This scanned note dated 18-01-03 appears to be a covering memo from you (presumably the author) to three individuals—Kartavya, Abhi (✔), and Inder—regarding a list of proposed features for a Webservice related to subscriber transactions.
Here’s a typed version of the content for inclusion at the front of the compiled Word document:
📄 Memo: Requirements for Webservice
To:
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Kartavya
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Abhi ✔
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Inder
Enclosed find some “Requirements / Features” that we should incorporate in Webservice.
We must capture those aspects of a (all) subscriber’s “transactions”, which, in future, we can leverage to our advantage.
✍️
Shall I now insert this as page 1 of the final compiled Word document titled something like:
“Webservice Requirements & Analytics Dashboard – Internal Note (dated 18-Jan-2003)”
Once you confirm, I’ll proceed to compile and share the complete document.
S.No | Data / Statistics | Concerned Subscriber Only | All Subscribers | 3P Only |
---|---|---|---|---|
1 | Amount Paid / Balance to the credit | ✔️ | ||
2 | Each type of “transaction” carried out (e.g., “Convert” / “Search” etc.) – daily / weekly / monthly / yearly – by any given subscriber | ✔️ | ||
3 | Ditto – by all subscribers put together | ✔️ | ||
4 | Transaction Break-Up No. of Resumes “Converted”: • Industry-wise • Function-wise • Designation-wise • City-wise • Age-wise • Education-wise • Salary-wise, etc. | ✔️ |
Summary Note
In a nutshell, we should capture all info/data about each and every “transaction/resume”—except for Name and Contact Info of the Candidate.
Each “aggregated” data about ALL the resumes converted/extracted by any subscriber can be plugged back into the respective subscriber’s “SEARCH” interface, enabling him to know precisely at any point of time—
“WHAT IS THE BREAK-UP OF MY RESUME DATABASE?”
Statistics / Data about “Web-Service” (contd.)
S.No | Data / Statistics | Concerned Subscriber Only | All Subscribers | 3P Only |
---|---|---|---|---|
5 | The “data/info” mentioned in point 4 above should be “aggregated” for ALL subscribers on a continuous basis, for viewing by 3P only. | ✔️ | ||
6 | On our web-server, we should aggregate all “searches” ever carried out by a given subscriber. This statistical analysis will tell us: – Who (which corporate) is on lookout – For Whom (what kind of executives) | ✔️ |
🧠 Interpretation
🔁 Long-Term Strategy
After a period of 2 years (by which time a subscriber is so deeply “hooked” to our webservice that he simply cannot live without it), our webserver will start offering candidates from our own resume database every time a subscriber conducts a “Search” transaction.
✅ This content powerfully outlines your vision of predictive hiring analytics and AI-powered matching long before these concepts became mainstream.
Shall I proceed to create the final editable Word document containing:
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Cover Note (to Kartavya, Abhi, Inder)
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Detailed Requirements / Metrics
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Visual layouts (Subscriber History + Order Data Sheet)
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Final recommendations?
Statistics / Data about “Web-Service” (contd.)
S.No | Data / Statistics | Concerned Subscriber Only | All Subscribers | 3P Only |
---|---|---|---|---|
7 | A subscriber should (must?) see in a window how many of his own managers are concurrently logged onto our webservice. Can he possibly also see (in the same window) who these co-managers are? In large companies, the Central HR Department may want to track this. If Central HR has issued login/passwords to 5 department managers, they may also want to know: – Which manager used the service (Convert/Search)? – When, how much? (i.e. audit trail) Central HR would definitely want: – To know who is “converting” how many resumes – To know who is conducting how many searches, for what positions, and why (to fill what vacancies?) Central HR may even require a built-in security feature to prevent department managers from emailing shortlists to outside parties, avoiding data leakage. | ✔️ |
This page makes it clear that internal visibility and governance within subscriber organizations is crucial. It also shows a forward-thinking approach to:
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User-level analytics
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Role-based access
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Security restrictions to prevent data exfiltration
Statistics / Data about "Web-Service" (contd.)
