Marketers handle data from many different sources, including ads, CRMs, social platforms, websites, and more. Each source uses a different format.
To make sense of this, you need a system that pulls all the data together, organizes it, and sends it where it needs to go.
That’s the job of ETL tools. ETL stands for Extract, Transform, and Load. These tools extract data from multiple sources, clean and organize it, and then load it into a data warehouse or reporting platform.
For marketing teams, ETL tools solve a major problem: fragmented data.
But not every tool is built for marketing. The best marketing ETL tools connect to your platforms, support advanced metrics, and serve as a central data warehouse.
In this post, you’ll learn what ETL means, how the process works, and what to look for in a marketing-focused tool.
What is ETL?
ETL stands for Extract, Transform, and Load. It is a data integration method used to move and prepare data.
In marketing, it helps bring together information from different platforms, organize it, and send it to a central location such as a data warehouse.
Marketers often work with numbers from tools like ad platforms, CRMs, and email systems. Each platform structures data differently.
Without ETL, combining this information takes time and often leads to mistakes. ETL tools fix that by collecting marketing data from multiple sources, aligning it, and making it ready for use.
The result is a consistent and accurate view of your data. You spend less time fixing numbers and more time using them to make data-driven decisions.
3 Stages of the ETL Process in Marketing
The ETL process in marketing follows three main steps. Each one turns scattered inputs into reliable data you can actually use.
These steps help you move from disconnected sources to a complete, organized view of performance:
Stage 1: Extract Data
The first step in the ETL process is to extract data from all the platforms you use.
These include tools like Google Ads, Facebook, email platforms, transactional databases, and CRMs. Every tool stores information in different formats, and most of it is not ready for reporting right away.
This stage is about pulling raw data from those systems and preparing it for the next steps. Whether it’s campaign spend, click-through rates, or email opens, you need to pull it in without changing anything yet.
That means capturing the data as it is, from every source that matters.
For marketing teams, data extraction is often the most time-consuming when done manually. But with the right ETL tools, you can automate it.
You can schedule regular updates, gather data from multiple sources, and move it into one place without copying and pasting.
The goal here is to collect data from everywhere you need it, without losing or changing anything in the process.
Stage 2: Transform Data
Once the data is pulled in, data transformation takes place.
The information you collect is often messy. Campaign names vary, metrics are tracked in different ways, and formats do not match.
In this stage, the data gets cleaned and organized. It includes renaming fields, fixing values, removing duplicates, and converting things like currencies or time zones.
When working with data from multiple sources, it helps to align everything so the numbers can be compared correctly.
Marketers also use this step to add new fields. You might combine values or create custom metrics to track things like cost per lead.
At this point, raw data becomes transformed data, ready for use in reporting and data analysis.
The data integration process depends on the quality of this step. If the structure is off, the rest of the data pipeline will not work as expected.
Stage 3: Load Data
The final stage of the ETL process is to load data directly into its destination. The destination can be a data warehouse, a data lake, or a tool for reporting and analysis.
Many marketing teams choose to load data into business intelligence tools like Looker, Google Data Studio, or Power BI. These platforms help turn data into visuals, summaries, and charts that support quick decisions.
Other teams send the data to storage environments that hold large data volumes, like a cloud-based data lake, which allows deeper analysis later on.
What matters is that the data reaches the target system in a complete state. Any missing values, timing issues, or mismatched fields can affect the final output.
That’s why ETL tools should have scheduling features, error logs, and connection checks. These make sure the data flow stays smooth and the information stays accurate.
Once this stage is complete, your team has reliable, up-to-date data in the right place. From there, you can build dashboards, generate reports, or share meaningful insights without going back to the source every time.
Common Use Cases for Marketing ETL Workflows
Every marketing team needs accurate data to make smart decisions. ETL workflows make that possible by bringing together scattered information, cleaning it up, and sending it where it’s needed.
The use cases below show how ETL supports key tasks across campaigns and channels.
Marketing Performance Optimization
To improve marketing results, you need to track what’s working and what’s not. That starts with clean, accurate data.
