Data is the biggest asset for a business today, no matter the size. But data on its own, without proper organization, segmentation, and understanding, is essentially useless. As a business owner, if you can properly handle your business data, it can become a source of truth about your financial health, growth, and opportunities. However, it can be tricky, especially in omnichannel sales, because the more sales channels you have, the more data you need to analyze. And primarily, you need it put together and presented in a convenient form so that you can understand what those figures are telling you. Data aggregation tremendously helps you at this point.
If you’ve just thought about data aggregation being something belonging to enterprise level and big data, you’re quite far from being correct. Businesses of any size can share the benefit that data aggregation offers. And in this article, I’ll try to break down data aggregation and how it can help you manage your business and achieve goals more efficiently.
Read on to discover:
- How does data aggregation work?
- Types of data aggregation
- Presentation of the results
- What data can be aggregated?
What is data aggregation?
Data aggregation is a process of collecting data from multiple sources and presenting it to the end user in the form of totals or summaries. It’s a universal technique that finds its application in almost all spheres of our life. Whether it’s business, manufacturing, healthcare, public and political institutions, education, and much more – data aggregation allows you to effectively analyze large amounts of information and obtain statistical data necessary for scientific research, strategic planning, making important decisions, and so on.
Applied to business, data aggregation is typically used to create the summary reports for business analysis and provide statistics necessary for better decision-making, helping achieve business objectives more efficiently. Done the right way, it can become a powerful tool to help you better understand your business in so many ways: from sales and marketing success to customer behavior and more.
How does data aggregation work?
Let’s make a quick dive into the process of data aggregation and look at the steps it takes, such as extraction, processing (also called transformation), and presentation.
1) Extraction is the first step, at which data aggregation tools extract raw data from one or multiple sources and put it into a data warehouse or another database or storage.
2) Once extraction is completed, it’s followed by processing – the extracted data is being processed by the tools within a database, aggregation software, or middleware to get rid of duplicates and erroneous data, in other words, to get cleaned. Also, at this point, various functions apply to provide the requested result.
3) Presentation is the final step of displaying the result in a convenient and understandable form of a report, chart, or statistics.
Types of data aggregation
Based on the method and means, data aggregation falls into several types, such as time vs. spatial and manual vs. automated. Let’s break them down.
Time aggregation involves collecting data from a single source for a set period, such as a day, month, year, etc. Getting the number of monthly sales from a given sales channel can be an example of the time data aggregation type.
Spatial aggregation implies gathering data from different sources within a given period, like calculating the total number of sales across all your channels.
The difference between manual and automated aggregation is pretty straightforward. Businesses that don’t have too much data or don’t deal with many data sources might prefer to go with manual data aggregation. It can be as much as downloading reports from various platforms a company might be using and uploading them into a single dashboard for a more comprehensive view of the data. But you can imagine how time-consuming it can be. What’s more, manual data aggregation bears a high risk of accidental omission of data or other errors. That’s why automated data aggregation is a recommended option for businesses regardless of their size, as apart from saving considerable time, it provides more accurate results.
Presentation of the results
Depending on what you want to analyze and what types of results you want to receive, data aggregation tools may apply various mathematical functions when processing data, such as sum, average, or counting, etc. They’re as follows:
Sum – This function adds together all the specified data to receive a total.
Average – This function calculates the average value of the specific data.
Max – The function identifies the highest value for each analyzed category.
Min – This function shows the lowest value for each analyzed category.
Count – The function counts the total number of data entries for each analyzed category.
What data can be aggregated?
Basically, you can aggregate any data that a business might need to analyze for different purposes: to get relevant insights into the current state of the business finances, assess measures taken for strategic planning, understand trends or patterns, and many more. Depending on the industry and business objectives, the sources for data aggregation may include social media, users’ browsing history, customer personal data from apps or IoT devices, sales and transaction data from e-commerce and payment platforms, etc.
In the e-commerce industry, for example, the most informative data is usually on sales, customers, and products, as it gives a comprehensive view of a business and provides valuable insights for sales, marketing teams, and management.
The ways data aggregation helps e-commerce businesses
Let’s look at how aggregating data of various types, such as sales, customers, and products, can help e-commerce business owners increase the efficiency of managing their business and feel more confident making informed data-driven decisions.
Sales are the lifeblood of a business, so it’s utterly important to have the most accurate and up-to-date information on your sales from all the sales channels and payment platforms you’re using. By knowing your numbers, you can have not just a comprehensive view of sales but also identify the bottlenecks faster and look for improvement.
Having an aggregated view of your sales and customer data, you can easily track your most profitable customers and products, see how price changes impact your total sales, understand your seasonality patterns and make use of them to increase your sales, and many more.
Track efficiency of various sales channels
In the times of omnichannel business, it’s vital to carefully track the performance of your sales channels. As selling through multiple channels allows you to reach a wider audience, you need to clearly understand and be able to answer the demand of your customers from each channel. It can be tricky without having accurate numbers on sales and customer behavior across these channels.
