Data Aggregation: How to Collect & Use Data [2025]

Imagine if you could leverage all the data generated by your company to make data-driven decisions in every field. Enter data aggregation.

Now imagine that you could accomplish this without tiresome manual data collection.

In theory, this is achievable for anyone willing to integrate data from all aspects of a business.

But realistically, you still have to cleanse data, set up storage, and engage in a lot of other data management activities. Data aggregation is not a silver bullet.

Yet, it's your ticket to the world of informed decisions backed with reliable data.

In this guide, you will explore everything you need to know about data aggregation and how to implement it effectively within your organization.

It's high time we dive in.

Tour de headlines:

What is data aggregation? Exploring the concept and significance of data aggregation.

Why is data aggregation important? A few words about the role of data aggregation in businesses.

An example of data aggregation. Let's see how data aggregation works on real-life examples.

Manual vs. automated data aggregation. The analysis of two different approaches.

Identify your data aggregation maturity level. This section helps you identify your current level of data aggregation in the company.

Data aggregation tools. Here, we review the best data aggregation tools on the market.

What is Data Aggregation?

Data aggregation is like tidying up a huge, messy room full of scattered information. It's about gathering lots and lots of data and neatly organizing it into a digestible, easy-to-understand format.

Whether you're working with a small data storage, like a spreadsheet or a vast data warehouse—think of it as a one-stop storage unit. Data aggregation helps you keep all your data neatly organized in that storage.

Best of all? It doesn't matter what industry you're in. Whether you're selling ice creams or jet engines, data aggregation is your secret weapon for staying ahead of the curve and constantly fine-tuning your operations. It's how the world's leading organizations are winning the game.

For example, marketing teams aggregate data across different platforms and channels to see the revenue generated by each channel and optimize budget allocation for profit.

Why is Data Aggregation Important?

Let's face it: data is a main competitive edge in today's realm. But actionable insights are often buried under heaps of redundant, duplicate data, making it hard to see the forest behind trees. That's exactly why data aggregation is so critical—it's your road map toward better business decisions.

Every click, every purchase, every customer interaction, generates a wealth of data. But without the right tools, this data might as well be a pile of puzzle pieces, interesting but not particularly useful. Data aggregation puts all those pieces together, revealing the big picture.

But it's not just about understanding your data—it's about making it work for you. When data is well-organized and stacked together, it uncovers patterns and trends and navigates you toward informed decisions.

Moreover, data aggregation helps reduce noise. Ad platforms often give a lot of irrelevant information, which can easily confuse you when trying to analyze it. With data aggregation, you can pick out the relevant bits (CPC, generated revenue, conversions, etc.) to facilitate decision-making and operate only with the data you need.

Data Aggregation Example

Let’s take a look at an example of data aggregation to better understand its value for businesses.

A marketing team dealing with cross-channel campaigns should analyze isolated data across tens of platforms to understand how their campaigns work. What’s more, they need to compare this data to identify the best-performing channels, recreate the customer journey, and, eventually, understand the channels they should invest in.

A team that aggregates data doesn’t have to deal with isolated data and gets all the insights from a single source of truth, like a data warehouse or a centralized spreadsheet at the very least.

With the rapid emergence of AI and machine learning, the need for organized and cleansed data has grown exponentially. The more data you have, the faster you can get business-ready insights and apply them.

In marketing, this applies to nearly everything, from adjusting your messaging to analyzing campaigns or even individual creatives. AI assistants can help you in numerous ways but require well-structured data to function properly.

Here’s our list of the top-rated AI lead generation tools to help you find the one that suits your use case.

Manual Data Aggregation vs. Automated Data Aggregation

When it comes to aggregating your data, you can try two different approaches.

Manual data aggregation is by far the most straightforward way to collect all your data in one place. Still, it comes with significant shortcomings, such as faulty data and inefficient time use.

Automated data aggregation, on the other hand, requires some preparation before you get your data but brings numerous benefits in the long term. Let’s take a look at both methods individually.

Manual data aggregation

Aggregating data is an extremely tedious process, especially if your company is in the early stages of adopting a data-driven culture.

Click the export button. Sort through an Excel sheet. Reformat it in a way your data from different sources aligns by format or naming conventions. Create charts to compare the performance/budget/progress of your multiple marketing campaigns.

Sound like a familiar routine? You’re certainly not alone.

This export/sorting/reformatting process is not unique or new - it is one of the most common ways to know how campaigns are performing at some point or another. Every marketer faces it frequently.

What’s so bad about it? Here’s what:

Manual data manipulations often lead to mistakes and faulty data.
Marketing teams waste over 30% of their time crunching numbers in spreadsheets.
It’s almost impossible to aggregate multiregional ad performance data for large brands.
The lack of a real-time view of marketing performance limits campaign and spend optimization potential.

The list may go on, but the main idea is evident at this point. Teams that ignore automated data aggregation miss opportunities to optimize campaigns and act on their data.

The main reason why most team stick with manual data aggregation is its simplicity. It doesn’t require technical skills or advanced data infrastructure. You can go straight to your marketing platforms and copy-paste data into a spreadsheet. But as you see, this approach won't get you far.

