This excerpt is from Small Business Computing. To view the whole article click here.
♦No longer relegated to the realm of big business, predictive analytics is taking its place in the toolboxes of many smaller companies. The power to crunch numbers and inform strategic decisions can be an important asset, especially when resources are lean. If you’re curious, this article explains the difference between predictive analytics and business intelligence.
Before you can effectively use predictive analytics to your small business advantage, you need to understand what the technologies can do. Fred Shilmover, CEO of business analytics firm InsightSquared, explains that predictive analytics is a three-part formula. “It’s looking at the past performance of whatever you’re trying to analyze, understanding the present, and applying that past to the present to predict the future.”
Predictive analytics often allows small business owners to broaden their time horizon when developing a strategic plan. Rather than focusing only on what should happen next, you can use predictive analytics to pinpoint the results you hope to achieve further down the road. “What are you trying to accomplish in a month, or three months, or six months?'” says Brandon Levey, CEO and founder of Stitch Labs, a provider of inventory management solutions. “Is there data you can look at that is going to predict how you can best accomplish that goal in the future?”
Small business operators are finding more ways to use predictive analytics to their advantage. Customer retention is one area and target marketing is another. According to Bala Deshpande, founder of SimaFore, predictive analytics consultants for small business, the technology can help small business owners “identify which prospect groups are most likely to adopt your products or services so that you can spend your precious marketing dollars on the most promising prospects.
However, demand forecasting is perhaps the most common application of predictive analytics. “Every business has historical sales data of some sort and, for small businesses, growing the top line is a matter of survival,” says Deshpande.
Demand forecasting may be of particular importance to small businesses involved in making or selling physical goods. If your company produces t-shirts, for example, says Levey, “You have an opportunity to look into the future and say, ‘I can spend $100,000 and buy what I think I should buy, but according to this I’m actually going to sell more, so if I’m willing to spend $130,000 today, I can generate more revenue for my business.'” On the flip side, predictive analytics may show the likelihood of selling those same shirts is actually lower. In that case, the business may choose to purchase fewer shirts and keep a tight lid on inventory.
Predictive analytics is definitely on small business radar when it comes to marketing. “That’s because of all the data points being gathered out there,” says Shilmover. What with Google Analytics, email marketing automation platforms, and similar tools, the amount of useful information generated by nearly any digital marketing effort is increasing rapidly.
“There’s a ton of data you can crunch,” says Shilmover. By using predictive analytics, that information helps a small business examine customers’ past behavior, so they can use it to improve future results.
Originally published at www.smallbusinesscomputing.com
Julie Knudson is a freelance writer whose articles have appeared in technology magazines including BizTech, Processor, and For The Record. She has covered technology issues for publications in other industries, from foodservice to insurance, and she also writes a recurring column in Integrated Systems Contractor magazine.
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