visit to your site, first contact with a sales representative, first purchase.
2. The journey as a customer: Consider the experience your paying customers have with your brand. While this journey will differ based on the product you sell, it will have a huge impact on customer retention and future purchase decisions.
3. The journey to becoming a loyal/repeat customer: Loyal customers are extremely valuable, both because they make repeat purchases and because they recommend you to others. Although customers who make it to this phase are a subset of your total base, your efforts here have lasting impacts.
To measure effectiveness in the first phase, look at net new customers and customer acquisition costs. In the middle phase, look at customer service and customer support costs as well as things like return rates. To measure your efforts focused on driving long-term relationships, consider customer lifetime value and referral business.
The power of journey analytics comes from the ability to provide a consolidated, connected view of typically silo-ed business metrics and linking them to specific customer actions. You already know how many web hits, phone calls and email opens you have, but you can’t see the connections between them. Journey analytics provides the real-life customer connection so you can see, for example, how many web hits came because of an email, then led to a phone call and finally a purchase. Seeing the connections offers insight into the most successful journey paths.
Measure The Journey Itself
When we look at customer journey programs in their totality like this — an aggregate view of all three phases — you can measure effectiveness by focusing on two variables: volume and velocity.
• Volume: How many people are embarking on the customer journey with your company and how many make it all the way through to conversion (and beyond)? Look at volume phase by phase. How many buyers turn into customers? How many customers become repeat customers? How many become advocates? Does increased volume in one phase turn into increased volume in the next? If not, why not? There will be drop-offs between phases, but overall volumes should increase.
• Velocity: How smooth is the customer journey? Can people move through it without friction? Certain touch points — first interaction, conversion, purchase, repeat purchase — can serve as mile markers in your customer journey. Measure how long it takes customers to move from one marker to the next. Where are there opportunities to speed things up? Are there steps you could remove to simplify the journey? The speed with which people move through the customer journey tells you a lot about how well you are managing and orchestrating it.
It’s important to note here that a customer’s path to purchase is rarely linear. Volume and velocity are crucial parts of demand generation, but elements of your customer journeys support a more cyclical architecture, which might bring customers to purchase in unexpected ways. Having rich omni-channel journey management practices in place allows for that type of customer capriciousness.
Measure The Overall Experience
According to Gartner, two-thirds of marketers say CX is the main basis for competition today, but customer experience is notoriously difficult to measure. Surveys, review sites, online forms and other avenues for collecting customer feedback can be effective, but they tend to confuse experience with satisfaction.
That said, customer satisfaction surveys and things like NPS scores give you insight into the effectiveness of your customer journey efforts. Overlaying customer and NPS data with journey analytics adds depth to satisfaction.
On the flip side, looking at metrics like journey velocity and customer lifetime value can also give you insight into the customer experience itself. If customers are moving quickly from one stage to the next, or customer lifetime value is going up consistently, then these are good indicators.
What’s The Goal Of Your Customer Journey Efforts?
You can’t successfully orchestrate customer journeys without effective customer journey analytics, but ultimately, you need to be measuring against clear-cut goals, dictated by an overarching strategy. For each level of analytics — from business outcomes to the journey itself and customer experience — establish what success means.
Journey analytics not only help orchestrate interactions effectively but also optimize ongoing orchestration. If you are not achieving the results you expected or hoped for, the analytics strategy outlined above should help you address whatever is going wrong and get your efforts back on track.