Marketing Solutions
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Do Movie
Marketing
Budgets
Need a Digital
Reboot?
Study Reveals a New Path to Box Office Sales
Do Movie Marketing Budgets Need a Digital Reboot?
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Do Movie Marketing Budgets Need a Digital Reboot?
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Table of
Contents
Introduction
04
Study Methodology
06
Key Findings
09
 Studio Ad Spends at a Glance
 How Much Credit Should Marketing Get for Driving Box Office Sales?
 Which Media Channels Powered the Most Ticket Sales?
 Which is the Most Efficient Digital Channel?
 The Role of VIV (Viral Impression Volume)
 VIV and Organic Search
Movie Marketers Should Rethink Revenue-Boosting Spend
20
Findings at a Glance
23
Methodology
24
About Neustar
28
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Introduction
In 1975, Universal Pictures placed a bold bet on a film release. To advertise an
upcoming summer film, the studio placed a then-astounding $700,000 into
national TV spots—at a time when studios barely spent on TV ads at all. The move
paid off. That film release was Jaws, the picture became the highest-grossing
movie to date; and nearly overnight, television became the new anchor of the
studio media mix.
Television took its place in studio marketing, largely because one film team
was ready to radically rethink its marketing investments. Is it time for studio
marketers to reconsider their investments once again? Based on findings from
Neustar’s recent analysis of the most effective movie marketing channels, the
answer is yes.
Neustar—engaged by Facebook—evaluated 70 major studio releases across a
wide variety of genres, representing $1.8 billion in marketing spend and the
majority of wide-release box office sales. Facebook had questions about its own
contribution to box office sales, particularly its impact on the overall media mix.
They asked us to study the following questions:
§§
What type of channel mix most effectively generates incremental box
office revenue?
§§
What specific role does Facebook play in this mix?
Neustar’s findings showed that while TV remains a highly impactful movie
marketing channel, digital advertising tops TV in some crucial areas of primary
importance to movie marketers.
The time may be right for marketers to jump back into the water. The marketing
mix tides appear to have, once again, changed course.
Neustar’s findings showed that while TV remains a
highly impactful movie marketing channel, digital
advertising tops TV in some crucial areas of primary
importance to movie marketers.
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Scripting the Research
Study Methodology
To conduct our analysis, we looked at the advertising channels for 70 US movies
released into theaters in 2016, representing the majority of wide-release box
office sales. The analysis covered eight different marketing channels—TV, online
display, online video, paid Facebook advertising, out of home advertising (OOH),
radio, print, and paid search—representing $1.8 Billion in total marketing spend.
Our study focused on the 15 weeks leading up to each film release and the six
weeks after the movies hit theaters.
We also evaluated the following factors to uncover the relationship between
channel spend and ticket sales:
§§
Impact of marketing on ticket sales: Were audiences more likely to buy movie
tickets after viewing ads on a given media channel?
§§
Influence of earned and organic digital marketing on ticket sales: How do
earned media like movie trailer social media shares (or “viral views”) and
organic search influence moviegoers’ purchase journeys?
§§
Role of key control factors: Our analysis also measured—and controlled
for—the impact of other influential factors, such as:
-- Seasonality: Was the movie released in the summer, or during “dump months”?
-- Competitive ad spend: How much of a role did ad budget size play
in film success?
-- Production budget: Did blockbuster-budget films outperform smallerbudget films, as expected?
-- Star casting: What is the relationship between big-name leads and the
bottom line?
-- Audience approval: How did early audiences’ feelings about a film influence
the release’s subsequent fortunes?
-- Economic Factors: Did our research bear out reports that movie
attendance goes up during hard times?
-- Type of film: To further eliminate bias, we compartmentalized our studies
into movie genre and how well each film performed—to avoid unfair comparisons of romantic comedies with family dramas1, or mega-blockbusters with
bottom-performing sleepers.
“Family dramas" consisted primarily of animated films.
