Virtually every marketing organization is taking steps to become more data-driven, but there are considerable gaps between vision and reality. According to a 2018 Salesforce report, only 47% of marketers have a completely unified view of customer data sources.

Meanwhile, customer data complexity is only increasing. According to Salesforce’s 2020 “State of Marketing” study, the median number of data sources leveraged by marketers is projected to jump by 50% between 2019 and 2021.

To bring their data together effectively for a true 360-degree view of customers, marketing organizations must follow the best practices below. For more details, download our ebook, 5 Best Practices for Bringing Together All Your Marketing Data.

1. Develop a Comprehensive Data Strategy

Even as marketing organizations increase their spend on data and analytics, many don’t have a comprehensive strategy. Instead, they leverage ad hoc, loosely coupled systems in an effort to infuse data into their operations. Additionally, buckets of data remain in separate silos and can’t be accessed or queried in real time.

Here are three areas a data strategy should address:

  • People: For marketing data management to be sophisticated, organizations need to recruit data scientists and analysts who are highly skilled at distilling insights from data, as well as IT managers to make customer data available to those individuals. 
  • Objectives: Which users need access to data, what are they trying to achieve, and how will the success of data-driven initiatives be measured?
  • Technology: Marketing organizations need clarity on the storage, security, and accessibility requirements to support their intended data use cases. They also need to determine whether to build their own customer data platform or buy an out-of-the-box solution to activate their customer data. 

2. Identify Which Data Sources Are Needed and How to Ingest Them

By zeroing in on the marketing data sources required to advance specific objectives, companies can avoid complexity and expense they might incur by grappling with more data than they actually need. For example, companies may not need to ingest clickstream data from Google Analytics if they are using Adobe Analytics as the source of truth for website behavior.  

Some customer data, such as purchase history, is stored in internal databases, but most data needs to be ingested from its original source. To avoid burdening engineers with ongoing data maintenance, marketing organizations need an ETL tool with prebuilt connectors to data sources. These solutions extract data from the original source, clean it or change it into a useful form for the company’s purposes, and load it into the company’s data warehouse. 

3. Unify Data to Create a Single Source of Truth

Once marketing data sets are ingested, the data needs to be stored in a single platform that can natively support both semi-structured and structured data. Its infrastructure needs to be sufficiently flexible and scalable to enable near real-time data integration. It also needs to provide a single source of truth in the form of clean, merged data sets that a variety of teams can use.

The solution is a platform that can instantly scale up capacity to deliver more computing power on demand, freeing up teams to produce outputs as quickly as they can. Instant elasticity removes scheduling and data batching concerns, letting data scientists run complex models and enabling nontechnical users to access dashboards whenever they need to, with no “noisy neighbor” challenges. 

4. Make Data Available to Nontechnical Users Across Functions

To unleash the full ROI of their platform, companies need to think beyond the productivity of data scientists. The platform should be accessible to a large cohort of less-technical users across business functions, including Operations, Compliance, Product, Business Development, Partnerships, and, of course, Marketing. 

If a platform is to cover a range of use cases and be adopted companywide, marketing, supply chain, finance, compliance, and other types of data needs to be unified with governance in place. Robust access controls to prevent data misuse are critical when sensitive information, such as the company’s financial performance or customer PII, is ingested.

5. Prioritize Areas Where Advanced Analytics Can Have the Greatest Impact

By querying and analyzing marketing data in one unified platform, companies can increase customer lifetime value, optimize ad spend, reduce churn, and more. It’s important to prioritize outcomes up front and then communicate those decisions to the entire marketing organization to ensure that collective energy is channeled in the right direction.

To learn more about best practices for unifying marketing data and making it actionable for high-priority marketing programs, download our ebook, 5 Best Practices for Bringing Together All Your Marketing Data.