In Part I of this series, I covered some of the key metrics and visualizations that contribute to a 360 degree view of your customers. Today let's explore two more metrics that reveal insights about your customers' relationship with your company, and the graphs that best explain the data.
Track Net Promoter Score with a Gauge or Bar Chart
At B2B companies especially, you'll often need to call upon your customers to serve as references in order to close new business. Some CRM systems like Salesforce.com enable you to add checkboxes to indicate whether a particular customer will serve as a reference or not. It's simple to run a report on that information, summarizing the number of checkboxes over the total number of customers, but visualizing a more robust metric on a dashboard keeps customer relationships top-of-mind with your marketing, sales, and customer support teams.
Many arcplan customers are going back to an old standby metric, the Net Promoter Score (NPS), which segments the percentage of customers who would recommend your products and services ("Promoters"), versus those who are satisfied but unenthusiastic ("Passives") and those who aren't happy and might go out of their way to voice negative opinions ("Detractors"). On a scale of 1-10 for the question "How likely would you be to recommend <<company>> to a colleague?", Detractors are the people who choose 1-6, Passives choose 7-8, and Promoters choose 9 or 10:
To get your NPS, subtract the percentage of Detractors from the percentage of Promoters. Benchmarks indicate that the average company has an NPS score of 5 to 10, so there is a lot of room for improvement for most organizations.
NPS isn't very demanding when it comes to visualizations. You can effectively graph it with a gauge or speedometer, like the one to the right, or even with a pie chart. If you're re-calculating the score often enough (say, after monthly customer support follow-up surveys), you can graph it in a stacked bar chart like this to tell the story of how the data changes throughout the year:
You might even have several of these NPS charts throughout your company, especially if you're global. There are cultural differences that cause people to rate things differently; for example, customers in Germany might not rate anything a "10" while US customers might have lower expectations and rate even mediocre interactions a "10." Don't make the mistake of unfairly comparing business segments against each other when it comes to NPS.
Net Promoter Score has gotten a bad rap because it doesn't provide much in the way of actionable information. It's often just the result of a question on a yearly customer satisfaction survey. To get more traction from this metric, follow up the question "How likely would you be to recommend <<company>>?" with "Why?" The answers might surprise you, and may lead to ideas that can easily be implemented to improve customer relationships.
It's an important customer metric to track, though it can't often be tied directly to revenue numbers. But if you have a consistently poor NPS, you'll be unlikely to deliver sustainable growth no matter how much money you dump into advertising, sales and marketing to acquire new customers.
B2C Sentiment Analysis
If you work in an organization that sells directly to customers, one important metric to analyze is customer sentiment. Social media sites like Twitter and Facebook serve as platforms for individuals to express their feelings towards a brand, potentially evangelizing and influencing followers and friends towards liking your brand, or on the contrary, creating a slew of "haters" who actively detract from your brand online.
Companies can use sentiment analysis to improve their relationships with customers. For example, customer service can reach out when something negative is expressed and try to turn a detractor into a promoter. This requires real-time processing to be effective though, and if the number of mentions your company gets online is large enough, this becomes a big data problem that requires more than simple business intelligence visualizations.
However, if part of your customer analytics program is measuring sentiment on an executive dashboard, the visualization below is something to consider. If you have enough processing power, it could reflect sentiment in real time. With arcplan, a chart like this could be real time since we offer direct connections to big data sources. As long as the data is real time, the arcplan visualizations will be too.
This visualization is a combination spider and portfolio chart. It maps the number of tweets and their apparent emotions, correlating them to a position on a good or bad axis. The X and Y coordinates define sentiment direction and magnitude and the bubble size defines sentiment volume. It is clear that most attitudes toward this brand are positive and that sentiment reflects high confidence in the brand. This type of analysis is great for analyzing customer attitudes and is much more descriptive than ratings alone, which do not take into account qualitative sentiments.
Are you using these metrics at your organization? What effect are they having on the way you do business?
In my next post, I'll take on customer analytics of particular interest to your finance team.