1
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We ran these inputs, plus box office data for each film, through a variety of
Bayesian statistical models (a statistical approach used for estimating real-world
scenarios that are characterized by a high degree of uncertainty). The outcomes
showed us how each of the factors were likely to influence box office sales.
We’re highly confident in our models, and in our findings. To test our models’
accuracy, we went back to the original raw data and ran it through the models,
to see if we could “predict” actual box office revenue. The models were accurate
to within five percent of actual box office revenue.
We’re highly confident in our models ... they
were accurate to within five percent of actual
box office revenue.
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Key Findings
A Sneak Peek
Studio Ad Spends at a Glance
On average, studios spent $27.4 million to market their releases. How effective
was that spend at driving moviegoers to new releases? And how could marketers
have changed the media portfolio across that $27.4 million to drive still more
box office revenue? These questions form the basis of our findings about media
effectiveness in the studio mix, highlighted below.
BENCHMARKING: FILM MEDIA SPEND BY CHANNEL
RADIO
PRINT, 1%
OOH
PAID SEARCH, 0.1%
ONLINE VIDEO
(EXCLUDING FB)
ONLINE
DISPLAY
3%
FACEBOOK PAID
IMPRESSIONS
2%
4%
5%
6%
TV
80%
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"I'd Like to Thank ..."
How Much Credit Should Marketing Get
for Driving Box Office Sales?
How much does marketing—and in particular, paid marketing—influence box
office sales? It’s a question many a studio CMO (and CFO) would like to the
answer to.
Our findings show that, across the 2016 movies analyzed, paid media plays
a huge role—but not the only one:
§§
44% of box office sales were attributable to paid media efforts.
§§
The remaining 56% were driven by non-paid initiatives, including PR, movie
talent, and other factors.
In short: Whether a film soared or bombed at the box office, media investment
drove (on average) 44% of the results.
WHAT WORKS AT THE BOX OFFICE:
PAID AND UNPAID CONTRIBUTION TO OPENING WEEK REVENUE
56
%
44
%
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Non-Paid Activities (PR, Talent, added
value, sponsorships, etc.)
Total Paid Media Influence
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In a Star Turn
Which Media Channels Powered
the Most Ticket Sales?
Just as some actors are known for their revenue-driving power, the same is
true with marketing outlets. Some channels drive more ticket sales than others.
In our study, two channels in particular stand out:
§§
Digital Media2:
-- Digital media were responsible for 46% of paid media-driven box office
revenue, making digital overall the channel with the biggest sales impact.
-- Digital also represented just 14% of marketing budgets, compared to TV’s 82%.
• Delivering four percent more sales than television at just a third of the cost,
digital was the most efficient medium within the studio marketing mix.
§§
Television: With its captivating power and broad reach, TV remains a powerful
“megaphone” for convincing moviegoers to see any given film. It was responsible
for 42% of paid media-driven box office revenue in 2016.
MEDIA EFFICIENCY AND SHARE OF MARKETING AND SPEND
5.0
PAID FACEBOOK MEDIA
3.2
OTHER OFFLINE
(OOH, RADIO, AND PRINT)
2.9
ONLINE VIDEO
(EXCLUDING FACEBOOK)
2.3
ONLINE DISPLAY
0.5
TV
% of Contribution/% of Spend
20%
4%
12%
4%
12%
4%
13%
6%
42%
82%
Share of Marketing Contribution
Share of Spend
igital media includes studio-owned digital properties, digital and social media platforms,
D
display and video advertising networks, exchanges, paid search, and more.
2
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"And the Winner is ..."
Which is the Most Efficient Digital Channel?
Diving deeper into digital media, the most efficient paid digital outlet was paid
Facebook media (advertising on Facebook). On average, paid Facebook media:
§§
Comprised four percent of the average film media budget, but delivered…
-- An average of nine percent of opening weekend box office revenue, and
-- 20% of marketing-driven sales.
§§
Saw a $7.91 return on ad spend (ROAS): for every dollar a studio spent
on Facebook, it earned close to eight dollars back.
