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Data-Driven Marketing: The Catalyst to Business Growth

I outlined 10 key steps that any business can take to start adopting a data-driven marketing strategy within their organization.

The idea of data-driven marketing is far from new, but it has become increasingly important in recent years as businesses have become more reliant on data to drive growth. The days of following a hunch or going with your gut when it comes to making business decisions are all but gone.

Data-driven marketing and growth go hand-in-hand. In order for businesses to grow, they need to continually improve. And in order to continually improve, they need to do more of what works, and less of what doesn't. The best way to uncover these opportunities at scale in today's modern business landscape is by leveraging data.

But how do you go about adopting a data-driven approach to marketing? The answer may vary a bit from business to business, but the good news is, it isn't that hard! In this post, I'll be going through 10 actionable steps that most businesses can use as guidelines for harnessing the power of data to unlock their growth potential.

What is Data-Driven Marketing?

As its name suggests, data-driven marketing is all about using data to inform your marketing decisions. More specifically though, it’s about using customer data to segment your audience, personalize your marketing messages, and track the effectiveness of your campaigns. With a seemingly endless number of marketing tactics to choose from, data can help bring clarity to which ones you should use and when. Simply put, it allows marketers to deliver the right message to the right audience at the right time.

Why Data Should Drive Your Marketing Decisions

Not sure why data-driven marketing is more effective and efficient than traditional marketing techniques? Look no further than the data. Undergoing a data-driven transformation allows businesses to spend smarter and improve the customer experience. Bayer is a great example of this, reducing its wasteful spending by 30% while increasing customer engagement by 50% after investing in its data stack.

Nearly 90% of marketers say that understanding user journeys across all channels and devices is critical to their success.
Credit: Think With Google

Taking a data-driven approach puts current and prospective customers at the forefront. Without being able to leverage customer behavior insights derived from big data, marketers struggle to decide:

  • Which marketing channels to prioritize (i.e. search engine optimization, content marketing, social media advertising, etc.).
  • What marketing message should be delivered.
  • How much to invest.
  • When the message will have the greatest impact.

One of the best parts about adopting this strategy is there are no bad outcomes. It allows businesses to run tests to find what works and what doesn't. Data-driven marketing creates feedback loops, which are important for anyone seeking constant improvement.

When data is central to how you operate, you unlock the ability to:

  • Be smarter with your marketing spend and maximize its return on investment.
  • Identify and segment target audiences.
  • Find the optimal marketing channels for the different stages of the customer journey.
  • Implement personalized marketing in your customer interactions.
  • Execute strategic marketing campaigns.
  • Improve customer retention.

However, it's important to understand how to implement a data-driven marketing strategy before you can reap the benefits. Luckily, there are some key steps that most companies can follow to harness the power of data and accelerate growth with this modern way of marketing.

How to Get Started with Data-Driven Marketing

While a fully integrated data-driven marketing strategy isn't something that happens overnight, there are some steps you can take to start leveraging data. These are the areas I would focus on if I were getting started with data-driven marketing from scratch:

  1. Data Stack
  2. Customer Data Capture & Enrichment
  3. TAM, ICPs & Personas
  4. Audience Segmentation
  5. Conversion Rate Optimization
  6. Retargeting
  7. Artificial Intelligence & Marketing Automation
  8. Call Tracking & Conversation Intelligence
  9. Marketing Campaigns
  10. Tests & Personalized Experiences

This list is not exhaustive and not all steps will be relevant to every business out there. That said, implementing even just one of these practices can help you glean valuable insights about your customers and start making data-driven decisions that will move your business forward.

Step 1. Build your data stack

The first step toward a data-driven marketing strategy is to build your data stack. A data stack is a collection of software applications and tools that are used to collect, process, and store big data. It's the foundation that supports data-driven decision making and allows businesses to track progress over time. Most stacks cover six main areas of data management.


This is where your data comes from.  It can be generated internally through things like your customer relationship management (CRM), or externally from sources like market research. To get started with some basic digital marketing data sources, set up Google Analytics, Google Tag Manager, and Google Ads.


Once you have data sources, you need to think about how that data is going to get into your system. The process of moving data from its source to a destination where it can be stored and processed is called data ingestion is the process. BigQuery Data Transfer Service (DTS) is a great option for this.


Next up is storage, also known as data warehousing. Data warehousing is the process of storing data in a central location so it can be accessed and analyzed. BigQuery is a go-to pick here as well.


Now that you have a warehouse of raw data, you need to start thinking about how to make that data useful. Data transformation includes things like data cleansing (removing bad data), data normalization (standardizing data formats), and data enrichment (adding additional context to data) to extract insights.


Data analysis is the next key component of a data stack and it's where visualization comes into play. This might include things like creating charts, graphs, and maps. Looker and Tableau are two popular data visualization and analytics tools.


The last thing to do is automate your data stack. Automation is the process of making your data stack work automatically, without needing manual intervention. This might include things like scheduling data collection, setting up data alerts, and creating automatic reports.

Step 2. Capture and enrich customer data

Your next course of action is to expand your data sources. There are a number of ways to do this, through both internal and third-party data sources.

