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Contextualizing Your Data

  
  
  

By Brandon Hemel, Director of Analytics

In a deep, dark corner of the Adams Hussey & Associates office sits a team of over-caffeinated data heads, who wake up way too early in the morning and speak in a strange language called SQL.

nerdAs the Director of Analytics at AH&A and leader of our nerd-herd - btw that is NOT me :) I often get this seemingly simple request: “Can you guys go into our data and see what it tells us?”

Without fail, I find that I need to do additional research to figure out not just what happened but why it happened.

So to help you in case you are ever asked that question, I’m giving you an inside look at the most vital part of data analysis and you don’t even have to go through the pain of learning Structured Query Language (SQL).

The key aspect of investigation is adding perspective and insight into your results to get the why and not just the what.

Five Handy Things to Keep Around While Doing Historical Data Investigations

Time Lines of World Events

wikiUnless your members and donors live in a vacuum, outside events will impact your fund raising efforts in both good and bad ways. But when looking back at your results after five or ten years has gone by, world events blend together. I find that Wikipedia.org and Infoplease.com are extremely helpful for these needs.

Metrics, Metrics, Metrics

Along with event timelines, consumer, government and world financial indices are great ways to compare and contrast your data against real world measures. My favorites are the Consumer Confidence Index, the Consumer Price Index and the Gross Domestic Product Index.

Metadata for your Source Codes

As Direct Marketers, we live and die by coding structure.  If your data has inaccurate source codes or you have changed the schema – let your data analyst know this ahead of time (please!).

A Second Set of Eyes

Deep sea divers always work in teams and so should your analysts. A fresh perspective is always helpful.

Most importantly – you should always have a

Big ‘ole Book of Historical Strategy

To understand the framework of what it means when you see a distinct change in your data (whether it is a huge jump in revenue or a deep decline in membership), old memos, year-end reviews, or at least a person with a really good memory are invaluable when contextualizing your data.

Tell us what you think. How does your organization add perspective to your data? Data for the sake of data may be fun (!), but it won’t help your strategy or grow your organization.

Comments

Great introduction to Analytics. Especially like the photo of Brandon. Question: can the AHA analytic process be applied to small databases as well?
Posted @ Tuesday, April 13, 2010 8:56 AM by David Rubin
Great article Brandon.
Posted @ Thursday, April 15, 2010 4:36 PM by Inga Beck
David - 
We can extract useful information from databases of any size. Within small data sets, there is always a possibility of a few outliers mucking up the analysis but if we go into the data mining knowing that outliers are there, we can then extract them and review the results without them.
Posted @ Monday, April 19, 2010 10:53 AM by Brandon
Comments have been closed for this article.