§§
Delivered five times higher returns than media overall—and even greater
returns for specific movie types:
-- Facebook delivered six times more returns than media overall in the action
and family genres.
-- Amongst top box office performers, it delivered seven times more returns
than media overall.
§§
Was 10x more efficient than TV ads at driving studio marketing ROAS.
On average, paid Facebook media was:
4
%
of the average film
media budget
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10x
more efficient than
TV ads at driving studio
marketing ROAS
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Share
of Marketing
Do Movie Marketing Budgets Need
a Digital
Reboot? Impact
Paid Search
Print
Radio
OOH
Online Video
Online Display
Facebook Paid Media
TV
0.7%
3.2%
5.1%
4.1%
11.6%
13.4%
20.1%
41.8%
Share
of Average
White
Paper Spend
0.1%
0.7%
2.2%
1.0%
3.9%
5.8%
4.0%
82.2%
RELATIVE IMPACT ON SALES VS. SHARE OF SPEND
90%
80%
70%
60%
50%
40%
30%
20%
10%
Paid
Search
Print
Radio
OOH
Share of Marketing Impact
Online
Video
Online
Display
Facebook
Paid Media
TV
Share of Average Spend
Relave Impact on Sales vs. Share of Spend
While TV was responsible for the lion's share of the budget (82%), it was responsible for
only 42% of the media-driven box office revenue in 2016. Facebook was, by far, the most
90%
efficient
of all media channels.
80%
It 70%
is clear that studios have the opportunity to make significant improvements to their
media
60% mix allocations, especially given the cross-channel inefficiencies that weighed
50% the total ROAS baseline.
down
40%
30%
20%
10%
0%
Paid
Search
Print
Radio
OOH
Share of Markeng Impact
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Online
Video
Online
Display
Facebook
Paid Media
TV
Share of Average Spend
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PAID FACEBOOK ROAS BY BOX OFFICE TIERS3
+7.4X
$27.62
+5.0X
+4.7X
+3.3X
$7.91
$5.24
$3.73
$1.59
All Titles
$1.13
Top 10
$0.22 $0.74
Middle
Total Media ROAS
Bottom 10
Paid Facebook ROAS
PAID FACEBOOK ROAS BY GENRE
+5.7X
+6.7X
+5.0X
$14.43
$10.92
+4.8X
$7.91
$5.09
$1.59
All Titles
$1.64
Action
Total Media ROAS
$2.51
Family Dramas
$1.06
Other
Paid Facebook ROAS
Top 10" includes the top 10 performing films by total box office revenues. "Bottom
"
10" includes the lowest 10 performing films by total box office revenues. "Middle"
includes the remaining films in neither the Top 10 nor the Bottom 10 categories.
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Our analysis also found that Facebook paid media impacted earned engagements
online. Facebook paid media drove six percent of film-specific Google search
activity, and 50% of viral film impressions. In other words: Facebook users who
were exposed to studio ads in Facebook were also likely to share those ads with
their friends, and to go to Google to learn more about the films.
HOW FACEBOOK IMPACTS THE BOX OFFICE
Total Box Office Revenue
Organic Search
20%
Viral Impressions
6%
50%
Paid Facebook Media
Share of Marketing Contribution
Of outcomes driven by marketing, Facebook is responsible for 20% of box office sales,
6% of film-related organic search, and 50% of film-related viral impressions.
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Supporting Actor Award Goes To
The Role of VIV (Viral Impression Volume)
In 1999 a team of unknown filmmakers set up a website for their new film, and
garnered 20 million page views before opening day. Boosted by that online
success, that film—The Blair Witch Project—went on to earn $249 million
worldwide, a nearly 10,000-fold return on the film’s under-$25,000 production
budget. Studios took note: there was a strong connection between box office
sales and viral success.
While we didn’t see 10,000x returns across any of our findings, we did see
significant correlations between viral activity and the box office. Specifically,
Facebook viral impression volume (VIV)—the number of movie posts, paid or
organic metrics sourced from FB Graph API, that have been liked, commented
upon, or shared by Facebook users’ friends—appeared to strongly impact box
office performance, particularly in the weeks ahead of the release.
