The rising prevalence and increasingly varied applications of business intelligence software and analytics solutions continue to be a hot topic in the business world. Companies in a wide variety of sectors are approaching these tools and finding different applications for them on practically an everyday basis. Specifically, certain analytics tools are coming to the forefront of the field due to their outstanding usefulness – and predictive analytics most certainly fit into this category.
In recent months, the market for predictive analytics solutions has surged ahead, to a point where analysts believe it has no signs of stopping any time in the near future. The reasons for this are quite simple. Essentially, software solutions that allow for this type of analysis of big data offer an undeniable edge to businesses – the ability to have a strong impression of what your current customers and potential leads will do as consumers. That level of foresight is nothing less than priceless.
Market worth projected to experience uptick beyond 2013
MarketsandMarkets recently released a report on the current and future state of the predictive analytics market. It placed the 2013 value of this field as being approximately $1.70 billion. By 2018, the firm expects this figure to increase exponentially, reaching a projected total of $5.24 billion. This makes for a compound annual growth rate of 25.2 percent, which is quite considerable.
Certain regions are expected by market analysts to have a greater share of the predictive analytics field than others. North American clients will likely be the most significant source of business for companies selling such products. However, while other continental markets will lag behind it, they are nonetheless projected to see considerable spikes in traction and increasing CAGRs.
Possibilities too exciting to ignore
The present – and likely future – success of predictive analytics is largely contingent on the exciting possibilities of such solutions. According to CITEWorld, a variety of new predictive models are offering business users ways to leverage data more effectively than ever before.
One such technique is persuasion modeling. This involves using data culled from current or possible customers' social media, email, mobile device and general web data to predict customers' likelihood of making purchases based on insights gleaned of their activities. Other possibilities include the ability to track the success or failure of marketing initiatives – such as daily deals or coupons – and make adjustments in real time for the benefits of customers.