While a dedicated marketing data warehouse isn’t necessary for every agency or brand, anyone interested in effective digital advertising today needs to know the basics of how data warehouses gather, store, and analyze marketing performance data.
What Is A Marketing Data Warehouse?
Marketing data lives across multiple advertising, analytics, and CRM platforms, such as Google Ads, Google Analytics, Facebook Business Manager, Hubspot, Salesforce, and thousands of other vendors.
A marketing data warehouse centralizes marketing performance data from various platforms for storage and analysis.
As the volume of data increases for an expanding business, the need to structure, organize and retrieve that data for various use cases becomes more of a necessity, as does the need for scaling your data warehouse capabilities to quickly adapt to the ever-increasing amount of data you're pulling.
Instead of manually spinning up more storage space (or worse, running out of storage space), one of the major benefits of an ‘out-of-the-box’ data warehouse provider is the ability to scale with growing demands.
Typically cloud-based, data warehouses differ from traditional data storage methods in that they provide more flexibility with storage and outside integrations, with cost and efforts both drastically reduced.
With enough coding and web development expertise, it’s possible to manually create a custom database through existing tools, and handle the Extraction, Transformation, and Loading (ETL) workload via MySQL and a big box database.
However, this approach to a DIY marketing data warehouse requires specialists, time, and lots of trial and error, making an existing data warehouse solution a more viable option.
What are some existing solutions/products that solve the marketing data warehouse problem?
Data Warehouse Options
- Big Query (Google) - A multi cloud data warehouse designed for business, Big Query is a serverless, scalable, and cost-effective data warehousing solution from Google. Able to feature query streaming data in real time, Big Query provides businesses with predictive analytics, secure data, and robust governance that offers a 99.99% uptime SLA.
- Snowflake - Snowflake is a data platform built to leverage the modern cloud data warehouse. Fast and reliable access to your data, Snowflake accelerates business intelligence analytics, all with little to no maintenance and administration. With cross-cloud data replication for seamless access across the globe, making 100% data-driven business decisions is attainable through Snowflake.
- Azure (Microsoft) - The Microsoft Azure Portal is a combination of cloud products and services designed to build, run, and manage data-based applications in a unified console. With the largest compliance coverage of any cloud provider, Azure provides comprehensive security and the ability to integrate and manage environments in a hybrid cloud.
- Amazon Redshift - Amazon’s data warehouse service, Amazon Redshift provides all the core benefits of on-demand computing, petabyte-scale data warehousing and exabyte-scale data lake analytics, in a fast deploying, scalable platform within AWS.
- Oracle Database - A fully managed & comprehensive cloud experience for data warehousing, Oracle’s Autonomous Data Warehouse is built on multitenant architecture that allows for faster analytics queries and consistent performance across a wide variety of databases and platforms.
How To Set Up A Marketing Data Warehouse
Whether it’s a growing amount of un-processable data, or a pressing need to track ROI across different channels, campaigns, products, and tactics, the signals and timeframes associated with setting up a marketing data warehouse will look different for every business.
If you have selected a data warehousing option, the work has really just begun.
Identifying the data source from which you’ll pull data, deciding how to pipe the data into the warehouse, and choosing an analytical and reporting layer are just a few of the steps & decisions required to get a marketing data warehouse up and running. Let’s go over each.
Identifying Marketing Data Sources
Effective marketing data warehousing starts with properly identifying the sources you’ll need to pull data from. Common data sources include;
- Advertising platforms like Facebook, GoogleAds, Amazon, LinkedIn, Twitter, Criteo, or Outbrain.
- Email marketing platforms like Marketo, Hubspot, or Mailchimp
- Social media platforms such as Twitter, Instagram, LinkedIn, and TikTok
- Analytics tools like Google Analytics, Adobe Analytics, and Microsoft Azure
- E-commerce platforms like PayPal, Stripe, Amazon, and Shopify
Although data identification is the first step in the process, once data sources are confirmed, it’s imperative to then establish the last step in your marketing data warehousing process; identifying the appropriate reporting tool to unlock insights through data visualization and analytics.
Selecting Marketing Reporting Software
There are several options for marketing reporting software for agencies and brands of every size and budget, including;
- Data Studio
- (*cough) NinjaCat
- And many others!
The real question is, do you need marketing reporting software?
Many marketing teams still struggle with properly communicating performance or campaign results from advertising. They are still handing over reams of spreadsheets to clients and stakeholders, letting them scroll through tabs and pivot tables,.
Whether it’s a dashboard, PDF, spreadsheet, or a slide deck, effective marketing performance reporting software has to crank out reports filled with relevant data to the audience, attuned to goal-based metrics, and communicated in an impactful way.
How an organization chooses to visualize and report on marketing performance, both internally & externally, can have a huge impact on the perception and trajectory of the business.
If the saying, “what gets measured, gets managed” is true, then the context & manner in which marketers choose to report performance results can define campaign results just as much as the contents of what’s in those reports.
Setting up a marketing data pipeline
Everyone in marketing loves the idea of Big Data, but few appreciate the technical details that go into properly establishing data pipelines for a data warehouse.
From engineering, to preparation, to analytics, a marketing data pipeline is the formalized set of processes and products that ingests, refines, and parses data from source to warehouse to reports.
There are plenty of competent and trained vendors in the data pipeline space, like Fivetran, Stitch, or Xplenty, it’s technically possible to create a data pipeline with free and open source software.
What are the reasons most businesses and brands don’t build their own data pipelines?
A majority of the workload and time-drain for any client reporting process is pulling data, so the quality and speed of the data pipeline has to be optimized and maintained.
Data warehousing is heavily reliant and coded off schemas, or tables, in order to function. Without getting too far into data management protocols, it’s important to use consistent naming conventions and standard schemas within your data warehouse in order to keep cross-channel data comparable.
Since most marketers don’t have insight into best practices around data modeling, custom schemas, API connections, and data transfers, it’s best to leave the data pipeline engineering to the professionals.
Better Marketing Data Warehouse, Better Marketing
While it’s important to use data to guide decision making, the quality of a data-based decision is only as good as the data it’s based on.
Marketers need technology that brings down the amount of hours spent making sense of data, and speeds up the time it takes to glean insights from it.
That’s why an optimized marketing data warehouse that enhances reporting, can lay the foundation for better insights and more informed strategies.