Predictive analytics is the new buzzword in CIO circles right now and for good reason. It offers significant advantages that can give your business an edge in a competitive marketplace. Predictive analytics can be used in any industry, from life sciences to consumer goods services.
To derive accurate results from predictive analytics, you need:
- A comprehensive set of data. Having data from a wide variety of sources will improve the accuracy of the results.
- Good problem definition. Predictive analytics can do a lot, but you need to define your goals first before it works.
There are many analytics services that can create algorithms to derive relevant results from your database. From that point, you can make decisions that will improve the overall profitability of a company.
It is easy to see why businesses have invested heavily in predictive analytics. Here are the top five reasons why you should too:
- Marketing optimization. Traditionally, analytics have been used to measure the success of a marketing campaign. Customer segmentation, pricing analysis, and marketing mix modelling have all been derived from studying data. Predictive analytics takes this to a whole new level. It works by using algorithms that can take data sets from different sources, identifying trends, and then creating a forecast you can use to identify where your marketing spend can have the greatest impact.
- Demand planning. Overcapacity and wastage are the results of poor planning. These can drain the profitability of a company. Predictive analytics can be used to optimize your resources so your company can meet customer demand without sacrificing quality. You can increase profits using the same resources as before through improved planning.
- Financial analysis. Financial markets have seen extensive usage of predictive analytics. From determining the credit risk of an individual to identifying investment opportunities in the stock market, predictive analytics can be used to evaluate current trends and create forecasts about the future behaviors of individuals, companies, or markets.
- Talent sourcing. One of the newer developments in predictive analytics is finding the best people for particular jobs. The US Special Forces has started using data models to assess new candidates. It can identify acceptable trade-offs such as trainability vs. experience. Given the amount of resources companies invest to find the right people, there will certainly be exciting developments in this field. Stay tuned.
- Location analysis. Social media companies such as Facebook and Foursquare have created algorithms that assess the location data of their users. This can reveal opportunities for businesses. By identifying where people are in real time (their routes, where they stay, etc.), it is possible to know which areas are up-and-coming and predict future developments in that area.
Predictive analytics holds massive promise. Business owners and executives can gain significant insights about their customers, trends, and the future. They can make better decisions that will help their business achieve optimal profitability.
What other important reasons or opportunities do you believe will drive the rise of predictive analytics?