Analytically determining revenue of internet companies using internet metrics

• US 20030014336A1
• Filed: 05/03/2002
• Published: 01/16/2003
• Est. Priority Date: 05/04/2001
• Status: Abandoned Application

• Current Assignee: Intellectual Ventures Assets 186 LLC (Intellectual Ventures LLC)
• Original Assignee: Intellectual Ventures Assets 186 LLC (Intellectual Ventures LLC)
• Inventors: Weerahandi, Samaradasa, Martija, Ricardo, Dao, Fu-Tak, Spacek, Thomas
• Application Number:
  US10/139,503
• Publication Number:
  US 20030014336A1
• Time in Patent Office: Days
• US Class Current: 705/30
• CPC Class Codes: G06Q 10/06375 Prediction of business process outcome or impact based on a proposed change
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0282 Rating or review of business operators or products
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/02 Banking, e.g. interest calculation or account maintenance credit or loans G06Q40/03
• CPC Class Codes: G06Q 40/12 Accounting

Abstract

With respect to a current quarter of unreported revenue for certain Internet companies, by processes performed by a computer revenue to date is analytically determined and future revenue for the remaining quarter is statistically projected by modeling revenue based on “Internet metrics”. Actual revenue performance is obtained and one or more “Internet metrics” are measured for a given Internet company. Using the revenue and measured Internet metric data from prior quarters, a regression analysis is performed in order to generate multiple models that reflect the relationship between the Internet metrics and revenue. From these models, one is selected that will most likely yield the best revenue estimates. This resultant model and current Internet metric data are subsequently used to estimate the company'"'"'s revenue for the current day, week, month, or quarter. These estimates are also used to project the company'"'"'s revenue for future days, weeks, months, and quarters.

Claims

1. A method for estimating current revenue of a company, said method comprising the steps performed by a computer of:

obtaining the company'"'"'s actual quarterly revenue performance for a plurality of prior quarters,

obtaining data points for an Internet metric over the plurality of prior quarters, wherein the Internet metric is related to the company,

generating a revenue model for the company using the obtained actual quarterly revenue performance and the obtained Internet metric data points,

obtaining one or more current data points for the Internet metric, and

estimating the company'"'"'s current revenue by applying the obtained current Internet metric data points to the generated revenue model.

2. The method of claim 1 wherein the obtained actual quarterly revenue performance and the obtained Internet metric data points for the plurality of past quarters are obtained for no more than six prior quarters.

3. The method of claim 1 wherein the generated revenue model is a quarterly revenue model.

4. The method of claim 3 further comprising the step of scaling the generated quarterly revenue model to a weekly revenue model, and wherein the obtained current Internet metric data points comprise one week of data points, and wherein the estimated company'"'"'s current revenue is revenue for this one week.

5. The method of claim 1 wherein the generated revenue model is a weekly revenue model, the obtained current Internet metric data points comprise one week of data points, and wherein the estimated company'"'"'s current revenue is revenue for this one week, said method further comprising the steps of:

obtaining current data points for the Internet metric over a plurality of weeks,

estimating the company'"'"'s weekly revenue for each of the plurality of weeks, and

summing the plurality of estimated weekly revenues to obtain the company'"'"'s revenue for the current quarter.

6. The method of claim 1 wherein the generated revenue model is a weekly revenue model and wherein the estimated company'"'"'s current revenue is for the current week, said method further comprising the step of projecting revenue for a following week.

7. The method of claim 6 wherein the revenue projection is made through a running average technique.

8. The method of claim 7 further comprising the steps of:

projecting revenue for all remaining weeks in a quarter beyond the current week, and summing all revenue estimates and revenue projections for a quarter to obtain a quarterly revenue estimate.

9. The method of claim 1 wherein the Internet metric is a page-hits metric, a visitors metric, a transactions metric, or a hosts metric.

10. A method for estimating current revenue of a company, said method comprising the steps performed by a computer of:

obtaining data points for at least two Internet metrics over a plurality of past quarters, wherein said at least two Internet metrics are related to the company,

creating new Internet metric data points over the plurality of past quarters by combining the data points from the at least two Internet metrics,

generating a revenue model for the company by using the created new Internet metric data points,

creating one or more new Internet metric data points for the current quarter by combining one or more current data points obtained for each of the at least two Internet metrics, and

estimating the company'"'"'s current revenue by applying the created new Internet metric data points to the generated revenue model.

11. The method of claim 10 wherein the new Internet metric data points for the past and current quarters are created through standard sums.

12. The method of claim 11 wherein standard deviations are used as a weighting factor in the standard sums.

13. The method of claim 10 wherein the generated revenue model is a quarterly revenue model, the method further comprising the step of scaling the generated quarterly revenue model to a weekly revenue model, and wherein the created new Internet metric data points comprise one week of data points, and wherein the estimated company'"'"'s current revenue is revenue for this one week.

15. The method of claim 14 wherein each of the plurality of generated revenue models corresponds to one of the plurality of Internet metrics.

16. The method of claim 15 further comprising the step of:

combining the past quarter of data points for each of the plurality of Internet metrics to create one or more new Internet metrics and corresponding data points, and

wherein the plurality of generated revenue models further includes a revenue model corresponding to each of the new Internet metrics.

17. The method of claim 16 wherein the choosing step comprises the steps of:

computing r² for each of the plurality of generated models, and choosing the revenue model for estimating current revenue based on the largest r² value, where r² is the coefficient of determination.

18. The method of claim 17 wherein the choosing step further comprises selecting the Internet metric or combined Internet metric used to make a prior revenue estimation.

19. The method of claim 14 wherein each of the plurality of Internet metrics is a page-hits metric, a visitors metric, a transactions metric, or a hosts metric.

14. A method for estimating current revenue of a company, said method comprising the steps performed by a computer of:

obtaining data points for each of a plurality of Internet metrics over a plurality of past quarters, wherein said Internet metrics are related to the company,

generating a plurality of revenue models for the company by using the obtained data points for each of the plurality of Internet metrics,

choosing from the plurality of revenue models a revenue model for estimating current revenue, and

estimating the company'"'"'s current revenue by applying currently obtained Internet metric data points to the chosen revenue model.