Data analytics is essential to understand customers and markets and plan the business’s future steps to achieve its goals. Here, we’ll discuss the need for industry-specific analytics and how it can empower organizations to make better and profitable decisions.
Data analytics is a keyword in today’s world. Every business wants to invest in analytics to gain a competitive edge. The market offers numerous data analytics and business intelligence tools for analyzing datasets and deriving insights.
According to Fortune Business Insights, the global data analytics market was $64.99 billion in 2024, and is predicted to touch $82.23 billion in 2025. It is expected to grow at a CAGR (compound annual growth rate) of 25.5% to reach $402.70 billion by 2032. Artificial intelligence plays a vital role, as data analytics tools powered by AI and ML technologies can provide accurate and quick insights.
However, with large amounts of data generated daily, how can organizations use this data for analytics? After all, statistics show that the global data creation will be 185 zettabytes by 2025. In such instances, the types of analytics you implement can determine your success.
So, what kind of analytical insights should you generate and use for decision-making? Can general analytics provide the same results as industry-specific analytics? What is the difference between them?
Let’s find out why industry-specific analytics are necessary for businesses in today’s scenario.
Data analytics is the process of examining vast datasets to identify hidden patterns and trends and provide useful conclusions or interpretations. These are called insights and help in making data-driven decisions. Business intelligence, reporting tools, and advanced AI analytics come under data analytics. While the tools and technologies used are different, the central concept of data analysis remains the same.
However, generic analytics are not as effective as analytics tailored for the business and industry. That’s because of the following reasons:
Generic analytics are just that and offer one-size-fits-all insights that don’t go into specifics. They can be broadly applicable but miss the nuances of how things differ from one industry to another. Industry standards, business KPIs (key performance indicators), the organization’s mission and objectives, or even the target audiences are not considered in generic analytics. There is no specific indication that the insights will help your business handle a certain situation effectively.
Without customized data analytics services, you have to rely on generic insights that may have misinterpreted the context or used a different dataset for the purpose. For example, a business manufactures and sells wooden kitchen appliances. To derive meaningful insights, it has to use data belonging to the kitchen appliances niche, especially items made of wood. Additionally, it should also consider the target markets. However, if it uses random data collected from the internet, the insights can be inaccurate and lead to wrong decisions.
Since generic insights cannot offer nuance, they are not always actionable, as in, they are not always useful for decision-making. Moreover, there’s a higher risk of deriving biased insights since the data is not carefully collected or processed. For example, the insights might show that the sales haven’t been as expected, but fail to provide the real reason for this. Or, they could indicate a wrong reason, which ultimately results in extra expenses and losses for the organization.
When you hire a data analytics company, you want to get back the return on investment. The ROI is measured based on various metrics, like how actionable the insights are, whether the data-driven decisions helped achieve the business objectives, and so on. However, when the insights are generic, you cannot use all of them for decision-making. But you continue to spend money on the process. This reduces the ROI and indicates that your investment is not worth the money you spend on it.
Customized data analytics solutions for every business based on industry standards and requirements can increase forecasting accuracy and promote better decision-making at all levels in the enterprise. That’s why many data analytics companies offer tailored services that align with the mission, vision, and goals of each client.
Here’s how industry-specific insights can help an organization be prepared for a better future:
Sector-wise data forecasting gives insights that target the industry, market, or customer base. This is done to get in-depth reports about how the various external factors influence the business and what can be done to make the best of the situation. When the insights derived are highly relevant, they help teams make empowered decisions to grow the business. For example, with targeted insights, you can understand why customers didn’t like a product or what can be done to increase sales.
Since industry-specific analytics share insights about the patterns, trends, and correlations in historical data, they can be used to make informed decisions and build effective strategies to tackle various situations. For example, you can understand customer purchase patterns during different seasons to plan an effective marketing campaign and attract more sales. This increases the ROI for the amount spent on promotions and establishes the brand in the market.
Every business aims to grow and expand into newer markets, increase its customer base, and achieve a higher share. For this, you should know which target audience to impress, how to convert them into customers, when to enter a new market, which products and services to promote, which marketing channels to use, and so on. The information to make these decisions can be provided by industry-specific insights. You can be ready for new opportunities and grow the business quickly.
Customers are essential for any business to survive in competitive markets. However, retaining existing customers and attracting new ones requires a clear understanding of who they are, what they want, and how to convince them. For this, you should segment customers based on demographics, purchase preferences, likes, etc., and send targeted ads, emails, promotions, and more. Additionally, using targeted analytics for business decision-making allows sales and marketing teams to use the right message for the right customer at the right time.
Customer behavior analysis is the process of understanding how different customers interact with the business and its products and services. It shows the customers’ journey with the brand, the touchpoints, habits, motivations, etc. Using this data allows you to identify patterns, which can help to enhance customer experience. For example, you can offer loyalty programs and additional discounts for VIP customers.
Marketing has come a long way in the last few years. By using data analytics to examine customer behavior, market trends, and the brand’s sales records, you can create personalized campaigns to target each segment group. This makes the messages resonate with diverse customers and results in increased interaction, engagement, and loyalty. It also leads to faster conversion and more sales. A few examples of personalized marketing are customized newsletters, targeted ads on social media and the internet, product recommendations, customer journey personalization, etc.
