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It is no secret that data analytics can be valuable for companies of all shapes and sizes. But do you know how to collect, harness and use it to drive better business insights?

How to Use Data Analytics to Drive Better Business Insights

how-to-use-data-analytics-to-drive-better-business-insights

[[p]]Data analytics can be a valuable asset for companies of all shapes and sizes. Data helps marketers get insights about their target audience and tailor content to match search intent to provide a seamless [[a href="https://digitalmarketinginstitute.com/blog/what-is-customer-experience-cx" target="_blank"]]customer experience[[/a]].[[/p]]

[[p]]However, just one out of five marketers report that their marketing data is fully integrated with the tools they use, and 30% believe the interactions between the tools used in their role were either slightly or very disjointed, according to HubSpot&rsquo;s &lsquo;The 2025 State of Marketing &amp; Trends Report&rsquo;.[[/p]]

[[p]]The challenge for many marketers when using data is gaining access to technologies capable of analyzing an abundance of data efficiently. While many companies can record large quantities of data, they are unable to process and analyze that information effectively.[[/p]]

[[p]]While [[a href="https://digitalmarketinginstitute.com/blog/ai-in-digital-marketing-the-ultimate-guide" target="_blank"]]artificial intelligence (AI)[[/a]] is helping to analyze data at scale, challenges remain, such as the availability of quality data, and integrating the technology with existing platforms.[[/p]]

[[p]]So, what can organizations do to use data analytics to achieve better insights that help you [[a href="https://digitalmarketinginstitute.com/blog/7-tips-on-getting-to-know-your-customers-better" target="_blank"]]get to know your customers better[[/a]] and drive sales?[[/p]]

[[p]]In this blog, we will explore:[[/p]]

[[ul]]
	[[li]][[a href="#heading_68041"]]What can big data achieve?[[/a]][[/li]]
	[[li]][[a href="#heading_68043"]]What do you need to understand about data?[[/a]][[/li]]
	[[li]][[a href="#heading_68058"]]Case studies: Netflix &amp; Walmart[[/a]][[/li]]
	[[li]][[a href="#heading_82046"]]Conclusion: Actionable data analytics checklist[[/a]][[/li]]
[[/ul]]

[[p]]The key to using big data is understanding what your business can achieve with it. While big data is frequently associated with [[a href="https://digitalmarketinginstitute.com/blog/12-tips-to-improve-seo-for-ecommerce" target="_blank"]]marketing and e-commerce[[/a]], it&rsquo;s a mistake to believe that data is restricted to just those sectors.[[/p]]

[[p]]With proper analysis, businesses across industries can benefit from data, enabling a company to stand out from the competition. Such practices may also detect potential errors before they occur or prevent fraud, particularly in the [[a href="https://digitalmarketinginstitute.com/blog/how-4-industries-are-navigating-digital-transformation" target="_blank"]]pharma or finance sectors[[/a]].[[/p]]

[[p]]The strategy for e-commerce companies such as Amazon, is to use data to their advantage. By evaluating the browsing behavior of their users, these companies can better understand the needs and habits of their shoppers. This information then helps businesses maximize their profits. It also enables the company to promote products online that specific users will be more likely to order and purchase.[[/p]]

[[p]]Before a company begins to collect large amounts of data, it is important to formulate a long-term plan and goal. Storing data can be costly, and analyzing the information even more so.&nbsp;[[/p]]

[[p]]Therefore, it is important to identify your company&rsquo;s goals for the data ahead of time. Ask questions such as:[[/p]]

[[ul]]
	[[li]]What data sources do you currently have, and how are you currently using data?[[/li]]
	[[li]]What data do you have and want access to?[[/li]]
	[[li]]What do you wish to get from your data? For example, do you want to learn more about your clients, or are you taking precautionary measures to prevent fraud?[[/li]]
	[[li]]Do you have business objectives in place and do they match your big data strategy?[[/li]]
[[/ul]]

[[p]]Once you have established the purpose of your data, you should create a roadmap that shows the gaps in your business and technology needs. The following six steps should help you use data to drive the needs of your business.[[/p]]

