2014 Session 7 Video Sales

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Forecasting Demand for Movie DVDs


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The Movie Business

Film making is a risky business

Studios make no money from films !!!

That is if we look at box-office alone

Over time, film studios have learnt that they must makemoney from post box-office revenues

Rental revenues

Pay-per-view

Sale of VHS tapes and DVDs to end users

In 2003, over 50% of revenues from a title come fromsale of VHS/DVDs to end users.


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The Motion Picture Industry

Typical Market Window From Release Date

0 12 24 84

Domestic theatrical

Foreign theatrical

Pay per view

Domestic home video

Foreign home video

Pay TV

Foreign TV

Network TV

Syndication

Time (in months)

Source: Vogel (2001)


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Interesting Data

In 2002, on average

To produce a movie: $59 million

To promote a movie: $31 million

To distribute a movie in theaters: $16 million

To make profit from a movie: priceless

FACT:Average domestic box office revenue: $32.5 million

Video: the cash cow of the motion picture industry

Box office: Domestic: $9.5 billion

International: $9.6 billion

Video Rental: $8.1 billion

Sales: $12.2 billion (remains strong even today)


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Forecasting Demand for Movies andRelated Products

Marketing people have worked for years on how toforecast success/failure of new products Products ranging from computers, cars, to soap and shampoo.

Movies: Experiential Products !!!

Perceptual heterogeneity as well as preference heterogeneity. Models exist to predict what movies will do well in the

box-office

Industry Response to this work is at best weak. Studios find this work useful but do not use it !

Single-period vs multi-period view of the world

DVD sales: no such issues it is a packaged good soldin Walmart there is no news about Walmart salesnumbers on CNN


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http://en.wikipedia.org/wiki/File:Mynameiskhan.jpg


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http://en.wikipedia.org/wiki/File:Chameli_poster.jpghttp://en.wikipedia.org/wiki/File:Fida.jpghttp://en.wikipedia.org/wiki/File:Jab_We_Met_Poster.jpg


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The Key Problem in Predicting DVD Sales

Rental Demand is very highly correlated with BoxOffice Performance [r-square = 0.9]

Direct Sell-through demand is only marginallyrelated to Box Office Performance [r-square = 0.4]

There is something about a DVD What is it about a DVD ..

Multiple viewings as opposed to one viewing.

Our research begins here.
http://www.amazon.com/exec/obidos/ASIN/6305499071/ref=ase_bestofcamerodiaz/102-7704295-6405740


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Traditional Modeling vs Our Approach

Traditional choice models in marketing rely on constancyof the choice set and attempt to forecast how demandcan be modeled as a function of marketing controlvariables price, advertising, product features etc.

There are a few key brands of toothpastes, cell-phones, cars, wewant to understand how shares might be affected bypromotions, advertising etc

We add a new brand to an existing set, what share it will get.

When it comes to movies and DVDs, the choice setchanges from one purchase occasion to the next.


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Idea of the Model splitting a pie

The basic idea of the market share model of DVD saleshas two parts:

1. Total sales of all DVD titles available in each week is the totalsize of the pie.

2. The pie is split by the DVD titles available in that week.

An example

DVD Sales of Week x, 2002

Shrek

20%

Dr. Seuss How

the Grinch

77%

Legally Blonde

3%


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Formulation of the Model (I)Total Size of the Pie

This is a linear regression, where DVD Weekly TotalSales is a function of DVD Installed Base, SeasonalityIndex (constructed by weekly DVD sales), and AverageBox Office of DVDs Released

the subscript t in the equation means week t

t

t

t

t

tt

DVDCountOfRlsDVDSumBOofRls

ySeasonalit

edBaseDVDInstall

edBaseDVDInstallotalSalesDVDWeeklyT

5

4

3

2

10


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Formulation of the Model (II)Given a pie, how is it split?

