Notes

cc: Kartavya / Abhi

Date: 03/10/03

Page: 4/6

Period	5% increase every 6 months	10% increase every 12 months
0	100	100
6 month	105	100
12	110.25	110
18	115.8	110
24	121.5	121
30	127.6	121
36	134.0	133

Sanjeev – Webservice Pricing

See enclosed report on how cell-tariffs are once again inching up after dropping for the last 3 years.
In context of our webservice, remember the following guidelines:

Smaller increases at more frequent intervals are more “digestible” than a big increase every few years (or every year).
You should not increase prices of all transactions at the same time. We should do this in rotation. So, if you have 12 “chargeable” buttons, you raise the price of only one button each month. So, you end up increasing prices of all buttons — once a year!

All price-increases (whenever made/announced) must not be of the same fixed percentage.

One button you may increase by 3% in January,

Second button by 5% in February,

Third button by 7% in March, and so on.

In between, in a particular month or quarter, you may not announce any price increase for any button, but you may transfer some one button from FREE to PAID category.
Then, in some month, you may be adding an altogether NEW button (new functionality) which is PAID. In such a month, you must not increase the price of any other button.

Many organizations have failed to develop mechanisms whereby they can quickly and easily differentiate between:

→ the increase/growth in the company’s annual revenue due to volume/quantity increases, and
→ the increase/growth in the company’s annual revenue due to selling-price increases.

This is a dangerous/misleading situation!

Let us say Recruitguru’s Net Collection goes up from Rs. 1 crore (in a particular year) to Rs. 1.5 crore (in the next year).

That is a growth of 50%!

But is that a reason to be overjoyed?

This increase could have been:

A → entirely due to increase in selling price only (i.e., no increase in volume/quantity)

B → entirely due to increase in volume/quantity only (i.e., no increase in selling price)

C → due to some increase in selling price and some increase in volume (no. of transactions).

In real business life, you rarely come across situations A or B. Mostly it is C.

In fact, the most likely situations are:

D → Increase in selling price / Decrease in volume, or

E → Increase in volume / Decrease in selling price.

So a company’s performance must not be judged simply based on a “% age growth in revenue over the previous year.”

It is very, very important to know how this growth came about — what factors contributed to this growth and how much was the contribution of each factor.

This Volume Variance / Price Variance analysis should be done not only at the overall company level but also at the level of each and every subscriber as well.

So, whereas ARPU (Average Revenue Per User) and specific individual revenue growth for each client are useful indicators, you must know at each subscriber level:

→ Is his volume usage growing & contributing to increased billing? — and how much?

Increase in selling prices are like inflation (consumer price index).

A business can simply increase its product/service prices by 15% each year and show a revenue growth of 15% each year without selling even one piece more than the previous year!

Shareholders and the bankers and the employees all will be “happy” to see the...

...results, and the share price will keep rising —

until someday the company is unable to raise its prices due to increased competition!
That will be the year of reckoning! The bubble will burst!

So, for a healthy and sustainable growth, both the volumes and the prices must rise to contribute to overall growth.

And we must be able to monitor separately the effect/impact of both the volume-induced revenue growth and the price-increase-induced revenue growth, year after year.

For Recruitguru, we will use the first FULL YEAR (viz., April 2004 – March 2005) as our datum — the Base Year — and compute for each subsequent year as follows:

Parameter	Base Year 2004–2005	2005–2006	2006–2007
Gross Net Collection (or BL₹)	e.g., Rs. 150L	200L	300L
Index (Gross)	100	133	200
No. of Transactions	5 Lakh	6 Lakh	8 Lakh
Index	100	120	160

Sanjeev

Date: 20/09/03

Auto-roaming: Cell Cos May Not Comply With TRAI Directive

(News clipping dated 19/09/03 – Mumbai)

Cellular operators seem set to flout the Telecom Regulatory Authority of India’s directive to discontinue national roaming charges for incoming calls. The TRAI had ordered all mobile operators to stop charging subscribers for incoming calls while on roaming from September 19. Operators have reportedly continued billing citing technical and revenue constraints, leading to consumer protests. [Further clipping text truncated in image.]

