http://storefrontbacktalk.com/supply-chain/wal-mart-eyeing-mobile-and-online-to-revamp-its-privacy-policy/ Techniques, Tools and Tirades about Retail Technology and E-Commerce Thu, 24 May 2012 17:32:15 +0000 hourly 1 http://wordpress.org/?v=3.2.1 http://storefrontbacktalk.com/supply-chain/wal-mart-eyeing-mobile-and-online-to-revamp-its-privacy-policy/comment-page-1/#comment-62979 Mike O'Sullivan Fri, 07 Aug 2009 17:58:08 +0000 http://www.storefrontbacktalk.com/?p=3398#comment-62979 This is a good example of taking the right steps towards integrating your customer intelligence so that analytical insight is actionable for relevant customer-facing operational communications— via phone, e-mail, online, mobile, and POS. While Wal-Mart is one of the first major retailers to tackle the privacy issue head on, the other side of the story is how a company can provide more personal, customized retail experience that customers have come to expect. Smart retailers like Wal-Mart recognize the need to integrate and cross-analyze data from many sources. Web intelligence packages enable companies to integrate and make sense of the interplay of offline (in-store, call center, etc.) and online data to track and determine what content that customers wish to see, so that customers get relevant messages wherever they interact. With this technology, catalog retailer JD Williams in the UK, for example, understands in detail whether a customer has truly abandoned a shopping basket on-line, and can identify if the item was later purchased from another channel, such as the call center. Based on detailed web data, they know which customers to target in campaigns, what products are most relevant to their personal interests, and a solid reason for making contact. Or JDW can identify when customers select an item to add to their shopping cart but the item is out of stock – and see what the customer decides to do next: 1)ask the business to notify the customer when the item will be available in the next 14 days, 2) abandon the item and log out 3) or choose an alternative item. They can then target the customer again when the item is back in stock – as appropriate. This also helps the market forecasting team determine the correct levels of stock required, based upon true customer demand. This is a good example of taking the right steps towards integrating your customer intelligence so that analytical insight is actionable for relevant customer-facing operational communications— via phone, e-mail, online, mobile, and POS. While Wal-Mart is one of the first major retailers to tackle the privacy issue head on, the other side of the story is how a company can provide more personal, customized retail experience that customers have come to expect. Smart retailers like Wal-Mart recognize the need to integrate and cross-analyze data from many sources.
Web intelligence packages enable companies to integrate and make sense of the interplay of offline (in-store, call center, etc.) and online data to track and determine what content that customers wish to see, so that customers get relevant messages wherever they interact.
With this technology, catalog retailer JD Williams in the UK, for example, understands in detail whether a customer has truly abandoned a shopping basket on-line, and can identify if the item was later purchased from another channel, such as the call center. Based on detailed web data, they know which customers to target in campaigns, what products are most relevant to their personal interests, and a solid reason for making contact. Or JDW can identify when customers select an item to add to their shopping cart but the item is out of stock – and see what the customer decides to do next: 1)ask the business to notify the customer when the item will be available in the next 14 days, 2) abandon the item and log out 3) or choose an alternative item.
They can then target the customer again when the item is back in stock – as appropriate. This also helps the market forecasting team determine the correct levels of stock required, based upon true customer demand.

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