The attractiveness of each DVD title (subscript j in the following equation)is defined as a linear function of multiple independent variables (Xjl in thefollowing equation), including Cumulative box office, 1st weekend boxoffice as a percentage of cumulative box office, MPAA rating, CinemaScore, etc. (variables listed in the results section)

The market share of each DVD titles is the attractiveness of itself dividedby the sum of attractiveness of all the DVD titles in that week. In thefollowing formulation, the more similar (similarity defined as a match-up ofgenre, MPAA rating and releasing week) two titles are, the morevigorously they are competing with each other.

kj ttandjk

jkkj

j

jtSimilaritynessAttractivenessAttractivedsOutsideGoo

nessAttractiveeMarketShar

...1110 jjj PercentWkdCumeBOnessAttractive


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Formulation of the Model (III)Combine the two above

The 1st 2-week market share of each DVD title is simplyits 1st 2-week sales divided by the total DVD sales ofthose weeks.

otalSalesDVDWeeklyT

WeekSalesDVDeMarketSharDVDWeek

st21

1


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Forecasting DVD Sales: Steps to Take

1. Estimate the market share model.

2. Calculate the pie in the week the DVD of interest isgoing to be released

3. By taking consideration of the competitive DVDs to berelease closely, predict the market share

4. Combine the results from steps 2 and 3 to forecast thesales


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Results I: Pie (Industry Sales) - Plot

Weekly Industry Sales

y = 0.9341x

R2= 0.8219

-1000000

0

1000000

2000000

3000000

4000000

5000000

6000000

7000000

8000000

9000000

0 1000000 2000000 3000000 4000000 5000000 6000000 7000000 8000000 9000000

Actual

Predicted


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Results I: Pie (Industry Sales)Variables Used

The following variables (signs of coefficients) are used inthe Pie regression:

(+) Seasonality

(+) DVD installed base

(-) Square root of DVD installed base

(+) Sum of theatrical box office of released DVD

(-) Count of number of DVD titles released


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Results II: Market Share - Plot

Market Share

y = 0.8706x

R2= 0.7372

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

Actual

Predict


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Results II: Market ShareVariables Used

The following variables (signs of coefficients) are used inthe attractiveness measure:

(+) Cumulative box office

(-) 1st weekend box office as a percentage of cumulative box office

(-) Holiday box office

(-) Number of days from theatrical release to DVD release

(+) DVD direct sale through

(-) Number of days from VHS release to DVD release

(-) MPAA rating G (-) MPAA rating PG

(-) MPAA rating PG13

(+) Cinema Score


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Results III: Forecast of 1st 2-week sales

Week 1 and 2 Combined DVD Sales

y = 0.9059x

R2= 0.7855

-500000

0

500000

1000000

1500000

2000000

2500000

3000000

3500000

4000000

0 500000 1000000 1500000 2000000 2500000 3000000 3500000 4000000

Actual

Predicted


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Postscript

The model was developed for a major studio.

We tested the prototype at Wharton for one year.

Every month we made forecasts for titles that have beenreleased in the box-office and have been running for 4 weeks.

The model was handed over to the studio for furtheradaptation and application.


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From Hollywood to . Bollywoodand finally to .Tollywood

What about India


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What inputs are needed to generate forecasts?

Example: Harry Potter and the Sorcerer's StoneDVD release date: 10/22/02To forecast DVD sales of the title, we need:

1. The projected DVD installed base around 10/22/022. All the DVD titles released

I. Within 1 week before 10/22/02;II. In the same week as 10/22/02; andIII. Within 1 week after 10/22/02

3. Say there are 10 such DVD titles, we need to know their: Cumulative box office 1st weekend box office Theatrical release date VHS street date DVD street date MPAA rating Genre Cinema Score

With such information we can use our model to forecast the 1st-2-weeksales of Harry Potter and the Sorcerers Stone.


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Backup Slides


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Pie (Industry Sales) Coefficients

The following coefficients in the pie regressionare estimated:

(+3.98x106) Seasonality

(+1.77x102) DVD installed base

(-1.70x104) Square root of DVD installed base

(+3.44x103) Sum of theatrical box office of released DVD

(-6.25x104) Count of number of DVD titles released


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Market Share Coefficients

The following coefficients in the attractiveness measureare estimated:

(+2.96x10-3) Cumulative box office

(-2.96x10-9) 1st weekend box office as a percentage of cumulative

box office (-1.19x10-3) Holiday box office

(-4.14x10-4) Number of days from theatrical release to DVD release

(+1.52x10-2) DVD direct sale through

(-3.73x10-2) Number of days from VHS release to DVD release

(-0.110070) MPAA rating G

(-4.84x10-2) MPAA rating PG

(-2.65x10-2) MPAA rating PG13

(+3.01x10-3) Cinema Score


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The Motion Picture Industry

Typical Market Window From Release Date

0 12 24 84

Domestic theatrical

Foreign theatrical

Pay per view

Domestic home video

Foreign home video

Pay TV

Foreign TV

Network TV

Syndication

Time (in months)

Source: Vogel (2001)

Documents

2014 Session 7 Video Sales