Your marketing team generates a treasure trove of valuable data that can help them make more informed decisions and drive better results. However, unlocking the full potential of that data can be a challenge. Your current analytics approach may not fully provide the insights your marketing team needs to capitalize on and maximize their ROI, despite you spending hours collecting and transforming data.
As per the CMO survey, top marketers have rated the impact of marketing analytics on a company’s performance as average, i.e., 4.5 on a scale of 7.
Traditional analytics approaches often fall short, leaving you stuck juggling excel sheets and struggling to gain meaningful insights. With the various tools and channels your marketing team uses, you need to adopt a sophisticated and integrated approach to analytics.
When it comes to finding a solution for integrated marketing analytics, you have plenty of options. But if you want the best of the best, the Marketing Data Stack is a clear choice. This advanced solution is designed to help you maximize marketing performance and ROI based on effective analytics. With its robust, scalable, and fully-automated capabilities, you can derive advanced insights in near real-time, giving your marketing team the power to make informed decisions and drive better results.
“Over 40 users generate and track core business metrics on a daily basis. Report generation hardly takes a few minutes, and this ensures that all the decisions made are data sound.”
Chushul Suri, Head Of Data Analytics, Meesho.
This article will take you through the Marketing Data Stack and how you can tap into its power to maximize marketing performance and ROI.
What is a Marketing Data Stack
A marketing data stack is a set of cloud-based tools that makes up the ideal marketing analytics solution to capture, transform, store, and analyze the complete marketing data.
These tools are easy to set up and scale, affordable, and need very little technical knowledge; therefore, the barrier to adopting them is low.
Let’s understand the six essential components to set up your marketing data stack.
Data Sources
Marketing has progressed significantly, with various tools and channels broadening the scope of marketing efforts. Currently, there are 9932 Martech tools and an almost endless list of channels for advertising.
Your team may be using a dozen of these tools (a mid-sized company typically uses 27 marketing channels or tools). If you’re invested in paid marketing, the number of channels can continue to grow, including platforms such as Facebook, TikTok, Snap, and Amazon Ads.
These tools contain valuable insights to help marketers understand customers and improve return on investment (ROI). For instance, marketers can use these insights to determine the attributed impact of each channel, identify bottlenecks in the customer journey, and more.
A marketing data stack ensures that the number of tools does not limit your marketing analytics, and data from each is captured and fully utilized to gain insights.
Following are a few common types of marketing data sources:
- Advertising channels – Facebook Ads, Google Ads
- Marketing automation – Marketo, Mailchimp
- Website analytics- Google Analytics, Mixpanel
- Sales CRM – Salesforce, HubSpot
- Product analytics – Mixpanel, Amplitude
- E-Commerce analytics – Shopify, Woocommerce
- Databases – MySQL, MongoDB
Data Warehouse
The data warehouse is the central component of your data stack; it is where all your marketing data is stored and can easily be accessed for analytics and querying. It’s a place where you can store, organize, and access your data consistently and efficiently.
One of the main benefits of a marketing data stack is that it centralizes all of your marketing data and maintains a single source of truth for the entire organization. The marketing data warehouse serves as that, storing all of the data in one place.
You can integrate data from all of your marketing tools and channels into your data warehouse. Every team can access the same data, eliminating conflicts between teams and users.
The data warehouse is optimized for storage and querying, allowing you to run numerous queries and models to generate insights on the stored data and push data or insights to different tools, such as visualization tools.
Data Integration
To make the most of your data warehouse, you should integrate and synchronize all your marketing data from various tools and channels like Hubspot, Mailchimp, Facebook Ads, and more. One way to do this is by manually exporting data from each platform and uploading it to the warehouse at regular intervals.
However, a more efficient approach is to use data pipelines to transfer data from marketing sources to the warehouse. Data pipelines capture data from marketing sources and load it into the warehouse, ensuring that all data is continuously updated and available for analysis.
Manually building data pipelines for each source can be time-consuming, taking weeks or even months to set up a complete marketing analytics data stack. Most modern data teams prefer to use a cloud data pipeline like Hevo Data, which provides plug-and-play connectors for all popular marketing channels and tools. With Hevo Data, you can easily set up data pipelines for your marketing sources in just a few clicks and start seeing fresh, up-to-date marketing data in your warehouse right away.
Data Modeling
It’s essential to transform the data stored in your warehouse and make it ready for analytics. This involves running queries and models, initiating workflows to extract insights, and joining tables from various sources.
For example, suppose you want to generate a campaign report. In that case, you’ll need to join tables from multiple channels like Facebook Ads, Google Ads, TikTok Ads, and Amazon Ads into a single table and format it appropriately.
There are a few ways you can transform your data. One option is to run queries from your warehouse console, which is not effortless. A more efficient approach is to use the data transformation capabilities of your data pipeline tool or a popular data transformation tool like Dbt.
Hevo Data offers built-in data transformation capabilities and native integration with Dbt models. With Hevo, you can easily schedule your models to run in sync with your pipelines, ensuring they are always up-to-date with the latest data in your warehouse.
Business Intelligence
Business Intelligence (BI) tool lets you view and deliver reports in visually appealing formats like graphs and charts. These software applications allow you to create and interact with dashboards based on the insights and data transformation you have done in your warehouse.
Many business intelligence (BI) tools are available, ranging from open-source to paid options with more advanced features. Some popular BI tools include Tableau, Power BI, and Google Data Studio (now called Looker Studio).
You can create different reports and dashboards for different teams, such as campaign reports, funnel reports, customer 360 view, and more. These dashboards will provide valuable insights and help you keep track of marketing performance.
