This may come as no surprise but data challenges are everywhere with 98% of marketers and agencies encountering barriers in data orchestration and utilization. This stat comes directly from The State of Data Collaboration: A Global Perspective research report summarizing a survey of more than 1,200 marketers and agencies across six global markets.
Data orchestration plays a fundamental role in integrating and harmonizing diverse data sources, providing a more holistic view of customers and facilitating actionable intelligence. By breaking down data silos across brand touchpoints and advertising channels, data orchestration allows for enhanced analytics and insights-driven strategies, ultimately improving customer relationships and acquisition. This unified approach also helps build enriched, data-informed audiences by combining first-party and partner data. Orchestration supports audience enrichment and persona building including through machine learning models.
Additionally, data orchestration enables consistent and up-to-date customer profiles across various platforms, which is essential for effective identity-powered activation. By ensuring customer identities are accurate, organizations can activate audiences reliably across multiple channels and safeguard addressable advertising.
While the examples above are some of the most important use cases for marketing data management, there are few limits when it comes to what businesses can do with all the first-party data they collect.
However, if your data is siloed and not reaching the right systems and teams, its usefulness is severely limited.
That’s where data orchestration enters the conversation.
What is data orchestration and its role in marketing
Data orchestration is an increasingly important automated process of moving, managing and merging data from different sources to break down data silos and make it available to more business units for deeper analysis and actionable marketing insights.
Data orchestration for marketing and advertising teams has arguably the most unique and challenging environment. For starters, the proliferation of marketing and advertising technology (madtech) has created a complex landscape. Marketing and advertising teams also have to deal with a wide collection of data sources including the aforementioned madtech, diverse digital channels, an array of data partners and more. Not only that, but they face changing and growing privacy concerns and regulations.
Whether it’s UX, analytics, audience intelligence, enrichment or hundreds of other functions, it’s fair to categorize it all as in pursuit of attracting, converting and retaining customers more effectively.
Altogether, industry research firms and vendors alike like to refer to this as a marketing data stack. A critical component of any platform or tool within this stack is integration, a core piece of the data orchestration process. Without it, automation goes out the window and marketers are forced to rely on manual data migration which is not only time-consuming and inefficient but also unnecessary given the myriad of tech available today.
For marketing organizations (and practitioners), key examples of how data orchestration can help include:
- Pulling together fragmented first-party customer data from multiple channels that can be activated for highly targeted, personalized campaigns.
- Data enrichment on your first-party data from other data sources that can help create a more comprehensive view of your customer, including their needs, interests, preferences and purchasing patterns. This leads to better decision making not just in marketing but throughout the organization, including product development, pricing and more.
- Not needing to spend hours manually exporting, cleaning, and organizing data. Data orchestration tools do this automatically, reducing errors and saving time. Instead, it lets marketers act more quickly by using real-time data to optimize campaigns on the fly, instead of waiting for reports to be compiled after-the-fact.
Data orchestration has become critical for marketers and advertisers precisely because it enables them to improve customer experience and achieve performance goals. By synchronizing data across various platforms, marketers can ensure customers receive the right messages at the right time, creating a cohesive and impactful brand experience.
How Data Orchestration Helps Common Marketing Data Challenges
The State of Data Collaboration: A Global Perspective research report also provides insights on data challenges across marketing orgs and agencies around the world. When asked about their challenges, here are the most popular themes:
We could go deep in the weeds on these common marketing data challenges but two higher level themes stay consistent across almost all of them: trust and complexity.
Challenge #1: Trust
It’s a common experience for marketing teams and executives to question the validity of their data at some point.
Data orchestration improves businesses’ trust in data by managing and optimizing how data flows across different systems, ensuring it’s more accurate, timely, and accessible.
Here’s how:
- Automated processes cleanse, transform, and validate data, reducing errors and inconsistencies that could affect accuracy.
- Standardized data provides confidence across the business, as it consistently meets accuracy and quality standards.
- By enforcing data governance policies and ensuring compliance with regulatory standards, organizations can use data responsibly, increasing trust.