[[p]][[strong]]Top tip:[[/strong]] Use our [[a href="https://digitalmarketinginstitute.com/resources/toolkits/targets-and-kpis-your-essential-toolkit" target="_blank"]]target and KPI toolkit[[/a]] to help you strategize and plan data, helping to set targets for web traffic, transactions and revenue.&nbsp;[[/p]]

[[p]]Figure out how your business intends to collect consumer data. The possibilities are nearly endless.[[/p]]

[[p]]There are several channels for data collection which include:[[/p]]

[[ul]]
	[[li]][[a href="https://digitalmarketinginstitute.com/blog/which-social-media-platforms-should-you-use-for-your-business" target="_blank"]]Social media networks[[/a]], such as Facebook and X[[/li]]
	[[li]]Search engine data, e.g. [[a href="https://digitalmarketinginstitute.com/blog/google-analytics-advanced-features" target="_blank"]]GA4[[/a]][[/li]]
	[[li]]Surveys[[/li]]
	[[li]]Transactional tracking, e.g. past purchases[[/li]]
	[[li]]Lead generation forms[[/li]]
	[[li]]Sign-ups or free trials[[/li]]
	[[li]]Online or website tracking[[/li]]
	[[li]]Customer journey or user observation[[/li]]
[[/ul]]

[[p]]Keep in mind there are different types of data from [[a href="https://digitalmarketinginstitute.com/blog/why-first-party-data-is-more-important-than-ever-and-how-to-use-it" target="_blank"]]first-party[[/a]] (consensual data such as an email address) to third-party data ([[a href="https://digitalmarketinginstitute.com/blog/preparing-for-the-cookie-free-future-in-digital-marketing" target="_blank"]]cookies[[/a]] from external websites).[[/p]]

[[p]]Next, you need to determine the true value of your data. How was the information collected? Information that has been compiled haphazardly may be inaccurate, full of flaws, and worthless.&nbsp;[[/p]]

[[p]]The [[a href="https://www.cloudapps.com/wp-content/uploads/2025/03/State-of-Sales-2025-2-1.pdf" target="_blank"]]&lsquo;State of Sales 2025: Trends, Challenges, and the AIPowered Future&rsquo; report[[/a]] found that data-driven decision-making is hindered by a lack of CRM adoption and ineffective KPI utilization, with 27% of sales reps failing to log essential customer interactions.[[/p]]

[[p]]Therefore, it&rsquo;s crucial to ensure the data you are collecting is accurate and comprehensive&nbsp; before spending time and money to analyze the data in the first place. This will help you determine whether the data will contain any valuable insights. If it doesn&rsquo;t, be sure to collect the data more accurately before moving forward.[[/p]]

[[p]]The majority of modern companies already store a sufficient amount of data regularly.&nbsp;[[/p]]

[[p]]To gain better insights, some questions need to be addressed first:[[/p]]

[[ul]]
	[[li]]How much do you know about your company&rsquo;s data and collection processes?[[/li]]
	[[li]]How frequently is the information updated and where is it stored?[[/li]]
	[[li]]Is the information analyzed regularly?[[/li]]
	[[li]]Are there any security or confidentiality concerns regarding the stored information?[[/li]]
[[/ul]]

[[p]]Gaining answers to these questions will give you an advantage and ensure you better understand your company&rsquo;s current practices &ndash; including compliance with local and international laws such as [[a href="https://digitalmarketinginstitute.com/blog/the-definitive-gdpr-checklist-for-marketers" target="_blank"]]GDPR[[/a]] or [[a href="https://digitalmarketinginstitute.com/blog/get-ready-for-the-california-consumer-privacy-act-ccpa" target="_blank"]]CCPA[[/a]].&nbsp;[[/p]]

[[p]]Additionally, be sure to consult with the team or individual who is responsible for analyzing your company&rsquo;s data; they may have more information to share with you.[[/p]]

[[p]]Storing and analyzing big data can be a huge and expensive process. Great skill and experience are needed to effectively scour through the information and utilize the associated software.[[/p]]

[[p]]According to the [[a href="https://www.bls.gov/ooh/math/operations-research-analysts.htm#tab-6" target="_blank"]]U.S. Bureau of Labor Statistics[[/a]], the demand for operations research analysts is projected to grow 23% from 2021 to 2031, much faster than the average for all occupations. This means that competition for these skills is high.&nbsp;[[/p]]

