An Empirical Analysis of the Modeling Benefits of Complete Information

4 Due to the vast amount of user data tracked online, the use of data-based analytical methods is 5 becoming increasingly common for e-businesses. Recently, the term analytical eCRM has been 6 used to refer to the use of such methods in the online world. A characteristic of most of the current 7 approaches in eCRM is that they use data collected about users' activities at a single site only. As 8 we argue in this paper, this can present an incomplete picture of user activities since it does not 9 capture activities at other sites. A more complete picture can be obtained by getting across-site 10 data on users. Such data is expensive, but can be obtained by firms directly from their users or from 11 market data vendors. A critical question for e-businesses is whether such data is worth obtaining, 12 an issue that little prior research has addressed. In this paper, using a data mining approach, we 13 present an empirical analysis of the modeling benefits that can be obtained by having complete 14 information. Our results suggest that the magnitudes of gains that can be obtained from complete 15 data range from 10% to 50% depending on the problem it is used for and the performance metric 16 considered. Qualitatively, we find that variables related to customer loyalty and browsing intensity 17 are particularly important and these variables are difficult to derive from data collected at a single 18 site. More important, we find that a firm has to collect a reasonably large amount of complete data 19 before any benefits can be reaped and caution against acquiring too little data.