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3 ways e-commerce sellers can improve ROI in 2020 with data analytics

As 2019 comes to a close, it's time for e-commerce sellers to re-evaluate how then can improve their business' ROI this coming year. A good place to start? Data analytics.

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Nathan Resnick
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Nathan Resnick

Nathan is a serial entrepreneur who currently serves as CEO of Sourcify, a marketplace of the world's top manufacturers. Having brought dozens of products to life, he knows the ins and outs of how to… (show all) Nathan is a serial entrepreneur who currently serves as CEO of Sourcify, a marketplace of the world's top manufacturers. Having brought dozens of products to life, he knows the ins and outs of how to turn ideas into realities.

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2020 will be here before we know it, and if you’re like me, that means that you’re already looking ahead to how you can improve your e-commerce business in the year to come.

While there are many things you can do to improve the profitability of your e-commerce brand, such as improving your supply chain or ensuring that your website is accessible for disabled users, few things will prove more important than properly implementing data analytics.

With quality data analytics and business intelligence tools, you can pull from a wide range of data sources — such as sales numbers, marketing data and even logistics information — to better understand the trends affecting your store. Even more importantly, you can gain key insights into the actions you can take to improve your business operations.

Using data analytics could ultimately make all the difference for your bottom line in 2020. Here are just three examples of how using data analytics can improve your ROI:

1) Targeted cross-selling and up-selling for more sales.

In my years in e-commerce, few tactics have consistently proven to be more effective for boosting sales than cross-selling and up-selling. When done right, it’s one of the easiest ways to get customers to spend more at your store.

According to reports, Amazon attributes 35 percent of its revenue to cross-selling. These are the suggested items that pop up under headings like “Frequently Bought Together” or “Customers Who Bought This Item Also Bought” that you see when looking at a product listing. Amazon also suggests items to users based on their browsing and buying history.

Knowing which items to show for these recommendations is derived from data analytics and AI — and if it’s made Amazon such a success, it can certainly help your own e-commerce store grow in profitability.

Depending on your industry, there’s a good chance that customers are actively interested in up-selling offers. Travel industry surveys reveal that “48 percent of airline passengers and 59 percent of hotel guests are interested in upgrades and additional services.”

Using data analytics can prove key in helping you identify which cross-selling and up-selling offers will most appeal to your store’s customers.

2) A unified view of data saves time and resources.

Chances are, you already pull data from a wide range of resources as you run your e-commerce store. There’s the sales data you collect directly from your website, marketing information from Facebook and Google, and logistics data from your manufacturing and shipping partners.

All of this information directly impacts the bottom line of your e-commerce store. But getting the most of it can be a time consuming process, to say the least.

This was the issue that faced headphone manufacturer Skullcandy. In a case study from Sisense, the company decided to consolidate its legacy information of 100 million rows of data from five siloed data sources into a unified platform.

Placing all information into a single data analytics platform ultimately allowed the company to gain new sales insights within a week of implementation, while also reducing administration and IT overhead costs.

Even if your e-commerce store isn’t dealing with millions of rows of data, chances are, you aren’t getting as much out of it as you could if you’re merely scanning through the numbers during your free time.

A comprehensive data analytics program does more than automate data entry and generate reports. It also looks for actionable insights based on the information coming from your various data sources.

This will help you save time in your own data analysis and decision making efforts. With data-backed decision making, you can also have greater confidence that you are allocating your energy to actions that will truly grow your e-commerce brand.

3) Growing profits through smarter price management.

According to research from Deloitte, price management initiatives can improve profit margins by anywhere from two to seven percent in a one-year period, delivering an ROI between 200 and 350 percent.

What makes price management so effective? For many customers, the decision of whether or not something is worth purchasing can come down to a simple change in pricing. With quality data in hand, you will be better equipped to know which pricing strategies will make the greatest impact on your customers.

As just one example, a research study conducted by Yale found that when two different types of gum were offered at the same price, only 46 percent of customers decided to make a purchase. In a separate scenario when the two types of gum were offered at different price points, 77 percent made a purchase.

Data analytics tools can offer clear insights into which pricing strategies will work best with your product lineup and target audience, and then clearly demonstrate how your actions impacted sales. For the previous example, it could tell you how much of a price difference you should use, and which product should be less expensive.

Data analytics is continuing to contribute to changes in the ways companies offer their products or services — even Netflix’s recently announced testing of sped-up video play draws (and will draw from) the data it receives from its customers. In 2020’s marketplace, quality data will lead to new innovations and help you drive profitability like never before …

You just have to be willing to use it.

This post is part of our contributor series. The views expressed are the author's own and not necessarily shared by TNW.

Published November 15, 2019 — 20:55 UTC