10 Ways to Use Business Analytics to Ensure the Success of Your Startup

The article features the top 10 ways to use business analytics to gain more profits

Presently, how organized you are in business is a key differentiator and how well you can achieve that is the real game changer. Organizations that use relevant data for the right touch point and at the right time are dominating the market. It is where business analytics comes in. Business analytics is basically a combination of skills, technologies, and practices used to examine an organization's data and performance as a way to gain insights and take data-driven decisions in the future using statistical analysis. Many startups are using business analytics to ensure success in the near future. The aim of business analytics for startups is to narrow down which datasets are beneficial and can increase revenue, productivity, and efficiency. With the help of top business analytics, we can accurately predict future events that are related to the actions of consumers, and market trends, and also assist in creating more efficient processes that could lead to an increase in revenue. Business analytics is used to analyze data from a variety of sources. This could be anything from cloud applications to marketing automation tools and CRM software. Here we will see 10 ways to use business analytics to achieve a successful business.

Taking business analytics as a priority

Many small businesses and software providers think that they are very small to need analytics or they do not carry enough data, but this is not true. Business analytics can play a crucial role in everything you do, and the time to start collecting data and making an analytics strategy for the future is now. Your startups already have a lot more data than you expect. Files, emails, call logs, server data, third-party data, and social media data are some types of data that often go overlooked but can act as a game changer for making decisions.

Create a data culture

Data is a mindset. It is basically a cultural shift away from 'gut-feel' business decisions to informed business decisions on the basis of business analysis. According to a recent report shared by Harvard Business Review, 99% of company executives put their efforts to move toward a data-driven culture, but only one-third report success. Creating a data culture will surely act as a key factor to ensure success.

Selection of the right technology

Digital transformation is moving your data to the cloud at a fast pace, so your analytics platform is also needed here. But while just about every analytics provider is "in the cloud," you want to look for one that's built for the future. You may not be familiar with the terms "cloud native" or "serverless," but when it comes to analytics, they make a big difference in what a platform can do and how much it will cost you. Look for an analytics platform that focuses on the latest cloud technologies will ensure your analytics are always moving forward.

Having artificial intelligence

Artificial intelligence is now not just science fiction and there is no need for a team of data scientists to make it a reality. Upgraded Business analytics platforms, such as Qrvey, can harness the power of AWS's machine learning to all of your analytics automatically without the need for coding or spending a fortune. Text recognition, object detection in photos, sentiment analysis, key phrases, and places are all integrated with the platform and are easily accessible to all your users, no matter whether they are non-technical ones.

Analytics Are More Than Charts & Dashboards

With the term business analytics, startups just assume about charts, reports, and dashboards, and if they are a SaaS or software provider, they think about embeddable charts, reports, and dashboards. But all thanks to the cloud, modern business analytics has moved beyond just visualizations to include your entire data pipeline. Some 3-in-1 analytics platforms like Qrvey combine data collection and transformation with analytics and visualizations and even machine learning to provide a complete solution for the next generation of analytics applications.

Collect all of your data

Having the complete data picture can only be possible if you are analyzing all of your data.  It means your analytics platform needs to process a lot more than just structured, SQL data sources. A platform is needed that can ingest all your data, including semi- and unstructured sources like NoSQL, files, emails, audio, video, social media, and lots more. If analytics doesn't include all of your data, you will not be able to see the complete data picture and it will hurt your ability to make informed data-driven decisions.

Watch Out for Infrastructure Costs

The cost of an analytics platform never stops at the price of your software license. Be sure to consider the cost of all your infrastructure as well. What is costing for your database and data storage, servers and processing, and associated cloud services? These items can rapidly add up and end up costing you more than the price of your analytics platform. As previously mentioned, analytics platforms that are cloud-native and serverless can eliminate the need for virtual servers that sit idly by spinning up services and functionality only when they are needed. These analytics platforms can even save money, by consolidating the data storage into a single repository.

Iterate, Iterate, Iterate

Many startups and software providers think they need to invest a big amount to do everything all at once. But now you can have a small start with just simple data collection and automation, then include analytics, visualizations, and advanced functionality as you rise. Start small and make analytics a core part of what you do, adding and iterating every month or with every software release.

Taking experts advice

Identify subject matter experts in each department who can provide instant feedback and ensure that data and analytics teams have the business context they need to generate effective data assets so everyone can use them and build further analysis.

Enable self-service analytics

By enabling self-service analytics your employees have the tools and power to solve their own questions and discover insights faster. They can collaborate to ensure customized metrics and dimensions have been agreed upon and support their team's goals.