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How Big Data Analytics Drives Digital Business Transformation

POSTED ON: August 28, 2020 TAG: Big Data

Every company depends on data and uses it to drive its business strategy and applications. Leaders make informed business decisions based on data analysis and plan investment in the field of analytics. One of the major reasons for the ever-increasing focus on data analytics is that it acts as the major driver to digital transformation. In the words of Gartner, data and analytics are the key accelerants of an organization’s digitization and transformation efforts. Modern big data analytics consulting services and systems help to make analytical processes faster and more efficient, offering a competitive advantage to businesses. In this context, let us see how big data aids businesses in the race for digital transformation.

Role of Big Data Analytics in Digital Transformation

Boosts Customer Retention and Acquisition

You may have a large and solid customer base, but if you fail to fulfill their expectations, your business success suffers. It thus becomes the most important to gather data related to consumer behavior and deliver what the customer expects. Through the power of big data analytics, you can observe several customer-related trends and patterns. Unless you observe customer behavior, you cannot be sure of their loyalty, let alone retain them. Having an effective customer data analytics mechanism in place and retaining your customer base gives you crucial behavioral insights.

Retaining customers is better than acquiring new ones and saves you costs. Besides, based on big data analytics reports, you learn about your customer traits and acquire customers by transforming your marketing and selling strategies. For instance, you find out that your customers are more interested in making purchases online than offline, so you increase your investments in online business – one of the steps towards digital business transformation and improving customer experience.

Manages Risks Effectively

Big data analytics and storage offers access to large volumes of customer data, be it historical records, previous transactions, or real-time data. It has highly contributed to developing risk management solutions while increasing the quality of risk management models. Businesses can quantify and model risks through the help of big data tools. Predictive modeling is one of the most used applications of big data to avoid fraud and monitoring.

Talking about the use of predictive modeling for credit card fraud detection, as data increases in terms of Peta Bytes (PB) and to improve analytical server performance in model building, there is an interface analytical framework with Hadoop that can efficiently read data and give that to the analytical server for fraud detection. Through big data analytics consulting services, you can analyze user behavior too for effective risk management. Organizations can thus predict and plan for unforeseen eventualities as well as disruptive events. Mitigating risks, making strategic decisions, and serving customers better are the key objectives of any business.

Offers Great Market Insights and Leads to Targeted Advertisement

Marketers can mine, integrate, and analyze structured and unstructured data in real-time through big data technology and analytics methods. As they explore varied patterns of how different groups of consumers interact with one another and make purchases, they can gain great marketing insights. Isn’t it cost-effective and time-saving to develop marketing campaigns targeted at your customers and fulfilling their needs? Besides, the rise of big open-source parallel platforms and in-memory computing enables data analysts to harness the power of big data sets and implement real-time data analysis.

And then, there is data monetization that helps businesses to generate new sources of revenue from the data available to them. For instance, in today’s times, when mobile phones have become the primary source of information for consumers, mobile network operators have access to large chunks of customer data. As data aids to generate consumer behavior insights based on location and demographics, as well as mobile engagement, they not only create a 360-degree customer view but also can easily monetize data.

Optimizes Supply Chain Management

The Internet of Things is driving industries all over the world with manufacturers having access to large data from external sources. If you carefully plot this big data in tandem with targeted analytics, opportunities have no end for manufacturers. Big data, when unified, offers contextual intelligence of the market as well as your operations. You can strategize, make accurate decisions, and anticipate any unfavorable situation. Leveraging contextual intelligence, you gain insights into real-time market trends, logistics efficiency, and consumer behavior. A manufacturing company can thus improve the quality of goods, responding to the market’s tastes and preferences.

Besides, real-time feedback on delivery records can be used to one’s advantage. Optimizing supply logistics affects the delivery of raw material and finished goods. A manufacturer can use GPS data gathered from outside sources for keeping supplies on track. As you analyze current data that is readily available, you learn how to optimize supply chain efficiency, amend standards, and minimize overall costs.

Drives Innovation and Product Development

There are several ways in which big data analytics consulting helps companies drive new product development, and thus, innovation. Companies can use optimization models to forecast quality and yield, predict demand, account for changes in production processes, ascertain return-on-investment (ROI) for every component in the production process, and employ mass customization strategies. Big data analytics can therefore strengthen decision-making and generate higher ROI as well as excellent performance.

Through predictive analytics and modeling, your organization can anticipate the product’s market performance pre-and post-launch in near real-time, decide on the optimal distribution chains, and optimize marketing strategies to accelerate customer acquisition at the lowest cost possible. Besides, modeling tools can aid to optimize media planning to help the organization accomplish its marketing goals. Firms into marketing analytics and in-house quantitative marketing teams can analyze the effects of marketing across channels and media. Organizations can thus assess marketing performance and adjust their marketing strategies in real-time to exceed their marketing goals.

Don’t forget the words of the famous American management consultant Geoffrey Moore, “Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway”.

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POSTED ON: August 28, 2020 TAG: Big Data

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