| June 2, 2019

[Guide] What Is Data-Driven Marketing & Why Should Marketers Care?

Alexandra Savidge

Alexandra is Head of Marketing at DAP. She uses her background in digital marketing, UX, content and e-commerce to create... Alexandra is Head of Marketing at DAP. She uses her background in digital marketing, UX, content and e-commerce to create impactful digital experiences for our clients.

Data-driven marketing is a set of techniques and tactics that leverages massive amounts of data to create effective marketing processes, targeting specific demographics and user groups at an individual level. This data can provide fantastic insights into consumer behavior, and taking advantage of it can be of vital importance to your company.


Data is increasingly important for elite marketers and has the potential to become the most valuable resource in marketing. Big data is taken directly from customer interactions and this is precisely the kind of information that can help refine, enhance and improve any marketing strategy.


In other words, it’s just as important to understand and organize this information, while deploying the right marketing tools and strategies to make the most of the data.


But this only begins to explain why data-driven marketing is so important.


Think of this article as a crash course into everything there is to know about data-driven marketing. Here’s what this article will cover:


  • History of data-driven marketing
  • Personalization and data-driven marketing
  • Benefits of a data-driven marketing Approach
  • Challenges with data-driven marketing
  • Data-driven marketing pillars and foundational blocks
  • Tangible examples of data-driven marketing


Are you excited to learn more about data-driven marketing? Then read along!


Interesting Facts & Stats About Data-Driven Marketing

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Data-driven marketing is tasked with enhancing the customer experience. It also creates automated campaigns which allow marketers to focus their time on the creative side of the business.


For example, data-driven marketing is suitable for targeting messages or offers, and studies show that most professional marketers use this process to enhance ROI measurability.


More specifically, 44% of marketers stated that increasing revenue was their main objective and according to CMO, 67% of marketers believe that the speed and accuracy are the primary benefit of data-driven marketing.


But is every other marketer not taking this same approach?


In fact, they are. A survey by Forbes recently discovered that 88% of marketers use third parties to extract big data for the purpose of marketing.


In this survey, it was also concluded that companies who deploy data-driven marketing are six times more likely to remain profitable year-over-year.


As a result, more and more marketers are turning to data in order to make decisions on how they should engage with their target audience. According to the statistics above, this gives marketers a clear advantage over the competition along with an opportunity to increase profitability.


That being said, in order to know why this process is so effective, we should look at the history and evolution of data-driven marketing:


The History of Data Driven Marketing

Customer Relationship Management (CRM) is largely responsible for the inception of data-driven marketing. This was the first system that gathered customer data for this purpose.


In most instances, data collected in a CRM was used to reach out to potential customers through phone calls or direct mail. In the ’70s and ’80s, records with customer names, addresses and phone numbers were stored in metal cabinets and as time passed, early adopters began to understand that customers could be profiled and targeted to increase sales in the future.


During the 1980s, marketers started to realize how this data could be used to establish personal relationships with customers, while banks and insurance companies were the first to take note.


Stepping into the 1990s, database marketing was commonly used for automating parts of the sales process, the basis for the modern CRM framework. Most sales teams were suddenly focused on collecting stats around user demographics for purposes of lead generation, deal tracking and opportunity management.


However, toward the end of the 1990s, cloud services took this process to the next level and provided an affordable way for businesses to acquire top-of-the-line CRM systems. When major players like Amazon started to influence the cloud space, cloud-based services became a mainstream practice for companies to use to collect and interpret user data for marketing purposes.


With this in mind, it was soon obvious that marketing was more effective when customers were exposed to personalized messages – to visual and audio stimuli they could relate to.


In addition, the popularity of targeted adverts took off and this enabled marketers to engage with customers in a more relevant and meaningful way.


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In more recent times, social media has  also become increasingly reliant on data-driven marketing in order to establish behavioral attributes and create customer profiles. What’s more, data-driven marketing  systems can help fine-tune content marketing and engage customers at a personal level.


Personalization In Data-Driven Marketing

Personalization is a complex aspect of data-driven marketing and needs to take into account various factors including data, creative, and media. In order to create a truly personalized experience, marketers need to focus much more intently on customer trends and behavior, along with the actual advert and channel of communication.


Marketing channels have become more complex. Different channels like videos, display ads, social media and emails each require different types of marketing creatives. For this reason, even a single creative can come in various formats. Data has not simplified marketing but this complex approach can produce better results.


But can marketers remain creative in the face of so much data?


