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Have you ever wondered about the immense potential that data holds for your business? As per BI-Survey, achieving a data-driven culture is one of the most critical business intelligence trends since 2021. It is no wonder that by 2025, global data creation is expected to reach a whopping 180 zettabytes.

From 2021 to the end of 2022, data creation will go up from 79 to 97 zettabytes. So, the biggest question is how much of this data would be helpful for your business?

Significant advancements in networking, processing, and storage are taking place, thus opening up endless opportunities for leveraging data. From automated financial planning to medical diagnoses, from self-driving cars to factory automation – advanced Data Analytics and Data Science are entering every aspect of our professional and personal lives.

Let’s discuss five ways to use data for unlocking business potential.

1. Locating the areas where the data is sitting

Pinpointing areas where data sits in a business is challenging. The job of executive teams and finance leaders is to develop concrete strategies for collecting data from various departments and systems within the company.

Once you find the data from the source systems, you can start working on the next layer which is to build a repository. With such a strategy in place, you can carry out data analysis on a subset or a copy of the data obtained from multiple sources. With this, you bring all kinds of data – operational, accounting, social, etc.- to one place for better business insights and unlocking the optimum value from your data.

2. Modernising the architecture

Many companies rely on legacy systems, which are challenging to scale economically, and are not proficient in coping with overwhelming amounts of data as well as newer technology requirements. For instance, you can use Apache Hadoop, which comes with a de facto solution for challenges associated with 3Vs of Big Data, namely velocity, volume, and variety.

Beyond the data dynamics of the 3V’s, it is time to think about Data Engineering, Artificial Intelligence (AI), Machine Learning (ML), and Smart Analytics. Machine Learning is taking Analytics to the next step – predicting the future of work. Businesses and industries use predictive analytics to make informed marketing, production, and business development decisions. With AI and ML, companies are delving deep into their data to gain a competitive advantage over rivals and increase efficiency.

3. Broadening the data horizon

Even in the age of Big Data, several companies are not aware of the wonders that data can do. An entrepreneurship expert opines that sometimes data makes us more human – you can personalize various services and products for better market reach. For instance, marketers can create personalized campaigns by using data on customer gender, age, purchasing history, location, etc., to enhance the customer experience.

Predictive sales analysis tools and social media platforms can collect data to deliver highly customized products and services. Online product reviews are the best examples of valuable insights for future sales and other marketing and distribution aspects.

From music and cab booking apps to online food ordering and gaming apps, there are numerous real-world examples where AI/ML technologies are leveraged to gather customer data. Analyzing this data provides valuable insights for refocusing marketing strategies and enhancing the customer experience.

4. Empowering sales teams by identifying niches

With proper data insights, the sales team can work on lead generation to maximize sales. Various shopping apps like Flipkart, Amazon, etc., provide suggestions to buyers by following their shopping patterns and preferences. When the sales team receives data sets of customers, they understand customers better. Sales professionals can work on their sales dialogue for increased lead generation and turn individuals into potential customers.

Businesses can accurately identify market niches with proper data insights. OTT platforms like Netflix use data analytics and machine learning to curate their catalog of movies and TV shows in alignment with the subscriber’s preference. With Data Analytics, companies can predict marketplace changes and respond accordingly. It is also possible to understand the requirements and demands of customers through insights. Companies that can anticipate trends are more successful in the long run.

5. Democratising and free flow of data

Organizational speed and agility are critical features in the modern business landscape. As per Harvard Business Review, 87% of business executives opine that frontline staff, particularly those in direct contact with customers, should have AI/ML-driven data insights for making impactful decisions.

Therefore, it is inevitable for team leaders and key decision-makers of the company to have access to dashboards and data flows. Every department or team will have a more detailed insight into opportunities and challenges.

Conclusion

You can unlock your data potential like never before with machine learning and artificial intelligence implemented through a modern data strategy. For instance, have you noticed how almost all websites use AI-enabled chatbots to offer customer service and assistance? The chat history is a rich data set for understanding customer requirements and preferences. At the same time, these digital assistants lessen the workload of human reps who can focus on more pressing issues.

With proper data leverage, you can experience better business revenues, higher customer retention and acquisition rates, lowered costs, and, most importantly, enhanced customer experience.