Automated data aggregation

So, what’s the better alternative? Automating the data aggregation routine is a more efficient way of preparing your data for further analysis.

Usually, teams use APIs of different platforms to automate data flow to centralized storage. Most marketing platforms and CRMs offer free access to their APIs so that teams with the required engineering skills can set up their own data pipelines.

Of the shortcomings, the need for continuous API maintenance, engineering resources, and strong data expertise can be noted. Google, for example, regularly rolls out updates for their APIs and marketing platforms in general (Adwords API sunset and Universal Analytics sunset are a few of the recent examples). These types of significant changes force teams to modify their pipelines and check the correctness of incoming data.

Thankfully, marketing teams that don’t have sufficient engineering resources can easily automate data aggregation using marketing analytics platforms.

Improvado, for example, integrates with 500+ marketing and sales platforms to pull all data in a centralized data warehouse. As a marketing-first platform, Improvado handles every tech aspect of data aggregation (API maintenance, storage setup, data cleaning, etc.), allowing marketers to do marketing, not data engineering.

You can connect new platforms in just a few clicks, and if Improvado doesn’t have a specific platform you might need, their team can build a custom connector on request.

The bottom line is that you don’t need to be a data guru to automate data aggregation. Marketing analytics solutions can automate all technical processes and significantly elevate your analytics.

A Deep Dive into Automated Data Aggregation

The automated data aggregation process works due to software that integrates with your data infrastructure. The aggregation solution extracts data from multiple sources to combine and bring it in a unified format. In terms of marketing, the platform pulls data from ad platforms, web analytics software, social media, and so on.

Then, the software normalizes data using pre-built normalization algorithms. They automatically clean the data from duplicates, align disparate metrics, and remove any inconsistencies. With all these operations, analysts receive analysis-ready insights that can be used for further research.

Then, the data aggregation system stores information in a dedicated warehouse. It’s much easier to access insights with centralized data storage. Mind that the warehouse should be optimized for the processing of large data sets. Google Big Query and Amazon Redshift are some of the most popular cloud-based solutions.

Finally, with the data in your warehouse, you can streamline it right to your dashboard or perform complex SQL queries for even more detailed insights. For example, Improvado offers ready-made dashboard templates that allow you to jumpstart your analytics and get detailed charts that bring more understanding to your marketing efforts.

Identify Your Level of Data Aggregation Maturity

There are different expertise levels to data aggregation. While some teams might be doing essential actions with their data, others are completely ignoring data aggregation processes.

We’ve identified three levels of data aggregation - beginner, intermediate, and advanced. Figure out which one you are and how you can jump to the next level.

Beginner at data aggregation

A beginner in data aggregation isn’t really aggregating any data at all. Your main source of truth for marketing performance is the platforms’ built-in reporting tabs.

For example, you might be using Google Analytics to identify pages that drive more conversions. So you use this information to direct traffic to that particular page and generate more conversions.

While you still make a decision backed with data, you’re missing a bigger picture because of ignoring data that comes from other channels. For example, you don’t know which campaigns drive the most promising traffic to your landing page and how much you’re spending on these campaigns. This hinders your spend optimization activities and overall marketing performance.

Intermediate at data aggregation

Next on our list are companies that manually aggregate data in spreadsheets.

While it’s not the most effective way to do analytics, it’s a significant step forward compared to the beginner level. At this stage, companies achieve a comprehensive picture of their efforts, even though it’s a huge time suck and data doesn’t update in real-time.

With spreadsheets, you can build customizable charts to visualize your data and calculate more complex metrics (such as ROMI or CPA across all channels).

The problem is that this dashboard is always stuck in the past. By the time you finish gathering your data, it already becomes obsolete. That’s why it’s good for tracking the global picture, but it doesn’t work for on-the-go campaign optimization or closely monitoring the performance of your marketing experiments.

Still, it’s a good place to start and it’s quite easy to advance to the next level with the right tool.

Advanced at data aggregation

Finally, we’ve arrived at the point of utmost proficiency in data aggregation. If you recognize yourself here, you’re most structuring your KPIs and marketing strategy around hard data rather than guesswork.

Your team has centralized storage for all the data they need for day-to-day activities and strategic planning. The storage is automatically populated with data via a data pipeline that seamlessly connects to any of the platforms you’re using.

Additionally, all your data should be cleansed and aligned in terms of format and naming conventions, so that you can make sense of it.

Marketing analytics platforms such as Improvado pipe your data from all platforms and send that data straight into your visualization tool and data storage.

You can also set up a data aggregation system on your own. However, finding a reliable vendor will save you time and resources, especially in the long run through omitting API and data pipeline maintenance costs.

The Best Data Aggregation Tools

Now, as we’ve discussed all the aspects of data aggregation, it’s the right moment to talk about the tools that can help you gather your data, organize it, and turn it into a digestible format.

Improvado - Large Brands & Agencies

What is Improvado?

Improvado is a marketing analytics platform that helps companies aggregate marketing and sales data. The platform gathers data from 500+ platforms in a storage of your choice to make it accessible for all team members, prepare for further analysis, and funnel it to a visualization tool.

