Predictive analytics relies on large quantities of data to make intelligent predictions about consumer behaviors. Naturally, businesses that have access to those data are more likely to be successful in using predictive analytics than businesses with only limited amounts of consumer information. Big businesses, with ample resources and capital, have no trouble using predictive analytics, but with 89 percent of marketers interested in predictive analytics, the technology is significant to companies of all shapes and sizes.
The question is, can small businesses take advantage of predictive analytics, despite having fewer resources and less access to capital?
There are some reasons to believe that predictive analytics can work for small businesses:
- Predictive analytics can predict anything. There’s no hard limit to what predictive analytics can do. Large-scale health insurance firms can use it to evaluate risk for millions of customers, but hypothetically, a local guitar instructor could make use of data to chart student performance and client retention just the same. The core of predictive analytics doesn’t discriminate based on the size or nature of the institution attempting to use it.
- Data may already exist. One of the biggest problems for small businesses is obtaining enough data to make use of predictive analytics—but in some cases, that data may already exist. Rather than spending the time or money trying to collect that data, these businesses may be able to leverage publicly available data sets as part of their analyses.
- The strategy can scale with the business. Predictive analytics can help businesses improve profitability by 20 percent or more over the long term. This isn’t a short-term strategy; if your business has a plan to scale over time, predictive analytics could be used as a tool to support and take advantage of that growth simultaneously. Starting early helps you utilize your first data sets, even if you won’t see the greatest benefits until your business is more mature.
However, there are some limitations to consider.
- Only big data will work. Small data sets could hypothetically give you the ability to make future predictions, but they won’t be as reliable or effective as big data. Businesses that have a limited customer base, or those that have only been in operation a few years, simply won’t have as much data as their bigger counterparts.
- Predictive analytics can be (comparatively) expensive. Even though costs have declined in the past few years (and will likely continue declining as technology advances), predictive analytics is somewhat expensive compared to other tools small businesses may be using. Small businesses on a tight budget may not have the resources to expend on this initially (unless they find a more cost-efficient way to pursue the strategy).
- Expertise is required. Having the data and calculating the results isn’t enough. You also need someone on staff who’s skilled in analyzing data. A full-time data analyst, and/or the cost of employee training, can be another burden in the way of small businesses taking full advantage of the technology.
Predictive analytics is still a young technology. For now, its expensiveness and baseline requirements makes it a tenuous investment for many small businesses—but there are enough advantages and avenues to success to make it a worthwhile consideration for even the freshest startups. SAP’s predictive analytics software can help businesses of any size with customer retention, more targeted marketing, and even high-level strategic business decisions, so give the platform a try before you write off the possibility of predictive analytics in your business.