Data Chaos!: Root Causes and its Dire Consequences

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The Saga of Unstructured Data

Introduction

For ecommerce to thrive, the data companies store needs to be structured and classified into appropriate taxonomies at all times. However, with bulk data, this often becomes impossible for companies to keep up with. What such neglect can lead to is a faulty product findability system, which would further result in the company losing customers. 

If the solution would be limited to correcting errors of this magnitude manually, then the company is bound to incur losses. In fact, a study by dataX.ai found that “sales teams typically spend 8 hours per week navigating scattered databases, legacy spreadsheets, and siloed tribal knowledge to find answers to these queries.” To tackle such data chaos, therefore, companies cannot rely simply on manual resources.

Possible Causes

But what is it that causes such mismanagement of data in the first place?

  1. Inconsistent Data Entry: This means that the data for the same product has been fed in different formats in the same database. For example, 8mL, 8ml, 8cc, etc.
  2. Lack of Standardization: With information that is unstructured and non-uniform, companies can face the problem of being inequipped to confidently answer questions about product relationships, compatibility, or equivalency. 
  3. Incorrect Classification: Products being classified into inaccurate categories, or being thrown into the "miscellaneous" category constantly, can lead to a disruption in the product findability system. 
  4. Duplicate Data: This involves the same product being logged multiple times into the database, often with each entry having some missing, or outdated, information. This crowds the storage unnecessarily, and leads to unreliable data. 

Conclusion

To prevent such data chaos from ensuing, companies need to be mindful and alert to their shortcomings, and employ techniques, such as automating certain processes, to tackle these challenges effectively.