BSI Good News about Bad News – New Findings on Word of Mouth

Marketing 2.0 Conference, Hamburg 2005
BSI




         Join the conversation
  MARKETING 2.0 CONFERENCE
        www.marketing2conference.com
Good News about Bad News
New Findings on Word of Mouth

   Presentation to WOM Conference
 Robert East, Kingston Business ...
Word of Mouth (WOM)
Communication between consumers about products,
services, companies etc
– we include emails and teleph...
Positioning Our WOM Research
In the past WOM was                Adoption of New Categories
implicit in research on the
ado...
WOM: Influential but Under-Researched
  WOM is often the most powerful channel for bringing
  about change
   – non-commer...
Previous Research Has Related WOM to
             Satisfaction
  But satisfaction is about 5 times as common as
  dissatis...
Customers Who Are Neither Satisfied nor
Dissatisfied Still Give WOM (Anderson 1998)
                 14


                ...
To Collect Data on WOM ...
We should
–   collect data from those who use a category
–   cover all the brands in a category...
Measures
How many times have you recommended any dentist in
the last six months?
                          Please write in...
POSITIVE AND NEGATIVE WORD-OF-MOUTH FINDINGS

    Service/product   N     Positive Word of Mouth in last 6 mths   Negative...
THE INCIDENCE OF POSITIVE AND NEGATIVE WORD-OF-MOUTH IN 15 CATEGORIES

                         Positive Word of Mouth in ...
Why Is PWOM Incidence Greater Than
        NWOM Incidence?
  First, there is about 3 times as much PWOM because
  about 3 ...
Are PWOM and NWOM About the Main
           Provider?

Category, all UK       Proportion of   Proportion of NWOM
         ...
PWOM and NWOM Incidences Are
Positively Associated across Categories
   Incidence of
   NWOM




     150.00
             ...
Consumers Who Give NWOM Are Much
     More Likely to Give PWOM
  Across all categories 75% of all those who gave
  NWOM ga...
Explaining WOM
What are the drivers of PWOM and NWOM?
– motivation: importance of category, relative evaluation of brands
...
We Corroborated the 3:1 Ratio with Two
          Other Methods
  Received WOM
   – we measured received WOM as well as giv...
The Relative Impact of PWOM and NWOM
             on Brand Choice
   A single instance of NWOM is thought to have more
   ...
Rarity: An Example
People might say each of the following equally often
Waitrose has:
–   higher quality (+)
–   a more pl...
Previous Work on Impact of PWOM and
               NWOM
 Arndt (1962) examined the real effect of WOM on
 purchase of one ...
Procedure
To address the weakness of single-brand studies, we
conducted 15 studies on categories
To make the work less art...
The rates of PWOM and NWOM and their reported impacts
Category                 Number in sample    Percent claiming      S...
Reported Impacts of PWOM and NWOM
              Category               Number in     Percent claiming effect Impact    Rar...
Alternative Measurement of Impact
“NWOM affected my decision” may indicate less
impact than “PWOM affected my decision”
– ...
Preliminary Findings
            Relative Impact of PWOM and NWOM
Category           Probability of purchase    Shift in p...
WOM in Relation to Market Share

                 Mobile Handsets
Brand           MS %     PWOM %        NWOM %
Nokia     ...
WOM in Relation to Market Share
                   Mobile Airtime
 Brand             MS % PWOM %            NWOM %
 T-Mobi...
What Brand Did They Talk About?

