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.
EDIT 6/1/11: Click here to access a recording of this incredibly popular webinar!
Join arcplan on June 1st at 2pm Eastern for How To Be An Analyst, a free webinar on common data analysis techniques and their real-world application in business intelligence.
Many of the scorecards and dashboards you see today are quick glances into the rear view mirror of a business, but what most businesses need is a deeper look into the metrics that drive performance. The issue is not a technology problem – most modern business intelligence platforms can easily perform more advanced analysis. It’s a people problem, and it’s probably not your fault. Many business managers were never taught to be analysts, have assumed the role because of a staffing shortage, or simply like being self-sufficient when it comes to answering business questions. But the truth is, it takes time to understand all of the nuances of data analysis in order to be able to extract meaningful information from rows and rows of data.
This presentation is a primer on the art (and craft) of being analytical. It’s for managers who are new to data analysis or have simply forgotten what they learned in school. We’ll begin with overviews and use cases of the basic methods of analysis including:
- Sorting and ranking
- Comparative analysis
- Contribution and Pareto analysis
- Projection and regression analysis
Then we’ll apply these methods to real world business intelligence scenarios that you see on scorecards and dashboards, including:
- Sales rep performance
- Revenue forecasting
- Accounts receivable and the aged trial balance
- Financial reporting, P&L, and balance sheet
- Pareto analysis (the 80/20 rule)
- Above-and below-the-line performance analysis
Becoming an analyst is a journey. This presentation will set you off on the right foot in your quest to master some of the most common data analysis techniques.
|Date:||Wednesday, June 1st|
|Time:||2:00 pm Eastern (New York City time zone)|
|Presenter:||Dwight deVera, Senior Vice President|