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Why Marketers Need Automated Data Integration

September 21, 2023

automated data integration

In today's digital age, marketers are swimming in a sea of data.

The amount of data sources and the granularity of data available continue to grow at an exponential rate. 

This data deluge can be a double-edged sword. On one hand, it provides marketers with unprecedented insights into customer behavior and market trends. On the other hand, it can be overwhelming, especially if you're still relying on manual data integration methods.

To put things into perspective, recent research reports reveal some staggering statistics. According to a survey of Chief Marketing Officers (CMOs), 99% are using more than 10 data sources in their marketing efforts. 

So, it’s no surprise that 67% of CMOs say they’re overwhelmed by the amount of marketing data they have access to. And, as the amount of data continues to grow, copying and pasting data into a spreadsheet is becoming an unsustainable way to run a data strategy. 

So, automated data integration tools are becoming a necessity to reduce the workload.

In this blog, we'll explore what automated data integration entails and why it has become imperative for marketers.

What is manual vs. automated data integration?

Data integration involves a spectrum of processes, encompassing tasks such as data validation, data mapping, and data enrichment. In short, it means getting all your data in one place and in a format that makes sense for analysis.

Seems simple enough, right? 

But if you’re doing this manually, it requires individuals to log into multiple platforms, extract data from each source, and copy and paste this data into a unified document (often a spreadsheet), and, more often than not, have to adjust the data to reflect different naming conventions or different currencies or different regions. It’s tedious, time-consuming work and opens data up to human error.

Automated data integration, on the other hand, delegates these tasks to specialized software, streamlining the entire process.

What's the problem with manual data integration?


While data integration can be performed manually, this method presents a myriad of challenges and drawbacks.

  • Time: Manual collection and consolidation of data from numerous sources can be exceptionally time-consuming, particularly as data volumes escalate.
  • Monotony: The repetitive nature of manual data integration can lead to reduced productivity and employee burnout as marketing teams spend excessive time on routine tasks.
  • Error: Manual processes are susceptible to human error, making data accuracy and reliability a significant concern.
  • Scalability: As businesses expand and data needs grow, manual data integration struggles to keep pace with this scalability.
  • Flexibility: Adapting to new data sources or making changes in manual integration processes can be cumbersome and time-intensive.

Example: campaign optimization

Let's dive into a practical example to understand the challenges of manual data integration. Consider campaign optimization, a crucial aspect of marketing. 

Scenario: You're running a marketing campaign across multiple channels and locations. Your goal is to identify which locations are responding well.

Problem: Manual data integration is slow and error-prone. By the time you gather, validate, and integrate data from various sources, valuable time is lost.

Consequence: You may discover that certain locations were performing exceptionally well. However, it's now too late to allocate more resources to them.

In this scenario, the consequences are clear: you’ve missed an opportunity. 

The same logic goes for spotting risks. If you're running an AdWord campaign, for example, a slow analysis might mean that inefficient AdWord campaigns continue draining your budget unnoticed until it's too late to redirect funds.

Manual data integration hampers your ability to optimize campaigns promptly and make informed decisions. This is where automated data integration becomes crucial, enabling you to navigate campaign optimization efficiently and effectively.

Benefits of automated data integration

Automating these repetitive tasks associated with data integration provides marketers with a distinct competitive advantage. 

In the fast-paced realm of marketing, timing is everything. 

The ability to access, analyze, and act upon accurate data swiftly can mean the difference between capitalizing on an emerging trend and missing out on a golden opportunity. This is where automated data integration comes in. 

The advantages of automated data integration encompass the following.

Improved data quality and trust in data

Automation reduces the risk of human errors, leading to higher data quality and increased confidence in the accuracy of the data.

More timely decision-making

With automated data integration, marketers gain access to real-time or near-real-time data, enabling them to make timely decisions and respond promptly to changes in the market.

More informed decisions on campaign optimization

Automated data integration provides immediate insights into campaign performance, allowing marketers to optimize their strategies for maximum impact.

Stretch budget further

Efficient data integration ensures that marketing budgets are allocated to strategies and channels that yield the best results, optimizing return on investment (ROI).

Ensure data security and privacy regulations are met

Automated tools can enforce data security and privacy regulations consistently, reducing the risk of breaches and regulatory fines.

Frees up time

By automating the mundane aspects of data integration, marketers have more time to focus on analyzing data and deriving actionable insights rather than spending excessive time on data gathering and consolidation.

