The idea of having a 360 degree view of your customers is not a new one, but actually getting it is a real challenge in our world of silo'd data. Customer analytics give you a better understanding of your customers, and the ability to spot trends, identify opportunities to cross-sell, up-sell or simply target them more effectively, ultimately optimizing your customer relationships. But to get these insights in one place, like a dashboard, you need to integrate separate data from CRM, accounting, and customer support systems. Without a BI platform in place – one that integrates data from many sources like arcplan – it falls on you, the decision maker, to waste time assembling the pieces necessary to come up with a view of your customers from these different systems.
But if you are looking to utilize your business intelligence software for customer analytics, this series of articles will help you define the metrics you should be tracking as well as the visualizations that most effectively portray the data.
Graph Customer Growth with Bridge Charts
The most common way to track customer growth over time is by using a bar graph to show year over year comparison. A simple bar graph might show you that 2 years ago, you had 100 customers, last year you had 107 customers and this year you have 120 customers. Using arcplan's linear regression formula, you expect to have 125 customers next year.
The numbers and the forecast look great, but the real story may be a little more shocking once you properly visualize it. A better chart for looking at a similar data set is a bridge chart, also known as a waterfall chart. Add the number of won and lost customers to the bridge, instead of just the cumulative total, and you'll see the full picture. The bridge will show you that 2 years ago you had 100 customers, but you added 14 and lost 7. Last year you started with 107 customers, but you added 30 and lost 18. In this example you can see that a dangerous trend may be forming related to customer churn. A bridge visualization tells the real story of customer addition and attrition, which is much more revealing than a simple bar chart.
Track Purchase History with Sparklines / Micrographs
Another popular customer metric you should monitor is standard purchase history, commonly known as historic sales reporting. The simplest form of historic reporting is done in spreadsheets with a list of products that customers have purchased. However an enhanced historic sales analysis can be visualized with sparklines alongside each table element. Monitoring historic trends using sparklines helps sales leaders identify patterns, make better predictions about future purchases, and brings information to life in ways that lists do not.
Find Your Most Valuable Customers with Pareto Charts
Sales is obviously one of the most important metrics to track since it's directly tied to company revenue. Accurate and effective visualization is therefore very important for analyzing how customer performance will impact your business. For this example, a quote from George Orwell's Animal Farm – "All animals are equal, but some animals are more equal than others" – can be rephrased to "All customers are equal, but some customers are more equal than others." The truth is that a handful of customers add more value to your company than the rest put together. You can prove this with Pareto analysis.
The Pareto rule, also known as the 80/20 rule, tells us that 80% of your business is driven by 20% of your customers. Pareto charts display descending values versus the cumulative percent of sales. Pareto analysis allows you to segment your customers into A, B, and C groups, in order of descending value to the organization. In the chart below, 38% of the customers make up 70% of the business; the next 24% make up the next 20% of the business, and the final 38% of customers make up the last 10% of the business. The real message gleaned from Pareto visualization is that your job is to keep the customers in the A segment happy, there may be real opportunities in the beginning of the B group, and you really shouldn't spend too much time with the C customers because they are the least profitable. It sounds harsh – and of course a smart business model is to keep all customers happy – but many businesses simply have to segment resources according to customer value, and Pareto analysis is a great way to figure out who the most valuable customers are.
More truths are coming up in my next articles on customer analytics. I'll explore which visualizations work best for pipeline, sentiment, customer support, and other customer financial metrics.