How To Prepare eCommerce Data for Analysis?

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No one would argue that data is an extremely valuable resource. The more applications you find for data, the more important it gets. However, making your data valuable requires sophisticated methods of eCommerce data analysis.

The process of collecting, modeling and analyzing data is called data analysis. Analyzed data helps you gain valuable insights and prepares you for rational decision making to optimize your business performance. The methods used for data analysis will depend on the goals you have for your data strategy. 

To have a better understanding about this topic, let’s delve into what opportunities eCommerce data analysis can unlock for your company.

No business works without customers. And the broader the audience, the trickier it is to make your business personal enough for them. Data analysis allows you to gain insights into all aspects of your ecommerce customer journey.

This includes:

  • The channels customers communicate with you
  • Their location
  • Activity
  • Interests
  • Purchasing history
  • Behavior
  • and more. 

In other words, a proper eCommerce data analysis can reveal lots of useful information about customers. Having such knowledge increases the success rate of your marketing strategies, allows you to discover new prospects and minimizes the risk of incorrect targeting.

When you focus on data, your decision-making transforms from intuition to factual. Data driven decision-making opens up growth opportunities. It can also be used for solving tricky situations before they escalate into problems.

Prepare your data for analysis

To receive maximum benefits of eCommerce data analysis you first need to prepare your data. Here are some of our tips to get you successfully prepared for eCommerce data analysis.

Collaboration with Teammates

Collaboration with key members of your company is essential before eCommerce data analysis is initiated. First, collectively decide on the vision for the company’s progress. Then, plan campaigns, strategic goals, and other objectives. These are the first steps that will help you prepare to advance further with your strategy.

The Questions You Ask

It’s always best to know what questions you want to answer. The questions will depend on the goals you aim to achieve. For example, when and why do customers abandon their shopping carts? What is the percentage of new customers vs returning customers; and what makes customers return?

Democratize Data

Collaboration with members of your company should not stop when the plan for campaigns and strategic goals are established. It’s important to make data easily and quickly accessible to anyone in your organization at any given time. This process is called data democratization—connect data from various sources and extract it in various forms, such as text, images, videos, numbers, etc. You can then perform eCommerce data analysis where everyone is on the same page and can contribute to it with their input and ideas.

Clean Your Data

Collecting vast amounts of data from multiple sources can be overwhelming. Because of the sheer size of collected data, some of it may be incorrect or incomplete. This leads to ineffective eCommerce data analysis. To avoid such situations, always clean your data. The process of cleaning data ensures that the data insights will be correct and accurate.

When cleaning data, there are several things to look out for. This includes removing any duplicate data which usually happens when using multiple internal and external data sources. Empty fields or incorrectly formatted data should also be removed.

Text data often needs cleaning too. It might occur when companies analyze customer reviews, surveys, comments on social media, or other text data. Text data needs to be verified to avoid any grammar errors, unsupported characters, or other mistakes.

To clean data is to avoid incorrect eCommerce data analysis and data insights that might negatively affect your business long-term. Cleaned data makes the process of data analysis much more efficient and easier to interact with.

Integrate KPIs

When you prepare by asking the questions you want to answer, selecting your data sources, and cleaning your data, the next recommended step is Key Performance Indicators. Key Performance Indicators (KPIs) are a great way to track and measure your campaign and goal progress. While you may have different methods in mind for tracking and measuring progress and results, definitely explore KPIs and how they can help your strategy.

Consider Data Governance Roadmap

Another useful step is to create a data governance roadmap – it helps your strategy to succeed. Primarily, it is used to store, manage and handle data internally. Data governance roadmap also makes your eCommerce data analysis techniques efficient and functional. It provides the ability to visualize your campaign and goal progress. The necessity of such a roadmap depends on how complex your campaigns and objectives are, but if you are willing and able to invest time and resources creating it, a data governance roadmap is worth having.

Use Data Analysis Platform

Today, analyzing data can be done in many ways. However, even when you think that you and your team got everything set up perfectly, you can never go wrong with integrating eCommerce data analysis technology.

Data analysis platforms help you get the most out of your data and data sources. Such platforms provide in-depth actionable insights as well as clear and concise marketing plans. They can also turn your data into information that is visual, interactive, easy to understand, and effective. 

This is not to say that everything will be done for you: the vision you have, the goals you have set will contribute greatly to your success. Once that is set, data platforms will make work much easier and more efficient.

If you would like to enhance your eCommerce data analysis performance, save time and effort, avoid critical mistakes that might come with incorrect and incomplete data, consider Verfacto.

Explore the AI and ML Technology

Artificial intelligence combined with machine learning technology revolutionizes the data industry. One of the products that uses these technologies is Verfacto. We help eCommerce businesses to effectively analyze and gain insights from data that increases business profits, revenue, customer retention rate, reduces the number of abandoned carts and more. Try out Verfacto and get actionable insights for your business!

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