ETL workflows help by collecting performance data from ads, email, websites, and more, then combining it into one reliable source.
When you pull in data from multiple databases, you avoid the gaps that come from looking at one platform at a time.
You can compare campaign results across channels, calculate true return on ad spend, and watch key trends over time. It helps you respond faster and spot what’s wasting budget.
Using ETL tools to manage this flow reduces errors and delays. Rather than checking every platform by hand, you get fresh numbers loaded into your cloud data warehouse or dashboard automatically.
That makes it easier to measure results and make changes that improve your return.
Multi-Touch Attribution and Customer Journey Analysis
Understanding how someone becomes a customer takes more than looking at the last click.
Most users interact with several campaigns before they convert. ETL workflows help you track these steps by combining data from different points in the funnel.
When you extract customer data from platforms like paid ads, relational databases, email tools, CRMs, and site analytics, you can line up those touchpoints in order.
Then, by using data transformation, you can standardize campaign names, time stamps, and channel groupings. It gives you a full view of the path someone takes from the first visit to the final action.
You can find weak spots, see what influences conversions, and adjust your marketing efforts based on actual behavior. Good ETL tools make it possible to track these paths automatically, across structured and unstructured data, without the mess.
Real-Time Data Analytics
Marketing conditions change fast. Campaigns shift, budgets adjust, and audience behavior can flip with little warning. To keep up, you need access to current numbers and not reports that are a day or two old.
That’s where automated ETL tools help. By pulling and loading data on a frequent schedule, you gain access to near real-time updates.
You can track ad spend, conversions, and engagement without waiting for end-of-week exports. When your data pipelines run often, you spot trends and fix problems faster.
With fresh data flowing into your data warehouse, you can respond to changes right away. You might pause a poor-performing ad set or increase the budget on a winning one.
It further lets you prepare more accurate reports for stakeholders, since the numbers are always up to date.
Data Integration for Personalized Targeting
Personalization works best when your data is complete. To send the right message to the right person, you need details from ads, web visits, emails, purchases, and more.
ETL brings together customer data from your tools, reshapes it during the data transformation step, and sends it to a target database or campaign system. That way, every outreach is based on a full customer profile.
Besides that, it creates smarter segments, sends better messages, and boosts engagement. Clean, connected data means your targeting isn’t based on guesses—facts drive it.
How Do ETL Tools Help Marketers?
ETL tools act as a bridge between your sources and the platforms where you’re using that data.
Without ETL tools, manual data extraction is a hugely time-consuming and certainly not the best use of a marketer’s time.
A survey by CrowdFlower showed that nearly 80% of data scientists’ time is spent on data cleansing and extraction. That’s before they even get to report and analyze data.
And when there are many clients or brands, each with data on multiple platforms, the efficient extraction, transformation, and warehousing of the data becomes even more essential.
Each ETL tool performs three main actions:
-
Connect to platforms - Instead of logging into each system, the tool links with your analytics and marketing platforms through built-in connectors.
-
Apply logic and formatting - It uses predefined rules to rename fields, fix formats, and apply formulas based on your reporting needs.
-
Send the output - Once processed, the tool delivers the result to a place where it can be used, such as a data warehouse, spreadsheet, or visualization platform.
Different Types of ETL Tools
There are different types of ETL tools, such as:
Enterprise ETL Tools
Enterprise ETL tools are for large companies that work with big datasets and multiple systems. These tools are usually:
-
Highly customizable - You can build complex data workflows and set detailed rules for each stage.
-
Require technical knowledge - Often used by data scientists or IT staff who manage deployment and scaling.
-
Not always marketer-friendly - Most interfaces are for back-end users, which means marketers may need help setting things up.
-
Stronger system integration - These tools connect with enterprise software and internal systems, but can be difficult to link with some marketing platforms.
Custom ETL Tools
Custom ETL tools give teams full control over how they move and manage data. Developers or data engineers usually build these setups from the ground up to allow precise tuning for unique business needs.
What you get with a custom build:
-
Flexible data management – You decide how to extract data, apply rules, and deliver results. Every step of the ETL process can match your exact needs.
