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Four Data Challenges for Retailers This Holiday Season

Few industries have greater access to data to drive analytics and insights than the retail industry. Data is the heart of this business. Yet as retailers prepare for another busy holiday season they face four significant data challenges that will help distinguish between the winners from the losers.

  1. Bridging the data gaps between in-store and online

    Consumers expect consistent treatment and a seamless experience from retailers regardless of the channel they use– be it in-store, online, via a mobile device or in-store kiosk. That’s what Omnichannel Retail is all about. But at most retailers, there are huge organizational silos between the stores and e-commerce divisions. It’s not uncommon for the Stores division to be in the U.S. Midwest while the e-commerce division is in Silicon Valley. These organizational silos are further complicated by technology and data silos leading to execution failures. Examples of issues that will frustrate consumers this holiday season include:
  2. – An online order placed for pick-up at the retailer’s nearest store will not be there when they arrive for pick-up. That’s because inventory data between stores and online is not integrated and updated real-time

    – Managing in-store returns for online purchases will be complex since in-store and online systems don’t necessarily talk to each other

    – Finally, stores were never configured for easy pick-up and delivery of products you bought online. Ordering online may not save you much time – if the product is not ready for pick-up when you reach the store

  3. Consumer insights and personalization
    While personalization is the hottest buzzword in the retail industry, the execution has been poor! Simply put, retailers fail to recognize their consumers and therefore fail to design the right offers for them. Retailers struggle with integrating data from multiple organizational and data silos like loyalty programs, POS transactions, online sales, demographics, and responses to promotions. Other data sources like social media interactions, online reviews, or calls into the call center are often just ignored because they are unstructured and too complex to evaluate in Relational Systems designed for rows and columns. Most statistical models built to predict future purchases and responses to promotions are often based on a very limited set of demographic and transactional data and ignore the richness of consumer data that is now available. So while the data for 1:1 marketing and personalization now exist, very few retailers are any good at leveraging it!
  4. Real-time vs. batch data especially for promotions

    Consumers respond best to promotions they receive real-time and at the point of purchase. Yet most retailers rely on batch data which is used to send consumers coupons at their residences or via email in the hope that they will clip or print out the coupons and then use them in-store at a later date. These delayed promotional offers result in low redemption rates for coupons that barely ever exceed 1% whereas targeted real-time offers using beacons to recognize consumers and based on their profiles can result in redemption rates of between 60 to 70%.
  5. Location and weather data
    An old saying goes that the key to success in retailing is location, location, and location! It’s all about tailoring your assortment of products and services to the consumers who live in your neighborhood! Yet with mergers and acquisitions, we’ve seen the growth of the undifferentiated mega store that has the same set of products and format regardless of location. Leveraging geospatial data and local market information to choose the right location and then tailoring the store’s format and its product assortment to its neighborhood is a key differentiator. Finally, it is really all about the weather – especially if you are in the apparel business and we have a warm winter. So incorporating weather data into your forecasts as early as possible is going to be important.

To summarize this holiday season successful retailers – the Winners – will break down the data silos they face and create the right insights to delight consumers! The Losers will spend 80% of their time wrangling data, generating very little insight, and being left behind!

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