{"id":773,"date":"2011-11-30T09:05:26","date_gmt":"2011-11-30T14:05:26","guid":{"rendered":"http:\/\/www.yupingliu.com\/wordpress\/?p=773"},"modified":"2018-06-06T18:32:07","modified_gmt":"2018-06-06T22:32:07","slug":"1-point-per-dollar-or-100-points-per-dollar","status":"publish","type":"post","link":"https:\/\/www.yupingliu.com\/wordpress\/2011\/11\/30\/1-point-per-dollar-or-100-points-per-dollar\/","title":{"rendered":"1 Point Per Dollar or 100 Points Per Dollar?"},"content":{"rendered":"<p>When designing a loyalty program, have you ever wondered whether you should give customers 1 point for each dollar they spend and require 100 points for a free reward, or if it&#8217;s better to grant 10 points per dollar and require 1000 points for the reward? On the surface, these two setups require the exact same effort from consumers and should make no difference to the effectiveness of your program. But <a title=\"Illusionary Progress in Loyalty Programs\" href=\"http:\/\/filebox.vt.edu\/users\/rbagchi\/Published%20Articles\/IllusionaryProgressManuscript.pdf\" target=\"_blank\">an article<\/a> by <a title=\"Professor Rajesh Bagchi\" href=\"http:\/\/www.marketing.pamplin.vt.edu\/faculty\/Bagchi.html\" target=\"_blank\">Professor Rajesh Bagchi<\/a> and graduate student Xingbo Li published in the <a title=\"Journal of Consumer Research\" href=\"http:\/\/ejcr.org\" target=\"_blank\"><em>Journal of Consumer Research<\/em><\/a> says it&#8217;s not quite as straightforward as you may think. Which option is better depends on whether you have a straightforward single point structure or a mixed structure, and whether your focus is on encouraging low spenders or rewarding heavy buyers.<\/p>\n<p align=\"center\"><img loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-781\" title=\"numbers\" src=\"http:\/\/www.yupingliu.com\/wordpress\/wp-content\/uploads\/2011\/11\/numbers.jpg\" alt=\"numbers\" width=\"404\" height=\"61\" srcset=\"https:\/\/www.yupingliu.com\/wordpress\/wp-content\/uploads\/2011\/11\/numbers.jpg 404w, https:\/\/www.yupingliu.com\/wordpress\/wp-content\/uploads\/2011\/11\/numbers-300x45.jpg 300w\" sizes=\"auto, (max-width: 404px) 100vw, 404px\" \/><br \/>\nPhoto by Flickr User <a title=\"Flickr user twitchcraft\" href=\"http:\/\/www.flickr.com\/photos\/twitchcraft\/\" target=\"_blank\">twitchcraft<\/a> | <a href=\"http:\/\/creativecommons.org\/licenses\/by-sa\/2.0\/deed.en\" target=\"_blank\">CC 2.0<\/a><\/p>\n<p><strong>Context<\/strong><\/p>\n<p>The authors conducted two lab experiments. The first experiment was based on a grocery store loyalty program and involved 246 undergraduate students. Various aspects of the loyalty program were manipulated, and the respondents reported how likely they would recommend the program to others and whether the program would increase their loyalty toward the store. In the second experiment, 375 student and non-student respondents made simulated purchases given a restaurant loyalty program. At the end of the simulation, they also reported their recommendation likelihood and perceived loyalty effect.<!--more--><\/p>\n<p><strong>Main Findings<\/strong><\/p>\n<ul>\n<li><strong><\/strong>Point ratio (low: 1 point\/dollar vs. high: 10 points\/dollar) has opposite effects depending on whether the program has a clear point structure (i.e., a clear point ratio is applied across the board) or a mixed structure (e.g., point ratio may vary across product categories or across time).<\/li>\n<li>Under a clear point structure, a high point ratio (10 points\/dollar) leads to similar reactions from consumers who are far from the reward threshold (e.g., has earned 20 out of 100 points required) as consumers who are close to the reward threshold (e.g., has earned 80 out of 100). A low point ratio, on the other hand, creates much more positive reaction among consumers who are close than among consumers who are far.<\/li>\n<li>Under a mixed point structure, the opposite is true. A high point ratio leads to much more favorable reactions among consumers who are close to the reward threshold than those who are still far. A low point ratio, in the meantime, does not make a significant difference.<\/li>\n<\/ul>\n<p><strong>What Does This All Mean to Practice?