Data aggregation allows a business to ingest data from different sources, bringing it into one place. It is a treatment of data that exists as a solution to a business problem: data silos.

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Data aggregation joins and scrubs the information into the same format so it is usable by the business. Basically, it breaks down silos. Data silos → connected data.‍

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Think of data aggregation in this simplified way. You are a business. You have different places where you collect customer information. These include: your customer relationship management (CRM) system, your email marketing service provider, your billing system for customers, your customer support platform. Similar customer information exists across all systems (email address, first name, company name). But the storage format is different. Data aggregation pulls it all together and formats it in a way that you can view and act upon it. In one place.

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Why Data Aggregation Is Important to Businesses

There are two very different worlds that can exist when it comes to data: 

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World Without Data Aggregation:

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Data lives in different places. Processes are very manual to act upon the data — whether to report on it or update it. Instead of going to one place, you have many different places to do exports or make edits. It takes 50 minutes to update information in 5 different systems vs. 10 minutes in one central place. Additionally, there are often redundant instances of a customer in each different system. Jane Doe has a sales record in the CRM. She also has a marketing  record in the Email Service Provider (ESP) platform. As a business operator, I must go into each system to piece together my understanding of the customer. There is no one place where I can see a unified footprint of their behavior or my outreach to them. 

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World With Data Aggregation: 

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With data aggregation in place, the business now: 

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• Has connections into different data sources
• Ingests the data into one place
• Matches different types of data into the same format 
• Analyzes the consistently formatted data
• Sends data to destinations
• Takes back information from destinations 
• Connects destinations to sources to measure performance

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Think of this example. I pull guest data together into one place. I then create a targeted segment of customers that I want to reach out to. I message them through a destination source. Then, I pull analytics from that destination source back into one place. This shows me revenue driven from that customer touchpoint. A platform that does this is called a Customer Data Platform (CDP).

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CDPs are important because without them, a marketing team has: 

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• Data silos
• Manual campaign triggering 
• No automatic ability to attribute performance in destinations back to sources 

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Data aggregation creates connections to sources to ingest data. Then, it enters it into a consistent format. We agree on this, right?

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As an analogy, think of a wash & fold laundry business. Neighbors bring their clothes in different bags to one address. Then, the owners clean and organize each piece of laundry to present it in the same format. At the end of the day, clothes are all folded, in a neat rectangular pile. 

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What Problems Exist With Implementing Data Aggregation? 

Despite what you would think, businesses forgo the benefits of data aggregation. Why? For the following reasons:

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Common Problem 1: Your Team Lacks Expertise

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No one on the team is technical enough to put the diagram above into place. 

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Common Problem 2: Buying a CDP Is Expensive 

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It costs $20,000 to $30,000 per year to buy a CDP.

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Common Problem 3: Lengthy Setup Process Is Prohibitive

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It can take many organizations months to get all groups of decision makers aligned to purchase a CDP. This involves a lengthy evaluation process. The process of data aggregation does not begin for at least a year, on average, after evaluation kicks off. 

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Common Problem 4: No Clear Path to Data Interpretation

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In a way, data aggregation is only half of the problem. You can collect data, but it's meaningless if you can't both analyze and act on it. This is why the second half of data aggregation is typically data interpretation. You need a process in place for analysis, resources to automate this process (the best data aggregators have this built in), and colleagues to own next steps off of insights.

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Let’s Recap: How Does Data Aggregation Work, Again? 

Data aggregation captures data and processes it into a consistent format.

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It gives businesses a full view of a customer. It provides insights across all platforms that are sources for the data aggregation. It treats the data in a way that it becomes actionable.

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Centralized, consistent data offers these benefits to marketers:

• See how sources perform against one another and recognize general trends over time. 
• Ask and answer questions about the business (which one brings the most data? The most revenue for the business? Which is growing fastest?) 
• See full customer profiles in a specific group (out of the customers in the groups above — who are they? What are their names, email addresses, full history with the business?) 
• Size customer groups. (Who has taken action X in Source A and done action Y in Source B but not action Z in Source C?)
• Use targeted marketing to communicate with customers based on their specific behaviors and preferences. 
• Prove marketing effectiveness by creating a sync between data sources and destinations.

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