My slides from SAScon 2013 on the topic of "Maximising your online reputation" with some tips around how to gain and use insights into social conversations to manage brand reputation online.

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Maximising Brand
Reputation Online
Nils Mork-Ulnes
@nilsmu

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The
Agenda
➡ How can you maximise something you
no longer have much control of?
➡ Tips for making sense of your online
reputation
➡ Going beyond basics

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People
growth
In the face of
Exponential
information
are getting smarter
at using and
filtering
information

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10.4
Source: Google/Shopper Sciences, The Zero Moment of Truth Macro Study
doubled to
the
average number
of information sources
used by shoppers
From 2010 to 2011

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You now have little control
Filtered Personal
Stream
Content User state
Timely
Relevant
Actionable
Valuable
Shareable
Grazing/Lean-back
Lean-forward
• Bite-sized/Visual
• Not actively considering
• E.g.,
• Competitions
• Videos
• Infographics
• Transactional
• Consideration & post-purchase
sharing
• E.g.,
• Forums
• Influencer content
• Tools/guides
Social graph
Interest
graph
Knowledge
graph
of the customer journey
Consumer
Facebook
Twitter
Google
Tumblr
Pinterest
Forums

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of
The role
word of
mouth

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2.1 billion
a day
Source: The Keller Fay Group, 2013, based on 1 year of data from more than 31,000 US consumers aged 13-69
WOM Brand impressions
IN THE
US ALONE

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6% occur online
MANY MORE THAN
Source: The Keller Fay Group, 2013, based on 1 year of data from more than 31,000 US consumers aged 13-69
Of all WOM
BUT SEEN BY
OFFLINE WOM

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Highly Credible
by 63%OF RESPONDENTS
Source: The Keller Fay Group, 2013, based on 1 year of data from more than 31,000 US consumers aged 13-69
Experience-based WOM rated

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51% say “try it”
5% Say “avoid it”
Source: The Keller Fay Group, 2013, based on 1 year of data from more than 31,000 US consumers aged 13-69
WOM tends to be positive

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Online word of mouth is correlated with sales
Positive Tweets explains 5x the variability in sales of advertising
for video games in study of 12 months of 2012 data
Tweets having generally a higher impact than negative Tweets. Therefore, to gain the most out of the online word-
of-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.
Table 1 summarises the impacts on sales volume from a 30% change in positive Tweets, negative Tweets and
traditional advertising on each genre, as a weighted average of the estimated title level impacts. 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?”
ng” in this
ers to traditional
above-the-
tising spend,
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
Overall
8.1%
6.3%
6.3%
4.2%
8.0%
3.1%
6.1%
2.4%
6.7%
3.3%
2.0%
7.5%
3.1%
3.3%
1.6%
0.7%
0.9%
1.9%
3.2%
3.9%
1.6%
Source: Deloitte analysis of data from GfK, Nielsen and Crimson Hexagon
than
alone.
The results show that for the key genres of shooter, sports and racing games, the impact of having more positive
sentiment is a multiple of the impact of increasing traditional advertising spend by an equal proportion. Across the
Caveat: correlation ≠ causation

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Still, Companies mostly use quant metrics
Measuring social media ROI
Source: Duke University’s CMO Survey, 2013

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Key points
People like to share
good experiences
more than bad ones
2 31
People trust
experience-based
word of mouth - and
when it happens
online it’s findable
for many
And yet many
companies don’t
measure this

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MAKING SENSE OF YOUR
ONLINE REPUTATION

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Don’t confuse
this thiswith
Carefully
researched
conclusions

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"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 their
tests of automated social media sentiment

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Monitoring is good
for spotting and fixing
problems quickly

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

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QUick methodology primer
21 3 4 5
Test and
retest queries
Clean data Sample Tag Aggregate Analyse
Random &
statistically
significant
By humans,
using custom
taxonomy
Do the sums
& eliminate
errors
Make sense
of it

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Key points
Do use SMM
software to
monitor for
problems
2 31
Do make the proper
investment in time
and £s if you want to
share data with the
C-suite
Make sure there is
methodological
rigour
? 28:32

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GOING BEYOND BASICS

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TROUBLESHOOT THROUGH
SEGMENTATION

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Segmentation gives diagnostic clarity
Top 10 (Dis)satisfaction
Drivers
Top 10 Attractors
and Barriers
Top 10 (Dis)satisfaction
Drivers Top 10 Attractors
and Barriers
1. Call Centres
2. Reliability
3....
4....
1. Pricing
2. Reliability
3....
4....
1. Call Centres
2. Reliability
3....
4....
1. Reliability
2. Features
3....
4....
Former Customers
4%
Non-Customers
18%
Considering Customers
12%
Customers
66%

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LOOK BEYOND YOUR
BRAND

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Most conversations aren’t about your brand
0.5%
0.5%
99%
You and your competitors
Their lives Brand A Brand B

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Cultural Tensions:
My needs
My family’s needs
Society
Popular culture
Brand Proposition:
How awesome we are
Meeting
needs
Content strategy
Branded utilities
Product development
Staying relevant

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“white space” ANALYSIS
Discover conversations that:
1.Fit with your brand
2. Are large or will be
3. Appeals to your audiences
4. Is "interesting"
0
10
20
30
40
50
60
70
80
90
100
Apr-12
M
ay-12
Jun-12
Jul-12
Aug-12
Sep-12
O
ct-12
N
ov-12
D
ec-12
Jan-13
Feb-13
M
ar-13
0.00%
0.00%
0.00%
1.73%
0.00%
0.65%
0.22%
HP
Oracle
IBM
Google
Cisco
Mcsft
GE
How “White” is the space?
Potential Market Value: $131 B
Trend data
“White Spaces” are topics that cover the common ground between a brand’s offerings—whether this offering is
as tangible as an actual product or as abstract as a value proposition—and the needs of its target audiences.

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“Pain Point” ANALYSIS
WHAT ARE MOMS DISCUSSING?
negative positive
VOLUMEVOLUME
Baby clothes
Car seats
Cribs
Diaper/changing
bags
Strollers
Slings/wraps
Maternity clothes
Feeding chairs,
furniture
CarriersProducts
Materials/fabrics
Comfort
Safety for baby
Ease of use/
installation/
navigation
(includes ability to
use outdoors)
Compatibility with
physical activity
Appropriateness
for baby (e.g., is
baby too big)
Ease of cleaning
colors
Patterns
Price/value
Attractiveness/
trendiness
Product CONSIDERATIONS
At which point of the need staGE CUSTOMER JOURNEY are moms posting?*
0%
Pre-awareness
7% 14% 17% 12% 67%
AWARENESS
FAMILIARITY CONSIDERATION &
RESEARCH
Purchase
Recommendation &
sharing
*Posting only about baby/maternity products or comfort/style with regard to pregnancy/taking care of baby.
WHICH EMOTIONS ARE MOMS EXPRESSING?**Posting only about baby/maternity products or comfort/style with regard to pregnancy/taking care of baby.
36%
Happiness
21%
Confusion/FEAR
19%
dissatisfaction
14%
Excitement/hope

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Key points
There is more to
social data than
just measuring
brand health
2 31
Diagnose problems
by segmenting data
Look beyond
mentions of your
brand and look for
new opportunities
to connect or pain
points to address

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THANK YOU
timefor your
contact us
Nils Mork-Ulnes
Head of Insights and Analytics, EMEA
+44 771 307 7994
nils@bynd.com
@nilsmu