E-commerce is a rapidly growing sector, and the COVID-19 pandemic has only accelerated this trend. Because this sector is now so profitable, online stores are mushrooming. According to Arlington Research, 44% of consumers tried new brands during the pandemic. E-commerce big data is growing along with the entire industry. And how is e-commerce big data utilized today? What do online stores do to grow sales and attract more customers? Let’s find out!
If we had to squeeze this entire article into just one sentence, we’d say that e-commerce big data help you sell more, attract more customers, and curb customer churn.
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It’s a resource that’s critical to every store owner, no matter how big your business is. In fact, we are pretty sure that you’re using e-commerce big data, even if your store is relatively small. Interested? Let’s cut right to the chase!
E-commerce big data in every store
When we talk about big data, sometimes people think that it’s a large companies’ field. After all, you have to have significant financial resources and tens of people on board to make use of big data, right? Well, not necessarily, and e-commerce is a great example of how big data can be extensive and common. How is that possible? Thanks to various analytics modules, with Google Analytics in the forefront.
E-COMMERCE BIG DATA: GOOGLE ANALYTICS
If you run an online store, most likely you already know and use this tool. Google Analytics is a free platform that provides all the relevant statistics regarding your website and online traffic. Thanks to this tool, you can easily measure the efficiency of your ads. This tool also measures the traffic on your website. Thanks to data provided by Google Analytics, you know:
- Who visited your website?
- For how long?
- Where did they come from?
- What actions did they take?
- Which section on your website was particularly interesting?
And more. Many people don’t know, however, that Google also has the Analytics Intelligence module, which makes the whole solution even more accurate and helpful.
For instance, thanks to the advanced machine learning algorithm, Analytics Intelligence helps you model conversions and build effective target audiences. This ML-based module can even answer your questions! For example, you can ask, which channel had the highest conversion rate in the past month? As you can see, this tool can seamlessly introduce you to e-commerce big data, even if you’ve just started.
In general, we advise you to use this tool. Its functionality is impressive! In fact, every performance marketing campaign is based on data that comes from Google Analytics. That’s why almost every e-commerce business uses this tool.
E-commerce big data: The most common uses
Now, let’s talk for a few moments, why online stores use big data? We’ve come up with six major uses. Let’s take a closer look at them:
Obviously, every online seller wants to know the next best-selling product before their competitors. E-commerce big data can help you with this endeavor. Thanks to big data and other AI-related technologies, you can harness predictive analytics that will help you predict future demand regarding products in your store or niche. This way, you can focus on promoting them before your competition and enjoy a quick win. Of course, you have to bear in mind that predictive analytics algorithms are no crystal ball. But they will direct you on the right course. In short, e-commerce big data makes predicting the future less incidental and more accurate.
Prices can indeed be tricky. All online sellers have to deal with this head-scratcher. Naturally, your prices can neither be too high nor too low. In both cases, you lose. You have to look for the perfect balance. And this is where e-commerce big data steps into play. There are big data-based tools that help you monitor prices (both in your store and in your competitors’ stores) and maintain their optimal level. These tools frequently are teamed with machine learning features that make them more effective.
If you are interested in price monitoring, take a look at these tools: Price2Spy, Dealavo, Pricemanager, Skuuudle, Price Rest. Thanks to so-called dynamic pricing algorithms, these tools can help you adjust prices in real-time. This way, whenever the price of a given product changes in your competitors’ stores, you are notified and can take necessary actions.
No, it’s not the same thing as predicting trends. Forecasting demand in based primarily on the historical data in your store. E-commerce companies use forecasting demand in order to deal with the dead stock problem and maintain cash flow. Dead stock occurs when you’ve ordered too many products that are now unsaleable. Frequently, this issue affects stores that sell seasonal (skis, clothing) or FMCG products. Of course, there are ways to deal with dead stock, but the rule of thumb says that you want to avoid this problem at all costs.
Forecasting demand helps you assess in an objective and accurate way how many products you should order. This way, you don’t have too many products in your inventory that are just lying around, and you don’t have too few products that cause losing potential customers.
