search-close-icon

Search here

Can't find what you are looking for?

Feel free to get in touch with us for more information about our products and services.

Applications of Data Normalization in Retail & E-Commerce

data normalization in retail and 3-commerce

From improving customer experience to establishing brand authority, data normalization has wide-ranging applications in retail and ecommerce.


Whether you’re in retail, hospitality or housing, it’s fair to say that any modern company deals with large volumes of data on a daily basis. This data could be anything from inventory product attributes, to customer information.

As data is arguably the most valuable commodity today, it is important to have a clear understanding of the processes involved to keep it organized, actionable and relevant at all times.

One of the most effective methods for teams to achieve this objective is data normalization, which is a process of cleansing, structuring and organizing datasets. The end result is consistent data that is free of anomalies, redundancies, etc., making it easy to process, analyze and gather insights.

Why normalize data

It is inevitable for the data that organizations have gathered over many years to contain redundant information. The main motivation behind normalization is to remove these duplicates to free up storage space and make accurate analyses.

Structuring any dataset has various other benefits for companies across industries, including:

  • Improve efficiency of marketing and sales efforts by maintaining more effective customer profiles
  • Optimize resources to reduce clutter, free up storage, and in turn, improve response times for better user experience
  • With site-wide consistency in messaging and formats, improve public trust and market authority

For a more detailed look on the importance of data normalization, please check out one of our older blogs on the topic:

Data normalization in ecommerce

Ecommerce, as an industry, is heavily reliant on product and customer data. Smart catalog and customer management is key to better customer satisfaction, revenue generation and growth. As such, data normalization holds greater significance in ecommerce compared to other markets.

product attributes
Data normalization ensures site-wide consistency of product attributes

Benefits for retailers

Data normalization offers retailers an effective way to easily manage ever-expanding inventories, and edit or add new attributes in record-breaking time.

The following are some of the major ways retailers can profit by normalizing their data:

  • Site-wide consistency throughout your website — achieved thanks to normalization efforts — ensures seamless experience for all your visitors.
  • With consistent messaging, users across geographies see the same information (product name, description, etc.) for the same product.
  • Organizing product data helps avoid duplication of any product, where conflicting information might otherwise be displayed — different specifications, prices, for example.
  • Data normalization also helps drastically improve the integrity and accuracy of data, leading to more effective analyses and better insights.
  • When new fields or attributes need to be added to product databases, normalization helps minimize complexities, drastically reducing server-side delays.
  • This in turn improves client-side access times. The wait time is then drastically reduced for visitors and apps that access and use your data.
  • Retailers who proactively structure their databases are also able to offer their customers additional guarantees, like automatic filling of delivery addresses during checkout, safe delivery of their purchases, and much more.
data organization
Normalization organizes your data, and makes it consistent

Consequences of non-normalized data

Once you understand the benefits of normalization, it is easy to imagine how detrimental not doing so can be.

For retailers, some of the consequences of non-normalized data are:

  • With hundreds of thousands of products in inventory, attributes like measurement units, currencies, volume, size, etc. are bound to contain multiple formats. Without normalization, this leads to data inconsistency.
  • Inconsistent information about products and their attributes then confuses visitors who may not be familiar with the different formats and units being used.
  • Without normalization, you could also be wasting your customers’ time by having them browse unnecessary pages before landing on the exact product page.
  • All of this ultimately leads to distrust in your brand authority. As a result, start to see diminishing ROI and revenue over time.

Make data normalization a habit

We’ve seen how beneficial data normalization is to any industry, let alone ecommerce and retail.

It may seem daunting to review and organize all your data today. But the rewards you reap later — via historical data insights — will help your business scale new heights.

In addition, normalizing data also improves an organization’s daily workflows, which is why every data-driven business should make it a habit.


About Grepsr

At Grepsr, our primary goal is to always deliver the highest quality data to our customers, and we have rigorous quality checks to ensure we fulfil it every single time.

The basic aspects of data normalization — deduplication, standardization, etc. — are always the first parts of our QA process. The datasets we deliver are therefore consistent, reliable and actionable straight out-of-the-box, so you’re able to quickly gather insights and charter the path of continued success.

Web data made accessible. At scale.
Tell us what you need. Let us ease your data sourcing pains!
BLOG

A collection of articles, announcements and updates from Grepsr

ETL for Web Scraping

ETL for Web Scraping – A Comprehensive Guide

Dive into the world of web scraping, and data, learn how ETL helps you transform raw data into actionable insights.

Web-scraping-terms

A Comprehensive Glossary of Terms for Web Scraping

Web scraping has become an essential tool for extracting data from websites in various industries.  However, understanding the terminology associated with web scraping can sometimes be challenging. In this blog post, we provide you with a comprehensive glossary of terms that will definitely guide you to navigate the world of web scraping easily.  Whether you […]

data quality metrics

Know Your Data Quality Metrics With Grepsr

The importance of data quality cannot be overstated. One wrong entry and the corruption will spread without exception. The best way to counter this threat is to set up effective data quality metrics. 

data refinement

Why Data Refinement is Important for Your Business

Did you know most analysts spend 50 to 80 percent of their time refining their data than any other function in the data lifecycle? Even when we include other steps like data extraction, data analysis, and data visualization? We’ve talked at length about the importance of data for your business. The only thing we’ve emphasized […]

Make Data Make Sense: Most-Used Techniques in Data Analysis

This is one piece of a three-part series that looks at the various methods, techniques, and essential steps to superior data analysis.

web scraping

A Smarter MO for Data-Driven Businesses

Data is key to future-proofing your brand. Web scraping is the first step towards achieving long-term data-driven business success.

data quality

Perfecting the 1:10:100 Rule in Data Quality

Never let bad data hurt your brand reputation again — get Grepsr’s expertise to ensure the highest data quality

data normalization

What is Data Normalization & Why Enterprises Need it

In the current era of big data, every successful business collects and analyzes vast amounts of data on a daily basis. All of their major decisions are based on the insights gathered from this analysis, for which quality data is the foundation. One of the most important characteristics of quality data is its consistency, which […]

QA protocols at Grepsr

QA at Grepsr — How We Ensure Highest Quality Data

Ever since our founding, Grepsr has strived to become the go-to solution for the highest quality service in the data extraction business. In addition to the highly responsive and easy-to-communicate customer service, we pride ourselves in being able to offer the most reliable and quality data, at scale and on time, every single time. QA […]

benefits of high quality data

Benefits of High Quality Data to Any Data-Driven Business

From increased revenue to better customer relations, high quality data is key to your organization’s growth.

quality data

Five Primary Characteristics of High-Quality Data

Big data is at the foundation of all the megatrends that are happening today. Chris Lynch, American writer More businesses worldwide in recent years are charting their course based on what data is telling them. With such reliance, it is imperative that the data you’re working with is of the highest quality. Grepsr provides data […]

Importance of Data & Data Quality Assessment

According to Charles Babbage, one of the major inventors of computer technology, “Errors using inadequate data are much less than those using no data at all.” Babbage lived in the 19th century when the world had not yet fully realized the importance of data. At least not in the commercial sense. Had Babbage been around […]

Introducing Grepsr’s Data Quality Report

Quality assured data to help you make the best business decisions

arrow-up-icon