Businesses have witnessed the growth of technological tools to automate areas of their operations and expand in others with the aid of data mining, artificial intelligence, data mining, machine learning, and operational analytics, which uses data analysis to help companies monitor activities in real-time.
Total transparency and real-time data make it possible for businesses to stay competitive and to stay updated on customer behavior and take the necessary steps to improve the weaker elements that are affecting their bottom line.
When it comes to use cases for operational analytics, there are countless situations when it can be used to identify and solve problematic occurrences.
The most practical use cases tend to reside within the areas of sales and marketing, where employees on those teams rely on current and exact data to inform their daily decision-making.
Discover the most critical reasons why your business needs to be using operational analytics to streamline company activities and improve productivity.
1. Automation Efforts
Efficiency is of premium importance for any business that is seeking to stay relevant in the modern age.
Making use of operational analytics for automation gives companies the ability to speed up their processes, streamline redundant tasks, redistribute human effort away from menial work and put it towards more impactful projects, and expand the range of data that team members have available to them.
Leads and transactions can be delivered to sales staff, message alerts can be sent through to the appropriate departments whenever the statuses of accounts go inactive, characteristics regarding product usage can land in front of the product team, and the marketing department can receive information that can improve their campaigns.
2. Enhanced Productivity
Operational analytics helps organizations streamline their workflows and empower them by giving them the ability to concentrate on pointing out inefficiencies to make the necessary tweaks that will improve their bottom line.
Businesses using operational analytics data can realize whether or not certain processes are being delayed by having to wait on gaining multiple approvals that could be accelerated.
Data gives employees much-needed facts to ask for company policies to get changed so that many of the turnaround times that are keeping productivity from moving forward can be corrected.
3. Informed Decisions
Organizations have to make decisions fast, with tremendous accuracy, and in many cases, in real-time.
Using operational analytics for analyzing and responding to customer data takes the guesswork out of the process and allows for confident choices that are backed up by evidence.
Decisions affect the staff as well as the productivity that is required to react to ups and downs in a company’s journey with customers.
Making adjustments to entire workflows carries enough weight to see the ripple effects in profitability and troubleshooting, which means that time is of the essence and can’t be wasted by having to clean up avoidable mistakes.
4. Marketing Execution
Marketing managers with an understanding of data systems have the responsibility of building up awareness of a company and managing its company’s image. This means that they need accurate and the most current data.
The marketing department can gain an edge by using operational analytics to gather results, adjust stagnant elements, and give more credence to promotional efforts that are succeeding.
5. Product Analytics
Leveraging operational analytics in product analytics platforms provides a clearer understanding of how customers are interacting with a company and its products and services.
Getting data that is associated with service areas, user ids, and product usage information in product analytic tools makes complex analysis much more of a reality and puts team members up to speed on what success is looking like at that moment.
6. Sales Improvement
Ultimately, where would any corporate business be if their sales take a turn for the worst and plunge?
Sales is another integral area where operational analytics can increase positive results. Some examples of the impact that operational analytics can make on sales include:
● Offering free customer accounts, the chance to pay a monthly fee for upgraded features.
● Identifying how many customers have signed up for the offered service
● Figuring out the percentage of free users who are becoming paying customers
With the help of this guide to operational analytics, it will be exciting to see how your organization will be able to reap the benefits of accelerating your data enrichment process with operational analytics to push clean data back into operational systems to enable even non-technical users to leverage it.