Pricing becomes a challenge when a company has thousands of products, and manual price-setting fails to unlock value that may be there if a full analysis were done for each of those products. In face of complexity, marketers simply lean on simplistic factors such as the cost-plus margins, prices for similar products, volume discounts etc. In these case, Big Data can be a significant contributor. B2C companies are typically better at managing and analyzing big data when compared to B2B cos. (insights from McK article at http://www.mckinsey.com/Insights/Marketing_Sales/Using_big_data_to_make_better_pricing_decisions).
Loyalty Programs: U.S. companies spend $50 bn annually on loyalty programs but the results are overall neutral (through vary by industry), but a company that pursues loyalty programs has 10% lower EBITDA margin when compared to company that does not (in the same sector). See the presentation at http://www.slideshare.net/McK_CMSOForum/making-loyalty-pay. It seems that me-too loyalty programs generally are bad (shocker), and the loyalty programs are useful when the incremental margin on the product is sufficiently high to absorb the cost of the loyalty program (and is able to bring customers that wouldn’t come otherwise). Grocers, car rentals and airlines can’t use royalty programs well because in case of car rentals and airlines, the products are commodities and they generally compete on price, whereas grocery shopping is all about convenience (distance from the house), so loyalty programs will end up attracting the people who would go there anyway. Drugs, hospitality, coffee and discount stores are good users. Drugs because of the high incremental margin, hospitality because the room probably would be unutilized otherwise, and discount store because the average tickets is high enough that people are willing to drive to the place to get that discount (plus business model forces a large ticket to begin with). I am not sure why coffee shops are so successful with the loyalty program; beats me.