What’s more, marketing techniques may work differently from channel to channel. For example, if discounts work the best for your, let’s say, Amazon audience, they may have a low impact on the sales at your Shopify store (or Instagram, or any other channel).
Understand and impact customer lifetime value
Customer lifetime value (CLV) is one of the metrics you need to track to understand the profitability of your business. It tells you how much revenue an average customer generates for you during their interaction with your company. So if you want to understand and improve it, you need an aggregated view of your sales and customer data. It can give you invaluable insights into customers’ behavior, such as how often they buy or what products they buy, etc. With this data in mind, you can come up with personalized offers, up-selling or cross-selling campaigns, or loyalty programs to encourage customers to buy from you more and stay with you longer.
Plan customer acquisition and customer retention activities
Do you need to work more with existing customers to increase sales or put more effort into acquiring new ones? It’s a question you can’t answer based on mere assumptions because the wrong strategy can drastically decrease your revenue. That’s why you need to know the percentage of your new and returning customers in general and for each sales channel. And it’s where aggregating data proves more than helpful, as it gives you the answer you need based on correct numbers from your sales channels. Thus, having less than 20-30% of returning customers, you know you need to focus on retention. And with more than 50% of returning customers, you can work more on acquiring new ones.
Better understand and track changes in customer behavior
Aggregating customer data enables you to transform customer behavior into measurable numbers that help track changes, identify and analyze specific trends and patterns in your customers’ buying habits, and evaluate customer satisfaction. It might enable you to plan efficient customer outreach and marketing campaigns with a higher level of conversion, and predict certain events, such as a seasonal drop in activity. For instance, it can help you analyze the effect of advertising campaigns, and so much more.
Manage inventory more efficiently
Inventory management can be very fruitful if you have all the necessary numbers neatly aggregated to give you a comprehensive outlook of your products on sale and in stock. It can help you evaluate the overall inventory performance, identify and minimize the risk of stock going obsolete, make more accurate demand predictions, and drastically cut carrying costs.
As you can see, data aggregation can be 360-degree useful, ensuring a better view and deeper analysis of your meaningful data to improve any part of a business you can think of. You can’t track your most essential business KPIs and metrics without aggregating data, and all the reporting is built on this technique.
How can you aggregate your business data?
The simplest example of data aggregation is writing down your numbers with a pen and paper and doing the necessary calculations manually. Frankly, I can’t imagine who’d want to do it this way for business analysis purposes (unless they sell, for example, a dozen hand-knitted mug cozies a month or something like that, but it looks more like a hobby). So let’s proceed with briefly looking at some more efficient data aggregation tools available for businesses.
Excel or Google Spreadsheets data aggregation tools
Excel and Spreadsheets are very good for reporting if you don’t have too much data to analyze. Their aggregation tools, Power Query and Query correspondingly, allow you to use simple functions, like Sum, Average, Count, etc., depending on the type of results you want to get. What’s particularly good about both Excel and Spreadsheets, they allow for visualizing the results of your aggregated data, making your reporting even more informative.
Data aggregation with Google Data Studio
Data Studio is a more sophisticated reporting tool that allows you to work with bigger data sets from many different sources. Its aggregation methods include Sum, Average, Count, Min, Max, and Count distinct. These aggregations can be applied not only to data sources but also to charts and calculated fields. The great benefit of working with Data Studio is that you can create various reporting dashboards by connecting multiple data sources, so you’ll be able to track, for instance, your KPIs in one place. The tool features a number of connectors that fetch your data from multiple sources, including social media, e-commerce and payment platforms, analytical tools, and more. It also features great visualization capabilities.
Data aggregation with SQL databases
Large companies that deal with huge data sets are more likely to use an SQL database to aggregate their business data. Databases also operate with the standard aggregation methods (Sum, Average, etc.) to present the needed results. Databases allow for storing and managing terabytes or petabytes of data. However, you’ll need to maintain powerful servers, and are likely to have to hire a database specialist, as managing a database requires some peculiar skills.
Data aggregation within business software
Many business software solutions, like CRMs, ERPs, accounting, e-commerce payment platforms, etc., come with in-built reporting functionality that allows you to have an overview of business operation and performance at different levels. Such reporting tools also use data aggregation to present the results from simple totals to averages, medians, percentages, and many more. In addition to using data from the internal storage, some of the solutions can pull data from external sources, which allows for a deeper analysis of various business metrics and performance indicators.
Thus, businesses may aggregate their data this or that way, depending on their purpose, capacities, and available resources.
Wrapping it up, data is an invaluable business asset. However, its biggest value lies not in the data itself but in the answers it can give you about your business, sales, customers, products, brand recognition, and more. Data aggregation is the technique that helps you get those answers. There are many ways businesses can aggregate data from different sources, from the simplest, like spreadsheets, to the most sophisticated, designed to process petabytes of business data.
Synder Insights is a powerful reporting and analytics tool that can aggregate data from a plethora of payment systems and e-commerce platforms, providing you with invaluable insights into your sales, customers, and product performance, powering up business management and informed decision-making.