[[p]]At the same time, many companies are unable to maintain and manage their in-house talent. While it may seem like a good idea to dedicate resources solely to data analytics programs, this might ultimately prove to be a costly mistake.[[/p]]

[[p]]To get the most out of your data, it is important to correlate data analytics and IT technologies. Avoid compartmentalizing! Instead, try to expand your resources across both sectors. Investments in IT infrastructure should coincide with data analytics technologies and vice versa.[[/p]]

[[p]]Once you have learned how to collect accurate data, it is time to carve out insights from the information. [[a href="https://digitalmarketinginstitute.com/blog/data-visualization-tools-tips-for-marketers" target="_blank"]]Data visualization[[/a]] is a key aspect of this process as it gives you the ability to represent the information in a way that&rsquo;s more understandable and allows you to [[a href="https://digitalmarketinginstitute.com/blog/brand-storytelling-in-the-digital-age" target="_blank"]]tell a story[[/a]].[[/p]]

[[p]]In all likelihood, your team will have a few people who are uncomfortable with numbers. To make sure your data is utilized efficiently, you need to display the information&nbsp; visually.[[/p]]

[[p]]The use of certain tools such as Google Charts or Datawrapper makes it possible to transform data into graphs and charts. Charts are easily understandable and will help ensure your team is involved and engaged.[[/p]]

[[p]]Advanced AI platforms can also transform complicated datasets into visual dashboards. Natural language processing integrations even allow you to ask questions like, &ldquo;What was our best-performing campaign last month?&rdquo; and get instant answers.[[/p]]

[[p]]Check out our video walkthrough with expert Clark Boyd to find out [[a href="https://digitalmarketinginstitute.com/resources/videos/walkthrough-using-chatgpt-to-visualize-data" target="_blank"]]&lsquo;How to Use ChatGPT to Visualize Data&rsquo;[[/a]].[[/p]]

[[p]]Having access to big data and being able to analyze it is not useful unless you can translate it into successful actions.&nbsp;[[/p]]

[[p]]Getting the necessary [[a href="https://digitalmarketinginstitute.com/blog/data-visualization-tools-tips-for-marketers" target="_blank"]]tools to analyze data[[/a]] is simply one step in the right direction. Whether the end goal is to increase security or drive profits, you should figure out how to transform data into knowledge to drive business insights.[[/p]]

[[p]]The CEO and senior executive team should be willing to use these business analytics for marketing activities. Customer insights should be incorporated into every decision-making step at all levels, whether it&rsquo;s establishing a new advertising strategy or strategizing elsewhere.&nbsp;[[/p]]

[[p]]Let&rsquo;s take a look at two case studies to learn about leveraging this information to improve and grow your business.[[/p]]

[[p]]You probably know about the [[a href="https://digitalmarketinginstitute.com/blog/the-unstoppable-success-of-netflix" target="_blank"]]unstoppable success of Netflix[[/a]], the streaming platform with over 300 million paid subscribers (Netflix Investors).[[/p]]

[[p]]One of the reasons that Netflix is so successful is related to how it uses big data. By understanding customer needs, the company has one of the lowest churn rates for subscription services, hovering between 1-3% in the last two years &ndash; well below the industry average which is around 5%, reported [[a href="https://www.tvrev.com/news/hooked-on-netflix-analyzing-the-streaming-giants-low-churn-rates" target="_blank"]]TVRev[[/a]].[[/p]]

[[p]]Netflix uses big data to [[a href="https://digitalmarketinginstitute.com/blog/how-to-use-behavioral-psychology-to-drive-marketing-success" target="_blank"]]analyze user behavior[[/a]] and then tailors its product with personalized content. For example, the company collects data such as the time during which their subscribers watch a show, whether it was binge-watched or watched over time.&nbsp;[[/p]]

[[p]]Netflix is planning to push out a major TV app redesign, with a top navigation bar and new recommendation features. It&rsquo;s also experimenting with generative AI and TikTok&ndash;style vertical video clips on mobile devices, according to Fast Company.[[/p]]

