Mastering data-driven marketing: How to make data the foundation of your marketing strategy

Marketing teams everywhere have amassed (and continue to gather) unfathomable volumes of data on their prospects and customers. But not all marketing teams are effectively leveraging that data to drive growth—and that’s a big mistake.

“Companies that effectively use analytics in service of marketing and sales performance are 1.5 times more likely to achieve above-average growth rates than their peers,” found research by McKinsey. “If outsized growth is the holy grail, adept use of commercial analytics is one clear way to get there, fast.” Yet, while “every company recognizes the power of data,” writes the Harvard Business Review, “most struggle to unlock its full potential.”  

“The problems start at the beginning of the process, when many companies struggle to identify goals for their analytics programs, such as preventing churn or increasing cross-sells,” continues McKinsey. “As a result, while every company has significant volumes of data, many […] companies lack the capabilities to translate data into relevant, usable insights that help them to sell more effectively by improving their understanding of their customers’ experiences, needs, and triggers.”

That begs the question: How do you build a data-driven marketing strategy that gets results?

In this comprehensive guide, we’ll walk you through building a data-driven marketing strategy from the ground up, from deciding what data you need to how to collect and connect it; how to analyze your data; the benefits of a data-driven marketing approach; common challenges and how to overcome them; and finally,  the future of data and marketing and how to prepare for it.

What is data-driven marketing?

Let’s start at the very beginning: What exactly is data-driven marketing? Essentially, it is when marketing teams use data and analytics to guide the direction of their marketing activities, analyze the results, and optimize or pivot their strategy when necessary.

In a traditional marketing approach, marketers rely on qualitative research, assumptions, and gut instincts to guide their strategy. Now that so much marketing takes place online, allowing marketers to gather vast amounts of data on their customers' preferences and behavior, marketers can use facts and figures as the basis of their marketing strategies and take the guesswork out of their approach. 

That’s not to say that marketers should abandon hunches altogether: the most powerful marketing strategies today are driven by a combination of creativity and data. “The most successful CMOs are deftly using the precision and rigor of analytics to anticipate and satisfy customer needs, guided by purpose and energized with creative approaches,” notes McKinsey.

What are the different types of data used in marketing?

Getting your head around the sources of data and types of data is an essential starting point for any marketing team looking to get started with a data-driven marketing strategy.

Sources of data for marketers

• Zero-party data: Zero-party data is information that individuals willingly and explicitly hand over to a business. It includes preferences, survey responses, feedback, and other data shared directly by the data subject. Zero-party data is considered the most valuable data, because it comes directly from the source, offering accurate insights into individual preferences and intentions.

• First-party data: First-party data is data collected by an organization directly from its own interactions with customers or users. This data is generated through customer interactions with a company's website, app, products, or services. It’s highly reliable and trustworthy, as it comes directly from your business's own interactions with your audience.

• Second-party data: Second-party data is essentially someone else's first-party data, which is shared or sold to another organization. it involves a direct data-sharing partnership between two entities. This data can be valuable when two businesses share similar target audiences, and it can be used for better audience targeting and insights.

• Third-party data: Third-party data is collected and aggregated by external sources, such as data brokers, without direct involvement from the organization using it. This data can include demographic, behavioral, or interest-based information. Third-party data is often less accurate than first-party data and may pose privacy and quality concerns, but it can be useful for expanding audience reach and targeting.

Types of data

In this day and age, the types of data you can collect on your customers are practically endless (as long as you’re complying with privacy legislation—see below for more on that), but some of the key data points marketers should focus on:

• Demographic data: Information about customers' basic characteristics that are relevant to your product or service, such as their role within a business or 

• Geographic data: data related to customers' location, including their address, city, state, country, and geographic preferences.

• Psychographic data: insights into customers' lifestyles, values, interests, hobbies, and personality traits. This helps marketers understand their motivations and preferences.

• Behavioral data: Information about how customers interact with your products, services, and marketing channels. This can include purchase history, website visits, app usage, and engagement metrics.

• Transactional data: details about customer transactions, such as order history, purchase frequency, transaction amount, and payment methods used.

How to implement a data-driven marketing strategy

Approach implementing a data-driven marketing strategy as you would any other business strategy: with care and consideration. “A critical yet often underestimated aspect of data-driven marketing is developing a long-term strategy,” says Riva Jeane May Caburog, a PR/Media Coordinator for law firm Nadrich & Cohen.