In addition, BI tools provide the ability to refresh data as needed and slice and dice it visually to dig deeper into insights. This will help your marketing team track their KPIs and metrics in near real-time and quickly diagnose any unexpected changes. By doing so, they can make more informed decisions, optimize campaigns, and drive better results.
Data Activation
Not all marketers or business users have access to a business intelligence (BI) tool. Many need specific insights on individual customers or content pieces, such as engagement scores for each customer or traffic for individual blogs.
You can directly deliver these insights to users within their business tools using an activation tool, also known as a reverse ETL tool. This tool conveys data and insights from the data warehouse to different SaaS applications. For example, the engagement score for each customer can be pushed directly to marketing automation tools, or the lead score for each lead can be pushed to the CRM tool for sales teams to prioritize their outreach.
Access to data within their tools provides marketers valuable insights about marketing interactions, product usage, or customer support. This can help them have meaningful conversations with customers, ultimately increasing retention and activation.
Benefits of a Marketing Data Stack
Here are the key reasons why you should adopt a marketing data stack and mature your marketing analytics.
- Automated reports: It automates all marketing reports and eliminates the hassle of manually consolidating data from multiple sources, saving hours of your time and effort and ensuring that your marketing team has accurate and fresh insights.
- Near real-time insights: By continuously loading data to your data warehouse in near real-time and connecting that data to your BI tool, you can provide your marketers with timely insights that help them optimize activities and avoid overspending.
- Flexibility: Get the flexibility to create multiple types of reports, diagnose any problem, or answer any question on marketing performance. You can do everything from website analytics and customer analysis to campaign analytics.
- Scalability: No matter how many more tools or channels you add to your marketing mix, you can integrate the data into your warehouse for analysis in a few clicks. And start delivering insights from each new source in minutes.
How to set up a Marketing Data Stack
Here is a step-by-step guide on connecting all the elements and setting up a powerful marketing data stack for marketers.
1. Setup a Marketing Data Warehouse
When choosing a marketing data warehouse, there are many options, such as Snowflake, Google BigQuery, Amazon Redshift, and Databricks. It’s essential to consider factors like cost, scalability, and integration with other tools to select the best warehouse for your needs.
Once you’ve chosen the appropriate data warehouse for your business, it’s time to set it up. This process involves creating an account and selecting a pricing plan, such as flat-rate or on-demand. Establishing Identity and Access Management (IAM) roles and permissions for your tables is also crucial to ensure that the appropriate team members have access to the necessary tools. By completing these steps, you’ll have a robust and secure data warehouse in place, ready to help you make the most of your data.
2. Identify Data Sources
Understand the reports and dashboards that your marketing team wants access to by checking with them on their specific requirements. This will give you an idea of the data required and where it can be found.
Some of the most likely sources of this data will be advertising tools, marketing automation tools, email marketing platforms, and more. Also, consider including data from sales tools such as customer relationship management (CRM) systems and product analytics tools. Once a list of sources is compiled, the next step is to determine how to load the data from these tools into a warehouse for analysis.
3. Set up Data Pipelines
Now that you have a list of data sources, you can start to load the data from these tools into your data warehouse using data pipelines. As mentioned earlier, using a no-code data pipeline solution is preferred to save time and effort rather than building data pipelines for each source.
When choosing a cloud data pipeline, it’s essential to consider crucial factors, such as whether it has connectors for all your marketing sources, how easy it is to set up, and how quickly it loads data. Hevo Data offers plug-and-play connectors for over 50 marketing and sales tools, including all the major ad platforms and automation tools. It allows you to set up a pipeline in just three steps – selecting sources, configuring the source, and selecting a destination.
You can schedule the pipelines depending on how frequently marketers want to access the reports. For example, campaign managers may wish to monitor their campaigns every hour, so you can set the frequency to every 5 or 15 minutes. For other reports and data, the frequency can be less frequent.
4. Prepare Data for Analysis
After loading all of the data into the warehouse using a data pipeline, the next step is to format the data for analysis. This involves tasks such as joining and aggregating tables, or computing fields like lead scores and channel attribution. As mentioned above, to prepare the data for analysis, you can query it using your warehouse console or a data transformation tool like Dbt.
We suggest using Dbt or a similar tool to perform scalable and complex data transformations. Dbt is the most popular data transformation tool where you can create scripts to format the data according to your needs. Doing so allows you to easily and efficiently prepare your data for analysis.
If you are using Hevo Data as the data pipeline solution, you will have access to built-in data transformation capabilities that are SQL compatible. You can also use Hevo Data’s interface to run Dbt models through the integration with Dbt.
5. Visualize your Reports and Insights
The final step in setting up your data stack is to sign up for a business intelligence (BI) tool of your choice, such as Power BI or Tableau, and connect it to your warehouse. With the BI tool, you can create interactive dashboards using the transformed data in your warehouse. Once you have built the dashboards, share them with the relevant users and make them easily accessible to your marketing team. Doing this will ensure that your team has the data and insights they need to succeed.
Sometimes, you want to deliver insights to your marketers directly in their business tools and trigger marketing workflows, such as email campaigns based on customer interactions. For this, you can set up a reverse ETL (extract, transform, load) using tools like Hightouch or GetCensus. This will keep your SaaS tools in sync with post-transformation data and insights in your data warehouse.
Finally, by implementing a marketing data stack, you’ll be able to mature your marketing analytics capabilities and unlock the full potential of your marketing data. This will significantly increase the impact of analytics on marketing performance and boost marketing ROI. Whether you’re looking to optimize your campaigns, improve customer acquisition, or increase loyalty, a marketing data stack can help you achieve your marketing goals.