Most organizations rely on at least 100 SaaS applications, as stated in a white paper by Productiv
. These apps cover a plethora of areas, including email, billing, CRM, HRM, and sales management. As companies rely on an increasingly larger number of SaaS apps, however, these can become more difficult to manage, and the information they contain can be more challenging to analyze in order to identify or change key strategies
. Currently, organizations are increasingly relying on add-ons that enable them to replace surveys and spreadsheets with updated online information that features advanced analytics into how users are interacting with their cloud-based applications.
The Importance Of Analytics For Cloud Apps
Salesforce reports that this year, the number of analyzed data sources will rise by 83%
. The growing volume of data kept by organizations means that they will be unable to obtain the full value of the information they review unless they rely on SaaS analytics to track user engagement
. Around 65% of underperforming organizations report that their analysts have inadequate training and resources. Analytics tools relying on AI can help analysts to do their job by providing information on users’ activities within the cloud, while also providing information on users’ acceptance of the system, inactive users, most/least read content, and more.
Embracing Scalability And Speed
SaaS analytics can do more than serve as a conduit between organizations and clients; it can also save organizations on cloud costs by adding data storage and data analysis capacity as the need for these arise. Businesses can therefore scale key functions such as storing and processing data, ensuring capacity is added in line with market conditions. Management making decisions on cloud expenditure can additionally access different types of data at once, thus exploring, testing, and evaluating the success of different SaaS apps. As analytics are stored on the cloud, this information can then be shared with other staff members, thus promoting more effective communication and strategizing.
A New Way To Secure Data
Embracing cloud analytics can serve as an additional way to secure data
. It also makes for better governance, since organizations are now able to manage controls to different data and to audit and analyze which users are accessing different data files. Security analytics itself can enable processes such as threat intelligence analysis, fraud detection, and endpoint and network behavior modeling. In the case of threat intelligence analysis, for instance, businesses can harness information on sources of attacks, signs that their system has been compromised, and behavioral trends regarding the use of their cloud accounts. Analytics can also be used to create predictability models, so companies can address threats more proactively. The massive event data processing abilities of the cloud enables organizations to detect and be notified of a plethora of different threats or potential threats.
Organizations are currently relying on around 100 SaaS applications, and this trend is only expected to grow as more businesses go digital. SaaS analytics is vital when it comes to achieving a greater understanding of how users are interacting with their apps. SaaS analytics can also be seen as a magnificent way to identify and stop threats before they undermine vital data, whose secure storage is key to maintaining a company’s reputation.