“You can only optimize data once you have a clear vision of your overarching business goals. This will serve as the foundation for knowing what data points are valuable, allowing you to see past short-term needs while anticipating data evolution over time.”

Here’s a five-step guide to developing and implementing a data-driven marketing strategy in your business:

1. Figure out what you want to achieve with your data first

How do you know what data to collect? “Companies should do two things to harness the power of analytics in their marketing functions. First, rather than create data and then decide what to do with it, firms should decide what to do first, and then which data they need to do it,” advises the Harvard Business Review. The publication suggests that marketing leaders “choose metrics with care”, making it clear what they want to measure and the metrics they expect their employees to use.

Marketer Mia Comic Instrumentl agrees. “My advice would be to establish clear, specific goals. What exactly do you hope to achieve with the data? Are you looking to increase your customer base, improve customer experience, or maybe you’re seeking to launch a new product? Clear goals will help you identify what kind of data you need to collect,” says Comic. “Moreover, always strive to collect quality over quantity of data. More data is not always better. What matters is having the right data that aligns with your objectives.”

The Harvard Business Review notes that, often, “marketers invest countless hours collecting a sea of data without a clear strategy for harnessing that data to drive decisions. That leads to mental fatigue and a tendency to revert to assumption-based decision-making. Our research has found that nearly a third (31%) of marketers say they face the challenge of “too much data to analyze” when optimizing ad performance. They’re swamped,” the publication notes. “To get back on track, start with the simplest dataset needed to make an informed business decision and build a virtuous feedback loop between data, insight, and action.”

A report by McKinsey on those companies that are successfully harnessing data for growth concurred. “Creating moments that are meaningful for customers requires analytical horsepower and precision to discover customer intentions, interests, and unmet needs. At a time when companies are generating massive quantities of data, however, purpose serves as the anchor for marketers to determine which insights matter most and to focus their efforts there.” 

2. Collect, connect, and clean up your data

We’ve said it before and we’ll say it again—most companies are not lacking in data. In fact, they’re overflowing with it. But once you’ve established what you want to measure and what you want to achieve with your data,  it becomes easier to sort the wheat from the chaff. “Today, there are countless micro-moments involved in the digital path to purchase, and the most significant moments of truth may not be what marketers expect,” writes the Harvard Business Review. “The moments in the buying process that influence the customer’s decision to purchase, and in turn influence revenue, should be analyzed, A/B tested, and optimized.” 

That data likely lives in different places and is owned by different teams, from CRMs to website analytics tools to marketing automation platforms. When your data is in silos, it’s incredibly difficult to maintain structural integrity and consistency across every data set. This means that even after you go through a lengthy process to get the data (ticket to your data analyst, SQL query, CSV download…) you’ll have a bunch of CSV files that can’t be easily combined. And even when you do the work to combine your files and draw your insights, there’s a high likelihood you’re looking at inaccurate or incomplete data. 

You can put an end to data silos by adding a customer data platform (CDP) to your tech stack. A CDP will bring data from marketing, sales, product, operations, finance, and support together to help your team find the data they need when they need it. When looking for a CDP to put an end to data silos, remember that your primary goal is accessibility to data and the ability to find the data you need. Your CDP should be your central source of truth for all departments across the business. 

It’s likely you’ll need to clean up your data, too. The thing about data is that, like the human beings it is connected to, it doesn’t remain stagnant and if it is not updated, then over time it can become essentially useless, which is where data enrichment comes in. The right tool can crawl the internet in search of data to keep your customer information updated. It takes the mundane task of researching customers and updating their profiles, or continuously asking customers to update their profiles themselves, and automates it all. 

“Focus on the quality of your data. Not all data is valuable, and raw data is not often “not fit for business,” says Ray Fernandez, Content and Communication Specialist for Biz Report. “Any data that is not updated, has errors in formatting, is incomplete, or has been gathered without consent puts a campaign at risk. “The last thing you want to do is alienate the consumer because of how you managed their data or someone else's, or have your campaign fail because you used useless data.”

3. Improve your team’s data capabilities

Data is only useful if your team knows how to operationalize it, so it’s important that once your team has access to the data they need, they understand how to use and analyze it. “Lack of experience in working with data is a common challenge. Most people need help to effectively analyze data or draw correct conclusions based on it. They lack experience analyzing quantitative data, have never used data visualization tools before, or cannot verify when data leads them into traps,” says Tomasz Adamski, Technical SEO Specialist at ePassportPhoto.