Improvado is more than just a data aggregation tool. It’s an end-to-end solution for all marketing analytics needs. Ranging from gathering your data across all sources to querying data and creating custom dashboards for any business use case, Improvado got you covered. With the platform’s professional services offering companies get hands-on help with any data engineering or analytics issues that might arise.

Who should use Improvado?

Improvado is designed to suit any requirements of marketing teams in large brands and agencies. Unlike other data aggregation solutions, Improvado allows you to dig deeper into your data and analyze paid ads performance data by ad and keyword levels. With this level of insight, you can see which individual keywords or creatives resonate best with your audience and which should be revised.

Plus, Improvado handles all things data analytics, from pulling data together to visualizing it in a neat dashboard. This allows marketers to dedicate more time to making informed decisions, experimenting, or spotting new trends in their campaign performance. You’d be surprised how many hours a week routine data operations might eat up.

Improvado also does a great job with support and customization services. Suppose you need any help with building custom dashboards, calculating custom metrics, or even deploying Improvado on your on-premise instances. In that case, Improvado’s team of analysts and data engineers can always help you out.

A willingness to go the extra mile for a client, compliance with all mandatory security protocols, and unlimited room for customization are what makes Improvado a great solution for big-time companies.

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Improvado Pricing

Improvado offers a pricing plan tailored to each customer’s requirements. It doesn’t tie clients to a one-size-fits-all package because each team has different use cases.

You can get a quote after talking to the company representative about data and reporting needs on a 30-minute call. That way, you can rest assured that you’ll pay only for the features you need.

Share some details about your company and choose the best time to discuss it with an Improvado representative.

Improvado.io Integrations

Improvado integrates with 500+ data sources, covering every aspect of marketing analytics, from ad platforms and web analytics tools to CRMs (Google Analytics, Facebook Ads, HubSpot, Shopify, Marketo, etc.).

This extensive library of integrations saves hundreds of hours on executing API requests, maintaining connections up and running, and fixing any errors that might occur.

Improvado extracts highly detailed data. The platform provides access to 37,000+ metrics and dimensions for the supported data sources. This is more than enough to cover the needs of the most advanced marketing teams that need a comprehensive overview of audiences, cohorts, paid ads performance, etc.

Domo - for basic data colletion

What is Domo?

Domo is data aggregation software that specializes in data visualization and business intelligence.

Domo is best for C-level executives at enterprise companies looking for a company-wide (non-marketing specific) BI tool to create executive level dashboards.

The important thing to note is that it is not specifically focused on marketing data, just business data in general. That means, it's capacity is vast when it comes to business intelligence and executive dashboards company-wide, but may not be the best pick for aggregating and visualizing marketing data specifically, because marketing integrations are limited, the connectors don't run as deeply and the tool overall may be too expensive for just the marketing team's use.

Domo Marketing Integrations:

52+

Domo Pricing:

Pricing is offered on an annual subscription basis, and depends upon the number of users that need access. The company does offer a 30 day free trial.

Stitch - advanced technical solution for data teams

What is Stitch?

Stitch is a cloud-first, developer-focused data aggregation platform for rapidly moving data. The tool allows you to aggregate your data where you want it in a matter of minutes.

Who should use Stitch?

The platform is a simple, extensible ETL built for data teams. Users can extract data from many different sources, load that data into leading data platforms, and analyze is with leading tools.

Stitch Pricing

Stitch offers a range of plans, starting at their free plan and up to $1,000 per month. There is also an enterprise plan with custom pricing.

Stitch Integrations

Stitch offers a little over 80 data sources.‍

Increase your marketing team's effectiveness with automated data aggregation

If you think that data aggregation could help your business, but don't have the required skills or resources to implement it, don't worry. Each of the above platforms can help save your time and nerves if you pick the one that suits your business case.

If you're a large company or an agency looking to automate marketing data aggregation and analytics—Improvado can help you out. Schedule a quick consultation with us.👇

Schedule a 30-min call to learn how Improvado can elelvate your marketing analytics with data aggregation.

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Frequently Asked Questions

What is data aggregation?

Data aggregation is the process of accumulating data in a normalized and structured format. Data from disparate sources requires thorough optimization. With data aggregation, you can extract raw data, turn it into analysis-ready insights, and store it in the warehouse of your choice.

What is data aggregation used for?

Analysts use data aggregation to accelerate and facilitate the analysis process. Having insightful datasets in your data warehouse rather than a chaotic pile of raw information helps data scientists gain a different perspective on the research object.

What is an example of data aggregation?

Advanced marketing specialists use data aggregation to gather actionable insights on their marketing performance. Automated systems such as Improvado or Adverity extract data from marketing data sources and align them with each other to facilitate further analysis. Then, platforms store data in a data warehouse and streamline insights to visualization tools to help advertisers create reports on their campaigns.

Why is data aggregation needed?

Businesses aggregate their data to accelerate the analysis process and uncover previously overlooked insights. A well-structured data doesn’t require any manual manipulations, thus increasing the speed and accuracy of the analysis.