Retail Analytics: A Guide for Growing Businesses [07/18 Update]

Retail analytics is a process that helps to provide crucial data for businesses with regards to inventory, sales, supply chain activities, consumer demand, and more. By implementing an analytics-driven retail environment, organizations can make better decisions for procurement, marketing, merchandising, and other operational considerations. This, in turn, enables retailers to create a better buying experience and for identifying opportunities for organizational improvement. 

Some questions that we will answer in this blog include:

What are the benefits and importance of retail analytics?

What are some current trends in retail analytics?

How can AI impact retail analytics?

What are some challenges to effective retail analytics?

What are some common tools associated with retail analytics?

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How to Choose the Right Data Quality Tool [06/2018 UPDATE]

Data cleaning is part of a greater effort to achieve the highest data quality possible in used in business decisions and operations. It requires organizational effort and participation throughout a business and when done correctly, can help to provide valuable insights and analytics for decision making. A few additional benefits associated with data cleaning include:

  • Streamlined business practices
  • Increased productivity
  • Faster sales cycle
  • Better analytics

Given the ever growing quantity of data for many businesses, automation is required in data cleaning. The right data tool can fill in these gaps and manage a number of issues automatically before they have a chance to become truly problematic. This can ultimately help businesses to become more efficient and more profitable in their efforts.

Choosing the right data cleaning tool for your organization is essential to getting the most utility for your investment. To help in your decision making, this post answers the following:

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34 Data Visualization Tools for Better Business

Humans are naturally visual creatures, so it is no surprise that we search for better ways to portray and understand what data is telling us. Data visualization is one of the most effective ways to achieve this because it enables us to take data or ideas that are abstract and difficult to understand as written, and turn them into something easily understood in a more graphical or visual format. To learn more about data visualization and how organizations use it, see our blog post.

However, for any data visualization to be effective, it requires the right tool – which in many cases can mean a multifunctional tool that includes capacity for both visualization and analysis.

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Improving Understanding with Data Visualizations

As we become better at collecting and analyzing data, we also have to become better at explaining what it all means. Data visualization is the use of algorithms to create images (graphical and pictorial) from data so that humans can more effectively understand and respond to that data. It is important because it enables us to digest large amounts of complex data that would otherwise be overwhelming or difficult to understand.

To better understand data visualization, there are several questions that we will answer:

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