Internal Sources

  • Customer surveys are a great for collecting detailed information about your customers' needs, wants, and preferences.
  • Web forms are an easy way to capture prospect and customer data on your website. You can use them to collect contact information and ask customers how they heard about you.
  • Sales data can provide insights into buyer behavior, such as seasonality, price sensitivity, and lifetime value.

Third-Party Sources

While first-party data is certainly valuable, it can be difficult to obtain in large enough quantities to be truly useful. That's where third-party data comes in. By working with a data provider, you can access a wealth of information about your target market, including demographic information, purchasing habits, and more. You can also use data enrichment tools to add additional context to your existing data so you can get a clearer picture of your customers.

Step 3. Calculate TAM, identify ICPs, and define personas

Use your data to begin evaluating your business opportunities and zeroing in on a key area of focus.

Total Addressable Market (TAM)

Start out by calculating your TAM to determine the revenue potential of your market. You can do this by multiplying the number of potential customers by your average contract value (ACV):

TAM = Number of Potential Customers * ACV ($)

Doing so will help you assess which markets to invest resources into and which ones to scale out of.

Ideal Customer Profiles (ICPs)

It's important to understand your TAM, but to get a better idea of where to focus your marketing efforts you need to identify your ideal customer profile(s). An ICP is a representation of your perfect customer and they generally have lower acquisition costs and higher customer lifetime values. They will typically make up at least 80% of your customer base.

To find your ICP, look for patterns in your customer data. Do certain types of customers have faster sales cycles? Do some churn less than others? Of these customers, what do they share in common? Are they in a specific industry? Does their business have a certain number of employees? Take the time to get your ICPs right and you'll find everything falls into place.


Depending on your product or service, you may also want to create customer personas. Personas are particularly helpful in business-to-business (B2B) sales as they can provide insights into which individuals your sales and marketing initiatives should be targeting.

To create personas, look for patterns in your customer contact data, such as:

  • Demographics, i.e. job title, seniority level, function
  • Psychographics, i.e. motivations and key pain points
  • Technographics, i.e. which tools they're using

Having a strong grasp of your target personas will help you figure out who to contact and how to create a more personalized experience.

Step 4. Segment your audience(s)

By this point, you should have a steady stream of enriched customer profiles coming into your data warehouse. Use this to your advantage and start segmenting your audience so that you can send them personalized messaging and decide which future campaigns to include them in.

There's an infinite number of ways to approach segmentation and what works for you will ultimately come down to trial and error. But once you find a few methods that work well, stick with them and continue to refine your segments over time. That's what data-driven marketing is all about.

Step 5. Optimize conversion rates

If you're a data-driven marketer, then you know that conversion rate optimization (CRO) is paramount. CRO is all about optimizing your creative assets, landing pages, emails, and other content to increase the percentage of visitors who take the desired action. While it may seem like a daunting task, CRO is actually quite simple if you follow these steps:

  1. Create a hypothesis for why there might be a reason to optimize something. This could be anything from the layout of a landing page to the copy that's used.
  2. Test and validate your hypothesis by running A/B tests or by analyzing your website's analytics.
  3. Assess your results, look for any changes, and repeat the process. Continue to test and measure the results of your changes until they're having the desired effect.

Use CRO as a key component of your approach to data-driven marketing. It creates more conversions, which means more leads, more customers, and more revenue.

Step 6. Set yourself up for retargeting

Retargeting is a powerful tool that can help businesses to improve their ROI and acquire new customers. Also known as remarketing, retargeting involves showing ads to users who have already visited your website or interacted with your brand in some way. By targeting these individuals, you can prime them for a conversion and increase the chances that they will take the desired action.

For example, if someone adds a product to their shopping cart but does not complete the purchase, you could use retargeting to show them ads for that same product in the future. Or, if someone searches for a particular type of product on Google but does not click through to your website, you could use paid search ads to target that individual with relevant ads.

In both cases, retargeting helps you to make the most of your paid advertising budget by targeting individuals who are more likely to convert. And because of everything you've done up until now to build a data-driven marketing strategy, you'll have no shortage of audiences to retarget.

Step 7. Leverage artificial intelligence and marketing automation

Data-driven marketing is increasingly relying on machine learning and artificial intelligence to collect, and derive insights from, customer data. This is done by using algorithms to find patterns in data sets and then using those insights to make predictions about future behavior.

For example, you could use machine learning to automatically segment your audience based on their past behavior. Or, you could use it to predict which products they're likely to be interested in and then show them ads or other relevant messages.

Artificial intelligence and marketing automation are two of the most exciting and game-changing technologies in data-driven marketing. By leveraging them, sales and marketing teams can truly scale their operations.

Step 8. Track calls with conversation intelligence software

We've all been on calls that are "monitored for quality and training purposes", but what does that really mean? In the world of a data-driven marketing company, it means recording and transcribing phone calls in order to extract valuable insights.

Conversation intelligence software is a new category of software that's specifically designed for this purpose. It uses advanced artificial intelligence algorithms to analyze recordings of sales calls and then provides detailed reports with actionable insights.

