900 bad buzz in 2016: mmc research findings

1 BAD BUZZ 2016: RESEARCH FINDINGS

Almost 900 bad buzz since 2015 (1)

(1) 871 bad buzz from 01/01/2016 to 12/31/2016(2) Inventory of significant bad buzz on English & French web

Bad Buzz

March 2017

+ 40 % vs 2015 (2)

2015

MMC BA

D BU

ZZ BAR

OMETER

2 PROFILE OF BAD BUZZ VICTIMS

B to C companies are still the most exposed to bad buzz even though a bit less than in 2015

Public administration & associations are more exposed to bad buzz in 2016 vs 2015

PROFILE

Locatio

nTactic

Trigger

Consequences

49

2516 9 1

55

2018

6 1

2016 2015

%

* Associations & charities

MMC bad buzz barometer -‐ 2016

3 SECTORS EXPOSED TO A BAD BUZZ

14 1311 10 10

7 6 64 3

1618

911

9

77 8 6 5 5

15

2016 2015

%

Media is less exposed than in 2015 but still the number one victim.

Internet is as exposed as restaurant-‐hotel

Culture is more impacted by bad buzz vs 2015

PROFILE

Locatio

nTactic

Trigger

Consequences


4 TRIGGER: COMMUNICATION VS OTHER INITIATIVES

Only 30% (vs 40% in 2015) of bad buzz result from miscommunication

30% 40%

2016 2015

Communication Other initiative (behavior…)

Does it mean communication & digital manager are more vigilant ?

Profile

Locatio

nTactic

TRIGGE

RConsequences

Events that trigger a bad buzz : communication or another initiative (behavior…)?


5 TRIGGERS: DIGITAL TABOOS

5 Sensitive topics explain nearly 70% of bad buzz: ethnical*, sexual & social discrimination, manipulation, disrespect towards clients

22

13 1310 9 9

6 5 4 3 6

18

1310

1110 9

4 4 0 3

18

2016 2015

%Ethnicdiscrimination is a more sensitive topic now

Religious discrimination has become part of the top ten sensitive topics

*Ethnical & regional discrimination

Profile

Locatio

nTactic

TRIGGE

RConsequences


6 PLACE OF EMERGENCE / ON LINE VS OFF LINE

Off line media lost ground vs On line media

2016 2015

On line media Off line media

Profile

LOCA

TION

Tactic

Trigger

Consequences

95% 93%

Where does a bad buzz break out On line or Off line ?Profile

Trigger


7 PLACE OF EMERGENCE / SOCIAL MEDIA

Social media has extended the lead over blogs & websites

Twitter is still the main place where a bad buzz appears

Facebook is catching up with Twitter

37

3025

7 1

36

21

35

4 4

Twitter Facebook Web sites & blogs

Video platforms

Other

2016 2015

%

Where does a bad buzz break out on the web ?

Tactic

Consequences

Profile

LOCA

TION

Trigger


8 FACEBOOK IMPACTED

40% of bad buzz impact Facebookpage & almost simultaneously Twitter

Tactic

Consequences

Profile

LOCA

TION

Trigger

9 TACTIC / COMMUNICATION VS SILENCE

In 2016, silence has kept loosing ground vs communication

2016 2015

Communication No communication

Profile

Locatio

n TA

CTIC

Trigger

Consequences

13% 16%

When hit by a bad buzz, how do the organizations react: communication vs silence ?

Communication is the number one tactic


10 TACTIC / MEA CULPA – BACK TRACKING

Mea culpa or back tracking are not yet the dominant reaction

56% 58%

44% 42%

2016 2015

Mea culpa or back track

Neither mea culpa nor back track

How many organizations do apologize or back track?Profile

Locatio

n TA

CTIC

Trigger

Consequences


11 TACTIC / MEA CULPA

Organizations are more likely to apologize for a miscommunication than a controversial initiative (behavior…)

47%30%

COMMUNICATION OTHER*

Mea culpa No mea culpa

How many organizations issue a meaculpa following a miscommunication vs another initiative ?Pr

ofile

Locatio

n TA

CTIC

Trigger

Consequences

*other initiative as an inappropriate behavior, product…MMC bad buzz barometer -‐ 2016

12 TACTIC / BACK TRACKING

In 61% of cases, it’s possible to back track (go back on a decision, cancel an advertizement…)

48%52%

Rétropédalage Pas de rétropédalage

Proportion of back tracking*

But only 48% of organizations choose this tactic

Profile

Locatio

n TA

CTIC

Trigger

Consequences

* When it’s possible to back track


13 TACTIC / BACK TRACKING WITHOUT MEA CULPA

More than 1/3 of organizations which back track don’t issue a mea culpa

How do organizations back track* ?

