How To Use Data-Driven Marketing To Drive Sales (2024)

Big data is everywhere in business, turning out troves of information and actionable insights about customer preferences, purchasing behavior, demographic trends, and much more. But data is just data—that is, until marketers harness it to build and execute a data-driven strategy.

“You need courage to do stuff with everything that you’ve learned,” Neil Hoyne, Google’s chief data strategist and author of the book Converted: The Data-Driven Way to Win Customers’ Hearts, says on an episode of the Shopify Masters podcast. “That’s what I think is fundamental to marketing.”

Here’s how to transform all that data into an actionable, informed marketing strategy for your business.

What is data-driven marketing?

Data-driven marketing leverages information collected from customer interactions and third parties to better understand buyer preferences and behaviors. Marketing leaders use these audience insights to make marketing decisions about how they create and tailor messaging, select distribution channels, and optimize overall strategy. This process involves customer data collection, data analysis, content strategy, and performance tracking.

Benefits of data-driven marketing strategies

Data unlocks a variety of digital marketing opportunities and strategies for ecommerce businesses, including:

Tailored campaigns

Data-driven marketing efforts can inform customer segmentation, which divides your target audience into groups based on common characteristics so you can market to each group. You can segment customers by a variety of factors, from age and gender to location and past purchases. For example, one audience segment may be more sensitive to price, while another focuses on the durability and perceived value of the product. 

“What you’ll see when you start grouping customers together is that some are incredibly valuable, while others might come back only if you offer them a great discount,” Neil says. “It helps you be more focused on who to pay attention to with the way you do business, the products you build, and the marketing campaign around all that.”

Higher ROI

Marketing can be expensive, so of course you want a strong return on that investment. A good ROI requires understanding which marketing channels and campaigns have the biggest impact, as well as where money is being wasted. A robust data-driven marketing strategy can help you fully understand the customer journey and guide more leads to conversion.

But not all shoppers are worth the marketing spend, Neil says, citing the following example: “In one case, a particular customer clicked so many times that even though she did—to everyone’s celebration—buy the shoes, in the end, the company spent so much money marketing to her that they still lost money.”

The main question, he says, then becomes: “Was it worth it all the time you spent building that relationship? If this woman turned out to have high customer lifetime value, it was worth our time and our effort. If we never see her again, we might rethink trying to acquire people like her.”

Personalized customer experience

A positive overall customer experience fosters brand loyalty, increases customer lifetime value, and drives word-of-mouth marketing. Customers want to feel that they matter to the brands they support, and they expect a personalized customer experience. Using a data-driven strategy can result in product recommendations based on purchasing or browsing history, retargeting ads, emails with discounts for birthdays or abandoned carts, social ads, relevant content, and VIP-only previews of new products.

Challenges of a data-driven approach

A data-driven strategy is worth the time and effort. But the journey can be challenging in a few ways:

Information overload

The wealth of data available is helpful. But it can also be overwhelming. Consider starting with a few common and rich sources of customer data, such as:

• Website analytics or app tracking

• Third-party data like market research and customer demographic data

A variety of tools can not only gather data, but also track it to produce data-driven insights. For example, Shopify offers several types of in-depth customer reports to gain insights into your customers, including their average order count, average order totals, and expected purchase value.

Short-term focus 

A holistic, comprehensive view of the entire customer journey is essential—and if you focus too much on short-term performance metrics and real-time data, you may miss the forest for the trees. When it comes to data-driven marketing, “The number-one mistake [people make] is that they’re too short-sighted,” Neil says. “They look at the metrics of what happened today, but in reality, consumers take time to build that connection with a product.”

Unnecessary data collection

Only gather data when it’s needed, not just because it’s there. “Don’t collect information just for the sake of collecting it,” Neil says. “Think about how you might use it to personalize your emails and customer experiences or deliver better value to them.”

It’s also important to avoid invading customer privacy by collecting too much personal information. Companies should only ask for relevant data about the shopping journey, and avoid using data for purposes other than enhancing the customer experience.

How to implement a data-driven marketing strategy

Some brands are eager to dive right into data-driven campaigns, but it’s essential to start with the objectives that align with your business goals. “Take a step back before you go into that data,” Neil says. “What do you think you could do to better connect with your customers? What information could change the way that you build products and service customers?” 

Determine which key performance indicators (KPIs) could help you answer those questions. Then, you can dig into your own data, identifying information you already have through Shopify, Google Analytics, and other tools.

Use data management tools and analytics tools to automate data collection processes and help generate insights. Analyze data to determine the messaging, channels, and strategies that resonate most with your customers so you can build more effective marketing campaigns. Finally, remember that this process is iterative: Analyzing data over time will help you design future campaigns and make changes as your customers and business evolve.