“The team delegated for the analysis should have interdisciplinary competencies and a willingness to learn. Team members should have basic statistical and analytical competencies and knowledge of the processes taking place in the company at every stage of sales. Hence, a good team for working with data should consist of several people who analyze the collected data based on real processes taking place on the market and in a given company.” 

In his guide to building a data-driven culture, David Waller says businesses should “use analytics to help employees, not just customers”. It’s easy to forget the potential role of data fluency in making employees happier,” he says. “But if the immediate goals directly benefit them — by saving time, helping avoid rework, or fetching frequently-needed information — then a chore becomes a choice.“

Pernod Ricard North America CEO Ann Mukherjee says building a data-driven culture starts at the top. “The CMO has to be a jack-of-all-trades. They don’t have to be a perfect expert when it comes to technology but must understand technology to stand side by side with the CTO and understand data architecture,” says Mukherjee. “In today’s world of analytics, the delivery of mass-personalized content requires the CMO to understand martech, to understand how data flows in the company and how to deliver that across multiple systems.”

4. Set up your reporting

Setting up your reporting is the final step in crafting a data-driven marketing strategy, ensuring that you can effectively monitor the data essential for assessing and optimizing your performance to make decisions firmly grounded in data. "I love having an overall marketing team dashboard—it’s something the marketing team can rally around and also something you can easily share with your executive team to prove the value of your projects,” says Kiley Sheehy, Marketing Operations Consultant.

Kiley recommends a strategic approach to setting up your reporting: begin by visualizing your end goal—the dashboard you aspire to have—and then work backward to determine the steps required to construct it. As with collecting your data, it’s important to ensure that you have the right tools in place for creating your reports and dashboards. Ideally, your reporting infrastructure should be integrated within your CDP and marketing automation to offer a single source of truth. Many CDPs and marketing platforms provide readymade report templates you can use, covering everything from campaign attribution to open rates.

Lastly, make sure your reporting is accessible to all relevant stakeholders, as per Kiley's advice: "Setting up a clear marketing dashboard makes your value clear—it gives executives a visual representation of what you’re working on and how your marketing activities are moving you closer to that goal."

By granting visibility to everyone who needs it, you not only communicate your team's contributions effectively but also empower your organization to align with its objectives through data-driven insights. “Marketing leaders are 1.6X as likely as their mainstream counterparts to strongly agree that open access to data leads to higher business performance,” notes Google.

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Benefits of data-driven marketing

“Nearly two-thirds of leading marketers say that decisions made with data are superior to those based on gut instinct,” according to research by Google. How? Data-driven marketing can improve the conversions and return on investment (ROI) of your marketing efforts through better targeting and messaging; better help you allocate (and get) resources; and, ultimately, prove the value the marketing team provides the business. 

Improved targeting and personalization

Data allows you to know to understand your customers inside in out, and target them with the right message, at the right time, at the right place, and increase the likelihood of conversion.

“The addition of granular data and analytics can unleash creativity more effectively to drive deeply personalized customer interactions using iterative, test-and-learn approaches. The ability to serve up exactly what the customers want, when they want it, and in their choice of channel, is rapidly becoming a baseline customer expectation. It requires real-time data and analytics to create customized pricing and promotion,”  notes McKinsey.

“Some leading companies are developing new levels of understanding by building systems that can pool and analyze structured and unstructured data, algorithms that can identify behavioral patterns and customer propensity, and analytics capabilities to feed that information into dashboards. Those companies’ customer-data platforms can connect a single customer across devices, cookies, and ad networks, and enable real-time campaign execution across touchpoints and channels.”

Marketer Marc Bjerring, co-founder at Spivo, agrees. “Data is absolutely pivotal in shaping and enhancing our marketing strategy, primarily because it provides invaluable insights into audience preferences, allowing us to tailor our content and delivery to meet their specific needs,” says Bjerring. “Whether it’s through social listening, online tracking, or customer surveys, data collection allows us to craft social media content and ads that appeal to our audience."