Data-driven marketers are turning to this software to:

  • Understand customer pain points at scale
  • Determine where leads are coming from
  • Gather sales data and identify sales opportunities
  • Monitor 100% of calls as opposed to randomly selected ones

The many uses cases of conversation intelligence software just make sense, and that's why so many businesses are adopting it in their data-driven marketing strategies.

Step 9. Run marketing campaigns

By now, you've all but fully adopted data-driven marketing in your business. Now it's about bringing it all together to reach new customers or engage existing ones with targeted marketing campaigns. There are several things to keep in mind when running data-driven campaigns.

1. Define your goals and objectives

What are you trying to achieve with your campaign? Are you looking to increase brand awareness, find potential customers, generate leads, or drive sales? Use your data to define the key metrics you will use to measure success.

2. Identify your target audience

Who are you trying to reach with your campaign? Leverage your audience segments and clearly define which one(s) your campaign is targeting.

3. Develop creative assets

What kind of content will you use in your campaign? Will you create a video, an infographic, or a blog post? Whatever you choose, make sure you're leveraging insights from your data to build assets that resonate with your audience.

4. Set up tracking

Make sure you're able to track the performance of your campaign so you can see what's working and what's not. Ensure everything is being captured by your data stack.

5. Test, test, test

Run A/B tests throughout your campaigns so you can create instant feedback loops and optimize your activities as needed. This will help you fine-tune your campaign for maximum impact and ensure you have actionable learnings for future campaigns.

Step 10. Start creating and testing personalized experiences

When all of this comes together, you'll be left with an audience you know like that back of your hand. This unlocks a plethora of opportunities to scale your marketing efforts, not the least of which is personalized experiences.

In a perfect world, all of your marketing activities would be tailored to the specific needs, wants, and interests of an individual. And thanks to data-driven marketing, this isn't just a pipe dream. There are a few examples of personalized marketing experiences you can create to better engage customers.

1. Personalized website content

Use data from your website to show each visitor the most relevant content for them. This could be in the form of blog posts, product recommendations, or even custom landing pages.

2. Targeted emails

Use data from your email list to send highly personalized messages that are relevant to each individual recipient. This could include abandoned cart emails, product recommendation emails, or even birthday greetings.

3. Social media posts

Use data from social media to create targeted posts that are relevant to each individual follower. This could include personal messages, product recommendations, or even special offers.

Personalized experiences are the future of marketing, and data-driven marketing is the key to making them a reality. Thanks to the power of data, you can now create highly customized content, products, and services that are tailored to the specific needs of your audience.

Key Considerations for Successfully Adopting a Data-Driven Marketing Strategy

The steps I shared are an excellent way to adopt a data-driven marketing, but there are a couple considerations to keep in mind.

Data is a marketing investment

Building out a robust data stack will come with a bit of a sticker shock. From implementing data-driven marketing tools to hiring data scientists, the costs can quickly drain marketing budgets. It's important to view these expenses as an investment; you're spending more now so you can waste less down the road.

Change management is critical

Not all marketing teams are accustomed to taking a data-first approach. In fact, most are used to working with gut instinct and intuition. As such, it's important to manage expectations and set up a clear change management plan. Clearly communicate the benefits of moving to a data-driven strategy and most marketers will come around.

Taking Data-Driven Marketing Strategies to the Next Level

This guide focused primarily on how sales and marketing teams can leverage data in their strategy, but it doesn't have to stop there. Other teams within organizations can take a data-driven approach as well.

1. Customer service

Customer service teams can use big data to proactively address customer issues, track customer satisfaction levels, and improve the overall experience.

2. Human resources

Human resources teams can use data to identify employee turnover risk, assess training needs, improve retention, and recruit top talent.

3. Finance

Finance teams can use data to track business performance, forecast future trends, and make better decisions about where to allocate resources.

Organizations that take a data-driven approach across all departments will be in a much better position to succeed in the long run.

Alternatives to Data-Driven Marketing

There isn't really a viable alternative to data-driven marketing today; it's the present and future of marketing, and it's only going to get more powerful with time. Marketing teams can find success working off of gut instinct and anecdotal evidence, but they'll likely be outperformed by those who embrace data.

Don't get me wrong, you can definitely find success without data taking a fully data-driven approach. But if you're not using data to guide your marketing decisions, you're likely misallocating your marketing budget and performing below your potential.

Wrapping Up and My Experience With Data-Driven Marketing

I've personally experienced the impact data can have on marketing teams. Team members are empowered to make better decisions, strategies are more focused and efficient, and the result is a higher performing team.

If you're not using data to guide your marketing decisions, you're likely missing out on some serious opportunities for growth. I hope this post helps you to start thinking about a data-driven approach to marketing in your own organization and helps you lay the foundation for future growth.

Looking for ways to work more efficiently beyond data? I also publish content about productivity. My list of work-from-home office essentials is a great place to start!

Written by

Keanen Buckley

Keanen Buckley

Vancouver, BC
Keanen is a marketer with experience across industries including SaaS, sports, and Web3. He's currently the Marketing Lead @ The Leap by Thinkific and Founder of