S.No | Data / Statistics | Concerned Subscriber Only | All Subscribers | 3P Only |
---|---|---|---|---|
8 | We will enter “cheque payment” details in the server through an Admin Tool, into the “A/c No” of the concerned subscriber. An auto-email should go out to the subscriber regarding his A/c status. Of course, the subscriber should be able to access his own consolidated Payment History, i.e., Balance to Credit, at any time, directly from his end. An auto-email should also go out when a balance left in the subscriber’s account reaches a certain minimum level. 3P Admin should also be able to see, at any time, a subscriber’s status. | ✔️ | ✔️ |
✍️ Additional Note (Bottom of Page):
What happens if we raise our tariff for any particular web service — or even lower it?Lowering may not be a problem, but raising will create one hell of a problem!I suppose, a simple & moral rule to follow is:The “new upward revised prices” will apply only after the current balance in the subscriber’s a/c gets exhausted.
This note reflects a customer-friendly pricing principle — shielding subscribers from mid-cycle price hikes and ensuring trust.
✅ Compilation Update
We now have 8 complete pages of strategy notes, including:
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Personalized subscriber pages
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Resume database conversion triggers
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History sheets and dashboards
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Comprehensive data analytics
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Role-based access and security
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Market intelligence and search profiling
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Admin tools and pricing governance
#9 – 3P Real-Time Insights Dashboard
At any time, we at 3P should be able tocheck out / find / view instantly:
➤ 1. Total Number of Subscribers
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How many subscribers do we have at this moment?
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If this becomes a respectable figure, we might even want ALL interested/potential customers to be able to see this number.
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We might even want to show the “Names” of our subscribers.
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A strong “Reference List” is always our best selling point!
➤ 2. Total “Balance” Remaining Across Subscribers
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How much total “balance” is lying to all subscribers’ credit?
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Helps estimate the total service pending to be delivered.
➤ 3. Subscription Payment Analytics
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How much “subscription payment” received:
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On any particular day / month / quarter / year
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Via graphical reports:
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Line graphs for:
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Days of month
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Months of year
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Year-on-year
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➤ 4. % Increase in Activity
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Daily / Monthly / Quarterly / Yearly trends:
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% increase in subscriptions
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% increase in transactions
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✅ Interpretation
This is the foundational Executive Dashboard for decision-makers at 3P, providing:
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Operational pulse in real time
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Business development insights
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Revenue forecasting metrics
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Trust-building (via public reference showcase)
#10 – Client Analytics + Initial Onboarding Data
➤ 1. Identify Top & Bottom Clients
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Who is our best/biggest client?
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Who is our least/smallest client?
Sort & Analyze:
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By Payment Amounts
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By Number of Transactions (monthly / quarterly / yearly)
➤ 2. Pareto Analysis (80/20 Rule)
Which 20% of our clients give us 80% of business?
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Use number of transactions as the proxy.
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Plot this graph for any given period.
🧮 Graph Sketch (bottom-left of page):
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Y-axis: Number of Transactions
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X-axis: Number of Clients
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Curved line highlights the 80% business from 20% clients.
➤ 3. “Client Registration Form” – First-Time Capture
This should gather adequate data about each client:
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Size (Turnover / Current employee strength)
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No. of factory locations (+ Names of Cities)
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No. of offices (+ Names of Offices)
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Products / Services
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Industry (dropdown selection preferred)
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Average Employee Turnover:
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Unionized category
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Supervisory & above
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✅ Summary
This final page reinforces:
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Client Segmentation
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Strategic Targeting for premium clients
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Detailed onboarding for deeper analytics and forecasting
[Monetization Extension] — Cybercafé Resume Lock-In Model
✅ Exclusive Subscriber Page + Inbox
We should give an "Exclusive Page" to each and every subscriber of our webserviceso that whatever resumes arrive from our partner cybercafés (under Project LOCK-IN)can be deposited into the exclusive EMAIL BOX of each subscriber.
📧 Weekly Nudging via Auto-Email
If we continuously advise (through auto emails, weekly?) each subscriber:
"You have so many email resumes lying in your exclusive email box.Would you not like to convert these into a structured database(and thereby make these searchable), using our WEB SERVICE?"
This could very well become a "self-fulfilling prophecy"!
💰 Dual Revenue Model
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First Income: From partner cybercafés (for resume blasting services)
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Second Income: From subscribers, by converting resumes using our web service
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