Notes

This is an ingenious way of making money!
Earlier, Airtel had started diverting unanswered calls to your Voicemail Box and treating all such calls as “Completed Calls” — charging the calling party!
“Automated Roaming” started free — now made paid! (And if you have purchased a pre-paid SIM card, you don’t have any option!)

Lessons for Recruitguru

These happenings have valuable lessons for Recruitguru, which is both pre-paid and pay-per-use.
All buttons which initially we propose to offer FREE,
must be listed on the Tariff Chart with the footnote:

“Currently Free” — implying that we reserve our right to make these PAID/PRICED at a future date.

As no. of clients and no. of transactions grow, one-by-one, gradually (without giving shocks), we must convert these buttons to PAID.

(Signed/dated: 20-09-03)

Sanjeev

Date: 19/09/03

Subject: Pricing – “Pay-per-Use” (USP)

R&G Satchet Spurs Washing Powder Price War

(Economic Times clipping dated 18/09/03)

Procter & Gamble has triggered a fresh price war in the detergents market by cutting the price of its Ariel and Tide sachets. Hindustan Lever is expected to respond shortly. Analysts attribute this to shifting consumer preferences towards smaller, affordable sachets offering pay-per-use convenience. [Further clipping text truncated in image.]

Key Insights

Whether it is Pan Parag or washing powder, whether it is Procter & Gamble or HLL — marketing guys are fast learning one thing:
→ Every consumer does not have the same amount of consumption.
→ Every consumer wants to pay for only what he immediately consumes — not for what he might consume tomorrow/3 weeks later/3 months later.

Examples

Mobile operators → Prepaid → Pay-per-use
Cable TV operators → Postpaid → Pay-per-use (CAS)
Music downloads → Prepaid → Pay-per-download (iTunes)
Xerox Me → Postpaid → Per copy xeroxed
Plain phones → Postpaid → Per call used

You would do well to compile an exhaustive list of “pay-per-use” services and make a PowerPoint slide for your presentation.

cc: Kartavya / Abhi

HLL Launches Lifebuoy at ₹2

(News clipping — 19/09/03, by Namrata Singh)

Hindustan Lever has launched Lifebuoy in a new ₹2 pack aimed at expanding its presence in India’s vast rural market.

The 100-year-old brand, with sales of ₹350 crore and 31.8% growth rate, will now be available in a smaller, more affordable sachet-like size of 18 grams, priced at ₹2.

This move targets deeper market penetration among lower-income groups and rural consumers, providing a “feel-good” factor to the economy.

Sanjeev

Date: 20/09/03

Subject: Pricing Strategy / Lessons to be learned (Lifebuoy)

100-year-old brand / ₹350 crore sales / 31.8% growth rate.
Repositioning for better penetration in rural markets. (Here too, we are talking of 30,000 cr in SME sector!)
₹2 for 18 grams, BUT strip of 12 packs.
Pay-Per-Use logic: Why must you buy 75g soap at ₹15/18 or 125g soap at ₹30/40 — especially if you need to use only 3g a day?
This is the reason (Pay-Per-Use logic) why sachets form 70% of total shampoo market.
With each passing day, we see around us glorious examples of “Pay-Per-Use / Penetration Pricing / Mass Market.”

(Dated: 20/09/03)

Kartavya / Abhi / Sanjeev

SriRam / Rajiv / Nirmit

Date: 16/09/03

Subject: Web-Service Pricing

Page: 1/6

In our meeting two days ago, I pointed out important guidelines regarding pricing of our Recruitguru Webservice, viz.:

INDUSTRY STANDARD

Our pricing strategy must enable us to become the de facto industry standard.
This means any competitor who cares to venture into the area of Recruitment Webservices would need to follow the practice set by us.
This is because the market expects the followers to offer a pricing structure which can be easily compared with the structure already established by the leader/pioneer.
If the next provider of recruitment self-servicing wants to charge per hour/per month etc., he would face stiff resistance from corporates who have already got used to Recruitguru’s per-click structure.

In essence, we as pioneers must set and establish the “Rules of the Game,” by which this entire new industry must play the game!

DYNAMIC

Our pricing structure must be dynamic.

We should be in a position to change it over a period of time — and as frequently as deemed necessary.

