It has become a truism that data is the oil of the 21st century. In the course of advancing digitization, more and more data are being generated: on the one hand by the online behavior of consumers, on the other by products increasingly equipped with sensors (Internet of Things). But what exactly is meant by Big Data and how can the vast amount of data be used in marketing?
Table of contents
- How Big Data is Transforming Marketing Strategies
- What is Big Data?
- Beyond Technology: Building a Big Data-Ready Organization
- The Benefits of Big Data
- Use Cases of Big Data in Marketing
- How to Get Started with Big Data in Marketing
- Essential Tools for Big Data Marketing
- Our service
How Big Data is Transforming Marketing Strategies
Data has arrived in marketing, but is not yet part of everyday practice in the marketing departments of all companies. Most of them already have access to a great variety of data, including their own customer data, data generated via various communication channels such as websites or social media channels, second- and third-party data, and product usage data (Internet of Things).
Many companies already use marketing automation software to analyze customer behavior in real-time and deliver relevant content to (potential) customers on the basis of their analyzes. Customers who have registered for a brand's newsletter, for example, and whose online behavior (clicks) indicates that they are interested in a particular product category automatically receive corresponding offers via newsletters or display advertising.
The benefit speaks for itself: the incoming data enable a 360° view of the customer. This enables more precise segmentation and predictions of future customer behavior. Marketing hence becomes much more targeted and sales will increase.
The use of data is now a matter of course in marketing. Many companies, however, only scratch the surface of what Big Data can really do for their marketing. Big Data does not just mean data amounts as such. There are other aspects that make Data really "big".
What is Big Data?
The consumer has become an incessant data generator through the use of digital technologies. This includes structured (master data, transaction data etc.) as well as increasingly unstructured data (content in social media, forums, pictures, videos, etc.). There are three dimensions that make data Big Data, the so-called three Vs: volume, velocity, and variety. Big Data is therefore an enormous amount of data collected and analyzed in real time. This data comes from a large number of sources and has different formats (structured vs. unstructured).
In addition, two other factors play a significant role when it comes to using Big Data profitably: validity and value. This applies to the quality of the data records and whether these can create a value for the company and its marketing activities.
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Beyond Technology: Building a Big Data-Ready Organization
"Traditional" software is not able to analyze Big Data. Therefore, companies must create a platform that allows them to store and analyze data coming from different sources (variety) in large quantities (volume) in real-time (velocity).
In addition to this technological solution, which is provided by various suppliers, the organizational structure is also important. Big Data needs employees who know how to mine valuable information and ultimately translate it into appropriate strategies. Moreover, an agile organizational structure that makes it possible to implement new data-based strategies is required as well. It is ultimately useless to know where an increased demand for a product or service is to be expected if a business lacks the ability to act on this insight.
The Benefits of Big Data
According to the Big Data Report of the University of Reutlingen, businesses pursue a wide range of interests with Big Data, including the analysis of customer needs, improving customer satisfaction, improving customer loyalty or developing new services. It is therefore clear that Big Data can be used to address customer needs in a targeted manner, while at the same time developing new products and services based on data-based insights. Put simply, it is about gaining competitive advantages.
Never have there been more opportunities to gain new insights. Sooner or later, Big Data Consumer Analytics will replace methods of traditional market research, such as customer surveys, as they are both time-consuming and time-delayed and hence deliver less comprehensive insights.
For a long time, only large companies had the means to profit from the flood of data of the 21st century. An early example of the successful use of Big Data Consumer Analytics came in 2012: using comprehensive data analysis, Target knew whether a consumer is pregnant – oftentimes before they had the chance to tell their family. Using their insights, the company send out highly targeted offers to the pregnant women. This example caused quite the stir back then, but has now almost been forgotten. One of the reasons for this is the fact that such examples of forward-looking marketing are now becoming more commonplace.
The already mentioned Big Data Report shows that a rising number of companies have started to look into Big Data and have launched the first projects. The time to act is now.
Use Cases of Big Data in Marketing
Big Data isn’t just a buzzword — it’s a powerful tool that’s already transforming how marketers work. Here are some real-world ways businesses are using it today:
- Customer Journey Mapping
Big Data helps track every step a customer takes, from the first website visit to purchase. This gives marketers a clearer picture of what works — and what doesn’t.
Result: Smarter budget allocation and better conversion rates. - Predictive Personalization
By analyzing behavior patterns, companies can predict what a customer might want next and tailor offers just for them.
Result: Up to 20% increase in engagement and click-through rates. - Dynamic Pricing
Retailers use real-time data like demand, competition, and seasonality to adjust prices on the fly.
Result: Improved profit margins and sales volume. - Campaign Optimization
Big Data enables A/B testing at scale, showing which messages or channels perform best — fast.
Result: More efficient campaigns with higher ROI. - Churn Prediction (Great for SMEs!)
Even small businesses can use data to spot early signs a customer might leave — and act before it’s too late.
Result: Better retention and lower acquisition costs.
How to Get Started with Big Data in Marketing
Getting started with Big Data doesn’t have to be overwhelming. Here’s a simple roadmap:
- Audit Your Current Data
Look at the data you already collect — from your website, CRM, social media, and email tools. - Define Clear Objectives
What do you want to achieve? Better customer insights? Higher conversion rates? Start with focused goals. - Choose the Right Tools
For small and mid-sized businesses, tools like Google Analytics 4, HubSpot, or affordable customer data platforms (CDPs) offer powerful features without the heavy investment. - Build a Cross-Functional Team
Bring together marketing, IT, and data-savvy staff. Collaboration is key to turning insights into action.
Starting small is better than not starting at all.
Need help building your data strategy? We’re here to support you — from tool selection to implementation.
Essential Tools for Big Data Marketing
Big Data only becomes powerful when you can actually use it. That’s where the right tools come in — helping marketers collect, analyze, and act on insights in real time. Here are some go-to platforms grouped by function:
| Category | Tool | Description |
|---|---|---|
| Customer Analytics | Google Analytics 4 (GA4) | Free and ideal for SMEs; great for web and app tracking. |
| Customer Analytics | Adobe Analytics | Advanced and customizable, best for enterprise-level tracking. |
| Marketing Automation | HubSpot | Easy to use, with built-in CRM and automation; great for smaller teams. |
| Marketing Automation | Salesforce Marketing Cloud | Enterprise-grade with deep personalization features. |
| Customer Data Platforms (CDPs) | Segment | Strong integrations, great for unifying customer data. |
| Customer Data Platforms (CDPs) | Tealium | Ideal for privacy-first and real-time data needs. |
| Visualization & BI | Power BI | Affordable, great for Microsoft environments. |
| Visualization & BI | Tableau | Powerful and flexible, best for in-depth data visualization. |
| Visualization & BI | Google Data Studio | Cloud-based tool for interactive dashboards; integrates well with Google services. |
✅ Quick Tip: A solid starter stack for SMBs could be GA4 + HubSpot + Google Data Studio — simple, scalable, and effective.
Our service
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Whether you're just starting out or looking to scale your existing data strategy, we tailor our solutions to fit your goals and resources. Let’s turn your data into real business results.
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