-
Optimized performance – You can adjust pipelines for speed, scale, or specific data formats. It works well when you’re pulling in high data volume from many systems.
-
Deep control over security – Custom setups help you follow internal policies, data governance standards, and industry-specific rules.
-
Built-in system alignment – You can connect to internal apps or legacy platforms that standard tools might not support.
Cloud-Based ETL Tools
Cloud-based ETL tools run entirely online. You don’t need to install anything or manage physical servers. These tools also function as a serverless data integration service.
Marketers often choose these tools due to the following:
-
Work through a browser – You can log in, build workflows, and connect platforms from anywhere.
-
Push data to cloud destinations – These tools send results to platforms like a cloud-based data warehouse or cloud storage for easy access and long-term use.
-
Avoid full data transfers – Instead of moving everything, they extract only what’s needed, which reduces load and improves speed.
-
Support frequent updates – Many run automatically throughout the day, keeping your dashboards fresh.
-
Remove the need for maintenance – You won’t have to manage updates or fix bugs. The provider handles all of that.
Open-Source ETL Tools
Open-source ETL tools are free to use and give you full access to the code. They’re a smart choice for businesses that want flexibility without paying for a license, especially if they have technical staff who can manage the setup.
What makes open-source tools different:
-
No licensing fees – You can download and use the software without paying upfront or recurring costs.
-
Full code access – You can change the tool to meet your own workflow or support custom data integration methods.
-
Active communities – Many tools have large user bases that share updates, plugins, and fixes.
-
Works across systems – Some tools support both structured and unstructured raw data for complex pipelines.
3 Factors in Choosing the Right ETL Tool
Choosing the right ETL tool depends on how well it fits your marketing setup. For marketing teams, three features matter most:
-
Complete platform connectivity – The tool should link to all your marketing data sources without relying on extra steps or third-party add-ons.
-
Support for custom metrics – Beyond basic cleanup, it should allow you to apply formulas, create calculated fields, and prepare your data for reporting.
-
Built-in data storage – It should store data directly so you can access, analyze, and share results from one place.
Manage, analyze, and share your marketing data from one platform. Start your free trial today!
1. Connectivity to All Your Marketing Data
Many ETL tools connect only to a limited number of data sources. So, if you’re using a tool that connects to Google Ads and Facebook Ads but not to your CRM or eCommerce data, there’s little benefit in using it.
Having to use multiple tools to bring all the data together for multiple clients or brands significantly wastes time and restricts your ability to scale.
TapClicks’ TapData Connects to Thousands of Data Sources
TapData supports hundreds of direct data integration tools, including major platforms like Google Ads and Facebook Ads, as well as niche options like Genius Monkey and Tiger Pistol. It connects to everything you’d expect and plenty more.
For sources without native support, the TapClicks Smart Connector™ fills the gap. It lets you bring in data from on-prem databases, offline systems, and even Excel files.
So far, teams have used it to connect over 10,000 unique sources.
Once you set up your connections, TapData starts pulling data right away. In most cases, it can also retrieve historical data going back 12 months or more.
With over 250 instant-on connectors, the platform automates daily updates and supports on-demand syncs. It saves time and scales smoothly across multiple clients or brands.
2. Advanced Calculations as Well as Data Transformation
In most ETL tools, the transformation step focuses on basic cleanup.
You can remove extra columns, fix schema mismatches, and prepare your data for transfer. After that, the data typically moves to another platform where reporting and visualization take place.
It’s fine when teams just want to collect and store data in one place. But marketers need to prepare data for analysis, reporting, and client delivery without extra steps.
TapClicks lets you go further by applying advanced calculations inside the platform. You can create and store custom metrics that stay available for future reports.
We remove the need for manual edits or spreadsheet work.
Example 1: Customize and Combine Metrics
Marketing metrics often carry different names across platforms, even if they measure similar actions.
For example, “Follows” on X, “Likes” on Facebook, and “Subscribes” on YouTube may all point to user engagement. When building reports, marketers often want to group these into one metric like “Total Social Engagement.”