<\/strong><\/p>\n<p>To translate these findings to practice, we can first consider the practical equivalence for being near vs. far from the reward threshold. For low spenders at a company, they are likely to spend more time being pretty far from the reward threshold. For existing heavy buyers, in contrast, they earn points easily and probably spend a good amount of their time being very close to the reward threshold. Based on this translation, the following chart shows how to determine the best strategy to use:<\/p>\n<p><strong><\/strong>\n<table id=\"tablepress-6\" class=\"tablepress tablepress-id-6 tablepress-responsive tbody-has-connected-cells\">\n<tbody class=\"row-striping\">\n<tr class=\"row-1\">\n\t<td class=\"column-1\"><\/td><td class=\"column-2\"><\/td><td colspan=\"2\" class=\"column-3\"><div align=\"center\"><b>Program Goal<\/b><\/div><\/td>\n<\/tr>\n<tr class=\"row-2\">\n\t<td class=\"column-1\"><\/td><td class=\"column-2\"><\/td><td class=\"column-3\"><b><i>Encouraging Low Spenders<\/i><\/b><\/td><td class=\"column-4\"><b><em>Rewarding Best Customers<\/em><\/b><\/td>\n<\/tr>\n<tr class=\"row-3\">\n\t<td rowspan=\"2\" class=\"column-1\"><b>Point Structure<\/b><\/td><td class=\"column-2\"><b><i>Simple<\/i><\/b><br \/>\r\ne.g., <a href=\"https:\/\/myrewardzone.bestbuy.com\/\" target=\"_blank\">Best Buy Reward Zone<\/a>, where you get 1 point every dollar spent<\/td><td class=\"column-3\">High point ratio<\/td><td class=\"column-4\">Low point ratio<\/td>\n<\/tr>\n<tr class=\"row-4\">\n\t<td class=\"column-2\"><b><i>Mixed<\/i><\/b><br \/>\r\ne.g., <a href=\"http:\/\/www.priorityclub.com\/hotels\/us\/en\/global\/support\/about-priority-club-rewards\/member-information\" target=\"_blank\">Priority Club<\/a>, where how many points are issued depends on the chain that you stayed at<\/td><td class=\"column-3\">Low point ratio<\/td><td class=\"column-4\">High point ratio<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<!-- #tablepress-6 from cache --><\/p>\n<p>Do these findings make sense to you? How has your experience been dealing with point ratio? I would love to hear your thoughts!<\/p>\n<p><strong>Reference<\/strong><\/p>\n<p><strong><\/strong>Rajesh Bagchi and Xingbo Li (2011), &#8220;<a title=\"Illusionary Progress in Loyalty Programs: Magnitude, Reward Distances, and Step-Size Ambiguity\" href=\"http:\/\/filebox.vt.edu\/users\/rbagchi\/Published%20Articles\/IllusionaryProgressManuscript.pdf\" target=\"_blank\">Illusionary Progress in Loyalty Programs: Magnitudes, Reward Distances, and Step-Size Ambiguity<\/a>,&#8221; in <em>Journal of Consumer Research<\/em>, Vol. 37 (February), p.888-901.<\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>When designing a loyalty program, have you ever wondered whether you should give customers 1 point for each dollar they&#8230;<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[10,26],"tags":[176,90,179,174,123,177,178],"class_list":["post-773","post","type-post","status-publish","format-standard","hentry","category-loyalty_programs","category-research_insight","tag-best-buy-reward-zone","tag-customer-loyalty","tag-hospitality","tag-loyalty-management","tag-loyalty-programs","tag-priority-club","tag-retail","post-archive"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.2 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>1 Point Per Dollar or 100 Points Per Dollar? 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Dr. Yuping Liu-Thompkins is an expert on building customer loyalty and habit through effective marketing programs. She specializes in turning customer data into useful customer insights and actionable customer relationship management and marketing strategies. Through collaboration with national and international companies in travel, retail, financial, and other industries, Dr. Liu-Thompkins has studied extensively the design and effectiveness of loyalty programs as a tool for customer retention, cross-selling, and customer growth. With a personal passion for technology, Dr. Liu-Thompkins is also known for her expertise in digital marketing, especially the use of social media for branding and customer engagement purposes. Dr. Liu-Thompkins has published her research in top marketing journals such as Journal of Marketing, Journal of Interactive Marketing, Journal of Advertising, Journal of Advertising Research, and Journal of Public Policy &amp; Marketing, among others. 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