What is data-driven marketing?

At Funnel, data-driven marketing is a way of life. We use data to both measure and inform all of our marketing efforts. 

It is so ingrained into our DNA, that we thought it was about time that Alex unpacks what data marketing is and how it can help you grow your business. You can either watch the video or read the extended article below.

Data-driven marketing is about analyzing performance data to see what’s working and what isn’t, then learning from the results to adjust your approach. It relies on performance data to improve how you market a good or service. You can be data-driven across nearly every channel or marketing style, including social media, content marketing, email, PPC and SEO. 

Just because you use digital marketing platforms with analytics features doesn’t mean you are already a data-driven marketer. There's using data, and then there's collating quantitative and qualitative data that you can use to measure campaign performance and drive continuous improvements.

If that sounds daunting, we promise it isn't. In fact, it's relatively straightforward to use these analytics features to analyze your marketing data and gain an edge over your competitors while providing a consistently improving customer experience. 

Time for a data-driven marketing strategy example

To help you understand the ins and outs of data-driven strategies, we've pulled together this quick example of how data trumps assumptions and hunches.

In this scenario, you've just got a fantastic marketing role at “Acme Enterprises,” a corporation very famous for its animated anvils. Your new chief marketing officer (CMO) stops by your desk on the way to lunch and notices you're drafting some Facebook advertisements. The CMO informs you that the company focuses solely on LinkedIn advertising and steers away from Facebook.

The underlying strategy is that Acme is a B2B brand, and LinkedIn is the only place to source B2B customers. Your CMO views Facebook as unprofessional and feels that mainstream social media platforms aren't the right marketing channels to reach the firm's current target audience.

As the new face on the marketing team, you may accept that statement as fact. However, you might still feel that there may be some opportunities to reach your customers on Facebook. You might even have some experience dealing with social media from your previous role.

The problem is that there's no usable data in this example yet. It's just your hunch versus Wile E. Coyote's... sorry, your CMO's advice. To make the right choice, you need to gather some data. That means it’s time to use Alex’s framework which starts with hypothesizing and relevant data collection and results in actionable insights.

Four steps to be more data-driven in your marketing efforts

As Alex says in the video, "Data is being created at all times, all around you, and this is the key to unlocking a way to edge ahead of your competitors."

It's true. Over 402 million terabytes of data are produced each day, and much of that data flows through busy companies. If you can learn to use that data to work toward your marketing goals, you're onto a winning strategy.

Creating a data-driven approach to your marketing strategy is simple when you follow these four steps:

1. Think it
2. Test it
3. Analyze it
4. Learn from it

Think it

The first step is to formulate a hypothesis. In the Acme Enterprises example above, we hypothesized that at least some of the company's customers use Facebook and would be open to receiving advertising messages while using the platform. 

There are several assumptions here, but they're fairly safe assumptions. As a marketer, you're counting on customers having a Facebook account and regularly using the platform. A less confident assumption is that these customers are reachable via targeted, paid advertising. So, you need to test this new theory that Facebook can play a role in their customer journey and boost leads or sales for the company.

Test it

With your hypothesis in hand, it’s time to test. You could take a small portion of your budget to run some highly targeted display ads that promote Acme’s anvils to your business customers. Set a meaningful timescale that allows you to gather a good amount of data, for example, three months. You could even make the process more thorough by introducing A/B testing to discover which aspects of Facebook advertising your audience responds best to.

Analyze it

At the end of your 3-month test run, you have a set of performance and sales data ready for review. This is where your marketing analytics tools come into play. While analyzing the data, you'll hopefully see that your ads performed fairly well. The click-through rate (CTR) was above expectations, and a few clicks led to sales. Also, some of the ads were shared on other platforms and you now have some data that suggests leveraging Instagram could be the next profitable move.

Customer acquisition has risen and you've even noticeably increased the number of positive customer interactions your company is enjoying. Great!

Learn from it

In the Acme example, you learned that you can drive the sales of this fictional company by advertising on Facebook. However, before diving head in and allocating an anvil-sized chunk of your budget to this channel, you may want to explore some further hypotheses and tests to determine how much advertising spend should be allocated to Facebook-based marketing activities.

