CORPORATE REPUTATION

CORPORATE REPUTATION INDICES (13-09-04)

• Job Advt. Click-Rate (Job Advt. Wise)

 = {No. of "Apply Online" clicks against a given Advt{No. of Alerts sent against a given Advt}}

• Overall Corporate Click-Rate [Corporate Wise]

 = {\sum {Individual job-advt. wise clicks (Total){Total No. of Alerts sent against all job-advts. (for a given Corporate)}}

• Feedback Rate

 = {No. of feedback clicks (made by an HR mgr) by a company{No. of Resumes delivered (so far) to a company}}

• Corporate Popularity Index

 = {No. of Votes polled by a Corporate{Total no. of votes CAST by all jobseekers}}

CORPORATE REPUTATION (09-09-04)

• How Good (or Bad) is your job-advt.?

How does it compare with job-advts. drafted by other Companies, for the same FUNCTION?

• Function: Sales
• No. of Job Advts Processed: 15263
• Y-axis: No. of Job Advts
• X-axis: Percentile Score (or Raw Score)
• A curve resembling a normal distribution is shown.
• A vertical bar is shown at a Percentile Score of 25, marked as: "Job Advt. No. by XYZ Company".
• Maybe we should allow only the concerned Advertiser (Company) to view this graph.

CORPORATE REPUTATION (06-09-04)

[Table with 4 columns for data, A, B, C, D]

Sr.	Date	Advt. Serial No. (Ref. No)	Position/Title	A: No. of Alerts Sent against this Ad	B: No. of Apply Online Clicks against this Ad	C: Cumulative Alerts (Till date)	D: Cumulative No. of Clicks
				a_1	b_1	c_1	d_1
				a_2	b_2	c_2	d_2
				a_3	b_3	c_3	d_3
Total				\sum a	\sum b

• c_2 = a_1 + a_2
• d_2 = b_1 + b_2
• c_3 = a_1 + a_2 + a_3
• d_3 = b_1 + b_2 + b_3

Response Index

• Job-Advt-Wise:

 {b_1}{a_1}, {b_2}{a_2}, {b_3}{a_3}, {etc.}

• Composite Index (for all job-advts processed so far)

 = {\sum b}{\sum a}

• Composite Cumu. Index

 {d_2}{c_2}, {d_3}{c_3}, {d_4}{c_4}, {etc.}

Reputation - Corporates (13-10-04)

A Company's reputation amongst jobseekers will depend upon

• Does this job advertiser give any "feedback" at all, to candidates applying for jobs?
• If yes, then,
• how "fast" does he give such feedback?
• Corporate: ABC
• Position on: Jan 2006
• Total Ads:
• Total Response: (Apply Online)
• Total Feedback:

Y-axis	Percentage of Applicants Receiving Feedback
X-axis	No. of Days within which "Feedback" sent to Applicants

• The curve is shown resembling a normal distribution.
• The Y-axis shows 10%, 20%, 30%, 40%, 50%.
• The X-axis shows days: 2, 3, 4, 5, 6, 7, ..., 15 Days.

A look at this graph will tell a candidate,

"If I apply to the company, in how many days can I expect to receive a feedback?"

Corporate = XYZ

• Y-axis: Percentage of Job-Advt Released
• X-axis: 0, 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%
• Curve 1 (Solid line): Resembles a normal distribution, labeled "a poor performance" on the left peak.
• Curve 2 (Dashed line): Skewed right, labeled "a better performance" on the right tail.

Average Response Index

{Total "Feedback" clicks (cumu){Total "Resumes" received (cumu)}} \times 100\%

Explanation

A Recruitment manager may not send same percentage of "feedback" to each & every job ad response.

• In one advt: For some ads, he may receive 100 resumes & give feedback to 30. (So Response Index = {30}{100} = 30\%)
• In another advt: he may receive 50 resumes & give feedback to 15. (So Response Index = {15}{50} = 30\%)
• And in still another advt: he may receive 200 resumes & give feedback to 50. (So Response Index = {50}{200} = 25\%)

Employers' Corner

• A list of all job-advts released on jobsites (chrono)

 \left[ {Incl.} = \begin{cases} {No. of job-alerts sent against each}  {No. of Resumes received} \end{cases} \right]

Click to reveal

• List of candidates who applied against each job-advt. (along with function/raw score/percentile score)

Click to reveal

• Resume of any particular candidate (Imagebuilder)
• \left. \begin{array}{l} {Function Profile}  {Salary Profiles}  {Design}  {Tenure}  {Population Profiles} \end{array} \right\} \quad {"Paid" (subscription) Service}
• IP addresses of 6^{{th}} I-WAY Cybercafes?
• 5^{{th}} Cum Ad (Phase II) {Ad-Compose (Phase I)}
• Job-Blasting
• DCA CD - 6.3 {L} Company data
• Names/email IDs of HR managers

• Resume Symmetry Profile
• Communities of Co-related Execs.
• Candidate Alerts
• Resume download (after Resume Search)
• Resume Search (Cum Search)
• Imagebuilder upload
• Job Mkt: Analysis (Tabulations/Graphs)