Every day, we produce a staggering amount of data. According to Statista, the total amount of data created, captured, copied, and consumed globally is projected to grow to more than 180 zettabytes by 2025. Data can aid organizations in gaining a deeper understanding of their clients, enhancing their advertising campaigns, personalizing their content, and increasing their ROI.

Articulating the importance of data, NordVPN tweeted a qoute from Tim Berners-Lee, inventor of the World Wide Web saying “Data is a precious thing and will last longer than the systems themselves.“

While raw data has great potential and contains valuable knowledge, you need data analytics to uncover its business growth potential. An increasing number of businesses today have realized the importance of data and are utilizing data to gain a real advantage over their competition simply by mining any and all available data and gaining actionable insights with the help of data analytics. With the use of data analytics, businesses can tailor their market presentations to each individual client, thereby reducing potential threats.

Data analytics tools empower businesses with cost savings, productivity gains, and better decision-making capabilities. According to a report published by MarketsandMarkets, the global analytics market is expected to grow from $ 10.5 billion in 2021 to $ 28.1 billion in 2026, with a compound annual growth rate (CAGR) of 21.7% on average. Analytics unlocks the door to actually “understanding” the customer.

Embracing analytics paves the way for businesses to develop innovative solutions, expand hyper-targeted advertising strategies, and personalize marketing campaigns according to their customer’s preferences. Data analytics can drive positive outcomes for businesses and their customers while still maintaining and facilitating the highest level of data protection. This blog outlines some of the benefits of data analytics that businesses can reap.

But before that, let’s look at what data analytics is.

What is data analytics?

The term “data analytics” refers to the process of analyzing chunks of raw data and datasets to draw meaningful and actionable insights. Data analytics helps businesses examine all of their data (real-time, historical, structured, unstructured, qualitative) to uncover trends and develop insights to guide and, in some circumstances, automate decisions, thereby bridging the gap between insight and action.
Many data analytics techniques now make use of specialized systems and software that incorporate machine learning algorithms, automation, and other features to solve specific problems and challenges. Data analytics enables firms to digitally transform their businesses and culture, shape business processes, and go beyond typical KPI monitoring and reporting in order to uncover hidden data patterns, make more innovative decisions, and foster business growth.

Geoffrey Moore, an American organizational theorist, management consultant, and author, best known for his book Crossing the Chasm: Marketing and Selling High-Tech Products to Mainstream Customers, articulating the importance of Data Analytics, tweets, “Without Big Data Analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.”

Types of Data Analytics

Let’s look at the different types of data analytics that can help businesses find out where they are falling short and what has to be done to correct the situation.

  • Descriptive Analytics: This surface-level analysis aims to analyze historical data via data aggregation and mining
  • Diagnostic Analytics: Diagnostic Analytics investigates the “why.” For instance, if a business experiences a sudden reduction in clientele, diagnostic analytics might help determine the cause
  • Predictive Analytics: As the name implies, this analytics aids in predicting the future course. This is achieved by providing businesses with the information they can put into action as they plot their course for the future
  • Prescriptive Analytics: Analysis of this sort illuminates the practical applications of foreseen results. It’s an advanced form of analytics that requires the use of algorithms, ML, and other computational modelling techniques

What is a data analytics strategy for business?

A data strategy incorporates and directs multiple areas of data inside an organization, such as how data is collected, stored, utilized, and maintained. A robust data analytics strategy will ensure that incoming data is high quality, homogeneous, and provides a comprehensive perspective of operational and commercial strategy and execution without introducing silos or bias. Businesses can ensure the reliability and applicability of their analytics by giving value across the whole data journey. Whether a company is a well-established business or a startup with an innovative new product or service, expanding the company’s operations requires the use of data analytics tools to make educated strategic decisions.

In an informative talk, Philip Evans talks about how data can transform business strategy

Philip Evans: How data will transform business

Benefits of data analytics for business

1. Informed business decisions

Many times, businesses make decisions based more on intuition than on facts and statistics. This could be due to a lack of access to high-quality data that can aid in more informed decision-making. One of the most important benefits of data analytics is that it helps businesses make better decisions in the long run instead of just relying on their knowledge and experience. With AI, ML, and data analytics, businesses can better gather relevant information, construct prediction models, and stay ahead of the curve using real-time data collection and historical data analysis.

Liv Boeree, former professional poker player, discusses in her vlog how data analytics in the game of poker can bring about optimal solutions and let users make decisions not just on gut feeling but with data-driven analytics.

2. Improves customer insight

Data analytics can be done on datasets from different sources of customer data, such as social media activity, customer purchase logs, third-party customer surveys, computer cookies, website or application statistics, and more, so that you can explore previously unknown data like client preferences, most-visited sites, time spent on site, comments, and form submissions. As a result, businesses may better meet their customers’ needs and boost their satisfaction levels.