For instance, does doubling the amount spent on Facebook Ads also double the number of sales? And can you further improve performance by tweaking ad copy or creatives? Test and continuously analyze data to make marketing decisions that genuinely drive business growth.

How a data-driven strategy helps you

By employing strategic marketing data analysis in your process, you can begin to make more informed decisions. This helps you gain a much deeper understanding of your target audiences and how to reach them. Tools like website analytics platforms such as Google Analytics help show you customer behaviors that you can use to drive more effective campaigns.

For example, if your blog post about your new Acme Facebook page got hundreds of hits, maybe that's indicating that regular news updates about what's going on at your firm are well received. Again, you've got to test that hypothesis. Create some more content and continue analyzing data on blog hits, clickthroughs, and whether conversions increase or not. Combine a data-driven approach with your traditional marketing efforts and remember, you're not replacing anything that works; you're just figuring out why it works and doing that even more.

Also read: A guide to performance marketing strategies.

Of course, as your marketing becomes more targeted and sophisticated, you should see increased conversion rates and lower acquisition costs across the board. 

Where to start your data-driven journey

According to Alex, there are a few things you should focus on if you want to become more data-driven today. Any successful strategy needs a good plan, and you can use the below framework to figure out how you'll move toward a more data-centric style of marketing.

Make an inventory

Firstly, you should create an inventory or checklist of all the platforms you currently use that could contain useful data. When creating this inventory, note what data you have, where the data is stored (on the source platform or in another destination) and what is being done with it. 

Looking at our Acme Enterprises example, we may have customer data stored on our e-commerce platform. The finance team may be accessing that data, too. Plus, revenue operations may export that data to Google Data Studio to visualize it and improve the sales process.

While this may require some collaboration with other parts of the business to prevent data silos, it’s essential to know what everyone has already done so you don't inadvertently duplicate data collation.

Do I have enough data?

If you don't have a lot of data available, don't worry. You don't need 'big data' for data-driven marketing. Even if you only have a small budget or no paid advertising at all, you can still analyze the data you have.

Look at all your LinkedIn posts or Google Ad texts. What marketing messages gain the most clicks or likes? What does that tell you? Every aspect of your business generates usable data.

Consolidate the data

Once you’ve completed your inventory, your next step is to centralize data in one place so you can review performance across all your marketing efforts simultaneously. This may require you to organize your data or even employ some data transformation tools. For more information on this, head over to our article all about data transformation. 

More hypotheses

Now, it’s time for some more hypothesizing. Think about what you’d like your data to tell you. 

• Do you want to see how your sales have grown? 
• Would you like to determine your return on ad spend (or ROAS for short)? 
• Are you trying to understand which marketing campaigns perform best?
• Would you like to know which target audience is more open to your marketing messages?
• Do you have a good idea of who your existing customers are, and can you use customer data to attract new customers? 

Simply identifying your needs up front makes your data much easier to analyze.  

Budget allocation

As you can see, data-driven marketing is about experimentation. You are trying out new ways to reach your target audience and get them to convert. Therefore, it is smart to reserve a portion of your marketing spend to test new things. 

One way to do this is by allocating your marketing budget according to the 70-20-10 rule that many marketing teams use:

• 70% of the marketing budget should go to proven marketing strategies that you can count on
• 20% is for new initiatives that you expect to work, but are still figuring out
• Reserve 10% of your marketing budget to test totally new things

This way, you can plan ahead and ensure that you have the resources you need to test a new marketing campaign or tactic.

Keep your data-driven marketing strategy customer-centric

No matter how much marketing data you use in your daily decision-making processes, you must remember that at the end of each data point is a whole load of customers or quality leads excited to interact with your brand. Data scientists can get consumed by the facts and figures, but your data should really tell stories about customer preferences, customer retention, and the overall consumer journey.

