Will social data eat the market research industry? A look at the opportunities and challenges of using social data.

Will social data eat the
market research
industry?
Nils Mork-Ulnes, Beyond
Twitter: @nilsmu @beyond

© Copyright 2012 Beyond. All rights reserved. Private and Conﬁdential

TECHNOLOGY
INSIGHT

LESS FINANCIAL RISK, MORE CREATIVE PRECISION, AWESOME RESULTS


SOCIAL

Our clients drive the social web
... and harness it
LONDON

NEW YORK
BAY AREA


The opportunity: From scarcity to abundance of data
“Between the dawn of
civilization and 2003,
we only created five
exabytes [of data];
now we’re creating
that amount every two
days.” - Google
Source: New York Times, 2013

@nilsmu @beyond

from this, Two kinds of digital data

1
2


Behavioral data
Attitudinal Data

This presentation will
focus here

“Word of Mouth” has a always had a large impact on brands but now we can measure it more readily

2.1 billion
a day
in the US alone
6% occur online

Source: The Keller Fay Group, 2013, based on 1 year of data
from more than 31,000 US consumers aged 13-69

@nilsmu @beyond

An industry ripe for disruption?
“the global market research market...
[is valued] at $31

billion...

...We believe 100 percent of the current
marketing analytics market can be captured
through social technology… with savings of
up to $1Bn”
- McKinsey, The social economy: Unlocking value and productivity through social technologies, July 2012

@nilsmu @beyond

The

BENEFITS
OF

SOCIAL
data
McKinsey report on
benefits of social data:

© Copyright 2013 Beyond. All rights reserved. Private and Confidential

➡Removes survey biases:

unprompted, uncompensated and unfiltered observations

➡Greater speed:

more timely insights into

preferences and trends

➡Cost:

reduced data collection costs allows more of

the budget to be spent on analysis

@nilsmu @beyond

The

challenges
OF

SOCIAL
data

➡Noisy unstructured data

is hard

to analyse at scale

➡Lack of standards

- and lack of

methodology maturity - leads to lack in buy-in in C-suite

➡Silos in organizations

means that

this data isn’t shared - social data tends to remain in
comms function

➡New biases introduced,

favoring

the vocal & connected consumer


@nilsmu @beyond

than
alone.

Tweets having generally a higher impact than negative Tweets. Therefore, to gain the most out of the online wordof-mouth embodied by Tweets, companies would be best served by addressing the balance of sentiment about
their games through increasing the number of positive Tweets.

short-term impact + predictive power, but...

Table 1 summarises the impacts on sales volume from a 30% change in positive Tweets, negative Tweets and
New game on each genre, as a WOM average of the estimated title level with sales
traditional advertising & movie releaseweightedhas measurable correlationimpacts. The results in
the table on the impact of positive Tweets correspond to a thought experiment: “How would the sales of a title
respond to a having a 30% higher number of positive Tweets about it?”

E.g., positive Tweets explains 5x the variability in sales of advertising for video games

Table 1. Impact of key levers on sales volume in the ﬁrst 10 weeks of release by genre
Genre

30% more positive Tweets

30% fewer negative
Tweets

30% more non-Twitter
advertising

Shooter
Sports
Racing
Action
Role playing
Other

8.1%
6.3%
6.3%
4.2%
8.0%
3.1%

2.4%
6.7%
3.3%
2.0%
7.5%
3.1%

1.6%
0.7%
0.9%
1.9%
3.2%
3.9%

Overall

6.1%

3.3%

1.6%

Source: Deloitte analysis of data from GfK, Nielsen and Crimson Hexagon

ng” in this
Caveat: correlation ≠ causation
ers to traditional
The results show that for the key genres of shooter, sports and racing games, the impact of having more positive
above-the© Copyright
sentiment is a multiple of the impact of increasing traditional advertising spend by an equal proportion. Across the
tising spend, 2013 Beyond. All rights reserved. Private and Conﬁdential
@nilsmu @beyond

Companies mostly use quant metrics
Metrics used

Source: Duke University’s CMO Survey, 2013

@nilsmu @beyond

"When we say it's positive,
the machine about 21% of
the time says it's negative"
Eric Schmidt, senior manager-marketing
strategy and insights at Coca-Cola, on
automated social media sentiment

Don’t confuse

this

with

this
Carefully
researched
conclusions


No Black boxes
For “market research grade”
insight, you still need sound,
transparent research methodology

getting the best from both
HUMAN: Ambiguity

Machines: Scale

Ex: Twitter using custom mechanical turk pool for “human
computation” = accuracy+scale


Key points
1

3

2
28:32

Social data is still a
massive untapped
opportunity for both
brands and agencies
to use along with
conventional
research

Abundance of data
means investments
must be made in
“human
computation” to
overcome challenges
of unstructured data

