11 Factors to Consider while Choosing an Analytics Tool

Analytics Insight Presents the factors to remember While Choosing Analytics Tool

The growth of artificial intelligence (AI), is delivering a flood of data to the industry in massive quantities. As per management consulting company Aspirant, all of this data is highly helpful for businesses, but many don't know how one goes about evaluating or analyzing such enormous volumes of information.

Each year, a slew of analytics solutions are introduced, with mostly similar features and functions. We've compiled a list of 11 critical elements to consider when assessing and picking an analytics platform so that you can make the best decision for your company.

What is a data analytics tool?

A data analytics tool is a piece of software that collects and analyses massive volumes of user data in order to discover patterns and anticipate user behavior.

Installing a tracking package on your site, smartphone apps, or servers to capture data is the first step in using data analytics software. The data analytics platform may then track activities like sessions, entry and departure points, video views, and items added to the cart.

Why use a data analytics tool?

Product teams can discover which functionalities keep people engaged and identify possible resistance or drop-off spots in the user flow by monitoring user behavior. You may use a data analytics tool to assess engagement by correlating factors like hours wasted in an application when utilizing a specific feature. If consumers aren't performing the desired action, you may discover drop-off spots and subsequently enhance the product to promote that action.

How to choose an Analytics Tool?

1. Business Objectives

Your analytics platform, like every other IT expenditure, should be able to serve both current and future business needs. To begin, you must determine your company's fundamental objectives and develop a list of desired business results. After that, disintegrate your business goals into quantifiable analytics objectives. Ultimately, select an analytics platform that gives you access to information and reporting tools that will help you meet your company goals.

2. Pricing

Do you have the expertise, resources, and experience to create and manage your own analytics solution? You must be completely informed of the expenses connected with the analytics solutions you are investigating, including memberships, growth, and extra costs, before picking an analytics tool. Varied analytics systems have different price structures, which you should be aware of before making a purchase.

3. User Interface and Visualization

Your workers will use your analytics tool whilst creating marketing choices. Self-service analytics must have a user-friendly design that can accommodate a variety of users. Even non-technical people must be able to generate and comprehend dashboards and reports with ease. While aesthetics may not seem significant, having unattractive images on your panels will have a detrimental influence on user adoption.

4. Advanced Analytics

Your analytics software should be able to spot patterns in data and predict what will happen, events, and results. It must go past basic mathematical calculations to provide contextualized insights, allowing you to develop complex predictive methods and future-proof your company.

5. Integration

You must consider if a standalone solution or an incorporated solution is best for your company when choosing an analytics tool. With standalone solutions, you have a range of alternatives, but with incorporated solutions, you can access analytics from apps that your people are already acquainted with. You must be able to link your analytics platform to your current systems and third-party information sources. You should also consider how quickly your data can be transferred to other platforms if the need arises.

6. Mobility

Mobile analytics is a simple and effective method to keep anyone in your company connected at all times and from anywhere. Businesses worldwide need mobile analytical capabilities to make data-driven choices on the fly. Before weighing your alternatives, consider the following:

• What analytical skills do your staff require on their mobile devices?
• Do they need to be able to merely see reports and dashboards, or do they need to be able to create and update them on the fly?

Mobile BI increases information accessibility, reaction times, and corporate communication. According to studies, mobile BI promotes user adoption.

7. Agility and Scalability

Cloud-based analytics systems are built to start small and scale up as your company grows. These compensation arrangements can help early-stage firms gain a competitive advantage and sustain them during periods of rapid expansion. With analytics that grows according to your company demands, you may receive rapid data access and analytics to make quick choices.

8. Multiple Sources of Data

Modern analytics systems can evaluate structured, semi-structured, and unorganized data and integrate many sources of complicated data. It's critical to use products that don't necessitate the help of your IT staff. You can get a full picture of your business performance by gathering and combining data from several systems into a single dashboard.

9. Customization

Because every organization has its own set of needs, you must choose an analytics solution that suits them. To integrate seamlessly into your processes, your company may require a bespoke analytics setup. You should also consider if the solution can be modified or expanded to suit both current and future requirements.

10. Collaboration

Self-service, interactive analytics facilitate brainstorming and make the problem-solving process easier. To enable better, collaborative decision-making, your analytics solution must allow people to exchange, analyze, and engage with data in various content forms. When you need to communicate and make choices, you should be able to swiftly disseminate information throughout your business.

11. Security

You must assess your analytics providers and vendor's security to verify that the appropriate safeguards are in place to protect your data. Establish standard security systems and procedures at all levels, processes, systems, and data, to restrict which people or groups have access to which data. It's also crucial to comprehend the consequences of mobile BI, as customers can view data from outside the corporation's firewalls.

Conclusion

However, determining which analytical tools to utilize is one of the most difficult aspects of data analytics. As per Josh Levy, a supervisor in analytics at Aspirant, when new analytical tools are introduced, organizations are having a more difficult time determining which is the greatest fit for their group.

According to Levy and Wells, it is particularly necessary for all groups within an organization to utilize the same tools. Companies would become fragmented and data will go underutilized if there is no supervision or consistency in analytical tools.