What Is Marketing Data Integration? How To Use Marketing Data

Great news: Your latest Facebook ad has already generated more than 1,000 clicks. But looking at a single data point doesn’t tell the full story. Marketing data integration matters because it reveals what happened after the click: who converted, what they bought, and how that ad’s performance compares across your marketing channels.

Bringing marketing data from multiple sources into a unified view connects the dots between all of your efforts. This gives you visibility into not only how everything is performing, but also where there are opportunities to better serve your customers and grow your business. Unifying customer data was a key factor that helped Magnolia Bakery scale its business beyond its Brooklyn storefront to nationwide shipping.

Learn more about marketing data integration, how Magnolia Bakery unified data to support its online expansion, and tools you can use to consolidate your own marketing data.

What is marketing data integration?

Marketing data integration is the process of consolidating data from multiple sources, like social media interactions, web analytics tools, and Google Ads, into a single source of truth. Instead of requiring teams to sift through fragmented data across disconnected spreadsheets and dashboards, integration breaks down data silos into one central location that simplifies analysis.

For example, merchants using Shopify could integrate data from Meta and TikTok into the platform and use sales conversion reports from Shopify Analytics to compare campaign performance. This makes it possible to see which ads are actually driving the most revenue, not just the most engagement.

That clarity can help you refine your marketing strategy to better target the right audience and invest in channels that actually deliver on your business goals.

Types of marketing data for integration 

There are four main types of customer data, each with different collection methods:

• First-party data. Information you collect by watching what customers do on your owned channels. Examples include pages viewed, time on site, purchase history, clicks, searches, cart activity, app usage, and email opens. First-party data is the most authentic and reliable since it comes straight from customers, providing clear insights into their behaviors. 

  Put your customer data to work with Shopify’s customer segmentation

  Shopify’s built-in segmentation tools help you discover insights about your customers, build segments as targeted as your marketing plans with filters based on your customers’ demographic and behavioral data, and drive sales with timely and personalized emails.

  Discover Shopify segmentation

• Second-party data.Second-party data is another company’s first-party data, shared with you through a partnership or data-sharing agreement. For example, if a fitness apparel brand collaborates with a complementary supplement business, they could share their customer data to gain insights on overlapping audience segments.

• Third-party data. Third-party information like demographics, behaviors, interests, and online activity is gathered by entities such as data brokers and market research firms that have no direct relationship with you or your customers. This kind of data helps you better understand broader market trends and expand your targeting capabilities.

• Zero-party data. Personal information that a customer intentionally and proactively shares with your company beyond what’s strictly necessary. This could include style, size, or product preferences, budget range, interests, or goals, or communication preferences like email or SMS. Because customers offer this information, it’s trustworthy and provides direct insight into their needs.

Tips for integrating and using marketing data

• Centralize customer behavior
• Connect your marketing platforms
• Use data reporting tools
• Turn insights into personalization

There are many ways to integrate and use your marketing data. You can use ecommerce platforms, business intelligence software, or a combination of tools to acquire the insights you need to best serve your customers. However, there are some foundational steps you can take to start the process.

Here’s how to get closer to integrated data management, with tips from Magnolia Bakery.

Centralize customer behavior

Centralizing where customers browse and purchase your products consolidates orders and gives you control of important customer behavior data. For Magnolia, that meant making magnoliabakery.com the primary destination for nationwide orders.

When expanding nationwide, Adam Schloss, Magnolia’s marketing director, looked for ways to capture shopping behaviors from all audiences, including local customers. This inspired three distinct sections of the updated website: a bakery locator, online orders for pickup or delivery, and a search tool to find Magnolia Bakery products in grocery stores. Not only did this consolidate data, it also created a seamless shopping experience that previously required visiting third parties like Amazon or Walmart.

Adam explains that bringing in all orders to one domain revealed purchasing patterns they couldn’t see before. “We uncovered learnings like a banana pudding purchaser is more likely to add a cupcake to their cart,” he says on Shopify Masters. Findings like these informed more relevant product recommendations, such as suggesting a cupcake to the right customers during checkout.

Connect your marketing platforms

Marketing tools like your email platform, Meta, Google, and TikTok all collect audience data such as clicks, conversions, and open rates. But when these platforms operate in data silos, you have to manually connect the dots to optimize your marketing efforts.

Integrating your marketing tools with an ecommerce platform like Shopify removes that friction by centralizing all your customer and performance data in one place. “Once we integrated all of our social media and platforms like Google with Shopify, it saved us a lot of time with reaching and prospecting new customers,” Adam says.