63%

32%

5%Back track + mea culpa

Back track + explanation but no mea culpa

Back track + no communication

*on the basis of the organizations which back track

Profile

Locatio

n TA

CTIC

Trigger

Consequences


14 TACTIC / CENSORSHIP ON FACEBOOK

Censorship has raised sharply (+13%) and has become a common practice

40%27%

2016 2015

Don't delete negative comments

Delete negative comments

How many organizations practice censorship on Facebook ? Profile

Locatio

n TA

CTIC

Trigger

Consequences


15 TACTIC EFFICIENCY / SILENCE

Silence is the most risky reaction

Tactics that calm web users down*

91%

9%

Communication No communication

* See methodology slide 24

Profile

Locatio

n TA

CTIC

Trigger

Consequences


16 TACTIC EFFICIENCY / COMMUNICATION

55% 54%

2016 2015

Success No success

Communication is not really more effective than in 2015

What has been the return on experience?

When Organizations communicate, how many succeed in calming web users down *?Pr

ofile

Locatio

n TA

CTIC

Trigger

Consequences

* See methodology slide 24 MMC bad buzz barometer -‐ 2016

17 TACTIC EFFICIENCY / MEA CULPA

Mea culpa is often the most effective reaction to calm web users down

74%42%

MEA CULPA NO MEA CULPA Success No success

Success rate in relation to mea culpa or not*

Profile

Locatio

n TA

CTIC

Trigger

Consequences



18 TACTIC EFFICIENCY / BACK TRACKING

When justified, back tracking is the most effective weapon to calm web users down

Sucess rate* in relation to back tracking or not

Profile

Locatio

n TA

CTIC

Trigger

Consequences

77%

40%

BACK TRACKING

NO BACK TRACKING

Success No success

MMC bad buzz barometer -‐ 2016* See methodology slide 24

19 TACTICS EFFICIENCY / CENSORSHIP ON FACEBOOK

Organizations which practice censorship on Facebook are less likely to calm web users down quickly. Is it just a coincidence?

45%

58%55%

42%

CENSORSHIP NO CENSORSHIP

Success No successMMC bad buzz barometer -‐ 2016

Success rate* if censorship vs no censorship

Profile

Locatio

n TA

CTIC

Trigger

Consequences


20 TACTIC EFFICIENCY / OVERALL RESULT

In 48% of cases, the reaction of the organization has not a positive impact

52% 50%

2016 2015

Success No success


No significant progress compare to 2015

Lieu

Proportion of bad buzz properly handled* ?

Profile

Locatio

n TA

CTIC

Trigger

Consequences


21 BAD BUZZ IMPACT / CRITICAL TABOOS

It’s much more difficult to handle a bad buzz in case of allegations of manipulation 58% 51%

40% 39% 30%

ETHNIC DISCRIMINATION

SEXUAL DISCRIMINATION

DISRESPECT TOWARDS CLIENTS

SOCIAL DISCRIMINATION

MANIPULATION

Success* No success* MMC bad buzz barometer -‐ 2016

Profile

Tactic

Trigger

CONSEQUE

NCES

Locatio

n

* Proportion of organizations which succeeded in calming web users down quickly

22 BAD BUZZ IMPACT ON THE ORGANIZATION

In almost 40 % of cases, a bad buzz has a negative impact on the organization 38%

62%

Negative impact

No negative impact

Proportion of bad buzz with negative impact

New criteria

Profile

Tactic

Trigger

CONSEQUE

NCES

Locatio

n


23

Main negative consequences of a bad buzz: additional costs,impact on business & online reputation

(1) Additional costs : to stop an advertising campaign, change a key process, offer a compensation to clients…

(2) Impact on business : decline in turnover, development project cancelled, product recall….

(3) On line reputation : social media deactivated or flooded with criticism for several weeks

Which impact is the most common ?

New criteria

Profile

Tactic

Trigger

CONSEQUE

NCES

Locatio

n

BAD BUZZ IMPACT ON THE ORGANIZATION

28% 24%

16%

9% 6%

17%


24 MMC RESEARCH METHODOLOGY

Study of the English & French (1) web from January 1st, 2016 to December 31st 2016

A significant bad buzz is defined as any controversy which happens to be critical for a company or a public organization and that takes place at least in two different locations on the web. Some may be «covered» offline as well.

MMC’s proprietary methodology used to evaluate the efficiency of the company-‐organization’s tactics when hit by a bad buzz, hinges on the analysis of several key factors such as the :

• Tone of web users’ comments following the reaction of the organization

• Evolution of the number of «supportive» or «understanding» comments vs «opponents»

METHO

DOLO

GY

(1) Almost 70 % of the bad buzz analyzed in this study are « covered » by the english web

25

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Key prevention tool : a predictive test to anticipate a controversy & a guide line to deal with a bad buzz