Improved ROI

Let’s be honest: The number one reason to take a data-driven approach to your marketing is the impact it will have on ROI. These improvements aren’t just due to increased conversions as a result of better targeting and personalization, but the ability to quickly identify what works and what doesn't. This allows you to make data-backed adjustments and optimize your marketing efforts. As a result, you can allocate resources to the most successful strategies, reducing wasted spending and improving ROI.

“Analytics help marketers make decisions at a faster clip by using marketing sensors to monitor changes in consumer behavior and make budget reallocations in real time,” notes McKinsey, adding that the most effective marketing teams are “1.6 times more likely to continuously allocate and reallocate marketing spend in real-time (or near-real time) to the most effective spend channels.”

Improved attribution

Reporting on marketing attribution is essential, but notoriously difficult. Attribution models can solve one of the biggest challenges marketers face — proving the ROI of marketing campaigns (a huge 40% of marketers say this is one of their top challenges). When you have the right data and attribution models in place, you can identify which channels and campaigns are making an impact. This information can then be used to optimize marketing strategies and campaigns and justify marketing resources. 

There are five common marketing attribution models marketers use to understand the impact of channels and campaigns:

• First-touch attribution: In this model, the first touch point is given 100% of the credit (opposite to last-touch attribution).

• Last-touch attribution: In this model, all the credit is given to the very last touch point before conversion. 

• Linear attribution: In this model, each touch point that leads to conversion is given an even weighting, as long it occurs within the attribution window

• Time-decay attribution: In this model, campaigns and channels are credited according to when the touch points occurred, with the touch points closer to conversion receiving a greater weighting. 

• Position-based attribution (aka U-shaped attribution): In this model, credit is given based on the point of conversion. First and last touch are given more credit and the remaining credit is distributed between the remaining touch points.

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Attributed revenue by campaign

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3 challenges for data-driven marketing

Implementing a data-driven marketing strategy isn’t without its challenges. From messy data to staying compliant with privacy legislation, here are three potential roadblocks to be aware of, and how to overcome them.

Compliant collection of data

From GDPR to CCPA, heightened consumer privacy laws have restricted brands from acquiring third-party data in many regions, and Google’s looming plan to kill cookies from Chrome is causing even more uncertainty for marketers. Other major players like Safari, Firefox, and Apple have also made changes that restrict access to third-party data. The sooner you prioritize zero-party data, the sooner your business can benefit. Ask yourself why a visitor, user, or customer should hand over the data you’re asking for, and ensure that the benefit is clearly communicated. 

Data security starts with data collection. Ensure that your data sources are secure and that all data you acquire is legally obtained.  When it comes to your existing data, it is crucial to stay proactive and futureproof security blind spots. Every company should have a clear data security practice in place, including a data usage policy, control over access to sensitive data, implementing change management and database audience, using data encryption, backing up your data, and identifying and classifying sensitive data. Any employee who handles data in any capacity should go through security and privacy training to ensure data is always handled correctly. 

“Maintaining data privacy should always be a cornerstone of any data-driven marketing strategy. With many regions implementing strict data privacy laws, breaching these can lead to high penalties. Make sure you're always compliant to avoid any adverse situations,”  Mia Comic. “The sustainability of data-driven marketing indeed rests on trust and transparency with your customers.” 

Disorganized data

Messy data is one of the biggest challenges for marketers who want to make data-driven decisions. Tom Mitchell, Senior Lifecycle Operations Manager at Sona, believes marketers need to be “as militant and efficient as possible in organizing their data". You must have the systems and processes in place to collect and manage your data effectively. "For example, if you're using free text boxes to categorize companies then rather than actually grouping them by using drop-downs, you're doing yourself a disservice because at the end of the day, your marketing is only going to be as good as your data.” 

Data could hold your business back in other ways, too. If you’re looking for investment, disorganized data could make or break for your business, says Sean Whitney, Principal at Craft Ventures. He cites the example of one company he believed was headed for unicorn status but lost out on investment because “their data wasn’t organized enough”.

“I understood they were waiting for the capital to hire the people who could put this all together, but, from our side, how can we trust that that's going to happen? And will that involve a lot of handholding on our side?” he says. “I still think that business is going to crush it, but I was in a position where it was killing the deal because I didn’t have a way of selling it to the partnership without the data."