- Automated checks identify and correct issues before flawed data reaches end users, ensuring reliability.
- Data orchestration offers a single, unified view of customer data from diverse sources like social media and CRM platforms, which enables a more comprehensive understanding of each customer.
- Accurate, clean data supports targeted marketing, allowing personalized content and messaging that customers are more likely to trust.
Challenge #2: Complexity
Pointing back to the discussion around the marketing data stack and how many layers and systems might be involved in your own stack clearly shows how complex data management and ops have become.
Data orchestration streamlines these complex data challenges to help marketers in a number of ways:
- Real-time synchronization ensures that decisions are based on the latest data, reducing reliance on outdated or fragmented information.
- Integrated data from various sources breaks down silos, creating a more complete picture and allowing for deeper, more relevant insights.
- Data orchestration automatically updates marketing data in real time, allowing teams to respond swiftly to trends and optimize campaigns on the fly.
- As data needs grow, scalable systems allow data operations to expand without compromising performance, supporting stable, secure operations.
- Orchestration aligns data across teams and platforms, making insights accessible and reducing redundant workflows for more efficient campaign management.
Why Marketers Should Care About Data Orchestration
You don’t need to be a data expert to reap the rewards of data orchestration. If you’re a marketer looking to streamline operations and improve campaign performance, here’s why investing in data orchestration is essential:
Increased ROI through more accurate targeting
Data orchestration enhances the precision of customer insights, which leads to more targeted campaigns and, ultimately, increased ROI. By connecting, cleansing, and unifying data across platforms, marketers can rely on accurate and complete profiles, making their targeting more efficient.
Orchestrated data enables sophisticated segmentation and look-alike audience building, improving both reach and relevance, which directly translates into campaign success.
Moving faster and responding in real-time
In today’s fast-paced marketing environment, agility is crucial. Orchestrating data in real-time allows marketers to monitor customer behavior and campaign performance as they unfold. For instance, if a campaign underperforms in its initial phases, real-time data orchestration allows marketers to adapt and refine their approach instantly, perhaps by tweaking ad copy or reallocating budgets across channels.
Adjust on the fly ensures campaigns are always aligned with the latest customer trends and preferences, maximizing their effectiveness.
Deliver the customer experience they’ve come to expect
Customers now expect a unified experience across channels—from email and social media to in-app messages and web interactions. Data orchestration helps marketers connect touchpoints from various systems, consolidating them into a single view of the customer journey.
Marketers can ensure consistency in messaging, timing, and offers, reducing friction and enhancing customer loyalty. This seamless experience is especially important for complex journeys where customers may move across devices and platforms.
Enhanced personalization through enriched first-party data
Enhanced personalization is the holy grail of modern marketing, and data orchestration is essential to achieving it (combined with data collaboration which we’ll get to shortly). By merging first-party data with additional enriched datasets, orchestration helps get you closer to a 360-degree view of each customer’s preferences, behaviors, and purchase history.
This enriched data not only deepens understanding but also allows for hyper-personalized offers and content recommendations. For example, an e-commerce brand can use orchestrated data to identify when a customer is likely to buy a certain product based on their browsing history, allowing for personalized emails and in-app messages that are far more likely to convert.
Combining data orchestration with data collaboration platforms
Data collaboration platforms pair well with data orchestration efforts as both enhance data’s usefulness for marketers, but in complementary aspects. Data orchestration automates the flow of data within an organization to ensure it’s accurate, timely, and unified, whereas data collaboration platforms enable companies to combine their data with external sources. This vastly expands data insights through first-party data enrichment, especially important for marketers who rely on diverse, updated data to understand their audiences in a post-cookie world.
Together, these tools help marketers create more comprehensive customer profiles and apply insights for personalization. Orchestration ensures the clean, real-time movement of data within a business, while collaboration platforms enrich first-party data with external insights. This combination enhances campaign precision, agility, and audience segmentation, allowing marketers to build personalized, seamless customer experiences that drive meaningful engagement and ROI.
