Personalized Recommendations Systems Overview Industry research indicates that successful online retailers, such as Amazon, are generating as much as 35% of their business from recommendations. This means that for many companies, sales are being lost every day. More and more, customers are expecting to be able to personalize their shopping experience beyond wish lists. Netflix and Amazon are great examples of how to companies can do this. The race is on to personalize, because once someone invests the time to train a web site to learn their preferences, they will prefer to shop there versus somewhere else. Imagine how much harder it will be for Blockbuster to steal Netflix customers, once they have given three months worth of feedback. Shoppers can tell when recommendations don’t make any sense. When this happens an opportunity is lost. Recommendations that Drive Sales (Creating a truly personalized shopping experience) Other systems promise to provide recommendations that… - Are relevant - Lead to discovery of new products - Engage the customer But, ours are more relevant because, we … - Use better data (feedback from your customers and transactions) - Apply leading-edge methods (we statistically map your brands in multi-dimensional space) Shoppers will discover new products if they trust and use a great system … So, we engage the customer by … - Collecting product ratings - Using scrollable recommendations The better the data, the better the recommendations. It’s that simple. Product Ratings Data: Since people aren’t always happy with their purchase, customer feedback improves the quality of recommendations. Collecting this data is also key to building a relationship. Sales Data: After ratings data, purchase data is the most useful. Removing gift purchases ensures that matches are based on the customers’ true personal tastes. Click Data: Widely available and used only as a last resort, click data provides little guidance as to whether the shopper will like a product enough to buy it - let alone be satisfied with it. Strategically, it does nothing to build a relationship. Philosophy: Collect the best data, derive a custom solution, then check the results by hand to make sure they make sense. Once foundation is set, profiles update in real time. Leading-Edge Methods The “Also Bought” method shows what’s popular, not what’s most relevant. We can do better… Our approach is different from what you see on other web sites, because we map brands in multi-dimensional space.  This provides extraordinary accuracy with recommendations, not only for new shoppers, but especially for returning customers.  Also has implications for pricing strategy and product line opportunities. Strategy Strategy New Shoppers Product Pages – Scrollable, community recommendations Checkout – Accessories, such as batteries Search – Displays everything the customer needs (not just list of products). Sort by popularity, price, etc. Repeat Buyers Home and Product pages – Scrollable, personalized recommendations. Profile Building: Collect product ratings “Smart Search” – User preferences influence results Clients Customize Recommendations by… Profit margin Inventory availability On-sale items and other criteria space Getting Started (It’s easier than you imagine) Provide data to Dart for analysis We use it to build a demo You evaluate it and when ready to implement… Insert the ready-to-use code provided by Dart No software hassles Four web-based patents Other uses for customer profile data … My-Gift Store (Recommend Gifts) Recommendations for when bill-to and ship-to don’t match Email gift reminders with recommendations Encourage customers to add new gift recipients New reasons to email Post-sale requests for product ratings Personalized promotions Telemarketing Up-Selling Direct Mail: Highly recommended products Catalog Merchandising More About Personalized Recommendations         Slideshow / Brochure (pdf) / Compare Results (pdf)         DVD Demo - Judge for yourself. Select from thousands of DVDs!         Coffee Demo - See how even new shoppers can influence                                          recommendations. Features unique brand map. DART Marketing, LLC