                                  Handset           Airtime
                             ...
Applications
With a database
– reduce NWOM by focusing on complainants, ex-customers
  and current customers (with differe...
Finally
If NWOM is “bad news”, the “good news” is that it is
not that common and usually has less influence than
PWOM when...
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Good News about Bad News – New Findings on Word of Mouth

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Good News about Bad News – New Findings on Word of Mouth

  1. 1. BSI Good News about Bad News – New Findings on Word of Mouth Marketing 2.0 Conference, Hamburg 2005
  2. 2. BSI Join the conversation MARKETING 2.0 CONFERENCE www.marketing2conference.com
  3. 3. Good News about Bad News New Findings on Word of Mouth Presentation to WOM Conference Robert East, Kingston Business School R.East@kingston.ac.uk
  4. 4. Word of Mouth (WOM) Communication between consumers about products, services, companies etc – we include emails and telephone advice – we exclude advice from sales personnel
  5. 5. Positioning Our WOM Research In the past WOM was Adoption of New Categories implicit in research on the adoption of new categories – led to focus on early adopters – the marketing problem was to identify and target these few Sales early adopters We are interested in WOM about brands in established categories – leads to focus on all category users, how they behave and what has to be done to induce Time them to give WOM
  6. 6. WOM: Influential but Under-Researched WOM is often the most powerful channel for bringing about change – non-commercial, quick and the advice may be interactive – Keaveney (1995), 50% found new providers via WOM But little research, WOM is difficult to study So mistaken beliefs about WOM persist: – that there is more NWOM than PWOM - false – that an instance of NWOM has more impact than an instance of PWOM - often false for brand choice I present evidence on these plus work on how WOM relates to market share
  7. 7. Previous Research Has Related WOM to Satisfaction But satisfaction is about 5 times as common as dissatisfaction in the USA (Peterson and Wilson (1992) And much WOM is unrelated to the satisfaction of the person giving it – we recommend what will suit the other person even if we do not like it ourselves – Anderson (1998) found that those who were neither satisfied nor dissatisfied gave 80% of the recommendation rate of those who were extremely satisfied or extremely dissatisfied
  8. 8. Customers Who Are Neither Satisfied nor Dissatisfied Still Give WOM (Anderson 1998) 14 12 10 8 Mean WOM Sweden frequency 6 4 2 0 Dissatisfaction Satisfaction
  9. 9. To Collect Data on WOM ... We should – collect data from those who use a category – cover all the brands in a category – do this for many categories – measure the proportion of respondents who give WOM (penetration) and how often they do so (frequency) The incidence of WOM is penetration × frequency We want the relative incidence of PWOM and NWOM
  10. 10. Measures How many times have you recommended any dentist in the last six months? Please write in (0, 1, 2 etc) ……. How many times have you advised against any dentist in the last six months? Please write in (0, 1, 2 etc) …….
  11. 11. POSITIVE AND NEGATIVE WORD-OF-MOUTH FINDINGS Service/product N Positive Word of Mouth in last 6 mths Negative Word of Mouth in last 6 mths Ratio Penetration Frequency Incidence Penetration Frequency Incidence Ip/In % per 100 % per 100 Ip In Dentist 208 44 1.7 75 9 1.3 12 6.2
