Name
Abstract | ||
|---|---|---|
Determining and setting maximal revenue expectations or other business performance targets---whether it is for regional company divisions or individual customers---can have profound financial implications. Operational techniques are changed, staffing levels are altered and management attention is re-focused---all in the name of expectations. In practice these expectations are often derived in an ad hoc manner. To address this unsupervised task, we combine nearest neighbor methods and classical statistical methods and derive a new solution to the classical econometric task of frontier analysis. We apply our methodology to two real world business problems in Verizon, a major telecommunications provider in the United States, more specifically in the print yellow page division Verizon Information Services: (1) identifying under marketed customers for targeted upselling campaigns and focused sales attention, and (2) benchmarking regional directory divisions to incent performance improvements. Our analysis uncovers some commercially useful aspects of these domains and by conservative estimates can increase revenue by several million dollars in each domain. |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1145/502512.502575 | KDD |
Keywords | Field | DocType |
real world business problem,performance improvement,regional company division,classical statistical method,frontier analysis,classical econometric task,business performance target,maximal value estimation,estimating business target,management attention,nearest neighbor,maximal revenue expectation,verizon information services,nearest neighbor method | Revenue,Information system,Data mining,Staffing,Computer science,Directory,Upselling,Artificial intelligence,Frontier,Machine learning,Benchmarking | Conference |
ISBN | Citations | PageRank |
1-58113-391-X | 0 | 0.34 |
References | Authors | |
10 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Piew Datta | 1 | 105 | 24.65 |
| James H. Drew | 2 | 0 | 0.68 |
| Andrew Betz | 3 | 21 | 15.51 |
| D. R. Mani | 4 | 81 | 20.82 |
| Jeffery Howard | 5 | 0 | 0.34 |