Methodological
rigour and
transparency
needed for C-suite
buy-in

@nilsmu @beyond

Social Methodology

Traditional Methodology

• Lower Cost: Permits frequent measurement

• Targeting : Filtering through demographic data allows

• Targeting of Influencers: Online conversations are often

traditional methods to target a specific sample segment

conducted by influencers

• Structured Data Collection: You will get answers to all your

• Uncovering Trends: Unprompted observations are likely to
lead to trend discovery

questions
• Scaled Response: You can quantify a consumer attitude or a

• Group Comparison: Fairly easy to identify people who are

feeling

pre versus post purchase
• Uncovering Intent: Previous research indicates that online

• Representative Sample: Targeting specific demographics

word of mouth is strongly related to intent

• Data Analysis: Analysing quantitative data is easier than

• Data Versatility: Conversational data is unstructured

analysing qualitative data, which is unstructured

allows the researcher to study a representative sample

and thus not limited by expected responses

• Lack of Demographic Information : Demographic

• More expensive: Incentives and human factors drive costs

information within social media conversation often has to be

• Group Comparison: Group comparisons are often costly and

inferred

difficult due to the additional sample required

• Possible Response Bias: People more likely to share a very

• Structured Trend Discovery: Discovery of trends is limited

positive or very negative experience than a more neutral

to the type of questions the researcher is asking

experience

• Selection Bias: Incentive based studies attract a specific type

• Difficult to Analyze: To get high quality data, unstructured
conversational data needs to be cleaned and analyzed in a

of respondent
• Observer Bias: Prompted observation miss what the

labor intensive manner

researcher did not think of measuring


@nilsmu @beyond

Examples of uses of social data
Social Data Type

Product
Development

Consumer Insights category (unsolicited)

Discover unmet needs

Crowdsourced
Insights - category/
brand (solicited)

Product co-creation

Marketing & Sales Operations

Customer Service

Proposition
development,
positioning, and
testing. Channel and
campaign planning.

Brand product/
service conversations

Brand health
measurement &
positioning

Positive word of
mouth; fan
interaction

Advocacy and loyalty
programs

Customer service
interactions via social


Forecasting &
monitoring

NPS measurement

Improve customer
service processes

@nilsmu @beyond

HOW WE APPLY IT

Service attributes: Segmenting by customer journey stage
Complementing
Voice of Customer
Research:

Top 10 Attractors and Barriers

Top 10 (Dis)satisfaction Drivers

1. Pricing

1. Call Centres

2. Reliability

2. Reliability

1. Ongoing monthly KPIs instead
of yearly cycle of VOC

3....

4....

4....
Current''
60%'

2. Fraction of the cost

Unknown'
27%*'

Former''
1%'

3. Captures important social
WOM factor VOC can’t
4. Captures moment-ofengagement rather than afterthe-fact

3....

Considering''
12%'

Top 10 (Dis)satisfaction Drivers

Top 10 Attractors and Barriers
1. Reliability

2. Reliability

2. SPEED

3....

3....

4....


1. Call Centres

4....

Consumer insights: which features people want
Complementing
qualitative research for
market entry in
electronic wallet space:

4%

Barriers to Adoption

4%
Pin

Battery dependency

Multiple cards

3%

Transaction tracking

RFID

2%

Threats%
Remote swiping

2%

Ads

2. Unprompted attitudes

P2P Payments

Frozen money

3. Competitor SWOT

Fingerprint verification

Digital/NFC keys
NFC Sticker
Sonic Payments
Barcode Scanning

Transaction errors

1%

Digital Receipts

Loyalty/Rewards cards

Customer service


3%

Deals/Coupons

1. Understand early adopter needs

4. Fraction of cost of focus groups/
surveys

Reasons to Adopt

Transaction Speed

1%

Digital tickets

0%
5"

Very%Nega*ve%

4.5"

4"

3.5"

3"

Balanced%
Avg. Sentiment

2.5"

2"

1.5"

Very%Posi*ve%

1"

@nilsmu @beyond

From social data through strategy to designing new Virgin.com
Fewer people are searching for virgin.com
All Organic Search Referrals to Virgin.com
"Virgin" Keyword Search Referrals to Virgin.com

30,000

Who’s talking about virgin and entrepreneurship?

Conversations align with some values and not others
Percentage of Conversations Including
Brand Value*:
Fair
Play
(4%)

Delightfully
Surprising
(19%)

68.1%

Heartfelt
Service

Red Hot
(29%)

Insatiable
Curiosity

Business/Technology Interests

2%
Eastern
Europe

7%
Asia

31.9%

Male

USA
Focus
7%
Western
Europe

USA

Insatiable
Curiosity
(4%)

10,000

11%
UK/Ireland

61%

Heartfelt
Service
(4%)

20,000

Skews Male

What Virgin should strive for in a
content strategy:

Female

Skews 18-35

Delightfully
Surprising

1%
M.E.

