Improve Sales: Product Data Aggregation and Analyzing

Data aggregation is getting information from several sources, compiling it, and simplifying it for further analysis. The collected data helps to understand the activities of the retailer and the interaction of the buyer with the shop's products. Also, aggregation shows the seller the consumer's journey from viewing the product to purchasing. It helps to understand the needs and motives of customers better.

The primary data for aggregation:

• population;
  
• demographic situation in the region;
  
• consumer habits;
  
• market infrastructure;
  
• trading base;
  
• the scale of sales.
  

As a method of increasing sales and profits, the aggregation has many positive aspects so that the retailer does not have to spend their time collecting and processing data manually. The main advantages of aggregation include:

You can collect, process, and analyze data manually. But it is a very voluminous and routine process that can take too much time. While one salesperson aggregates data using a notebook and pen or spreadsheet, another uses special tools, simplifying work and saving time. Inefficient manual data aggregation may impact your business negatively. It happens due to several reasons:

Progress in the e-commerce world does not stop for a second. Therefore, while someone counts the number of goods and sales manually, competitors make profits.

Data aggregation tools make this process much easier by automating it. Solutions for collecting and transforming information have several options to implement in a business, which depend on the sources and software used. How to aggregate product data at different stages:

When choosing the right tools for aggregating data, keep in mind two main features of these tools:

• Collecting customer information.
  
• Analysis of the received data and preparing reports.

Aggregation tools must perform their functions in a complex. Otherwise, the picture won't be complete, and promotion solutions won't be effective. Good software should identify all available data sources, compare the information received with external resources, and analyze and provide reports in a readable format. It will be good to have a tracking panel allowing sorting data by different parameters. These features make aggregation much easier and faster. After all, processing large amounts of information is a lengthy task, even with automated tools.

It would seem that the answer is obvious: to increase sales and profits. But that's not all that aggregation can do. Having all the information about sales, you can distinguish separate categories of indicators: consumer preferences, user experience, market trends, and so on. It expands the opportunities for retail promotion.

Aggregated data is essential for aggregated marketing. It is a strategy that focuses on the general needs of buyers for a particular product or service. That is, it analyzes the entire target audience in the market as a generalized unit with similar interests, motives, and expectations. That's why aggregated marketing is also called mass marketing.

Also, sales data contribute to building new business development strategies. On their basis, a universal marketing program may be formed with a single offer for all consumers. Aggregation is always based on the "one product — one strategy" model. Therefore, a product promotion plan should be repeatedly reworked and suitable for promotional events aimed at a specific product or service.

Marketers consider aggregation as a versatile method of expanding their customer base. After all, it does not focus on consumers' finances or their preferences when choosing a particular product. The main advantage of aggregation is the ability to immediately interact with large groups of the population, which ensures better business indicators.

For effective work, it is necessary to set up means for converting information. Aggregation tools should collect data from reliable sources. It is especially true for the personal information of consumers. Compiling such information is provided via the Internet of Things. For example:

• social networks;
  
• interactions with a web page;
  
• product view histories;
  
• purchase histories;
  
• linked email addresses.
  
  

After receiving information from these sources, it is ready to be processed. You get compiled databases that can be edited at your discretion or transformed into another format. It allows you to highlight only the information necessary for solving a specific task.

Further activities are connected with data analysis. Before you get started, you need to state the research purpose clearly. Determine how to handle data. For example, provide categorization and counting. The final result of the analysis is best presented as a report. For clarity, you may prepare a graph.

In the context of aggregation, you need to learn another process called disaggregation. It means the division of received information into smaller categories. This practice is often used to improve average turnover rates.

How do product managers analyze marketplace data? Let's look at the online retailing example. Suppose there is an online platform with many positions and product categories from various retailers. You need to collect all the available data and then disaggregate it. It allows you to discover differences among the same group of products or sellers. On closer inspection of these "units of measurement", you can find some interconnections. On their basis, you analyze what products are in demand and which are often ignored. It also helps to draw a parallel between goods and sellers: where consumers buy items and where they just browse desired ones.

Data disaggregation can be much more powerful in other contexts. This method is useful for retailers to expand their business, attract new audiences and retain existing customers. In marketing, it helps you find new options for advertising products. It also increases the loyalty of regular customers by analyzing population groups and their consumer motives.

As in any other industry, there are rules and laws in e-commerce about collecting personal information about customers. Aggregating data implies obtaining it for further use. Therefore, it is necessary to request permission from consumers to use their data. The principles and conditions regarding user data have changed significantly in recent years. Owners of websites and trading platforms need to be as transparent as possible in their policies. In addition, you need to take care of the reliable protection of the information received: in fact, if the rules are violated, legal problems may arise.

Data aggregation is a powerful tool for improving sales. Having it in your arsenal for market and target audience research, you get accurate indicators. Do not forget about the disaggregation method, which helps develop advertising campaigns and attract new customers.

Competition in online markets is growing, and new players are emerging every day. Every entrepreneur tries to optimize and improve their performance. Therefore, advanced automated data aggregation tools help you succeed much faster than calculating manually.