Rather than manually identifying prospective customers who share traits with Magnolia Bakery’s current customers, Adam lets Shopify piece the puzzle together. Now, he can trust Shopify’s algorithm to reach new customers by automatically creating lookalike audiences.

Use data reporting tools

Once your apps are integrated with a centralized platform—like Shopify Analytics in Magnolia Bakery’s case—you can create a dashboard that visualizes information like sales by channel, top-selling products, and more. For Adam, Shopify Analytics opened the door to testing what works.

“Shopify’s analytics are the most in-depth that I’ve ever seen, and I can spend all day just sitting in the analytics tab of our Shopify dashboard and coming up with a list of things that we should test and learn,” Adam explains. That included testing everything from Magnolia’s paid media strategy to the on-site experience to see what led to more sales.

 Data reporting tools also let you see trends over time. “Now that our Shopify platform has been live for over two years, the most valuable data sets for us are the year-over-year learnings,” Adam notes. These include seasonal spending habits, revealing the best times to promote certain products. 

Turn insights into personalization

Once reporting tools uncover valuable insights from your integrated data, turn them into actions that drive sales. Magnolia Bakery used consolidated customer data from its email database and purchase history to create highly personalized marketing campaigns.

“If a customer is ordering a pie for Thanksgiving, we want to make sure that Shopify is tagging that customer as such so that next Thanksgiving, they get an email about pies,” Adam explains. The same logic applies across the business—orders containing “Happy Birthday” in gift messages get tagged as birthday purchasers for future birthday-specific reminders.

This approach has dramatically improved the bakery’s precision in sending the right message to the right customer. “We’ve become a lot better in making sure that specific messages are tailored to the right audience so that we’re not just distributing a marketing message to the full file of our audience every time we have a message,” Adam explains.

Marketing data integration tools

• Ecommerce platforms
• Marketing data pipeline management
• Data storage
• Data visualization

There are multiple ways to achieve unified data using multiple platforms and tools. Here are some of the most common approaches:

Ecommerce platforms

Ecommerce platforms like Shopify and BigCommerce act as central hubs for marketing data by integrating with apps like Klaviyo, Facebook, and Mailchimp. These integrations bring together product and customer behavior data, providing a more complete view of marketing performance across channels.

For example, after integrating your email platform, social media apps, and digital campaigns into Shopify, you can explore your analytics and reporting dashboards to better understand what’s performing best or return on ad spend.

Marketing data pipeline management

Marketing data pipeline management means pulling multiple data sources into one location for analysis. For example, you might have Shopify campaign outcomes, email performance tools, and ad platform metrics. Rather than manually pulling all of this information from each source, a marketing data pipeline tool extracts it automatically and sends it all to one centralized location.

A tool like Supermetrics manages data pipelines specifically for ecommerce. It connects data from sources like Meta, Shopify, and Google, automating data transfers and eliminating the need to hunt down each source individually.

Reporting tools like Shopify Analytics cover the fundamentals of data analysis. Data pipelines become valuable when your marketing dashboard isn’t sufficient for what you want to measure, share, or automate. For instance, if an ecommerce company wants to combine ad spend, on-site behavior, and repeat purchases into one platform, then Shopify Analytics alone won’t provide that level of depth. This type of data integration requires combining Shopify data with external sources like Google Analytics or your customer relationship management (CRM) platform.

Data storage

If you’re using one data pipeline for many data sources, you need a centralized place to store that information. The two most common storage options are data lakes and data warehouses:

• Data lakes. Store both structured and unstructured raw data. This includes social media comments or product reviews that have not been filtered or analyzed for patterns. Amazon S3 is a commonly used data lake.

• Data warehouses. Store structured, organized data, like sales data about specific SKUs and ad campaign metrics. Google BigQuery is an example of a data warehouse.

Data visualization

Data visualization tools convert raw data from multiple sources—like browsing history from ecommerce platforms, Meta campaign performance, and point-of-sale (POS) data—into charts, graphs, and dashboards that make patterns and trends immediately apparent. 

For example, if you have physical retail stores, you may want to explore your net sales for various products by region. Your visualization tool would allow you to customize a data report that creates bar graphs depicting sales for each product by region, making it easier to see where demand is strongest.

Platforms like Shopify come with reporting dashboards like Shopify Analytics, but there are also standalone options available. Google’s Looker Studio (formerly Google Data Studio), for example, is designed to work with Google services to turn data into shareable, visual dashboards. Tableau is another powerful reporting tool that combines multiple data sources to create interactive, customizable visualizations.