§§
Overall, top-performing performing films had nearly double the VIV of middle-
performing films, and eleven times that of bottom-performing releases.
§§
An increase of 25% in VIV corresponded to a six percent increase in box
office revenue.
IMPACT OF VIRAL IMPRESSIONS ON BOX OFFICE REVENUE
Box Office Revenue
90,000,000
80,000,000
70,000,000
60,000,000
50,000,000
40,000,000
30,000,000
20,000,000
10,000,000
-
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25%
50%
75%
100%Viral
Average
Impressions
Volume:
8.5M
Impressions
125%
150%
175%
200%
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TOP-PERFORMING FILMS:
59 MILLION IMPRESSIONS
MIDDLE PERFORMING FILMS:
31 MILLION IMPRESSIONS
Week 6
Week 5
Week 4
Week 3
Week 2
Opening
Week
T- 1
T- 2
T- 3
T- 4
T- 5
T- 6
T- 7
T- 8
T- 9
T- 10
T- 11
T- 12
T- 13
T- 14
T-15
AVERAGE WEEKLY VIV
BOTTOM PERFORMING FILMS:
5 MILLION IMPRESSIONS
Top-performing films have nearly 2x the VIV compared tomiddle performing films and 11x the bottom performing films
The Road to Better Performance
VIV and Organic Search
At the total box office level, VIV and Organic Search-another major source of
unpaid digital engagement-showed strong correlations to box office sales as
well as to each other. Leading up to opening week, VIV proved 2.6 times more
impactful on film performance than organic search did from 15 weeks before
films hit the theaters up until six weeks ahead of launch. As the release date
approached, the impact of the two kinds of engagement evened out; post-launch,
organic search became the slightly more impactful of the two.4
4
It should be noted that while both VIV and organic search were strong indicators for box
office performance overall, the results varied widely across individual film releases.
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Box Office Revenue
THE IMPACT OF VIV
AND ORGANIC SEARCH
R2= 0.57174
Box Office Revenue
Facebook Viral Impressions
R2 = 0.21361
Organic Search Index
*Outliers removed from analysis
AVERAGE MOVIE TREND FOR
VIRAL IMPRESSIONS AND ORGANIC SEARCH
15 Weeks - 6 Weeks
from Launch
5 Weeks – 1 Week
from Launch
While in Theaters
VIV is 2.6 times stronger as an
indicator of Box Office Revenue
As a near term indicator
Organic Search is slightly
stronger than VIV
Online Search has a
correlation of 0.86 while
VIV is only 0.75
Viral Impressions
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Organic Search
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VIV may be a signal of future box office success,
but due to the fact that virality is unplanned—and
therefore not causal—it would be more useful as a
directional planning metric than as a primary KPI.
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Moral of the Story
Movie Marketers Should Rethink
Revenue-Boosting Spend
Across the movie titles we analyzed, television was the biggest media driver of
ticket sales—but not the most efficient one. Instead, our study found that at
the current spend levels within each channel, digital outlets were significantly
more efficient at driving box office revenue than any type of offline media—
TV included. For the most impactful marketing mix, the way forward is clear:
movie marketers should continue investing in television, but capitalize on digital
efficiency by shifting a portion of their TV dollars into digital media.
The specific best ratios will vary from one release to the next. However, we
can offer two indications of the opportunity at hand. Our models show that,
on average, studios that shifted six percent of TV spend over to digital could
see a seven percent increase in box office revenue. Further, our findings also
saw that earned viral activity (specifically VIV) driven by paid engagements could
very well be an early indicator of box office success.
In the movie business, rethinking an old story can result in a new classic. Like we
saw with Jaws and The Blair Witch Project, this is as true for marketing as it is for
the film itself. Our findings show that it’s time to rethink the story once again.
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Shifting 6% of a title’s TV budget over to digital media
could yield an average 7% net box office increase.
