People do crazy things, especially during the holiday season. On Black Friday – and even on Thanksgiving evening – customers will wait in line for hours to grab the best deals and knock items off their wish list. Retailers offer ridiculous discounts on high-priced items and keep doors open 3 days straight to cater to buyers around the clock, then web retailers kick in their own Cyber Monday promotions. Black Friday has remained the number one shopping day for the past decade, accounting for most of the sales that businesses reign in during the holiday season. But smart retailers don’t have to wait until Black Friday to ramp up their bottom line. Your analytical or business intelligence platform can keep a pulse on operations year round and help increase sales before the 11th hour. Here’s how:
1) Use analytics for in-store promotions
Analytics can help guide store layouts by tracking which products perform best on an aisle shelf vs. an endcap in various cities, and what products should go on sale in a given month and region based on sales history and inventory levels. Using business intelligence, you can run scenarios based on historical data and make predictions about programs designed to drive in-store business. For example, if you increase the circulation of your direct-mail flyer, how much additional business can you expect it to drive? Similarly, if you offer in-store coupons for a certain timeframe, what kind of sales uptick can you expect? Essentially, you can analyze past customer purchasing behavior to determine how to best influence future purchasing behavior.
arcplan’s retail customers use our platform to track KPIs and run what-if scenarios to ensure that products are priced appropriately. For retailers, one important KPI is the cost of goods sold (COGS) – the price paid for the product, plus shipping, handling and other expenses to get it ready for sale. By keeping track of COGS…
I’m wrapping up my series on customer analytics and their associated visualizations with a discussion of 3 more metrics you should track on your customer dashboards – customer lifetime value, accounts receivable, and bookings & backlog – and why these simple visualizations are effective because they extend the reach of data to more people in the organization.
Track Customer Lifetime Value with a Stacked Bar Chart
One of the most underutilized metrics is customer lifetime value (CLTV), which sits at the intersection of sales, marketing and finance. CLTV calculates the historic value of a customer over time and helps establish how much customer relationships are worth – and therefore how much money can be spent to acquire them.
It’s conventional wisdom that it costs more to acquire new customers than it does to maintain existing business. For many companies, customers become more profitable over time. It costs less to pick up the phone and sell additional licenses to an existing software customer than it does to fly a sales person to meet with a prospect for the first time. It costs less to run loyalty programs to keep customers happy than it does to sponsor a trade show to meet new prospects. But the costs of these programs, all of which are necessary for running a business, have to be taken into account when using the CLTV metric. Customer lifetime value shouldn’t be something that only finance teams look at. Sales and marketing professionals must use it to ensure that their acquisition program costs are in line with CLTV.
There are many ways to calculate customer lifetime value, but the simplest is…
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:
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 Visual Guide to Customer Analytics
Recorded Date: Wednesday, July 17, 2013
Speaker: Dwight deVera, SVP of Professional Services at arcplan
About this webinar:
It’s been popular for a number of years to talk about having a “360 degree view” of your customers, but achieving it in our world of silo’d data has been another matter. You know how difficult it can be to connect individual silos of information into one integrated view. You likely have many systems and technologies in place at your organization, and 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.
This webinar is a back-to-the-basics, practical guide to getting a 360 degree view of your customers. We cover how to combine metrics in self-service dashboards that give everyone in your company 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, and ultimately optimize your customer relationships.
In this webinar, we present:
- The sales, operations, financial, and customer support metrics you should be looking at
- A way to leverage available systems and technology to remain nimble with your metrics (prioritizing and subscribing to them)
- A solution for pulling together silo’d data into one integrated view