That’s why founders must ensure they have solid tracking in place from day one. “Without knowing what's going on in your tool, you're kind of screwed. Build that dashboard as early as possible to track the raw table stakes stuff like signups, but also what features are being used and which aren’t,” says Sean. “If I were founding a company, or if I was going out for a series A or, you know, even a C, I would want to have all that buttoned up.”

Focusing on the wrong metrics

Failure to focus on the right metrics could see your marketing team - and the wider business - wasting time and money. “The problems start at the beginning of the process when many companies struggle to identify goals for their analytics programs, such as preventing churn or increasing cross-sell,” notes McKnisey. “As a result, while every company has significant volumes of data, many B2B companies lack the capabilities to translate data into relevant, usable insights that help them to sell more effectively by improving their understanding of their customers’ experiences, needs, and triggers.

Martin Gontovnikas, Co-Founder and GTM Advisor at HyperGrowth Partners, advises focusing on metrics that are directly tied to revenue. “We were doing a lot of experiments on our activation emails, trying to optimize them for open and click rates, and we increased them a lot,” he says. “But we only realized a couple of months later that what we should have been optimizing for was activation. Once we looked further into that, we found that activation was actually worse for those who got the email versus those who didn’t get it.”

They realized then, says Gontovnikas, that every single one of their KPIs should be linked to the bottom line in some way, whether that’s in terms of revenue or customer retention, rather than testing for testing's sake. “In our case, the open and click rates weren’t related to revenue, but activation rates were. After that, we placed much more attention onto actually picking the right KPIs, because otherwise, you might spend months optimizing something which hurts your revenue.”

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Data-driven marketing in a cookieless future

In 2024, Google will end support for third-party tracking cookies, following Firefox, Safari, and Edge, which will fundamentally change the nature of data-driven marketing. A study by Adobe found that 60% of executives thought “the loss of third-party cookies will have a disruptive effect on their marketing”.

But it’s not all doom and gloom. In a recent study conducted by Google and Boston Consulting Group (BCG), they found that brands that are prioritizing and utilizing zero- and first-party data for key marketing functions saw their revenue increase by 2.9 times.

So, “while some are dreading a cookieless world, adopting new strategies that go beyond cookies will ultimately keep you current with the industry,” notes Forbes. “Marketers should lean into first-party data, which will be instrumental in this new, more transparent ecosystem.” 

Three ways to collect more zero- and first-party data:

1. Single sign-on

Also referred to as SSO, single sign-on is the process of offering the option for customers to sign up using their Facebook or Google accounts. This option benefits everyone. The user is provided with a fast and straightforward sign-up process without having to think up (or reuse) another password. The advantage for the company is that they gain access to first-party data including name, ID, profile URL, interests, and location.

2. Register website visitors

Forms and pop-ups are one of the best ways to have your website users register their visit. They tend to be far more successful when you offer the visitor something in exchange for completion.  For example, this could be as simple as a sign-up to a weekly newsletter, or access to a whitepaper or ebook. The key here is to keep the pop-up or form as short and simple as possible, while still retrieving the information needed—asking too many questions may deter people from registering their details. 

3. Tap into your customer support channels and reviews

These channels are often forgotten or not used to their full capacity. In reality, they can provide you with a wealth of first-party data. Your customer support team engages in one-to-one conversations where customers are more likely to offer additional information.  This information can be manually tracked in platforms like HelpScout or Zendesk by your support representatives and automatically updated into your CDP.  

Reviews can also be a great channel for collecting first-party data. They can be linked back to your CDP and act as another layer of data for your customer profile. It can be a way to tag customers as brand advocates as well as prompt other customers (with 5-star engagement) to leave their own reviews.  

Final word

By now it should be clear: Taking a data-backed approach to marketing boasts a broad range of benefits, from better personalization to improved ROI. But for data-driven marketing to be successful, you need to get clear on your goals, identify the data you need to meet them, and then bring it together in one place for improved reporting and visibility. 

Ultimately, “creating moments that are meaningful for customers requires analytical horsepower and precision to discover customer intentions, interests, and unmet needs. At a time when companies are generating massive quantities of data, however, purpose serves as the anchor for marketers to determine which insights matter most and to focus their efforts there,” notes McKinsey. 

“Creativity also includes the ability to bring novel and disruptive new ideas to the surface, where those ideas can be refined, tested, and either scaled or discarded. That last part, however, is heavily dependent on the strategic analytical muscle, especially the ability to collect proprietary data and use it to generate insights that can drive value.”