Capping IT Off

Capping IT Off

Opinions expressed on this blog reflect the writer’s views and not the position of the Capgemini Group

Tailor Product Data for your customers' local requirements

Product Data life cycle revolves around the customer. Consistent and accurate product data dictionary builds trust and transparency over the product to spur customers’ buying decisions. It is also important to increase customers' stickiness to the product and drive lifetime value.

Industry research from multiple analysts has indicated that between 68% to 90% of customers engage in comparison-shopping, refer to multiple sources of data, review numerous data attributes and research online reviews before making purchasing decisions. Product data taxonomy, attributes, content and presentation which are specific to a retailer’s and supplier’s target demographic segment increase the relevance of the brand and make it more attractive to the customer. Attributes can range from product content, dimensions, statutory information, packaging, shelf life, images, videos, reviews, variants, shipping information amongst others. There are mandatory attributes that need to form part of the data set such as ingredients, allergens, genealogical source, shelf life, legal compliance and list continues to grow exponentially. There also exist other non-mandatory attributes such as long description, reviews, images, etc. which enhance the product preference for the customer, create a multi-way engagement with the customer and a lasting brand loyalty.

The industry has come together and defined a global system of standards (more on standards later, it's a whole new topic) that provides a framework for product data readiness across categories. However, there still exists an opportunity for retailers and suppliers to tailor the global guidelines for local market requirement and specifically for their target customers. In an omnichannel environment, there is a multitude of other considerations such as product classification and searchability which, in combination with high quality product data, is proven to impact category-wise revenue uplift. In conclusion, there is no one size that fits all.

Read our POV: The Devil lies in (Product Data) Details to gain insights into our learnings from our product data engagements with global retailers. The White Paper also highlights the results of our global product data benchmarking survey of 30 global retailers. The findings of the survey reveal that the leaders in the industry are the ones who have worked towards closing this gap of physical and online data and have advanced along the Product Data maturity curve.

About the author

Sunitha Ray
Sunitha Ray
Sunitha Ray is a Principal in Consumer Goods and Retail Sector based in Chicago, IL, USA. She brings enterprise applications, product management, data transformation and transformation / turnaround competencies in retail and grocery industries with about 20 years in consulting, sales leadership and software delivery areas.

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