Content
0
1-Sep-08

1-Jan-09

1-May-09

1-Sep-09

1-Jan-10

1-May-10

1-Sep-10

Virgin.com referrals from search have grown by people searching for
Virgin’s brands.

1-Jan-11

1-May-11

1-Sep-11

1-Jan-12

1-May-12

1-Sep-12

Smart
Disruption
(49%)

Fair Play
Smart
Disruption


Entrepreneurship Subthemes within Social Media Conversation
High
Penetration

Business Tips
and Advice

Small Business
Focus

• Harnessing Virgin’s community
of followers to write content
about entrepreneurship – tech
and startups in particular –
could provide content on either
side of the neutral line to help
drive conversation.

Startups + Tech
Culture

Young
Entrepreneurship

Social
Responsibility
Work/Life Balance

Negative
Tone

Neutral
Tone

Low
Penetration

Sustainability

Positive
Tone



Technology/Engineering
Startups
Sports and Fitness
Art and Design
Music
Travel
Environment

Business Owner Focus

0%

63%

34%

3%

18-35

35-65

Over
65

Central /
Latin
America

4%
3%
Other
Africa

3%
South
Africa

Australia
and N.Z.

31% Business Owner Self/Employed
22% Corporate Executive
17% Works in /with Technology
11% Musician/Artist/Writer/Filmmaker
3% Student
16% Other employee type


what emotions are surrounding the conversations?
Takeaway

Takeaways

• Content could take more of a
stance or instigates a response,
put forth a genuinely unique
idea, or looks at business from a
different angle.

2%
Under
18

* Out of a sample size of 900 conversations

Conversation is on average neutral

General Business

Red Hot

People searching for Virgin itself have decreased.


36%
20%
18%
7%
6%
5%
4%
2%

Target personas*
personas
“Music Festival Junkie”

Music festival content should build on consumers’ sense of anticipation, as
well as aim to keep the experience alive after the festival itself.
Emotive Reaction Within Conversations

What triggers reactions in the
Emotive Conversations?
Contest:
Anticipation:

Call to
Action*

31%

2%

20%
No reaction:
47%

(47%)
(29%)

Wonder:

(8%)

Recommendation:

(4%)

Experience:

(1%)

Humour:

(1%)

Other:

(9%)

*Call to action: the post actually directs users to engage with the content
or with Virgin itself (e.g., “you must read this ASAP”).

“Self-made Musician”

Kate
Randolph

• Loves to dance
• Interest in sports and fitness
• Uses Facebook, Twitter

Sam Spear

James Fallow

@samuelspear
Age 37
Senior Account
Manager, PWC
London, UK

@singinjames
Age 28
Independent Musician
Austin, TX

@kran2010
Age 20
Student
Manchester, UK
Key points:
• Student at university
• Very outgoing, social
• Knows hot music trends

“Enthusiastic Music Advocate”

Key points:
• Devoted to his craft
• Trying to ‘make it big’
• Seeking sponsorship

• Side job as radio DJ
• Uses Twitter, Facebook
• Works at a recording studio

Key points:
• Self-proclaimed music fanatic
• Explores the current trends
• Side interest in sports and art

• Mid-level employee
• Often attends concerts
• Spreads taste to peers

and a local venue at night
What’s important to her?
• Keeping up-to-date on the music fests in the UK with
lineups, prices, dates and giveaways.
• Having a great time dancing and listening to music
with her friends, as well as meeting new people with
whom she can share these fun experiences.

What’s important to him?
• Making time outside of his work to write his music
and practice the guitar, as well as prepare for shows,
promote himself, and try to raise money for an EP.
• Maintaining his musical originality and seeing its
effect on people’s pleasure.

What’s important to him?
• Being the tastemaker among his group of friends
by discovering the best new indie and pop artists.
• Attending concerts and music festivals after work
and on the weekends to meet new people and share
common interests about music and other culture.

What’s she looking for?
• Deals on tickets and special access for the music festivals
she wants to attend, as well as information on early
lineup releases, new venues and after-hours shows.
• Fun ways to enjoy the music festivals she can’t attend
from afar, via television, streaming or a combination.

What’s he looking for?
• New methods for promoting himself, financing a
record, travelling to shows and finding equipment.
• A means to get involved in the music community by
keeping a handle on the scene and by supporting his
fellow musicians.

What’s he looking for?
• An online content destination where he can discover
new artists, read profiles and download playlists.
• Exclusive behind-the-scenes looks at music festivals
and concerts, ways to watch concerts and festivals he
isn’t able to attend, and access passes for other shows.


*Personas are formulated based upon the most common trends within
the demographic data. They are not actual people.

THANK YOU
for your
time

contact us

Nils Mork-Ulnes
Head of Insights, Analytics &
Strategy
+44 (0)2079 086556
+44 (0)7713 077994
nils@bynd.com


Will social data eat the market research industry? A look at the opportunities and challenges of using social data.

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Will social data eat the market research industry? A look at the opportunities and challenges of using social data.