TapClicks lets you define these umbrella metrics once, using Channels. After that, the metric stays active and updates automatically with fresh data. You don’t need to rebuild formulas or repeat the same setup across reports.
You can include actions like clicks, phone calls, purchases, and installs. Or group reactions based on your own definitions of engagement.
Once set, that metric lives in your account and pulls the latest data every time you build a report.
Example 2: Set Up Advanced Calculations in a Few Clicks
TapClicks lets you apply advanced logic to your data without leaving the platform. You can group campaigns, define rules, and calculate metrics in minutes.
Say you’re running ads for multiple brands. TapClicks can scan campaign names, tag matching items, and group them under a single label.
You can use the same approach to group data by product, region, or campaign type. Once set up, those definitions stay active and update automatically.
TapClicks also supports calculated metrics like blended CTR or cross-platform ROAS. Instead of averaging platform-level results, you can use totals across all campaigns to get accurate performance numbers.
If needed, you can pull in external data, like Salesforce revenue, and connect it directly to ad spend. Everything stays in sync and ready to use, without rework.
3. Data Warehouse Facility
Most ETL tools collect, clean, and move your data to a separate platform. That destination is usually a database or warehouse that requires technical knowledge to access.
If you want to run reports or analyze trends, you often need a developer or data analyst to help.
TapClicks handles this differently. It doesn’t just collect and transform your data. It stores it too.
We act as your fully managed data warehouse, where you can track trends, build reports, and access historical data without writing code or using another tool.
You can store all your data in one place. You can use that same platform to build metrics, calculate performance, and deliver reports.
No switching between systems. No asking for support. No delays.
Deliver Data Anywhere with TapData
TapClicks also gives you full control over where your data goes. If your team prefers to use Tableau or Google Sheets, you can send data there using TapData’s built-in Data Exporter.
Set your schedule, choose your destination, and TapClicks will push the data automatically. You don’t need to move files manually or involve another platform to finish the job.
Whether you’re working with a small team or managing hundreds of brands, TapClicks simplifies the entire process from data collection to delivery.
Deploy a Unified Marketing Data Layer With TapClicks
Managing data across different platforms takes time and effort.
When data lives in silos, it’s hard to get a full picture of performance. We solve this by giving you a single platform that pulls everything together.
TapClicks unifies your marketing data across all channels, clients, and tools. It combines the data collection process, transformation, storage, and delivery into one system.
You can access campaign data, apply advanced calculations, build reports, and send insights anywhere without needing multiple tools or manual effort.
Everything you need is in one place. All your marketing data is connected, clean, and ready to use.
With TapClicks, you don’t just centralize your data. You build a scalable, automated layer that supports smarter reporting and faster decision-making.
FAQs About Marketing ETL
What is an ETL in marketing?
In marketing, ETL refers to the process of pulling data from different marketing platforms, cleaning and standardizing that data, and then loading it into a centralized system such as a data warehouse or dashboard tool. It marketers maintain data quality by ensuring consistent formatting, accurate values, and usable inputs across platforms. The main goal is to turn fragmented information into relevant data that is ready for analysis and reporting.
What are common marketing tools that use ETL pipelines?
Tools like TapClicks, Supermetrics, Funnel, Adverity, and Improvado use ETL pipelines to manage marketing data. These platforms extract information, integrate data from various sources, and prepare it for reporting. ETL pipelines help align naming conventions, remove inconsistencies, and make sure teams work with the same data across platforms.
How is ETL used in platforms like TapClicks or other marketing tools?
In TapClicks, ETL manages the full cycle of how marketers process data. The platform connects to multiple sources, extracts campaign data, and transforms it into clean, structured formats. It then loads that data into dashboards or third-party tools. TapClicks also improves data accuracy and reduces the need for manual updates.
What is the difference between ETL and ELT?
ETL (Extract, Transform, Load) transforms data before loading it into the destination system. It helps ensure data quality upfront. ELT (Extract, Load, Transform) moves data into the storage location first, then performs transformation within that environment. ETL is useful when data needs cleaning before it reaches the reporting layer. ELT is better for modern platforms that can handle large volumes of raw data and support transformation after loading.
