How To
Aug 3, 2023

Unleashing the Power of Data Analysis on Your eCommerce Business

If you’re an eCommerce business owner, you’re always searching for innovative ways to build a competitive advantage for your brand and stand out in crowded markets.

While there are no shortcuts to gaining an edge over your competition, analyzing your eCommerce data can act as your lightning rod.

Think of it as the silver bullet to analyze every customer interaction, understand their preferences and buying habits, and get ahead of your buyers to predict their next move. It's like having a crystal ball that reveals the future of your business.

But how exactly can you consolidate and analyze so much customer data for your eCommerce store? You can try making an Excel spreadsheet, using Google Sheets, or any other hacks you’ve heard online. All these tools will likely leave you disappointed because they’re not built to handle massive customer datasets.

That’s where Gigasheet can make all the difference for you.

In this article, we'll explore how data analysis with Gigasheet can create transformative magic for your eCommerce store. So buckle up and get ready to unlock the power of data—it's time to change the game!

Using customer data to optimize your eCommerce business!

eCommerce business owners can use meaningful data for multiple purposes. Let me break down a few essential use cases for eCommerce datasets:

  • Customer behavior insights: Understand purchasing patterns and behavorial trends by analyzing different touchpoints, like website, social media, apps, and more. Leverage this data to make informed decisions related to pricing, new product designs, marketing campaigns, personalized experiences, and more.
  • Inventory management and forecasting: Granular customer data can also help you optimize your inventory for every season. Review your historical sales data to map the demand patterns and seasonal shifts in conversions. This is important for avoiding stockouts or overstocking products to ultimately maximize profitability.
  • Better marketing strategy: Another huge benefit of building and analyzing eCommerce datasets is the ability to implement and measure your marketing campaigns. You can analyze website traffic data and identify the best channels driving conversions to allocate your budget accordingly. You can also enhance your website’s product recommendations to feature the best sellers.

How to use and enhance your eCommerce dataset with Gigasheet

Gigasheet is a big data spreadsheet built to process and analyze massive datasets. You can work with millions of data points to better understand your ideal customers.

Let me show you everything you can do on your eCommerce dataset with Gigasheet.

Navigate your database with filters

You might struggle to work with a large database and derive useful insights. After all, analyzing a large database is like trying to find a needle in a haystack, except the haystack is the size of Mount Everest, and the needle is wearing camouflage!

But with Gigasheet’s data magic, this nearly impossible task feels like a cakewalk. Let’s look at a few quick steps to use filters for navigating an eCommerce database.

In this example, I’ve used the sales dataset of an online electrical store. So, for my first filter, I chose to filter the results by the brand name.

eCommerce dataset

To find all the products purchased from a particular brand, I have to set this filter: WHERE [brand] [equals] [brand name]. This condition will show all the orders placed for products from my chosen brand. Let’s see the results for Apple.

Here are the results I found for my filtered search for Apple. You can see that this database only has Apple’s orders.

I added a second condition to the filters to further segment the results and display only orders of value $1000 or higher. This way, I could see get an estimate of all the orders placed above this benchmark.

Gigasheet took less than two seconds to filter through more than 800,000 rows and consolidate data for Apple products purchased at $1,000 or more. Data points like these can tell you your high-value items and tell you the categories to focus on.

You can also check other related factors like order time and location for your marketing campaigns.

Group data to find patterns

You can also play with your eCommerce database using the Group feature. It lets you categorize and organize all the data into defined groups so that you can analyze it properly.

In this example, I first grouped all the data by category code to arrange the orders into their respective categories.

The results looked something like this, where each category showed the number of orders within the group. When you open any of these groups, you can see all the information for individual orders within that category.

You can create as many groups as needed to organize your dataset. For instance, if you’d like to get a price-based division of orders within each category, you can create a sub-group for price.

This will divide each group into price points and list the orders under those price points. The group feature can give you an overview of your customer behavior and sales to determine the highest-selling products, brands, and most common price points.

If you combine the group feature with a filter, you can narrow down your database to specific details. In this case, I filtered this segmented data for the brand Apple. The results showed me two of the highest-selling product categories for Apple: smartphones and headphones.  

Within both of these categories, I could see the most popular price points. In the smartphone category, it’s $418, $856, and so on.

Expand database with functions

Another cool Gigasheet feature to make your eCommerce dataset more interesting is Functions. The platform gives you several functions to set your preferred conditions and add more details to your data.

Let me show you the If function in action.

You can add a new column to your database to further segment it using specific conditions. For example, if you want to categorize orders into high and low according to the order value, you can choose the If function and add a new column named ‘Order Value.’

Then set the condition: if the price is greater than $3, then the order is high value, otherwise low value.

When I pressed “Insert,” Gigasheet added a new column for order value and automatically divided all orders into high and low value based on my condition.

Make the most out of your eCommerce dataset!

Data is the lifeblood of any eCommerce store today. You have to rely on accurate and quick data analysis to stay ahead of your customers and competition.

With a robust big data solution and online CSV viewer like Gigasheet, you don’t have to worry about analyzing and managing huge eCommerce datasets. You can dive deeper into your data and pick up crucial details about your customers with all the Gigasheet functions we discussed in this guide.

So, what are you waiting for?

Sign up on Gigasheet for free and take it for a spin!

Also, if you want to twist a dummy dataset before playing around with your actual dataset on Gigasheet, you can try the one we showcased in this blog post. You can access it here.

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