That's why data visualization is so important because it transforms raw data into meaningful images. You can then easily talk about data in terms of how your decisions impact customers or clients as well as your bottom line. Engaging customers is the most critical aspect of marketing. After all, that's literally why marketers exist, to try and understand and adjust customer behavior so that leads become qualified sales.

Data can become a critical aspect of your overall marketing strategy but it shouldn't overshadow the human connection. In fact, when done correctly, it enhances the way your company appears to customers. With the right insights driving smart marketing content and ads, you can show your audience that you're in touch with their pain points and focused on delivering a fantastic customer experience with every interaction. The ability to leverage data to boost brand health enables marketers to demonstrate to all stakeholders just how impactful campaigns are across multiple channels.

With that in mind...

Figure out what data you can use and what you can't

Some marketers struggle with the fact that not all business data is free to use in any way they want. You have a wealth of consumer data tucked away inside your customer relationship management (CRM) platforms, for example. However, unless you have explicit consent from those customers to use that data, you can only use it for necessary updates such as order updates or a newsletter they've subscribed to.

You can't use their email address to send marketing emails to unless they've given explicit permission for that. Or bombard their cell number with texts offering discounts, even if you identify trends that show your target audience is currently receptive to SMS marketing.

Gaining a deep understanding of what you can and can't do with the data at your fingertips helps you work better with the data sources you can use. Business intelligence relies on sifting through huge volumes of data. Just ensure you're not inadvertently using personal consumer details that you shouldn't be. Data privacy regulations are very strict on this, and with the upcoming loss of third-party data via cookies, marketers should get used to using first-party data, proper consent and different ways to retrieve that.

Be the Roadrunner rather than the Wile E. Coyote in your marketing story.

Not everything can be measured

While data-driven marketing offers powerful tools for optimizing your strategies, it’s crucial to understand that not everything can—or should—be measured. One of the key challenges in becoming truly data-driven is the need for data literacy. It’s not enough to simply gather data; you must also have the skills to interpret it correctly.

For instance, can you distinguish between a real shift in your data and normal variance? Many marketers struggle with this, often chasing trends that are merely noise rather than meaningful changes.

Moreover, relying solely on data can lead you down the wrong path if you don’t combine it with real-world experience and expertise. Data can tell you what has happened, and sometimes even why it happened, but it rarely tells you the whole story. A data-driven approach that doesn’t account for qualitative insights can result in misguided decisions.

When data driven decision making goes wrong

For example, Nike’s recent struggles highlight the limitations of a purely data-driven approach. The company’s shift to a “data-driven” strategy, advised by consultants, led them to focus on easily measurable outcomes, at the cost of more nuanced but critical elements of their business. The result was a $25 billion loss in market cap—an expensive lesson in the dangers of over-relying on data without sufficient understanding or context.

The takeaway? Data should inform your decisions, but it should not be the sole driver. Combining data with a deep understanding of your business, your customers, and the market allows you to use that data effectively. Being data-driven is as much about knowing when not to trust the data as it is about knowing how to use it.

The core takeaways

The key to any data-driven plan is to keep things simple at first. There’s no need to create complicated graphics and charts that are difficult to build and analyze. Start with the performance metrics that you already know and understand. Then, build your data-driven marketing strategy from there. Use platforms that do much of the hard work for you via data visualizations that are simple to digest.  

At the core of data-driven marketing is the ability to learn from your past performance to evolve your marketing efforts going forward. Data-driven marketing leaders try new things all the time, evaluate them and use those findings to continuously improve their campaigns. 

It’s important to reiterate that data-driven marketing isn’t all about paid advertising or large marketing campaigns. You can use performance data to inform your marketing funnel, creative concepts, public relations outreach, and even the sales process. Apply data-driven principles to content marketing, physical media, and all types of consumer interactions for valuable insights that drive profitable campaigns. With increased data and analysis comes more informed decision-making and better performance. 

If you’re interested in becoming a more data-driven marketer, check out Alex’s video walkthrough above, and subscribe to our YouTube channel to get our latest tips and tricks.

You might also like to read:

• • The formula for a winning full-funnel marketing strategy 
  • Everything you need to know about sales and marketing funnels