  12. 12. THE INCIDENCE OF POSITIVE AND NEGATIVE WORD-OF-MOUTH IN 15 CATEGORIES Positive Word of Mouth in last 6 Negative Word of Mouth in last 6 Ratio months months Penetration Frequency Incidence Penetration Frequency Incidence IP/IN % per 100 % per 100 (IP) (IN) Restaurant 80 3.6 285 40 2.0 78 3.7 Elementary school 73 3.4 248 12 1.6 19 13.1 Car (univ. sample) 68 3.5 235 10 2.4 23 10.2 Coffee shop 77 2.9 219 41 1.9 80 2.7 ISP (gen. public) 56 3.7 207 38 5.0 186 1.1 Car (general public) 48 2.6 123 11 1.4 15 8.2 Cell-phone airtime 40 2.3 90 23 2.2 51 1.8 Car service 37 2.3 87 10 2.4 24 3.6 Dentist 44 1.7 75 9 1.3 12 6.3 Dry cleaning 28 2.2 62 5 1.2 6 10.3 ISP (univ. sample) 33 1.9 61 7 2.3 15 4.1 Credit card 31 1.8 58 16 2.3 37 1.6 Optician 36 1.5 55 21 1.5 31 1.8 Car insurance 24 1.5 36 1 2.0 2 18.0 House cont. insur. 16 1.3 21 3 4.3 11 1.9 Means (unweighted) 46 2.4 124 17 2.3 40 Ratio 3:1
  13. 13. Why Is PWOM Incidence Greater Than NWOM Incidence? First, there is about 3 times as much PWOM because about 3 times as many people give it – mean penetrations are 46 (PWOM) and 17 (NWOM) – mean frequencies are much the same 2.4 (PWOM) and 2.3 (NWOM) Many people may lack negative examples that they could advise against – this would reduce the NWOM penetration but not the frequency, as we found, – mostly PWOM is about their main provider
  14. 14. Are PWOM and NWOM About the Main Provider? Category, all UK Proportion of Proportion of NWOM PWOM about about other providers main provider than main provider % % Cars 98 87 Dentist 98 79 Bank 88 51 Mobile phone handset 88 87 Mobile-phone handset 80 80 Mobile-phone airtime 79 81 Mobile-phone airtime 74 52 Mobile-phone airtime 68 89 Restaurants 65 72 Restaurant 52 88 Mean (unweighted) 79 77
  15. 15. PWOM and NWOM Incidences Are Positively Associated across Categories Incidence of NWOM 150.00 Linear Regression R-Square = 0.28 100.00 50.00 0.00 50.00 100.00 150.00 200.00 250.00 Incidence of PWOM
  16. 16. Consumers Who Give NWOM Are Much More Likely to Give PWOM Across all categories 75% of all those who gave NWOM gave PWOM Those who gave NWOM were 3.5 times more likely to be in the PWOM group than the non-PWOM group (which were about equal in size)
  17. 17. Explaining WOM What are the drivers of PWOM and NWOM? – motivation: importance of category, relative evaluation of brands – opportunity based on individual abilities: category knowledge, verbal skill – opportunity presented by the environment: salience of category and brand, social contacts, others seeking advice etc Motivation and opportunity boost both PWOM and NWOM in categories - so they are positively associated But lack of knowledge of negative cases is likely to restrict NWOM more in some categories than others - so ratio of PWOM to NWOM will vary across categories
  18. 18. We Corroborated the 3:1 Ratio with Two Other Methods Received WOM – we measured received WOM as well as given WOM Conditional Intention – we asked respondents to state whether they would give PWOM and NWOM if asked, or if the topic arose in conversation – this gives penetrations for conditional PWOM and NWOM that can be compared with the penetrations for given PWOM and NWOM – the conditional WOM is elicited behaviour, not recall
  19. 19. The Relative Impact of PWOM and NWOM on Brand Choice A single instance of NWOM is thought to have more impact than a single instance of PWOM One reason could be that rare information has more impact – surprise causes attention (Berlyne and McDonnell (1965) – rare info is more informative (Lynch, Marmorstein and Weigold 1988) – But, although we have shown that NWOM is rarer than PWOM, negative information about brands may not be rarer than positive information
  20. 20. Rarity: An Example People might say each of the following equally often Waitrose has: – higher quality (+) – a more pleasant environment (+) – a good delivery service (Ocado) (+) – more expensive product (–) – so, you could have 3 times as much PWOM as NWOM about Waitrose although the NWOM and PWOM facts occur equally often Note: people assign fewer negative than positive attributes to brands (Mittal, Ross, and Baldasare 1998)