Contextual accuracy in data analytics is when the datasets are interpreted by considering the relevant details like the situation, influencing factors, and so on. This gives more credibility to the insights and makes the predictions reliable. For example, a report shows that sales increased in a certain month. While this is encouraging, knowing why the sales have gone up will allow you to recreate a similar environment and sustain the development. Or, you can be ready for more orders when the event repeats. For this, you need to know the context.
Every business competes with several others in the industry and markets. You should have something that makes your brand stand out and attract customers. This can be the products, services, or processes. Industry-specific data analytics gives organizations a competitive edge by streamlining various processes, reducing costs, and improving customer experience. Data processing plays a crucial role in enabling real-time analytics in an enterprise as it converts raw data into useful insights.
Dynamic Adaptation refers to the process of adjusting and optimizing the systems based on analytical insights. Data analytics is used to monitor how the systems work, identify patterns, and highlight changes. Based on the insights, the system will automatically adapt its processes and responses to align with the conditional and environmental factors. For example, predictive analytics in manufacturing is used to schedule maintenance sessions for machinery to prevent unexpected breakdowns.
Data fusion, as the name suggests, is the process of combining data from several sources to create a comprehensive and centralized database that can be accessed by employees from across the enterprise. End-to-end data analytics services often include data warehousing where data from internal and external sources is brought together, cleaned, formatted, and structured to be stored in a central repository. This is done to ensure the insights derived are more contextual and accurate.
Detecting and preventing fraud can be a concern in many industries, like banking, finance, insurance, retail, eCommerce, etc. Industry-specific data analytics are useful in implementing fraud prevention strategies, sending alerts to managers, and reducing the risk of losses due to criminal activities. For example, banks can identify the risk of money laundering based on the transaction history of an account.
Data engineering companies offer tailored and sector-wise analytics for businesses to effectively use their data and make proactive decisions. Here are a few benefits of using industry-specific analytics in your organization.
Customers are no longer happy with blanket services. They expect everything to be personalized to suit their tastes. From product recommendations to ads and loyalty programs, personalization is not a choice but a necessity to enhance customer experience and keep them happy with the business. Tailored analytics helps by providing in-depth reports about what appeals to each customer and how to ensure their satisfaction with the business.
With tailored data insights, an enterprise can identify bottlenecks in various processes and find effective solutions to overcome the challenges. From choosing a more suitable vendor to shortening the production cycle and eliminating unwanted expenses, customized insights provide valuable information for optimizing business processes and increasing overall performance.
Demand forecasting uses machine learning algorithms and statistical models to analyze historical data and predict the possible future outcomes for a business. This helps in adjusting production volume, managing inventory, distributing the goods on time, and planning promotional campaigns to increase sales. Additionally, it streamlines resource allocation and efficiency.
Industry-specific analytics tools are used to derive tailored insights while ensuring compliance with data security and privacy regulations. Sensitive information is protected from unauthorized access by setting up security measures like encryption, restricted access control, remote backup, etc. It increases trust and transparency in the business and reduces the risk of legal complications due to leaked/ compromised data.
From effectively resolving customer queries and complaints to better communication, reduced friction between the brand and the customers, and new product development, tailored data analytics can help an organization become customer-centric instead of process-centric. This allows you to put the customer first and provide them with better products and services.
Data analytics consulting is a great way to reduce costs without compromising quality. Experts with domain expertise assist enterprises in creating tailored strategies to enhance various processes and reduce overall expenditure. It also increases the return on investment and profitability for the business by identifying cost drivers.
Industry-specific analytics provide accurate, actionable, and reliable insights for diverse businesses to make data-driven decisions in real-time. Whether it is to make the most of an opportunity or to avoid risks, the insights guide decision-makers in the right direction.
Partner with experienced data engineering companies to create a robust data-driven model in the enterprise and implement a tailored solution for customized analytical insights. With AI-powered predictive analytics and industry-specific insights, you can stay one step ahead of competitors and achieve your business objectives.
Data analytics services are essential for SMBs, MSMEs, and large enterprises to use business data and derive meaningful insights to make various decisions at multiple levels. It is useful in every industry to support strategic planning, risk mitigation, and competitive advantage. With tailored solutions to derive industry-specific insights, enterprises can streamline their processes and strengthen their brand presence in the global market.
Read the links below for more about how data analytics can benefit your business.
Yes, a consulting team offering end-to-end tailored data analytics solutions can help businesses build custom dashboards for pre-defined KPIs based on industry-wide metrics. For this, the service provider has to have expertise in the industry and know how the markets work. Choose a data analytics company with the required industry experience in its portfolio.
The process of engaging with a data analytics partner follows many steps. It starts with the business understanding its objectives and existing conditions. Then, the organization has to discuss these issues with the consulting company and check its project portfolio to determine if they can work as partners. Factors like pricing, transparency, communication, industry expertise, and testimonials should be considered.
Fact checked by –
Akansha Rani ~ Content Creator & Copy Writer
