Key to Success:
- Our content experts consulted the e-commerce team to propose a revised content workflow
- Defined a Minimum Viable Content (MVC) framework to ensure onboarded products fulfilled certain key product content requirements
- Accessed competitor and customer search data to enrich product content with relevant keywords
- Leveraged machine learning algorithms to rapidly onboard MVC compliant products at scale
A large IT distributor built its multibillion dollar business with an expansive sales force. With the onset of digital, the client witnessed 25% growth in e-commerce sales. To further accelerate this growth, the client began enriching its product content to improve search. However, after enriching the product content, the client’s team found that only 28% of their products had basic content like product images, specifications, etc. The need to fix this gap was reiterated by the company’s user survey, which listed incomplete product content as a top concern for online shoppers. However, the team lacked the internal content expertise to effectively improve product content.
We worked with the distributor’s e-commerce team to understand its former content process. After a thorough content audit, we proposed a revised content workflow.
We also introduced a Minimum Viable Content (MVC) framework which identified some mandatory content requirements such as product name, image, objective text (key selling points), and description. Every SKU onboarded had to fulfil these MVC requirements. Compliance of these guidelines were ensured through regular and timely checks.
Our recommendations include updating the distributor’s Product Information Management (PIM) system, as their current legacy PIM had several limitations. We helped the distributor evaluate and smoothly transition to a new PIM system and were able to gather product information from multiple data sources to enrich product content. We further enhanced this content with relevant keywords, which were extracted from competitor and consumer data.
Our use of machine learning enabled the rapid onboarding of SKUs at scale. Finally, certain metrics were put in place to track and measure the impact of complete and enriched content.
Before and After