In today's digital age, marketing technology (MarTech) is an essential part of any successful marketing team’s strategy. With a 11% growth rate since last year and a staggering 7,258% increase since 2011, the MarTech landscape is constantly evolving. While these platforms offer new tools for marketers to streamline their operations, they also bring new challenges such as efficiently extracting insights from an unprecedented volume of marketing data.

Data-based roadblocks are holding back your customer experience

Despite the rapid growth of MarTech platforms and the data they produce, only half of marketing decisions are data-driven. This points to a disconnect between the investments marketing teams are making and the ROI returned. In a fast-paced world, wherein online trends and cultural movement influence customer engagement in real-time — lacking and scattered data practices hinder your team’s overall success. 

As macroeconomic headwinds continue and budgets remain tight, marketers must automate processes to efficiently sift through marketing data and get more value out of their MarTech investments. The data these solutions produce can vastly improve customer experiences, improve your marketing team’s effectiveness and unleash greater levels of efficiency.

Common obstacles to unlocking insights include:

• Data silos: Data silos occur when data is stored in different locations, making it difficult to get a complete view of customers. Think about how your email platform’s data is separated from your web analytics — and how that prevents both your email manager and your web team from moving in unison. 
• Manual data aggregation: Manually aggregating customer data from multiple sources is a tedious and error-prone process. Time is a commodity (and an expensive one at that), manually combining data from multiple sources is an inefficient use of everyone’s time. 
• Custom-built pipelines: Custom-built pipelines are expensive and time-consuming to develop and maintain. They serve as an operational burden for data engineering teams and a bottleneck to providing consumable data for downstream marketing use cases. 
• Disconnect between analytics and data science tools: Analytics and data science tools are often designed for different purposes and require different skill sets. Those skills aren’t always transferable and that quickly creates a knowledge gap.

As AI takes on a more important role in helping marketers gain a deeper understanding of their customers, overcoming these data roadblocks is critical to leveraging these data-based tools. According to Gartner, 75% of organizations wanted to utilize AI to be more productive and leverage it for strategic initiatives last year. Without mature data practices, that’s nearly impossible. 

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The solution: An AI-powered Modern Data Stack built on the Data Intelligence Platform

If you plan on leveraging AI and overcoming these data-based obstacles — the modern data stack built on the data intelligence platform is a more efficient way forward. 

Time spent manually aggregating data or maintaining homebuilt pipelines is wasted time better spent on valuable projects, such as uncovering insights and driving growth. 

By leveraging a modern data stack (MDS) built on the data intelligence platform, organizations can automate and tackle data challenges. The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance and is powered by a Data Intelligence Engine that understands the uniqueness of your data. 

A modern data stack consists of:

• A fully managed ELT (extract, load, transform) data pipeline
• A cloud-based data destination like the data intelligence platform
• A data transformation tool
• A business intelligence or data visualization platform
• AI/ML capabilities

Unlocking the potential of your data with Fivetran and Databricks Data Intelligence Platform

Fivetran offers a fully automated data movement platform with 400+ managed connectors, including over 60 specifically designed for marketing analytics, enabling efficient movement of data from popular SaaS applications, on-premises and cloud databases, data warehouses and data lakes into the Databricks Data Intelligence Platform. 

This eliminates the data silos that various MarTech platforms can create and centralizes your data into your lakehouse. Suddenly, rather than having to manually aggregate data from your email and web analytics platform, or worse, asking your data engineers to build pipelines to do so — you have a near real-time stream of data ready for use. 

The best part? It’s fully automated and managed — making it as reliable as electricity, so that you can forget the architectural details and focus on how you’re using it. 

For your destination, Databricks’ Data Intelligence Platform is a unified platform for your data that is consistently governed and available for all your analytics and AI. It’s an ideal destination to build a modern data stack as it provides both a world-class serverless data warehouse and end-to-end MLOps and AI development solution that’s built upon a unified approach to governance and security. 

This means that instead of copying and transforming customer data in multiple systems, you can access all your data in one place and share one common solution stack within your marketing organization — along with your data engineering and data science counterparts. And Databricks Unity Catalog provides one security and governance model, eliminating data access issues for all teams that need visibility into customer data. 

Finally, with machine learning capabilities like Databricks AutoML built into the same data intelligence platform, marketing analysts can quickly generate baseline models and experiments to jump-start new ML projects such as forecasting campaign performance and predicting the most efficient marketing channels. 

By centralizing data from scattered sources all over your organization into the Databricks Data Intelligence Platform with Fivetran’s fully-managed connectors, your team can: 

• Lower your total cost of ownership 
• Democratize access to data and AI
• Free up data engineering teams to do more impactful work
• Connect analytics teams to customer data in real time to gain insights into the marketing mix (what’s working and when), marketing funnel, customer 360 and more

What this looks like in practice

Let's take the example of Condé Nast, the global media company with over 88 million consumers in print, 419 million in digital and 432 million across social platforms. Before Fivetran and Databricks, they battled bottleneck issues, siloed data and custom scripts that made it cost-prohibitive to pull data from each MarTech platform's API. 

With Fivetran, they seamlessly centralized their data into the Databricks Data Intelligence Platform, saving over a week of engineering resources per connector as they no longer needed to manage custom connector scripts. 

Condé Nast is now effortlessly leveraging trillions of data points combined into a Customer 360 and trusted audience segments. Further, its data scientists now build better machine learning use cases on the Databricks Data Intelligence Platform for personalizing Condé Nast’s products in advertising, consumer experiences and content recommendations.

Learn about how easily a modern marketing analytics stack comes to life with a Databricks demo (including AutoML) or try Fivetran for free today. You can also try a sample project for marketing analytics using Fivetran and dbt on the Databricks Data Intelligence Platform.

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