Enables data maturity

Academic research has unveiled a compelling correlation between data-mature businesses and their resilience to economic downturns such as recessions. Data-mature organizations demonstrate a higher ability to absorb economic shocks and adapt to evolving market conditions.

What are some challenges with implementing automated data integration?

While automated data integration promises a plethora of advantages, automating data integration is not without its share of challenges. Navigating the landscape of technology, budget considerations, and organizational dynamics can be complex. 

Lack of tools

Selecting the appropriate automated data integration tools that align with your business's needs can be a daunting task, given the multitude of options available.


Investing in automated data integration tools and infrastructure can be financially demanding, and not all businesses have the budget to support such initiatives.

Integrating with your pre-existing data stack

Efficiently integrating automated data integration tools with your existing data infrastructure can be complex and time-consuming.

Time to insights

Realizing the full benefits of automated data integration may require time, and organizations may not experience immediate results.

Fostering a data-driven culture

Cultivating a corporate culture that embraces data-driven decision-making can present a significant challenge, necessitating a shift in mindset and practices.

Data talent gap - upskilling vs. hiring

Addressing the shortage of data talent within the organization involves deciding whether to upskill existing employees or hire new personnel with the requisite skills.

Marketers need three things to get the most out of their data

To enhance data maturity, organizations should focus on cultivating a data-driven culture, making strategic technology investments, and advocating for automation. These strategies consistently lead to higher pre-tax earnings during economic crises. 

Although the temptation to prioritize short-term cost-cutting measures during crises is strong, adopting a long-term perspective and investing in compelling marketing efforts can not only help businesses weather the storm but also emerge stronger. 

Achieving and maintaining resilience and competitiveness hinges on a steadfast commitment to data maturity. So, to better understand what makes a business data mature, let's delve into the three key pillars of data maturity.

how to get the most out of data

Source: Adverity

Pillar 1: Technology

Selecting the right data stack is crucial for organizations to gain a competitive edge. Integrating data automation tools with complex reporting processes can be challenging but essential for long-term success. 

According to recent research, Insufficient data tools affect 18% of organizations, leading to overwhelmed teams and hindering effective decision-making. To address this, CMOs should invest in data tools that streamline data management and reporting processes.

Pillar 2: People

Expertise is vital for understanding and operating data automation tools. However, the shortage of data skills within teams inhibits investments in data automation tools, despite 85% of CMOs recognizing their competitive advantage. 

The data skills talent gap makes hiring and retaining data specialists difficult. Creating an environment where data professionals can thrive through automation, training, and a culture of experimentation is essential to overcome this challenge.

Pillar 3: Culture

Establishing an automated data workflow is crucial, but ensuring data reaches the right people and drives informed decision-making is equally vital. Data democratization, allowing all employees to access and utilize data effectively, contributes to a data-driven culture. 

Lack of support from the C-suite is a common issue, affecting 17% of organizations. Fostering top-down support for a data-driven culture requires framing data-driven solutions in terms of critical business questions.

Legacy systems and bottlenecks also hinder progress, affecting 15% of organizations, but investing in tools that bridge gaps and democratize data can break down silos and unlock valuable insights.

Embracing automated data integration

As the volume of data sources and the granularity of data available to marketers continue to grow, automated data integration has become a necessity rather than a luxury. It empowers businesses to establish a solid foundation of accurate, well-governed data that is readily accessible. 

In turn, this foundation unlocks exciting opportunities, including multi-touch attribution, cookieless tracking, personalized content delivery, and more advanced analyses involving technologies like artificial intelligence (AI) and predictive analytics.

In summary, automated data integration equips marketers with the tools needed to harness the full potential of their data, make informed decisions, and gain a competitive edge in today's dynamic marketing landscape. 

Embracing automated data integration is not just a choice; it's a strategic imperative for businesses looking to thrive in the era of data-driven marketing.

Learn more about data integration techniques and how they can help make strategic decisions. 

Data Integration Tools Automation is possible

Find the right data integration tools to pull data from several sources and formats into one place.

Data Integration Tools Automation is possible

Find the right data integration tools to pull data from several sources and formats into one place.

Why Marketers Need Automated Data Integration Discover the power of automated data integration for marketers. Find out how to streamline insights, optimize campaigns, and stay competitive.
Irina Prevalova Irina Prevalova is Director of Organic Marketing at Adverity. She is responsible for driving organic growth across all Adverity channels, and is based in Vienna.

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