Marketers need to understand that any fixation on data is likely to be at the expense of creativity. In this sense, the need for creativity is more important than ever and deploying smart tactics is the solution.


For example, Krispy Kreme ran a campaign in recent times called “Office hero” in which they targeted people who buy doughnuts on their lunch break for everyone at work. As part of this data-driven approach, marketers used company data to identify the location of this target market majority which happened to be London.


Another example is when the Three mobile network created a television ad which featured a dancing Shetland pony. Three network devised this ad based on a combination of data and creativity to produce one of the most viral ad videos in recent times.


How Beneficial Is A Data-Driven Marketing Approach?

People discussing the results displayed by a bar graph on a laptop.

Data-driven marketing enables marketers to identify what works, what doesn’t and how to optimize marketing efforts to include the most effective tactics. For this reason, the process allows for faster decision-making and better insights into what the customer wants from the brand.


Here are just a few benefits of data-driven marketing:


Time and Clarity – With an immense database in hand, marketers can quickly filter through critical data and determine the most relevant and accurate information on which to take action.


Segmentation – Data-driven marketing can also help to segment a target market which helps to ensure that these personalized messages are falling in the right place.


Personalization – Personalized marketing can help brands connect with the right target markets and deliver more personal and meaningful messages. Needless to say, this helps provide an improved user experience, while placing relevant products or services in front of the customer.


Customer Experience – Many marketers use data-driven marketing to improve the user experience via user feedback forms or customer surveys to provide even more insights into what areas need improvement.


Product Development – Data-driven marketing can significantly reduce the risk of product failure, while helping businesses better understand what consumers would like to see in future products.


Multi-Channel – Big data can be used to reach out across multiple channels and communicate the right message through adverts and content marketing.


Challenges with Data Driven Marketing

At the same time, you should know that there are some challenges when it comes to data-driven marketing:


Locating the Right Data – Data is everywhere and filtering through an endless sea of information is very time-consuming. For this reason, it’s important to make an informed decision in terms of what data will be most effective or beneficial for data-driven marketing.


Asking the Right Questions – Having data is easy. Turning data into insights – not so much. You also need to ask the right questions about the data you have access to. After all, asking the wrong questions will inevitably lead to irrelevant answers and a bunch of time wasted.


Normalizing Big Data – It’s important to remember that no two customers are the same and data is always very different from one individual to the next. Normalization can separate this data into two or more data sets and define the relationships between these various data points.


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Interpreting data – As mentioned previously, you simply must understand the data in order to know how this information can be used effectively. To this end, finding relevant information is merely the first step in the process.


Gathering Real-time Data – You will need the right marketing tools and experience to gather and analyze big data. Insight is everything for data-driven marketing and tools are necessary for acting on this insight.


Linking Data – If you can link data to form a cohesive ‘big-picture’, this will enable you to determine just how much success you can expect from the strategy. On the other hand, if certain data cannot be linked to other data points, there’s a good chance that the information is irrelevant and not beneficial to the strategy.


Data Driven Marketing Pillars and Foundational Blocks

People looking over their Data-driven Marketing plan.

Campaign Management

Campaign management is essential for pulling everything together and ensuring every aspect of a specific marketing campaign is on track for success. At the same time, experience and knowledge will only go so far and marketing tools are necessary for ensuring the campaign runs smoothly.


As part of the HubSpot marketing software, marketers can access live chat or community support but the range of tools available is quite staggering. From social media marketing and creating landing pages to SEO and content marketing management, this is essentially a one-stop-shop for managing a data-driven campaign.


On the other hand, you might want to check out Curata which is mainly focused on helping small to medium-sized businesses. More specifically, Curata provides a well-rounded system which includes strategy, production and analysis tools for data-driven campaign management.


Unified Tracking

For a successful data-driven strategy, marketers need to collect data throughout the campaign and use performance metrics to keep track of progress. Tracking progress enables marketers to know what may or may not be working so well, this also provides insight with regard to user behavior.


With these insights in hand, it’s possible to refine the target audience and make the campaign as efficient as possible. After all, identifying high performing content is a great indication in terms of what type of content should be emphasized or reproduced in the future. Over time, constant effort should create a well-oiled machine and a marketing strategy that is much more likely to succeed.


For example, if the website is not converting enough leads, Whoisvisiting is a marketing tool that can help marketers identify the best campaign channel for increasing revenue. However, even just knowing precisely who might be visiting a website is a great advantage, for this enables companies to identify products or services that will be of most interest to these individuals.