[[p]]Another example is mega-retailer, Walmart. With over 245 million customers across the globe in&nbsp; over 10,000 stores, Walmart collects 2.5 petabytes of unstructured data from a million customers every hour, according to [[a href="https://www.projectpro.io/article/how-big-data-analysis-helped-increase-walmarts-sales-turnover/109" target="_blank"]]ProjectPro[[/a]]!&nbsp;[[/p]]

[[p]]The company uses this data in a variety of ways to improve customer service, acquire and retain customers, and drive revenue. In its [[a href="https://digitalmarketinginstitute.com/blog/10-ways-to-maximize-your-ppc-strategy" target="_blank"]]PPC strategy[[/a]], Walmart analyzes 100 million keywords every day to optimize bidding. It also tracks every action such as social media activity, in-store and online purchases, and local events to tap into.[[/p]]

[[p]]Walmart Labs also analyzes every click on the store&rsquo;s website to explore:[[/p]]

[[ul]]
	[[li]]What consumers buy in-store and online[[/li]]
	[[li]]What&rsquo;s trending on X[[/li]]
	[[li]]Local events[[/li]]
	[[li]]How local weather deviations affect buying patterns[[/li]]
[[/ul]]

[[p]]It can be a challenge to understand what data to collect and how to use it to engage customers and drive revenue. DMI&rsquo;s short [[a href="https://digitalmarketinginstitute.com/students/short-courses/data-and-web-analytics" target="_blank"]]data and web analytics course[[/a]] will introduce you to the fundamentals including GA4 and dig into data security and compliance and how to visualize and present data. Get started today to leverage your data.[[/p]]

[[p]]By leveraging [[a href="https://digitalmarketinginstitute.com/blog/ai-in-digital-marketing-the-ultimate-guide" target="_blank"]]artificial intelligence (AI)[[/a]], marketers can move beyond basic reporting to uncover actionable insights that would otherwise be buried in the noise.&nbsp;[[/p]]

[[p]]Here&#39;s some ways you can leverage AI to help with data analysis:[[/p]]

[[p]]AI tools can use [[a href="https://digitalmarketinginstitute.com/blog/the-ultimate-guide-to-marketing-automation" target="_blank"]]automation[[/a]] to process massive datasets much faster than humans. So, platforms with machine learning algorithms can sift through customer data, metrics, and web analytics to uncover patterns, trends, and anomalies without the need for manual labor.[[/p]]

[[p]]AI-powered predictive analytics can help you anticipate what your customers will do next. That could be making a purchase, lead scoring, churn prediction or responding to a specific offer. These insights allow marketers to tailor campaigns, refine messaging, and allocate budgets more effectively.[[/p]]

[[p]]Use AI to analyze customer preferences in real-time to enable hyper-personalized content, recommendations, and product suggestions. This allows marketers to personalize at scale rather than one-to-one efforts that can be time consuming.[[/p]]

[[p]][[a href="https://digitalmarketinginstitute.com/blog/what-are-the-best-ai-and-marketing-automation-tools" target="_blank"]]AI-driven tools[[/a]] can continuously monitor your campaigns and automatically adjust elements like bid strategies, audience targeting, and content variations to maximize ROI. This type of real-time optimization helps marketers achieve better results without constant manual intervention.[[/p]]

[[p]]Watch our webinar on [[a href="https://digitalmarketinginstitute.com/resources/webinars/webinar-build-your-personalized-ai-marketing-assistant" target="_blank"]]&lsquo;Build Your Personalized AI Marketing Assistant&rsquo;[[/a]] for some tips and guidance.&nbsp;[[/p]]

[[p]]To wrap-up, here&rsquo;s a quick checklist for you to refer to that will help ensure that you get the most from your data, in order to get actionable and relevant insights:[[/p]]

[[ul]]
	[[li]]Define KPIs aligned to business goals[[/li]]
	[[li]]Select analytics tools (GA4, BI tools, embedded insights)[[/li]]
	[[li]]Choose analytics type (descriptive &rarr; predictive &rarr; prescriptive)[[/li]]
	[[li]]Visualize and present findings[[/li]]
	[[li]]Build AI into workflows[[/li]]
	[[li]]Monitor performance and refine[[/li]]
[[/ul]]

How to Use Data Analytics to Drive Better Business Insights

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