How to Get Started with Marketing Data Orchestration
Starting or maturing your company’s data orchestration program involves several strategic steps, from foundational groundwork to scaling and optimization. Here’s a helpful way to approach it:
1. Define Clear Objectives, Requirements and Stakeholders
The following advice applies to any program or major software investment. Identify why you even need this in the first place, in this case, data orchestration. Define specific goals, such as improving data quality, streamlining real-time analytics, or enhancing customer personalization (likely all of the above). Engage key stakeholders across departments—marketing, IT, and data analytics—to ensure alignment and cross-functional support. Build a requirements doc that you’ll use when assessing different vendors/tools
2. Assess Data Sources and Infrastructure
Inventory existing data sources, integrations, and infrastructure including finding where data silos exist, evaluating data quality, and understanding the current data flows across teams. Don’t forget shadow IT in this review. Businesses in the early stages might prioritize consolidating scattered data in their most critical systems (or just don’t have that many systems yet and want to get ahead of it), while mature organizations may look to improve data velocity or enhance data governance.
3. Choose (or Build) a Data Orchestration Platform
The next step is selecting the right platform. For businesses just starting, look for an orchestration tool that offers user-friendly interfaces and essential features, such as data integration, transformation, and automated workflows. More mature programs might invest in platforms with advanced capabilities like real-time data processing, machine learning integrations, or support for multi-cloud environments. While other organizations may want to build their data orchestration without having to introduce yet another third-party tool into their data stack. Whether you build or buy, also consider how a data collaboration platform will add significant value once your data orchestration process is up and running.
4. Establish Data Governance and Compliance Protocols
Data governance is crucial as orchestration scales data access and processing. Set protocols for data privacy, security, and compliance (such as GDPR and CCPA), ensuring data flows meet both internal standards and regulatory requirements. Mature orchestration programs often integrate automated governance checks to maintain compliance continuously.
5. Implement, Test, and Iterate
It’s pretty normal to start with a pilot program, focusing on a specific use case like real-time data for marketing personalization or whatever is most pressing to your business. Once implemented, test the workflows and monitor that it’s working the way you’ve planned. Collect feedback from teams to identify areas for improvement. Over time, mature programs should adopt iterative practices, continuously refining workflows and expanding orchestration capabilities to new areas.
6. Expand with Scalability and Optimization in Mind
As the program grows, focus on scalability and optimization. This includes integrating new data sources, improving data processing speeds, and possibly adding AI-driven features for predictive analytics. Mature organizations might also consider automating data orchestration further to reduce manual oversight and enhance efficiency.
Starting with clear goals, foundational tools, and governance protocols allows businesses to lay a robust groundwork. Maturing the program requires iterating on this foundation, enhancing capabilities, and scaling to meet evolving data demands, ultimately enabling the organization to make smarter, data-driven decisions at every level.
By now, it’s likely clear how crucial automation has become for businesses, especially when it comes to managing the ever-growing volume of marketing data. With countless systems, tools, and channels to navigate, ensuring a smooth and clean data flow is essential.. Data orchestration provides a framework and guidance to this newer data automation and management challenge facing businesses in the digital age.
The bottom-line is data orchestration simplifies and streamlines a lot of formerly manual work, letting you and the rest of your marketing colleagues focus on insights, strategies and execution instead of excessive and cumbersome data operations. Once you’re in good shape, you can keep up with customer demands and market trends more effectively, turning data into an advantage not a chore.
How Does Lotame Help with Data Orchestration?
Lotame’s data collaboration platform, Spherical, is a critical destination for marketing teams and their data as it’s where your first-party data can come to life in more expansive ways. Digital marketers can use Spherical to combine data internally and partner externally for actionable customer intelligence, data informed audiences, and identity powered activation.
As companies continue to face challenges with data clean rooms due to high costs and technical challenges, they’re looking towards solutions like Spherical as they offer a more versatile solution with a broad set of use cases and tangible outcomes, such as improved audience targeting and enhanced personalization. (State of Data Collaboration Report, 2024)
If you want to learn more about how Lotame can connect, enrich and activate your first-party data, contact the team here to get started.