AVERAGE MOVIE BUDGET BEFORE
AND AFTER 6% TV REALLOCATION
-$1.3M
Budget ($M)
25
20
$22M
$20.7M
+$1.3M
$54.8M
10
$3.8M $5.1M
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+$3.9M (+7%)
$58.7M
15
0
AVERAGE BOX OFFICE REVENUE BEFORE
AND AFTER 6% TV REALLOCATION
TV
Digital
Original
Budget
Shifted
Budget
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The Plot Synopsis:
Findings at a Glance
Television advertising was
responsible for roughly
42% of media-driven box
office performance, and
approximately 82% of the
overall marketing budget.
Digital media was responsible
for 46% of media-driven box
office sales, and 14% of the
overall advertising budget.
§§
Within digital: Facebook paid
media represented four percent
of film media budgets, but drove
20% of media-driven sales.
$4
million
in additional
box office revenue
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Shifting six percent of TV over
to digital media would yield on
average net increase of seven
percent to box office revenue.
§§
For the average $27.4 million
advertising budget for a film
release, this would translate
into an additional four million
dollars in box office revenue.
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Appendix
Methodology
The Neustar MarketShare Analytics Approach
Neustar MarketShare uses econometric regression—a methodology of finding clear patterns
in the noise of market data—to establish the mathematical relationships between marketing
investments and sales outcomes. Our work correlates brands’ marketing tactics with their
weekly shifts in sales, while controlling for other factors that may impact those sales—such as
the economy, price, and competitive actions. Doing this lets us pinpoint which tactics drive
the most revenue, and what factors may negatively impact sales.
Other approaches look at the impact of a single marketing channel at one moment in time.
However, we believe this point of view oversimplifies the realities that marketing impact
changes over time, and that the impact of any one marketing channel is actually the result
of a wide array of variables. Because that’s so, we base our marketing analyses on three key
tenets for evaluating marketing effectiveness:
1. Evaluate Diminishing Returns: Multiple studies of the relationship between advertising and
sales demonstrate that, past a certain spend level, returns on incremental ad spend begin to
wane and finally disappear. The impact of any marketing channel will rise with each additional
dollar, but will ultimately peak and wane.
2. Separate Marketing Effectiveness from the Base: Sales revenue is driven by two factors:
§§
The base—the ongoing factors that influence sales absent any marketing at all. These variables
range from the economy, to local market trends, to the weather and time of year.
§§
Marketing’s role is to use levers within its control—such as media—to push sales beyond
that base.
To evaluate the impact of each marketing channel, brands must first understand the base;
then, they must see how customers have changed their likelihood to buy beyond the base.
3. Measure Synergies Individual marketing resources do not work in isolation, but rather in
conjunction with one another. For instance, a TV ad may prime a viewer to be more responsive
to an online display ad later on. Because this is so, marketing spend in any given medium
typically increases the impact of all other media—and measuring the impact of any one
marketing channel must take these synergies into account.
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To capture how the different variables work together, our models identify the full range of factors
flowing into media effectiveness and of what influences sales, whether paid or unpaid, direct or
intermediate. This includes how media touchpoints work together—for instance, how direct mail
is made more effective when accompanied by TV and online display. This also includes the ways
media impacts sales through intermediary touchpoints: for instance, if a TV ad drives an organic
online search or social media buzz (e.g., earned conversations)—indirectly driving up sales.
We model the variables independently; then, in the final model, we link all the equations
together, providing a more complete view of the direct and indirect impact of media on sales.
The approach we use is called a log-log multiplicative model, which is based on the equation:
log(Sales) = log(Base) + 1log(X1) + 2log(X2) + 3log(X3) + error
(In practice the structure—and the equation—is far more nuanced; but the fundamental principles
are the same.)
Model Validation
To make sure our models are correct, we run through a series of checks to ensure accuracy
including:
§§
Checks for multicollinearity: This refers to what happens when multiple factors correlate
equally with an outcome and it’s nearly impossible to determine whether both factors are
driving the outcome, or if one factor is impacting all the others. We identify multicollinearity
and, depending on the circumstances, either combine the multicollinear factors, or throw
them out entirely.
