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    Recorded - available as on demand webcast

    In today’s competitive online retail marketplace, winning is defined by a retailer’s ability to differentiate the customer experience to drive greater loyalty.  Customer experience has been heralded as the next battlefield for digital commerce.

    89% of companies expect to compete mostly on the basis of customer experience by 2016, versus only 36% five years ago (Gartner).

    The ability to curate product information and merchandize products in ways that customers want to shop for them is critical for differentiation. Realizing this vision is accomplished by laying the right information management foundation and maximizing its value with the right product information management (PIM) platform.

    In this informative webinar, we will cover the best practices for building a product information architecture and how to leverage it for the greatest business impact with the market-leading PIM platform. Real world examples will be use to illustrate strategies you can use to enhance the customer experience provided by your own digital commerce engine.  

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    [RECORDED] Product Data Mastery - Reducing Returns to Increase Margin Through Better Product Data

    Improving product data quality will inevitably increase your sales. However, there are other benefits (beyond improved revenue) from investing in product data to sustain your margins while lowering costs. One poorly understood benefit of having complete, accurate, consistent product data is the reduction in costs of product returns. Managing logistics and resources needed to process returns, as well as the reduction in margins based on the costs of re-packaging or disposing of returned products, are getting more attention and analysis than in previous years. This is a B2C and a B2B issue, and keeping more of your already-sold product in your customer’s hands will lower costs and increase margins at a fraction of the cost of building new market share. This webinar will discuss how EIS can assist in all aspects of product data including increasing revenue and reducing the costs of returns. We will discuss how to frame the data problems and solutions tied to product returns, and ways to implement scalable and durable changes to improve margins and increase revenue.