Needless to say, this is just one example. Measuring the progress of a campaign is crucial for removing unnecessary processes and fine-tuning every other aspect of the campaign.



At a time when online users have access to so many choices, competition is fierce in each and every industry. For this reason, it’s essential to stay ahead of the curve and identify trends as they happen, while ensuring that you properly understand the behavior and needs of the target market. To do that, you need to leverage user analytics.


Google Analytics is the most powerful marketing tool for assessing these analytics and leveraging statistics to generate new ideas and more effective strategies (check out our quick crash course on this powerful tool). In this respect, insights from analytics can better prepare marketers for future trends and enable better decision-making going forward.


However, there are many useful tools like Mixpanel or Amplitude  that can make an audience even more powerful for data-driven marketers. With their unique methodologies, these analytics solutions are especially good at analyzing the quality and size of your existing audience.


Whether you need to improve user experience, increase revenue or monitor the movement of users online, Google Analytics is certainly the best tool for any data-driven marketing strategy.



Reports can have a transformational impact on a business. Simply put, producing a logical output from big data enables marketers to make informed decisions and create powerful marketing campaigns.


While there are many reporting options out there, DataHero is a popular data-driven marketing tool which enables marketers to put all the most important data together and display this data in chart form.


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For many businesses, refining a campaign is most often the most productive way to make progress and a much better option than starting from scratch. Collecting data can be a very efficient way of refining your campaigns.


Whether this refers to retargeting customers or improving content, optimization is also one of the most affordable ways to enhance a campaign. For instance, Optimizely provides a variety of optimization tools that performs A/B tests on websites and devices. As a result, marketers can use this tool to check what content is performing well or even what versions of an experience is more likely to drive more conversions.


On the other hand, SEO agencies offer a range of services that can optimize existing content and increase traffic, sales and profitability in general.


But what does data-driven marketing actually look like?


Some Examples of Data-Driven Marketing

A person looking at a computer while the words "Data-driven Marketing" are displayed.

Re-targeting Previous Customers

Re-targeting is increasingly effective for data-driven marketing — this essentially means that when a customer makes a purchase from a website, marketers can reach out to these customers again with similar deals.


Similarly, you can take this same approach with previous visitors and use adverts to re-target these users in order to entice them back to your website.


Moreover,  retaining customers and selling to them is often easier than converting new leads.


Highly Targeted Advertising

Social media is renowned for having an especially high rate of interaction. Creating ads based on big data is a powerful way to take advantage of social channels such as Instagram and Facebook.


With this in mind, you can encourage your audience to sign up or ‘learn more’. This exchange will also provide even more critical data which you can feed into your existing database.


Investing in Paid Search

When you know the most popular keywords for your target market, you can leverage this information through paid-search and position your website at the top of multiple search results. As you may know, paid-search is incredibly effective but the data is key to driving the right traffic at the right time.


Email Campaigns

In spite of what you might read elsewhere, email marketing is alive and well. You can use big data to segment a target audience and create a personalized email for each group. For the most part, this process is then fully automated but you can also optimize these messages to interact with customers on a one-to-one basis.


All Is Not Great Though with Data Driven Marketing

Okay, now that we know how amazing data can be, let’s consider a potential problem with data-driven marketing – it’s not fool proof. In other words, simply having access to data is not enough to make decisions.


You see, data driven marketing often looks at what worked in the past and then uses this information to create new campaigns. However, consumer behavior is always changing and just because something happened in the past, does not mean that something will happen again.


In addition, data can help marketers identify certain patterns but experts will know that this information is not enough to establish why customers do what they do. Understanding consumer behavior is incredibly important and this data is simply unable to explain the reason ‘why’.


Meanwhile, data-driven marketing has a tendency to kill creativity and this is often the fuel that drives the most successful marketing campaigns. In fact, you could say that marketing is part science and part creativity which implies a fine balance is needed to ensure that a data-driven campaign is effective and successful.


Final Thoughts

Successful data-driven marketing comes from fine-tuning relevant data and taking a creative approach in terms of reaching out to customers. At a time when marketers are increasingly reliant on consumer behavior to predict future trends, this is also the most accurate solution for a successful campaign.


In many ways, data-driven marketing is needed due to the changing expectations and progressive needs of customers. However, the many challenges and intricacies of this approach need to be addressed and only then, can you create a robust and truly effective marketing strategy.

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