Top Data Challenges Facing Modern Retailers

While gathering operational and consumer information can benefit businesses, they often face obstacles. Some of the top data challenges in the retail industry involve collection and application. Gathering massive amounts of information can be relatively easy, but properly utilizing it can be complex, leading to these data challenges.

1. Insights

Gathering insight from consumer information is one of the top data challenges modern retailers face. Around 90% of all data is unstructured. It’s generally more challenging to manage with traditional approaches. While tools like machine learning technology can process it, visualizing it can still be complex. Collections of consumer details are only effective for businesses if a sound strategy accompanies them.

Because producing valuable insights out of unstructured information is one of the top data challenges, businesses need a way to analyze their collections. Data analytics in the retail industry may be the solution. It relies on searching for patterns and trends to give companies insights into operations and consumer purchasing behavior. They can use it to properly inform their marketing and financial actions. A machine learning scientist or artificial intelligence (AI) technology is an excellent candidate for the role.

2. Privacy

Most retailers collect consumer-specific details on top of general demographic statistics, which carries more compliance concerns. Data privacy is the management process of PII (personally identifiable information) like consumer financial or health data. For example, a company could retain consumers’ credit card numbers after online checkout. Proper storage is necessary to prevent data breaches, but adequately containing and monitoring extensive collections can be challenging. If anything leaks, they can face fines and public backlash.

Privacy is one of the top data challenges in the retail industry because the government is moving to make compliance measures more strict. The American Data Privacy Protection Act in 2022 was a proposed bill to standardize information collection and use nationwide. Although it ultimately didn’t pass, the attempt reveals that Congress focuses on modern business practices.

Generally, retailers are safe from regulatory action and fines as long as they protect their collected consumer data. They can install monitoring software or hire cybersecurity professionals to enhance information security. Paying attention to bills on the horizon can also help prepare them for potential regulations.

3. Quantity

Managing data quantity is one of the most significant challenges in the retail industry. Most businesses collect information from multiple sources, so they have many text, image, video, and audio files. In addition, they typically house their collections on numerous storage platforms. Managing all those details can be challenging, especially when various stores share access.

The solution for data quantity challenges in the retail industry lies in enhanced storage and management. Integrating software that can automatically categorize or process could solve the issue of being overwhelmed by information. For example, retailers could analyze and reveal trends much faster with a big data platform. It also can ensure they retain quality details since they don’t have to limit how much they collect.

4. Quality

Most retailers have dealt with irrelevant results even when using automatic processing systems like AI. The underlying issue is quality. Analysis software is only as good as what it processes — inadequate or inferior input can lead to substandard applications. For example, feeding an algorithm statistics about consumer purchasing behavior from stores in one location might lead to poor optimization in another because the data might not be applicable.

This issue scales with the size of collections, meaning it becomes more challenging to audit and resolve as a company gains more information. Retailers should monitor the details they input and make minor adjustments when possible. While standardization can be beneficial, ensuring their actions are applicable is essential. Instead of broadly applying their knowledge to all stores or customers, they must have a strategy to ensure data quality.

5. Standardization

Retailers often gather information from many places at once, so they have multiple types to store. They could have audio files, videos, text, and images. On top of that, they must figure out how to categorize structured and unstructured data. They typically store them apart from each other in silos because integrating them seems complex and time-consuming.

Usually, this process makes each type incompatible with the other. This issue is one of the most significant challenges in the retail industry. When it comes time to use what they’ve collected, they must pull everything out individually and analyze it collectively. The result typically contains duplicates and inconsistencies because of the original separation. Merging everything poorly can make applying the information challenging and time-consuming.

Standardizing collection and application is essential. A retailer must connect data silos across the entire organization for proper consolidation. To do so, it can use an integration system or platform. It should regulate the processes for all stores to ensure maximum efficiency.

Facing Data Challenges in Retail

Quantity, insight, privacy, standardization, and quality are some of the top challenges retailers face when handling data. Businesses looking to make their process more effective or efficient should look to software or professionals to help manage and analyze their collections. Data analytics in the retail industry may solve many application issues.

Originally posted on OpenDataScience.com

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