You may also fing it interesting – eCommerce case studies with machine learning
Personalization is your key to success in e-commerce. It is all about improving customer experience (CX). How does it work in practice? When the customer enters your website, they should see their name. Are you sending an email or newsletter? Write to Peter/Rachel, not to “Dear Sirs”. If there are product recommendations in your store (they should be!), let them be based on the previous purchases of a given person. Nobody likes to feel like a statistical number. Various market researches confirm this statement.
According to Gladly’s Customer Expectations Report 2020, 64% of all customers still feel like a ticker number, not a real person. This means that there’s still a lot of work waiting for e-commerce entrepreneurs. Perhaps, you are in this group, too. If so, use e-commerce big data in order to know more about your customers and communicate with them in a personalized, engaging way.
OPTIMIZING CUSTOMER SERVICE
The same report says that 51% of customers switch brands after just one or two poor customer service experiences. This is a real problem! That’s why online stores do whatever they can to improve customer service, and they use e-commerce big data to do so. Online stores use e-commerce big data in order to:
- Shorten response time
- Make store’s layout transparent and legible
- Streamline the customer journey
- Welcome mobile users
All these elements are of essential importance. And e-commerce big data provides you with the necessary knowledge to introduce demanded adjustments in your store.
GENERATE MORE SALES AND MORE CONVERSIONS
If you run an online store, you know that there are three significant performance marketing tools designed exclusively to help you sell more. These tools are:
- Google Ads
- Google PLA
- Facebook Ads
And yes, all of them are based on e-commerce big data. Consider Facebook Ads. Because this social media platform has 2.6 billion monthly active users, it’s a perfect target audience for your performance marketing campaigns. Facebook gathers a lot of information about its users, especially regarding their interests, profession, education, and activities. This way, they can use that data to offer accurate and effective ads. Did you know that there are over 1,300 targeting options, 15 objectives to choose from, and 6 main ad formats available in Facebook Ads? Thanks to Facebook Ads, you can generate sales by attracting precisely the right people.
And what about Google PLA? This abbreviation stands for Product Listing Ads. Google PLAs are designed primarily for e-commerce businesses, and they offer the opportunity to highlight your products when they match a given user’s search phrase. Product Listing Ads are used by e-commerce businesses to promote products, increase website traffic, and acquire potential customers through a search engine. Google PLA ads are displayed in Google and Bing search results along with the product’s image, title, price, your store’s name, and link to the landing page.
What’s also worth mentioning, Google PLAs, unlike other Google ads, are displayed based on product descriptions and categories, not keywords. PLAs are displayed at the top of the SERP (Search Engine Result Page), above the text ads and search results. They are incredibly useful. If you run an online store, you should definitely be interested in Google PLA!
E-commerce big data tools
Every online store owner should be interested in tools that help them sell more and run business more effectively. We’d like to show you some of the most interesting tools and solutions. The vast majority of them is based on e-commerce big data.
- Marketing: SEMrush, Ahrefs, SurferSEO
- E-commerce platform: Magento, Shopify, BigCommerce
- Monitoring: Brand24, SentiOne, Hootsuite
Naturally, the list of tools you might need is much longer, but that’s a subject for a different article 🙂 In this article, we wanted to show you that e-commerce big data is definitely worth utilizing. It will help you improve your online business and grow sales. And, as it turns out, you don’t have to be Amazon or Zalando to use this resource.
If you’d like to find out more about e-commerce big data and how you can start using it, drop us a line! E-commerce is one of our major areas of expertise. We will gladly show you possible big data-based solutions and guide you through the multitude of possibilities. With our help, big data is intuitive and straightforward!
 Karolina Kulach. Ecommerce Stats to Inform Your 2021 Strategy. Nov 19, 2020. URL: https://www.cmswire.com/digital-experience/ecommerce-stats-to-inform-your-2021-strategy/. Accessed Feb 1, 2021.
 BlueCorona. Your Ultimate Guide To Types Of Facebook Ads. Mar 28, 2017. URL: https://www.bluecorona.com/blog/types-of-facebook-ads/. Accessed Feb 1, 2021.
 Stephanie Mialki. Everything You Should Know About Product Listing Ads to Maximize Revenue This Year. Feb 25, 2019. URL: https://instapage.com/blog/product-listing-ads. Accessed Feb 1, 2021.