Introductory text or abstract, then

to read more:

Here is the doc

so the steps are:

upload pdf to drive

change settings to public

copy the link

then in blogger, new post, compose, insert link and whatever text

then publish, it will appear on Google+.

Check: as a reader, click on link, it takes you to the pdf on owner's google+ or googleDocs whatever, click yet again on that and it leads to to full pdf.

If this is what Google does with simple pdf publication, how can we trust them to design a self-driveling car?

# theta_etc

musings and solutions to interesting problems: Ones that I think are easy, but then have a lot of structure.

## Thursday, August 25, 2016

## Sunday, June 7, 2015

### Video CPM as a Function of Demand - Complete

# Experiment description and Analysis

# 13 biggest client tactics representing about 9% of total video revenue were duplicated with all prior restrictions (geo, site, device etc.), additionally restricted to Tier I-III inventory and budget-density tested at 1X, 2X, 6X and 12X daily budget on 25, 12, 4 and 2 buckets respectively.

# For each of these budget points we have the spend, cost and impressions in the TierI-III inventory.

# From other sources (Roni's presentation) we know that about 15% of all our impressions (50% of all avails and 20% of cost) are in Tier I-III,

# so for all the video tactics which weren't restricted to TierI-III as part of this test, we uniformly apportioned 20% of spend and cost (assuming margin was same) and 15% impressions in the tested user buckets to TierI-III inventory.

# The above spend cost and impressions were added to those for the tested tactics,

# and CPM vs daily cost was plotted and fitted to a power law.

# Why a power law? Because cost (CPM) elasticity of demand (total cost) is the ratio of the logarithmic derivatives, which is just the exponent in a power law.

# dailySpend = AnnualSpend/365

# dailyCost = (1-margin)*dailySpend

# actualDailyCost = (spendFraction + (1-spendFraction)*costFraction) * dailyCost

#
Cost Based CPM from fit to elasticity curve evaluated at actualDailyCost

Revenue CPM = CostCPM/(1-margin)

## Wednesday, June 3, 2015

### ClickMePushYou

## The Puzzle

*If you click on *me...

*I* will disappear.

**Try clicking me away!**

### No, dooon't!

## How did you do?

Your score = 6 - (number of clicks + page_refreshes)

## Tuesday, June 2, 2015

### Player size restricted Video CPM as a function of Demand

# Experiment description and Analysis

# Biggest client tactics representing about 9% of total video revenue were duplicated with all prior restrictions (geo, site, device etc.), additionally restricted to Player size > 400 X 300 and budget-density tested at 1X, 2X, 6X and 12X daily budget on 25, 12, 4 and 2 buckets respectively. For each of these budget points we have the spend, cost and impressions in the player size inventory.

# We are clearly having trouble delivering at scale for the higher budget density - we are delivering only about 35%. For example, to hit the actual budget density points, every tactic in a line item (targeting different numbers of user buckets) should have had the same cost, yet on 5/19/15 the cost in "2 buckets" is only 129 instead of 379. Hence, while the goal was to explore a range 12X the current total video revenue, in practice we've only been able to get to about 4X.

# From querying our database

# we know that about 35% of all our impressions and 35% of video cost are for player size > 400X300, so for all the video tactics which weren't restricted by player size as part of this test, we uniformly apportioned 35% of spend and cost (assuming margin was same) and 35% impressions in the tested user buckets to player size restricted inventory.

# The above spend cost and impressions were added to those for the tested tactics,

# and CPM vs daily cost was plotted and fitted to a power law.

# Why a power law? Because cost (CPM) elasticity of demand (total cost) is the ratio of the logarithmic derivatives, which is just the exponent in a power law.

# The Calculator

# dailyCost = (1-margin)*dailySpend

# actualDailyCost = (spendFraction + (1-spendFraction)*costFraction) * dailyCost

#
Cost Based CPM from fit to elasticity curve evaluated at actualDailyCost

Revenue CPM = CostCPM/(1-margin)

## Monday, April 27, 2015

### Annual Video spend to Cost CPM calculator

# Experiment description and Analysis

# 13 biggest client tactics representing about 9% of total video revenue were duplicated with all prior restrictions (geo, site, device etc.), additionally restricted to Tier I-III inventory and budget-density tested at 1X, 2X, 6X and 12X daily budget on 25, 12, 4 and 2 buckets respectively. For each of these budget points we have the spend, cost and impressions in the TierI-III inventory.

# From other sources (Atul's presentation) we know that about 15% of all our impressions (50% of all avails) are in Tier I-III, so for all the video tactics which weren't restricted to TierI-III as part of this test, we uniformly apportioned 20% of spend and cost (assuming margin was same) and 15% impressions in the tested user buckets to TierI-III inventory.

# The above spend cost and impressions were added to those for the tested tactics,

# and CPM vs daily cost was plotted and fitted to a power law.

# Why a power law? Because cost (CPM) elasticity of demand (total cost) is the ratio of the logarithmic derivatives, which is just the exponent in a power law.

# How do I put in formulas? dailySpend = AnnualSpend/365

# dailyCost = (1-margin)*dailySpend

# actualDailyCost = (spendFraction + (1-spendFraction)*costFraction) * dailyCost

#
Cost Based CPM from fit to elasticity curve evaluated at actualDailyCost

Revenue CPM = CostCPM/(1-margin)

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