All about analytics — definition, history, and where it’s headed

Data is everywhere. Each time a customer engages with a brand, that’s more data marketers can use to reach them with more relevant experiences in the future. And here lies the major opportunity — the more that experiences resonate with customers, the more trust and loyalty you can build with them. But to make sense of data in ways that translate into delivering the right experiences, you’ll need analytics. By understanding what analytics is, you can use it to help your own business.

In this article about analytics, you’ll learn:

What is analytics?

Analytics is the process of defining a method to transform data into actionable insights by identifying meaningful trends, making predictions, and working smarter.

As the strategy behind a company’s data use, analytics can change as the brand matures. This is especially true in today’s digital world, where data processing happens faster than ever. For example, artificial intelligence (AI) and machine learning (ML) provide valuable insights in real time. Additionally, using the right data platform will allow your team to share their data and insights with the rest of the company. That way, everyone can stay on the same page about how the business is interacting with customers and how insights align to business goals.

Why is analytics important?

Analytics is a valuable process for piecing together your customer data into a rich story that you can act on.

Get a full picture of your data

Brands need to reach customers in the ways they’re most likely to interact, but customers are always switching between different channels. They might explore a website, get distracted by social media, then later switch to using a mobile app. Brands that use analytics to make sense of all their data in one unified platform can understand their customers better and are able to deliver more seamless experiences across these channels.

Invest in the right touchpoints

Brands that want to reach their customers in the right ways need to invest in content across different touchpoints. But with so many, it can be difficult to know which to invest in the most. Analytics can help identify which channels are making the most impact so that businesses can adjust their strategies and use resources more efficiently.

Uncover emerging trends

Customers’ needs and behaviors are constantly changing. With the help of predictive tools powered by AI and ML, brands can identify patterns even in the most extensive data sources. That way, they can quickly get ahead of emerging trends with products and experiences that match what’s predicted to be the most relevant.

Build more intelligent websites

A brand’s website is often central to the digital experiences they deliver. It’s where customers can learn more about products, gather information about specific topics, and connect with experts. All these interactions are gathered as data — like customer pathing, traffic sources, content effectiveness, and video engagement — that the brand can then use to target personalized experiences to that customer. By integrating your website with a powerful data platform, your brand can harness these insights and act on them quickly across channels.

The history of analytics

The origin of analytics extends far back into history. For example, it’s believed that statistics, a form of analytics, was used to build the pyramids in Ancient Egypt. Societies throughout history have collected data to measure things like population growth that informed how they would plan their cities.

When computers were invented, data and analytics looked very different from today. In the earliest stages, basic “tabulating machines” processed data recorded on punch cards. Even as computers became more complex, the data was still clunky to work with. It was stored in physical locations with a limited memory. If companies wanted to use analytics to gather insights from their data, it was a manual process that took many resources to achieve basic information.

As the internet brought customers online, big data emerged. With it, the amount of data that organizations could access about customers blossomed. Data mining became a way to discover patterns within large datasets. Cloud computing allowed businesses to flexibly store all their data in a remote location and make it accessible to multiple users simultaneously. Businesses could use the insights efficiently gathered from large amounts of data to inform their business decisions.

Analytics today

For companies looking to make sense of their data, analytics have come a long way. Not only is there more data than ever, but there is also more advanced technology to turn that data into actionable insights. Instead of using analytics to understand just what had happened in the past, businesses can also use it to predict what will happen in the future. For example, data analysts and data scientists use programming languages like R and python to develop ML algorithms. These algorithms enable businesses to make smarter predictions that unlock hidden opportunities. They also allow teams to work with large, unified datasets and create complex visualizations that help teams like marketers and business strategists easily make sense of the insights.

Instead of data being stored in physical locations on a company’s property, data warehouses allow massive amounts of it to be stored in the cloud. This not only allows brands to harness more information about their customers’ needs and behaviors, but it also frees up IT resources so that they can focus on more complex technical needs, like building AI and ML algorithms. Data warehouses also allow brands to flexibly manage the amount of data they are storing, which is useful during high volume times like holidays or seasonal sale periods.

Because data now comes from multiple channels, it can easily become siloed. One team may have access to the data for one set of products or channels, while another only has it for certain geographics. To avoid this, data platforms unify customer data from across an organization. These platforms avoid situations where data is stored in duplicate locations or accidentally left out of crucial analyses. Instead, they create one complete view of customers that can be updated in real time as new data flows in.

How will analytics change in the future?

As analytics evolves, it will become more accessible to everyone within an organization. Because data can be unified into one powerful platform, it can be automatically updated in real time instead of teams relying on analysts to bring in the most up-to-date sources. While a unified data platform still takes technical expertise to build and maintain, desktop business analytics tools also now allow less technical teams to self-service the reports and data visualizations they need so that IT teams can focus on the more complex data processes.

Analytics also has an ongoing need to address privacy, especially with legislation like the General Data Protection Regulation (GDPR) in Europe and the California privacy law. With the ever-increasing number of channels, there are going to be brand new datasets that you'll need to securely integrate with existing data. For example, alongside web and mobile channels, brand need to consider channels like new social media platforms, augmented reality, and virtual reality spaces.

Automation is also a major innovation for analytics. As huge amounts of data flow into a unified platform, automated processes can clean that data of inconsistencies like duplicates and incomplete sources. From there, AI and ML tools can automatically analyze and produce insights that teams across the organization can access and use.

Get started with analytics

Data is only as valuable as the insights you can gather from it. Analytics is a valuable process for transforming data from a huge source of information into a clear story that you can use to build and deliver better experiences for your customers.

Having strong analytics allows your business to create a single view of your data that anyone across the organization can access. That way, you can identify patterns and predict upcoming trends with more informed insights. Analytics also helps uncover how experiences are performing across channels so that you can make better decisions about where to invest your resources to create a more seamless customer journey.

While we’ve covered analytics as a broad topic, there are multiple types to explore further. For example, data analytics is the process of examining large amounts of qualitative and quantitative data, while mobile analytics focuses specifically on gaining insights about customer behaviors on mobile apps and devices.

Adobe can help

Bringing analytics into your organization takes having the right technology. Adobe Analytics empowers you to make the most of your data through in-depth analysis, versatile reporting, and predictive intelligence. That way, you can understand your customers better and deliver more impactful experiences.

To learn more, watch the Adobe Analytics overview video or request a product tour.