3 Things You Can’t Forget When Analyzing Business Data

Feedback and sales data are essential to analyze where your business has been as well as to plan for where your business will go. However, to effectively plan for the future and figure out what has and what hasn’t worked in the past, you can’t just guess by looking at numbers. There many important aspects you can’t forget when analyzing business data, all of which comprise the “context” of the data.

business data

1. Location Matters

Different locations will produce different data simply from the fact there’s a different set of people living in that area. For example, you may discover that Product X is selling extremely well in all of your store locations in Southern California. Excited to capitalize on its popularity, you shift most of the marketing budget for this product and launch a nation-wide campaign. Then you’re disappointed to find that it doesn’t do anywhere near as well as you hoped on a nation-wide scale, and your investments in the product are gone.

If you’d paused to consider how location matters, you may have been able to figure out that Product X was only more popular in Southern California because it appeals to the type of person living there: A young person with excess income, for example, or a person who lives in moderate temperatures year-round. If you consider the location aspect of context, you would have known to focus marketing only on that area or in areas with a similar demographic.

2. Trends Affect the Data

Current trends in the industry play a role in determining the context of business data as well. Say a book becomes a bestseller and your product has relates to the book in some way — if you see a sudden boom in sales, it’s not time to risk everything and invest in a huge marketing campaign and product line development assuming the trend will last forever. Make use of current positive trends, but always plan for negative trends in the future, just as a failsafe.

On the other hand, don’t despair over a downturn in sales and believe there’s no end in sight. Think of the trends in the industry. Maybe high unemployment rates have caused fewer people to spend money on luxuries. A reduction in price or a new line of more practical products could boost your sales.

3. Marketing Makes a Difference

The blame for a poor-selling product doesn’t lay entirely with the product itself, and neither does the reason for a successful product. When looking at data, either positive or negative, consider the marketing strategies you’ve employed to get there. If you can’t or don’t think you need to tweak a poor-selling product to garner more sales, tweak the marketing campaign. Perhaps you’re completely missing the targeted consumer for the product, and you could reach them more effectively through social media than TV ads. Consider what you’re doing to market popular-selling items and incorporate some of those strategies in future sales.

Midsize Insider reported 42 percent of IT workers surveyed by the Society for Information Management in 2013 pointed to data analysis and business intelligence as the number one expense in their budget. Rather than wasting money and employees’ time in dealing with too much data, you should focus on discovering the context of all the data you gather. The context brings the truth buried beneath the numbers to light so your business moves forward in the right direction.

Get an Advanced Education

Sometimes it’s not simply a matter of forgetting the context of your business data, but lacking the tools and necessary expertise to know how to accurately consider the context. Study up-to-date strategies and expand your analytical power with an advanced degree such as a master’s in business intelligence. Encourage your employees or colleagues to do the same. While earning your degree, you’ll learn how to use the most recent technology to make your job of figuring out the context easier. Some apps and programs are especially helpful, and heading back to the classroom can give you the chance to practice using the technology with sample data.


About the Author: Nancy Ellis is a data analyst at a Fortune 500 company in New York with an MBI.


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