3. Personalize the customer experience

Data analytics enables businesses to create comprehensive customer profiles and provides you with more information about your consumers, allowing you to adjust your customer service to their needs, provide greater personalization, and build stronger relationships with them. Consequently, your data can provide information about your consumers’ communication preferences, interests, and much more. To optimize the customer experience further, organizations can use behavioral analytics models to analyze consumer data and enable businesses to react in real-time and make the consumer feel personally valued.

4. Personalization of products and services

Businesses can no longer get away by offering just standard goods and services. Products and services that cater to each customer’s specific requirements are highly sought after. Analytics can be used to track client preferences for various content types in order to provide suggestions according to those tastes. Utilizing data analytics to cater to each customer’s specific needs is a great way to increase loyalty and repeat business.

5. Identify customer behavioural changes

In today’s world, clients have a lot of alternatives. If enterprises are not tuned to client wishes and expectations, they might soon find themselves in a downward spiral. Customers tend to change their preferences as they are frequently exposed to new information in this era of digitization. With large amounts of customer data, it is almost hard for enterprises to make sense of all the changes in consumer perception data without employing the power of analytics. Analytics gives you insights into how your target market thinks and whether there is any change. Hence, being aware of a shift in client behavior can provide a significant edge to organizations so that they can react faster to market developments.

6. Mitigating risk & fraud

Today’s businesses thrive while facing numerous threats, including theft from customers or employees, failure to collect outstanding invoices, threats to employees’ physical security, and legal liability. In order to ensure the safety of your business and prevent any instances of fraud, you need to have access to effective data analytics capabilities; this is because deterrence requires mechanisms that enable businesses to swiftly detect potentially fraudulent activity, anticipate future activity, identify and track perpetrators, and so on. Using statistical, network, path and data technologies to predict fraud will enable rapid responses via real-time threat identification, automated warnings, and mitigation. Moreover, combining data management with fast and transparent reporting of fraud incidences would enhance fraud risk management operations. Furthermore, integration and correlation of data across the enterprise can offer a unified view of fraud across various lines of business, products, and transactions. Multi-genre analytics and data foundation provides more accurate fraud trend analyses, forecasts, anticipation of potential future modus operandi and identification of vulnerabilities in fraud audits and investigations.

7. Enhance security

Risks to data security affect every company. A company can utilize data analytics to determine what went wrong with previous data breaches by analyzing and interpreting the processed and visualized information. The IT team, for instance, can employ data analytics programs to examine and map out audit logs to trace the origins and methods of an attack. IT teams can more easily find security holes and fix them using this data. Also, IT security teams can utilize statistical models to prevent future assaults. Attacks frequently entail anomalous access patterns, especially load-based assaults like a distributed denial-of-service (DDoS) attack. Organizations can configure these models to run continuously, with monitoring and alerting systems stacked on top to detect and flag anomalies for prompt action by security professionals.

8. Streamline operations

Data analytics also has the potential to help businesses find possible ways to optimize internal operations and boost revenue. It aids in recognizing prospective problems and preventing their occurrence. This allows businesses to determine which activities have provided the best overall results under varying conditions. In addition, many organizations struggle to optimize their inventory levels, particularly in the retail industry. Utilizing seasonality, holidays, and secular trends, data analytics can assist in determining the appropriate supply for all of an enterprise’s products. Using data analytics to plan, regulate, and streamline organizations operations in the development of products or services results in increased efficiency and effectiveness in meeting consumer expectations and attaining operational excellence.

9. Enhances marketing campaign efforts

Data analytics takes the guesswork out of marketing, making products, content creation, product development, and customer service. It enables businesses to roll out targeted content and fine-tune it using real-time data analysis. With the use of data analytics, businesses may find out which kinds of marketing have the greatest influence on their target audiences as well as the extent to which they could implement these tactics. With the help of analytics, marketers may streamline their efforts to boost conversion rates while decreasing unnecessary spending on advertising.

In conclusion

Data offers a wealth of opportunities that are hard to ignore. Smart, data-driven businesses increasingly leverage new tools to understand their customers better, run advertising campaigns, automate processes, and streamline complex operations. Data analytics help businesses improve operational efficiency, change how they promote their products, drive new revenue and gain competitive advantages, engage with clients, and manage finances. Along with actionable user behaviour insights, data analytics can help with cost savings, revenue growth, and creating a one-of-a-kind client experience that encourages repeat business. Sparity offers data analytics services that allow businesses to gain quick, frequent and flexible analytical insights from their data. Get in touch with our team of data analysts so that we can help you with your data problems.