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The ability to create switching costs and build customer loyalty has also been argued to be a major driver of success in e-commerce businesses (Reinchheld and Schefter 2000). However, it has been observed that over 50% of customers stop visiting com- pletely before their third anniversary (Reinchheld and Schefter 2000)
If switching costs are inherently low and firms are unable to lock in customers, long-term prof- itability may be difficult to attain, especially in many B2C e-commerce environments with low entry barriers (other than customer acquisition costs) and limited dif- ferentiation. Crypto has low barriers to entry. Permissionless for users. Low barriers for entrepreneur
As a result, it becomes critical for a firm to manage its retention ability, which is determined by switching costs and attrition rates. The first step for managing retention is to be able to measure the mag- nitude of switching cost and identify what factors affect switching and attrition. As Shapiro and Varian (1998) argue, You just cannot compete effectively in the information economy unless you know how to identify, measure, and understand switching costs and map strategy accordingly
As classified by Klemperer (1987), there are at least three types of switching costs: transaction costs, learning costs, and artificial or contractual costs. Trans- action costs are costs that occur to start a new relation- ship with a provider and sometimes also include the costs necessary to terminate an existing relationship. Learning costs represent the effort required by the cus- tomer to reach the same level of comfort or facility with a new product as they had for an old product. Artificial switching costs are created by deliberate actions of firms: frequent flyer programs, repeat-purchase dis- counts, and “clickthrough” rewards are all examples. Besides these explicit costs, there are also implicit switching costs associated with decision biases (e.g., the “Status Quo Bias”) and risk aversion, especially when the customer is uncertain about the quality of other products or brands.
First, the market is large and sig- nificant and is considered to be one of the “killer ap- plications” in B2C electronic commerce (Varian 1998, Bakos et al. 2000). There were over 140 online retail brokers by the end of 1999 and they managed just over 1 trillion in customer assets in 2000. By year-end 1999, these accounts represented about 15% of all brokerage assets and 30% of all retail stock trades (Saloman Smith Barney 2000). Second, as noted in the Introduction, this industry has very aggressive customer acquisition tac- tics, partially because of the high lifetime value of an active account (1000). Third, the complexity and fi- nancial significance of a stock trade makes it likely that consumers generally face learning costs and other de- terrents to switching, including a difficult process of either transferring assets or liquidating stock positions in order to switch brokers
In our earlier analysis, we found that attrition (custom- ers who have a brokerage account at some time but do not return to any broker in the future) is a significant problem.
It is also important to note that demographics typi- cally are not good predictors of behavior except for a few isolated results on attrition. One notable result is that women are found to be more likely to become inactive. This gender effect appears consistent with a recent study by Barber and Odeon (1999) which found that men trade online significantly more frequently than women, so it is not surprising that women are more likely to become inactive
Moreover, to the extent that systems usage encourages retention through system-specific learning, it would imply that firms could improve retention by encouraging consumers to frequently visit and use their sites. Our analysis also suggests that systems design characteristics such as personalization and ease of use should be reconsidered both in terms of their measurement and in further eval- uation to determine whether they have the intended effects on long-term customer behavior.