How Data Analytics drives business growth?

Data Analytics is the science of extracting raw data, analysing it and deriving inferences which enable decision making to enhance business processes and growth. The entire process is automated by Business Intelligence Tools which are driven by algorithms that work on raw data. The findings help Businesses optimise performance, enhance the growth of the business, generate higher revenues by tapping into the inferences.

Data is collected or extracted, stored, analysed and studied to understand customer behaviour, needs, emerging market trends and patterns. This in turn helps in strategising appropriately to attain desired business results. Data can be obtained from various sources - historical data or new data that is obtained for real time analysis, internal systems or external data sources.


How Data Analytics help in Business growth?

Data Analytics services help increase revenues, improve operational efficiency, enhance customer service, respond quickly to emerging market trends thus enhancing business growth and performance.


1. Enhanced operational efficiency : Analysing historical data helps understand gaps in logistics and operations and bridge the gap with appropriate control measures. Whether it is inventory management issues leading to excess shelf life of products or parts or delay in meeting the demands of customers due to supplier issues, data analysed will highlight it and enable decision making to avoid these and ensure smooth operations. With real data analysis highlighting market trends, appropriate forecast can be made on customer demands enabling Business to be ready to meet the same.


2. Target marketing via Social media: Social listening by tapping into social media helps understand customer needs, likes and dislikes indirectly. Also customer feedback on a product or service as stated via comments on social platforms enable Businesses to offer specific service to customers or target Ad campaigns. This is Target marketing which is possible by analysing customer behaviour based on data received via feedback or comments on social media. Furthermore, clicks on ads placed strategically on various pages, can be counted to evaluate the customer traffic to their website. Tracking bounce rates helps understand if the click-throughs were not accidental by finding out how long the customer spent on the website before moving away from the landing page or if the customer further moved to other content links on the website. These metrics help redesign website and its content to make it more appealing to the customer.


3. Target marketing via Predictive Analytics: By understanding Customer’s buying patterns and internet browsing habits, Businesses can target specific products or services using Predictive Analytics.


4. Improve employee efficiency: By tracking data on time effectively spent by the employee on priority tasks and separating the mundane repetitive tasks from the workload by employing Robotic Process Automation instead, employee efficiency can be improved.


BI tools and Analytics services:

Business Intelligence Tools (BI Tools) and Analytics services help understand emerging trends and derive inferences that help make strategic business decisions that drive growth and provide an edge over the rivals. Also in some cases, Business Intelligence tools alert the business about impending issues, help resolve them, forecast future trends or outcomes of actions taken today. BI Tools monitor trends in business, identify new opportunities, improve productivity, perform predictive analysis, enable machine learning, help in planning and analysis. They cater to companies of all sizes - small, medium and large enterprises. They enable data access via desktop, web or mobile interface. They connect to a wide variety of data sources including Excel, SQL, ERP, CRM, Oracle databases. They present the final analysis in the form of graphic visualisations, dashboards, reports etc.


Data analytics service providers typically implement a data analytics solution that is enterprise wide that could consist of designing and implementing a data lake, data warehouse, OLAP cubes and reporting as the need may be. This may be established in house for continuous use into the future. Or, they may work on the raw data shared by the customer and provide analysis in the form of reports and dashboards in a typical ‘outsourcing’ model. They may cover a broad range of areas in analytics such as customer analytics, marketing analytics, sales analytics, financial analytics, performance analytics, operational analytics, industrial analytics etc. Reports of which enable decision making.