§§
“Sanity checks” comparing our learnings against:
-- Known business truths, including what we’ve learned over the course of building thousands
of models across products and industries.
-- Industry standards for the degree to which given factors typically influence marketing
impact (marketing contribution, source of volume change, and relative effectiveness of
each touch point/coefficient)
§§
“Predicting” the past: Once we’ve built our models, we return to the original raw data and
run it through the models, to see if we can use those same models to identify actual market
events that happened in the past. If the models can use the data to accurately predict
outcomes we know have happened, they are likely to be highly accurate.
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Applying the Methods: The Box Office Study
In this study, we used Bayesian hierarchical regressions—Bayesian models specifically
designed to capture multi-layered problems with a wide array of variables in play. We ran
movie title sales and marketing data through these regressions to evaluate the impact of
various media channels on box office sales.
The resulting models were multiplicative—they were designed to reflect the reality that media
influence is something that builds with every additional channel. For a purely illustrative
example: a TV ad might make a moviegoer five percent more likely to see a film, a display ad
might make the same moviegoer four percent more likely to see a film, but the combined effect
of seeing the TV ad and the online display unit may make the viewer a full 12% more likely to
see the film. We were sure to capture that synergistic effect within the models.
We created our research models in two stages. First, we captured the impact of media
on each individual film. Next, we combined our learnings from each movie into category
averages—grouping findings by categories including genre and movie performance level.
We also looked at the influence of non-marketing factors—like seasonality and the movie
cast’s “star power”—which may have either helped or hurt box office performance, and
that we would need to control for in our models.
We ran our media, box office, and control variables through the following steps:
§§
Using a battery of Granger tests—which show whether one set of occurrences are likely to
foreshadow another— and correlation analyses, which show when variables often emerge
together. These gave us the test factors which were good predictors of box office sales.
§§
We ran cluster analyses, grouping variables together including movies by genre and movies
by performance level.
§§
We identified multicollinear variables—such as Facebook paid media spend and 10 second
video views (as mentioned above).
§§
We also threw out variables that did not vary enough from one movie to the next, as that
lack of variance made them poor predictive factors for film performance.
§§
We ran the remaining factors through further models to correlate how strongly they seemed
to influence box office sales, and to rank those influences from strongest to weakest.
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The metrics and indicators we examined include:
Paid Metrics
Earned Metrics
Ratios
Video Views
Video Views
Paid to Organic
Page Impressions
Page Impressions
Paid to Shares
Page Post Impressions
Page Post Impressions
Paid to Likes
Page Engagements
Page Engagements
Paid to Reactions
Total Impressions
Viral Impression Volume5
Paid to Engagements
10s / total earned video
Our data sources included:
Data Source
Data Description
Facebook
Paid and Organic activity
Kantar Media
Offline Media, Paid Search
Pathmatics
Online Display, Online Video
WARC
Average Media Costs
Rentrak
Box Office Sales
Moody’s
Economic Indicators
iral Impression Volume (VIV) is the number of movie posts that have been liked, commented
V
upon, or shared by Facebook users’ friends
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About
Neustar.
Neustar, Inc. is a leading global information services
provider driving the connected world forward with
responsible identity resolution. As a company built on
a foundation of Privacy by Design, Neustar is depended
upon by the world’s largest corporations to help grow,
guard and guide their businesses with the most complete
understanding of how to connect people, places and
things. Neustar’s unique, accurate and real-time identity
system, continuously corroborated through billions of
transactions, empowers critical decisions across our
clients’ enterprise needs.
More information is available at
w w w.marketing.neustar
©2018 Neustar, Inc. All rights reserved. All logos, trademarks, servicemarks, registered trademarks,
and/or registered servicemarks are owned by Neustar, Inc. All other logos, trademarks, servicemarks,
registered trademarks, and registered servicemarks are the property of their respective owners.
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