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Social media research - new horizons Where and when SMR will kill traditional research methodology Pavel Lebedev 23.05. 2014 ESOMAR BEST OF - RUSSIA 2014

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Pavel Lebedev presentation about Social media research on Esomar Best of Russia 2014

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Page 1: Lebedev esomar 2014

Social media research - new horizons Where and when SMR will kill traditional research methodology

Pavel Lebedev

23.05. 2014

ESOMAR BEST OF - RUSSIA 2014

Page 2: Lebedev esomar 2014

What are we analyzing: facts vs opinions

2

Who? When? How often? How

much?

What people think? Why?

What is the opinion?

Polls are usually approximate,

sometimes deadly incorrect

Only technological

measurements in 5-10 years

Interaction with TA in any form

structures an object

Social media monitoring

(listening) deals with organic

conversations

Page 3: Lebedev esomar 2014

What opinion does really exist?

3

What is public opinion?

What is representativeness of public opinion?

Page 4: Lebedev esomar 2014

3D opinions

4

Per

son

Opinion

Polls tradition equalize

people with different media

effects

In the Internet media effect

can be measured, not only

detected.

Media effects: not just an ability to distribute some opinions, but also

put them into the minds.

Page 5: Lebedev esomar 2014

What is social media monitoring?

5

What are they “saying”?

How do people interact with each

other?

Friends connections

What content do they like? How does information spread?

Who discuss brands?

Automated collection of public posts and comments (+ related data) on a particular

subject (determined by a list of keywords).

Page 6: Lebedev esomar 2014

Monitoring vs Polls

6

Research design

(questionnaire, sample)

Search query

(key words)

Interviewer / self-filling

Data with preset structure

and amount

Report, spreadsheet,

infographics

Automated collection

Texts with metadata

Report, spreadsheet,

infographics, data stream

Page 7: Lebedev esomar 2014

SM Monitoring peculiarities

7

Search query

(key words)

Automated collection

Texts with metadata

Report, spreadsheet,

infogaphics, data stream

Unknown data structure. Amount of data is

known only after collection.

Message (not a person) is an analysis unit.

General totality

Analysis (structuring) plan is developing after

data collection.

Some aspects may not be discussed.

