Analytics software is fast becoming one of the most vital tools across all of the IT industries. The market for analytics software is set to increase substantially to reach $22 billion by 2020. At its core, analytics software is defined by the use of algorithms which can be used to discern relationships between various units of historical data.
One of the key drivers in the increased investment into Analytics software is big data. The ability to derive insights hidden deep within structured data is propelling interest among businesses. In conjunction, the increasing sophistication of analytics software has resulted in products that are more agile, easier to use and have the ability prescribe actions for a wide range of businesses.
The Crozdesk Market Radar™ reveals a market that is dominated by Google Analytics which has consistently been popular since its launch in 2005. That said, the market is competitive with a high number of vendors that are on the precipice of the leader segment, and a substantial amount of vendors in the challenger segment who are offering more niche solutions, such as error analytics and form analytics.
A fairly recent trend in the market is the demand for analytics that can make customer behavior more comprehensible. In the last few years, there has been a high degree of vendors offering features such as heat maps, visitor session replay, and behavior alerts. All of which gives businesses the ability to pinpoint problem areas of their websites.
Businesses today gather large volumes of data, ranging from customer information to something as basic as the client location. The process of converting the data into actionable information is called analytics. Analytics software analyzes each bit of data your business gathers by filtering out the unnecessary information and using only the data that matters. However, a large amount of software products tend to focus on web analytics exclusively. Methods can range from historical to predictive and a business’ analytical requirements tend to vary based on use and application. The main factor to consider is the analytical model you want to use, such as regression or clustering and the primary channel / location of your data sets. Additionally, there are numerous subcategories of analytics, including, but not limited to, predictive analytics. Read the full software guide...