From Price Discrimination To Value Discrimination
Leveraging the power of IBM Analytics Technologies & Solutions
Leveraging the power of IBM Analytics Technologies & Solutions
Background
Traditionally industries and businesses with pricing power adopted various degrees of price discrimination strategies to maximise profits. In today's fast changing globally competitive environment with rapid commoditisation of technology and network access, no business is likely to enjoy the exclusive status for an extended period of time. Businesses need to look for ways to mine more value for individual customers and formulate strategies for value based pricing strategies vis-a-vis pure price based strategies.
And the good news is IBM has technologies and solution assets that helps customers do that!
And the good news is IBM has technologies and solution assets that helps customers do that!
Value Discovery & Price Discrimination in Traditional Markets
Let me illustrate the idea with some real life examples. While I was studying for my graduation, I used to visit used-book stores to buy books so that I could buy them cheaper compared to new ones. Recounting old memories, I feel that I always got ripped off by the canny salesman at the used-book shop even though I thought I was smart enough to have bargained 60-75% off the initial quoted price.
Obviously he observed each of my traits very keenly and was very quickly able to predict the “value” (and hence likely price) that I attached to the book. He possibly observed the quality of my shoes, the brand of my shirts and trousers I wore, the characteristics of the friends I took them along, the bag of other items I bought and carried with me and even the degree of sophistication of my speech and looks.
I believe he could consistently predict and discover value and price thresholds and ranges for every customer he dealt with. With his adept price discrimination strategies he could maximise profits on his every sale.
“Used Car Salesman” belong to the similar breed and if you have had personal experiences with some of them you may be able to personally relate the point I am trying to make.
Value Discovery & Discrimination Leveraging Technology
Obviously In today's fast changing globally competitive environment with rapid commoditisation of technology and network access, no banks, telcos or any large business for that matter enjoy price discrimination for an extended period of time. In fact the reverse is true – they are under lot of competitive pricing pressure.
In such an environment, one viable approach is for businesses to have technology capabilities that can help discover value points for each individual customer. Discovering and sharing value metrics with customers is by itself a great value added activity in the overall buying processes. This increases customer trust, customer satisfaction, loyalty, increases the value of each sale and possibly shortens sales cycle times.
The big difference here is – unlike the used book or used car salesman who keeps the manual value discovery process as top secret with the intention to exploit the customer with maximum possible price, the enterprises leverage automated predictive analytics and optimisation technologies to discover and share maximum value possibilities with the customer based on “knowns” such as customer personal, family and income profiles, risk preferences, past transactions, product use behaviours, channel interactions, social interactions etc.
The net outcome is customers are able to make insightful and informed buying decisions and are willing to part with premiums for such value added services and organisation is able to quantify customer's present and future value.
Key to success : Helping CXOs identify opportunities for business transformation & growth
IBM provides consulting services to help customers identify value creation opportunities using deep analytics capabilities across industry and functional domains. For rapid Time To Value (TTV), IBM also
offers related solution accelerators such as “Action Clusters” and NBA (“Next Best Action”) built on IBM's predictive analytics technologies SPSS and iLog Optimisation engines.
offers related solution accelerators such as “Action Clusters” and NBA (“Next Best Action”) built on IBM's predictive analytics technologies SPSS and iLog Optimisation engines.
