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Ecommerce
2020-09-04

How will data analytics transform e-commerce?

Laura Villa Méndez
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Data science is an interdisciplinary field that uses various methods and algorithms to extract valuable information from data, which can be collected from the web or other sources. In e-commerce data analysis can be used for different purposes, one of them is that it allows companies to know their customers better and their behavior when making a purchase.

Today, technology has enabled the storage of large amounts of information, which can generate transformative benefits for organizations, if they know how to interpret them. Analyzing data allows you to turn information into a competitive advantage to perfect products and services, the reason why e-commerce businesses must realize the value of the data provided to them by their customers.

E-commerce businesses have different resources to identify what is working properly and what is not. Access to statistical information about their different activities on the web will help the owners of these companies understand the trends, the market demands, the strategies, and marketing channels that are being profitable and the adjustments they must make. Having data information is a gateway to increase profits.

Where is the data?

One of the concepts for performing web analytics is funnels, this means that the target audience will go through a step-by-step flow to achieve the goal: to shop in the online store. In this process, you need to know how to evaluate the percentage of people leaving the funnel, which will help you determine what are the barriers and why customers behave in a certain way. 

  • Google Analytics

This is an important tool when it comes to performing web analysis. It is easy to use, provides different types of reports, and it is free. You can integrate sales data by enabling email tracking in your Google Analytics administrator.  With this feature enabled, you can track data such as sales amount, number of orders, billing location, average order value, and more from a website or mobile app in Google Analytics.

The analytical reports provided by a shopping cart are relevant, however, you need to make this tracking setting for your website, so, if you have an online store, you could correlate the sales data, with the website usage data, which will eventually lead to analyzing the performance of your campaigns.

  • Email marketing

Email marketing campaigns are one of the most used strategies by e-commerce to create communication channels with their customers. Studies indicate that 72% of people continue to prefer email as the primary mode of communication with brands.

It is possible to obtain different data using this method. Have access to the number of emails that are sent, the percentage of people who opened it, the people who clicked, those who arrived at the landing page, and those who finally performed a specific action such as subscribing to a newsletter or buying a product.

With a robust email marketing strategy, it is possible to turn potential customers into buyers, increase sales, receive reviews and reviews, promote customer loyalty, offer information about exclusive offers and products, and present your business. Getting practical customer data will help you send the right types of emails to the right segments and create personalized and engaging emails.

  • Social media

Social media is a very important channel for e-commerce businesses, as they allow you to implement the complete funnel process for marketing campaigns. Facebook Analytics, for example, presents statistics that can be used for analytics. You can visualize the scope of posts, impressions, the impact they generate; all this information in a dynamic and always up-to-date way.

What can be done with data analysis?

1. Make personalized product recommendations

Data analysis is transforming e-commerce companies since through this process it is possible to make personalized recommendations for products or services. Using a recommendation system will help simplify the volume of data and give the customer what might be most attractive to them, consolidating the online buying and selling process. You can make these recommendations based on user behavior, preferences, and feedback. If a customer finds what they want more easily, they will for sure have a positive shopping experience. 

Amazon Personalize is a service that improves the level of user engagement and customer conversion rate through targeted marketing promotions and the use of personalized recommendations for products and content that are generated in real-time.

It is a solution that is based on more than 20 years of machine learning experience and research for Amazon recommendations. It uses machine learning algorithms to create high-quality recommendations that respond to the needs, preferences, and changes in the user’s behavior.

According to the data presented by Evergage in a 2019  customization trend report, 90% of sellers using customization, reported a measurable increase in results.  

Image: Evergage - 2019 Trends in Personalization

2. Predictive analytics

The data can also be used to make predictions. Previous purchase history, economic indicators, customer searches, and demographics can help e-commerce be prepared.

With data, it is possible to study the different consumption characteristics of the customers to anticipate future consumptions that may be highly relevant. Data analytics also allows you to recognize trends and products that are in high demand.  All this from the patterns that leave the user's behavior.

Today, many companies around the world have advanced and simple data analysis solutions at the tip of their fingers, letting them know what will happen in a few months in the market. Companies in sectors such as finance, retail, or energy use application programming interfaces (APIs)  to build predictive models and extract valuable data to predict customer behavior and adjust supply.

IBM is a company that has a predictive analytics solution for Big Data, through which it is possible to easily combine unstructured data, develop visual and flat language summaries so that the analyst understands the value of the information, and from this, achieve demand projections and personal customer profiles.

3. Study customer behavior and purchasing patterns

Another benefit of data analysis is to be able to study customer behavior and purchasing patterns. For an e-commerce company, it will be important to understand what influences the purchase decisions of users.

This will lead to rethinking on how to generate more impacts on customers and how to get new ones. According to statistics presented by HubSpot Research, people prefer to visit the company's official website if they want to learn about a brand and obtain more information, so it's critical that a website is easy to navigate and is always up-to-date.

Image: www.hubspot.com - HubSpot Research Global Buying Behavior in 2020

Analyzing data helps to comprehend the users' preferences when they are making an online purchase. Also, it can help the company to manage its marketing and pricing channels more efficiently.

4. Improving the customer experience

Online sales should not solely depend on comments on products or services left by customers to make the respective improvements. Through data analysis, it is possible to obtain valuable information to provide better customer service, without having any complaints. Of course, it's important to keep reading your feedback, but it's also possible to get ahead of yourself to improve the user experience.

In a survey conducted by HubSpot, it was revealed that  80%  of respondents said they stopped shopping at a company because of the poor customer service experience. It is clear that if customers are not satisfied with the customer service that is provided, they can easily switch stores and look for other products.

Tools like Text Analytics help you gain valuable insights into customer reviews and ratings.  It integrates a sentiment analysis function, which evaluates the text and returns sentiment scores and labels for each sentence. This is useful for detecting positive and negative feelings on social media and customer reviews. With data analytics, e-commerce companies will be able to identify and solve problems in the products or services they offer, eventually fully improving the customer experience. 

5. Provide security

According to data provided by Comparitech, consumers in the United States suffered losses of $3.5 billion due to fraud last year. Also, Symantec data shows that in 2019, 87% of consumers left their personal information exposed online.

From data analytics, it is also possible to guarantee customer security. E-commerce companies can combine data science and machine learning to detect in their online stores, suspicious behaviors, and fraud attempts. As an online store, it is important to assure the customer the complete security of their data and give them confidence when purchasing a product.

The transformation:

E-commerce should track as much data as possible, set up data collection, analysis strategies, and reports from services such as Google Analytics, Facebook, and more. These analytics will help you make business decisions. The above ideas were based on the tools that are at your fingertips, but why not think bigger?

As the number of customers and sales grows, so does the data. E-commerce business owners should always think about adding more value to what they offer, so it is necessary to consider how data analytics could transform their businesses. Also, the competitive advantages that these actions can represent for e-commerce will generate an impact on the online sales industry. 

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