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2. FYI, you can get 50% off everything at Old Navy right now

   www.aol.com/lifestyle/you-can-get-half-off...

   $20 $40 Save $20. See at Old Navy. Water-Resistant Sherpa-Lined Hooded Parka Coat for Girls ... that's just one small slice of everything you'll find that's on sale at Old Navy right now, so we're ...

3. PromotionCode.org - Wikipedia

   en.wikipedia.org/wiki/PromotionCode.org

   Originally, the site was an online forum and coupon rewards website for teachers. After being highlighted by Jean Chatzky on The Today Show and its website, [ 5 ] PromotionCode.org transitioned from its forum format into its current structure with promotion codes organized by store.

4. 40 Unique Christmas Ornaments You Won't Find on Grandma ... - AOL

   www.aol.com/lifestyle/36-unique-christmas...

   Make your tree the talk of the holiday season with these unique tree ornaments and Christmas decorations that glimmer with festive cheer. 40 Unique Christmas Ornaments You Won't Find on Grandma's Tree

5. Coupon - Wikipedia

   en.wikipedia.org/wiki/Coupon

   In marketing, a coupon is a ticket or document that can be redeemed for a financial discount or rebate when purchasing a product. Customarily, coupons are issued by manufacturers of consumer packaged goods [1] or by retailers, to be used in retail stores as a part of sales promotions. They are often widely distributed through mail, coupon ...

6. Personalized marketing - Wikipedia

   en.wikipedia.org/wiki/Personalized_marketing

   Personalized marketing, also known as one-to-one marketing or individual marketing, [1] is a marketing strategy by which companies use data analysis and digital technology to show adverts to individuals based on their perceived characteristics and interests.

7. Coupon collector's problem - Wikipedia

   en.wikipedia.org/wiki/Coupon_collector's_problem

   An alternative statement is: given n coupons, how many coupons do you expect you need to draw with replacement before having drawn each coupon at least once? The mathematical analysis of the problem reveals that the expected number of trials needed grows as Θ ( n log ⁡ ( n ) ) {\displaystyle \Theta (n\log(n))} .