We should be able to make this change online (through ADMIN) so that automatic email announcements go out to:

Existing clients
Potential clients

Whereas for potential clients, the new structure becomes applicable (through revised Tariff Chart) instantly, for existing clients it will become applicable when their current Credit Balance becomes NIL / ZERO.

They (the existing clients) must not be in a position to “cheat” us by depositing another cheque for Rs. 5 lakhs the moment they hear that the per-mouse-click prices are going up!

If the new prices announced are reductions (i.e., going down), I have some solution, but Sanjeev must come out with his proposals.

LOCK-IN

One — perhaps the most important — feature of any pricing structure is to “Lock-in” the customer and then make him pay for the rest of his life!

This is why drug peddlers offer free dings in the beginning — once you get addicted, the extortion process sets in!

This is exactly what Reliance has done by offering a mobile handset for mere ₹501/– and then making you pay ₹220/– p.m. for 36 months!

If you want to quit in between, you need to “refund” ₹8,000 / ₹5,000 / ₹3,000 (1st / 2nd / 3rd year)!

Of course, a far subtler and unseen way of locking a customer is the non-portability of your mobile no.!
If you have given this no. to hundreds of friends/relatives—and worse, to your customers—you are hooked forever!

The cost of switching—over to another service provider—no matter how cheap or how excellent—will be mind-boggling.

This is why we should price our “Extraction / Conversion” button at no more than ₹5.00 (or even ₹2.50), so that having converted 1 lakh / 5 lakh resumes, the customer has no choice but to remain locked-in!

MASS CUSTOMIZATION

Our pricing structure must enable us to “customize price for each and every (paid) mouse-click for any given customer.”

So, if there are 2,000 customers, theoretically, we can have 2,000 different prices for (say) Extract Button 1.

So, if we have 5 paid (not free) buttons, we would have 2,000 × 5 = 10,000 prices!

We (Sanjeev) must use this fantastic mass-customization feature to extract maximum money out of each customer — all the while giving the customer a feeling of being uniquely / specially treated.

And for extracting maximum money out of each client, Sanjeev will, every month, closely examine the Customer-wise Usage & Revenue + Server-load graphs shown in Annex.

This study will tell him:

What are customer-wise usage patterns.
In which mouse-click we are losing out.
In which mouse-click we are achieving max. revenue (₹80/₹20 rule / A:B analysis as shown in “U” graphs).
Which mouse-clicks are loading our server most.

The actual “Cost of Conversion” is irrelevant to our pricing strategy — which must remain geared to our “Lock-In” strategy.

Remember that we have to make money overall from each customer. This would require some buttons / some mouse-clicks getting subsidized by some better-paying / better-yielding mouse-clicks!

So what is far more important is to decide/figure out — and then enforce — ARPU (Average Revenue Per User per month of course!)

Customer Base = 432 (as on 20/09/03)

(Graph 1: Frequency Distribution)

X-axis: Monthly ARPU (₹)

Y-axis: Frequency (No. of Customers)

Two curves shown:

Bad Model: High frequency at low ARPU (steep early peak, quick fall).
Good Model: Broader distribution peaking toward higher ARPU (flatter curve).

(Graph 2: Cumulative Curve)

X-axis: Cumulative No. of Customers

Y-axis: Cumulative Monthly Revenue (₹ Lakh)

Shows a rising curve flattening toward saturation — illustrating diminishing returns after top-paying customers.

At a glance, such a monthly graph would tell Sanjeev:

→ Which (few) customers are Most Valuable and deserve max. personal attention (the CAKE!).

→ Which (large no.) customers are Good Value and deserve regular email communication to encourage them to stay on / increase their usage (the BREAD!).

→ Which (few) customers are Value-less and deserve to be politely got rid of (the CRUMBS!).

Web — and more so, a Webservice — enables us to carry out real fine-tuning of pricing, dynamically over time, in respect of each customer, so that someday, our ARPU graph looks like this:

(Graph illustration — ARPU Rs/Month vs. No. of Clients)

A bell-shaped curve with high, stable middle, representing balanced revenue spread.

Possible — if we are clever!

(Signed and dated: 16/09/03)