Opinion structure (topics, sentiment) and

media field dynamics

Page 8: Lebedev esomar 2014

Ex. No1. Analysis of brand perception

8

Regular SM Monitoring

Retailer brand with 6 competitors

Evaluation of 20+ Retailer characteristics

The spread of newsworthy for PR needs

Page 9: Lebedev esomar 2014

Types of contents and types of authors

9

Users Brand Media /Publics Bots

News / events yes yes

Histories yes yes

News & Histories reposts yes yes yes

User opinions yes

Irrelevant mentions yes

Spam yes

Brands are usually interested in user opinions

Page 10: Lebedev esomar 2014

People are engaged in discussion about brands

10

2023

3327

5437 5662

6999

5296

2565

4475

6030 5568

5166

3679

801 950 1623

1585 1272

1043

207 332 241 239 192

215

1181

2969

2551 2109 1859 1752

743

2010

1186 1308 1307

1012

1658

4020

4892

4299

2853 2627

0

1000

2000

3000

4000

5000

6000

7000

8000

September October November December January February

Shop 1

Shop 2

Shop 3

Shop 4

Shop 5

Shop 6

Shop 7

Page 11: Lebedev esomar 2014

Evaluation of retailer characteristics

11

43%

23% 19%

16% 13% 13%

10% 9% 7%

5% 4% 4% 3% 3% 3% 2% 1% 1% 1% 0% 0% 0% 0%

12%

0,7 0,7

0,5 0,7 0,8

0,4

0,7

0,1

0,6

0,5

0,1 0,2

0,1 0,2 0,3

0,6 0,7 0,7

0,4

0,2 0,3

0,8 1,0 1,0

-1,0

0,0

1,0

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

41%

26%

7%

17%

4%

11%

2% 8%

5% 5%

2% 6%

1% 4%

1% 1% 1% 1% 0% 0% 0% 0% 1%

15%

0,5 0,3

0,7

0,2 0,4

0,2 -0,1

0,2 0,1

0,1

-0,6

0,2 0,1

0,0

-0,3

0,3

0,0

0,6

0,1 0,3

-0,5

0,0

0,9 1,0

-1,0

0,0

1,0

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

Ass

ortm

ent

Inte

rnet

sho

p

Ret

ail s

tore

Pric

e

Bon

uses

Qua

lity

of G

oods

sale

s pr

omot

ion

Cus

tom

er-o

rient

atio

n

Del

iver

y

Hol

d fo

r pi

ckup

Cal

l cen

tre

Exc

hang

e of

goo

ds

Com

pete

ncy

Ser

vice

cen

ter

E-m

ail /

SM

S

Infr

astr

uctu

re o

f ret

ail

stor

e

Ban

ks

Ads

, Mar

ketin

g

Ser

vice

s

Ext

ra g

uara

nty

Just

ice

Fin

anci

al r

esul

ts

Dev

elop

men

t

Oth

er

% of mentions NSI

Net Sentiment Index (NSI)= (positive+ neutral- negative)/ total

Shop No7

Shop No2

Page 12: Lebedev esomar 2014

Shop No1

Extra guaranty

Internet shop

Hold for pickup

Justice

Delivery Banks

Customer-orientation

E-mail / SMS

Services

Retail store

Competency

Bonuses

Ads, Marketing

Financial results

Shop No6

Exchange of goods

Development

Service center

Quality of Goods

Infrastructure of retail store

Assortment

Price

Shop No7

Shop No3

Shop No4

Shop No5

Shop No2

Call centre

sales promotion

Process on online shopping External activities

Interaction with clients Goods features

External activities

Internal activities

Objective features

Inte

ract

ion

ret

aile

r -c

onsu

mer

s Perception map

Page 13: Lebedev esomar 2014

The spread of Media Markt newsworthy

13

1

5

2

8 10

3

4

6

Number of mentions 1 267

Unique authors 1 190

Reach: 11 639 531

Engagement 3 358

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MediaMarkt начинают принимать батарейки от населения.

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10 Другие

9

Page 14: Lebedev esomar 2014

Results

14

Different types of mentions for different research goals.

User opinions cover many sides of brand activities.

They are about things that people really care and discuss

spontaneous.

News and “viruses” circulation as a part of media research,

evaluation of PR-effect.

Page 15: Lebedev esomar 2014

Ex. No2. Ad campaign discussion in SM

15

Ad campaign image monitoring

Reasons for spontaneous interest to the Ads

Insights about ads perception and engaged audience

Page 16: Lebedev esomar 2014

Beverage brand

16

Brand mentions – 360 mentions per month

Ads mentions – 42 mentions per month (11%)

First month of campaign

0

5

10

15

20

25

30

35

40

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Упоминания бренда

Упоминания анализируемой рекламы

Brand mentions Ads mentions

Page 17: Lebedev esomar 2014

17

Brand mentions – 1700 mentions per month

Ads mentions – 800 mentions per month (47%)

Soundtrack mentions – 745 mentions (44%)

Other ads mentions – 55 mentions (3%)

Beverage brand

х 4,7

х 19

Second month of campaign

0

20

40

60

80

100

120

140

160

180

200

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

Упоминания бренда

Упоминания анализируемой рекламы

Упоминания саундтрека рекламы

Brand mentions

Ads mentions

Soundtrack mentions

Page 18: Lebedev esomar 2014

Socio-demographics

18

31%

9%

3%

2%

2%

2%

2%

2%

2%

47%

Moscow

St. Petersburg

Volgograd

Novosibirsk

Rostov on Don

Ufa

Ekaterinburg

Krasnodar

Samara

Others

Discuss brand

23%

5%

3%

2%

2%

2%

2%

60%

Moscow

St. Petersburg

Novosibirsk

Izhevsk

Perm

Rostov on Don

Ufa

Others

Discuss ads

Discuss brand

Male

Female

Discuss ads

Male

Female

Second month of campaign

Page 19: Lebedev esomar 2014

Results

19

Ad campaign stimulates growth of spontaneous discussions

about brand, not only ads.

Unexpected context of ad discussion (soundtrack) .

Lack of interest in promo mechanics.

Where are two different audiences: one is interested in brand,

the other – in ads.

Page 20: Lebedev esomar 2014

Summing up: main advantages of SM Monitoring

20

Organic Conversations

Niche Audiences

Cost-effective

Fast and Flexible

Direct access to unfiltered conversation, allowing

researcher to understand how consumers discuss

the brand or category.

Access to incredible amounts of data, including

historical data, with the ability to drill down and find

niche audiences

Quick, cost effective research

Changes can be made quickly if the research isn’t

being productive or if new avenues need to be

explored