Product managers know individual user data offers tremendous insight into a product’s strengths and weaknesses, but interpreting raw data presents a challenge. Even the best data analysts can’t convey much about each individual customer journey from staring at data tables. When browsing data for analytical takeaways, you want immediate answers to questions without the need for complicated SQL queries.
Enter funnel visualization. The customer conversion funnel tracks the progress of users from their first click through their most recent interaction. Google Analytics has familiarized many with the concept of conversion funnels as its product reaches a mass market, but conversion funnels can provide even deeper insights when they display the actions taken by each user.
Your customer journey can be subdivided and visualized in many ways depending on the data and the query. Here are three distinct visualizations for customer funnels that help you glean insight from your data:
Donut Funnel
While a donut chart is among the most basic data visualizations, it is useful in offering easy comparison between a few subdivisions, or slices, of a whole.
In Figure 1 above, the donut chart is part of a multipath funnel and the slices represent the type of device a customer is using to access a website. Android users (in yellow) make up more than a quarter of the visitors to the site in the first donut, but as the users move through the funnel, far more Android users churn than those on other devices. By the time the funnel reaches the final donut chart — customer conversion through a purchase — Android users comprise only a sliver. This indicates to product managers and developers that their site is ill-designed for Android users.
One drawback to using donut charts (or pie charts) within a funnel visualization is that a greater number of slices make the chart harder to interpret. Humans are quite bad at judging the difference between multiple similar angles, so while there is a significant difference between 17% and 11% of a whole, you may not spot it easily within a donut chart. As such, they are best used in funnels comparing the behavior of two to three groups.
Bar Chart Funnel
Conversely, a bar chart laid atop your funnel is perfectly suited to represent proportional differences between many groups. This visualization is easily customizable as well; you can move each segment of the bar chart up or down to better show the story the data is telling.
Bar chart funnels are particularly useful at identifying the key points of friction in the customer journey, as each step in that journey is represented in a new bar. When the customer completes a step in the conversion funnel, they can either continue to the next step — where they will be represented on the next bar — or churn and drop off of the chart altogether.
In Figure 2 below, a company has introduced a feature entitled “PetCam” with the aim of enticing animal lovers to engage more with their site. The bar chart funnel shows, however, while new users and existing customers alike will connect and open “PetCam”, the feature is not doing much to drive blog traffic or new subscriptions. It might be a fun feature in its own right, but the data shows it’s not having the intended impact.
Sankey Diagram
There is no doubt Sankey diagrams are more obscure than pie charts and bar charts, but you may be familiar with their uses in chemistry and physics. They map the flow of energy or materials through several different stages in a process, keeping track of losses and inefficiencies. When your funnel needs a greater sense of scale across intervals, Sankey diagrams are preferable to pies and bars.
As your product becomes more complex, your customers’ journeys become less linear. There is unlikely to be a single route customers take through your site or application. The Sankey diagram can identify many different paths that result in successful customer conversion. Take the example in Figure 3.
The same company using the “PetCam” has displayed its customer conversion funnel as a Sankey diagram. Given the goal is for users to purchase a product, it seems the most important aim is to increase the number of users with accounts. The product manager can then reset the diagram to focus on what users do before creating accounts, and mine those successful customer journeys for additional insights.
Conclusions
Funnel visualizations intuitively express user decisions in greater depth, through data. Successfully navigating the customer journey with text or data tables requires a machine-like ability to crunch numbers and follow threads. We are all human. Product managers, marketers, and data analysts alike can use funnel visualizations to better understand the nonlinear human decisions their users make. Data paves the path for your team to design a personalized user experience to increase sales and customer conversions. Even a basic pie chart can show the way.
Source: https://towardsdatascience.com/telling-your-data-story-with-funnel-visualizations-1bea6d0f64df