  21. 21. Previous Work on Impact of PWOM and NWOM Arndt (1962) examined the real effect of WOM on purchase of one new brand – NWOM depressed purchase twice as much as PWOM raised it – but brands/categories vary, so more evidence is needed Alhuwalia (2002) used attitude change in lab studies – if people were committed to brands, they discounted negative data (but they accepted positive data) – so negative data was not more influential But we want to measure the impact on brand choice in real settings
  22. 22. Procedure To address the weakness of single-brand studies, we conducted 15 studies on categories To make the work less artificial, we asked “did the last instance of PWOM/NWOM that you received affect your decision?” This gives the percentages of respondents whose decisions were affected by PWOM and NWOM
  23. 23. The rates of PWOM and NWOM and their reported impacts Category Number in sample Percent claiming Sig. of Impact Relative receiving effect on decision difference ratio rarity PWOM NWOM PWOM NWOM (4/5) (2/3) 1 2 3 4 5 6 7 8 Restaurant (1) 96 25 80 80 ns 1.0 3.8
  24. 24. Reported Impacts of PWOM and NWOM Category Number in Percent claiming effect Impact Rarity sample receiving on decision of … ratio ratio PWOM NWOM PWOM NWOM (4/5) (2/3) 1 2 3 4 5 7 8 Restaurants, Iranian 79 58 100 73 1.4 1.4 Restaurants, type of cuisine 85 43 83 48 1.7 2.0 Restaurant, main 97 25 80 80 1.0 3.8 Restaurant, main 161 117 78 74 1.1 1.4 Restaurant, main 68 38 72 87 0.8 1.8 Holiday destination 131 92 71 64 1.1 1.4 Cell-phone handset 157 155 70 35 2.0 1.0 Optician, UK 48 28 67 43 1.6 1.7 Luxury brands 72 36 64 44 1.4 2.0 Cell-phone airtime 149 152 61 53 1.2 1.0 Coffee shop 74 60 54 72 0.8 1.2 Cell-phone airtime 49 54 47 26 1.8 0.9 Credit card, UK 92 85 40 42 1.0 1.1 Car, UK 134 110 34 36 0.9 1.2 Supermarkets 42 35 33 54 0.6 1.2 Mean (unweighted) 96 73 64 55 1.2 1.5 • Categories vary but, overall, PWOM has a little more effect than NWOM (64% versus 55%, ns) • PWOM and NWOM impacts are correlated (cols 4 and 5, r = 0.52; p < 0.05) • The impact ratio is not explained by relative rarity (r = –.11, p = 0.69)
  25. 25. Alternative Measurement of Impact “NWOM affected my decision” may indicate less impact than “PWOM affected my decision” – if most brands have little chance of purchase, NWOM cannot reduce this chance much but PWOM might increase it a lot – the measure should look at the shift in purchase probability
  26. 26. Preliminary Findings Relative Impact of PWOM and NWOM Category Probability of purchase Shift in probability of purchase Prior to Prior to After After PWOM NWOM PWOM NWOM Rest. Iranian 0.44 0.22 .31 –.02 Restaurant, fav. 0.35 0.59 .39 –.48 Restaurant type 0.36 0.41 .34 –.22 Supermarket 0.43 0.39 .16 –.16 Mobile phone 0.39 0.36 .20 –.07 Mobile airtime 0.32 0.41 .19 –.10 Luxury brand 0.54 0.56 .16 –.16 Means 0.40 0.42 .25 –.17 • Prior probabilities higher than we expected • It appears that PWOM again has marginally more effect overall but it varies by category
  27. 27. WOM in Relation to Market Share Mobile Handsets Brand MS % PWOM % NWOM % Nokia 40 40 24 Sony-Eric 24 21 22 Motorola 14 20 15 Samsung 10 11 11 Siemens 4 2 9 Panasonic 2 1 6 Others 4 3 15 • PWOM follows market share • NWOM for mobiles relates to MS but is flattened
  28. 28. WOM in Relation to Market Share Mobile Airtime Brand MS % PWOM % NWOM % T-Mobile 25 23 14 Vodafone 21 24 8 Orange 19 15 29 O2 12 18 8 3 11 8 33 BTcell 8 8 5 Virgin, Fresh 2 4 3 • PWOM follows market share • NWOM for airtime shows spikes for Orange and 3. - Orange: 58% about coverage, 18% about reliability - 3: 39% about coverage, 32% reliability and service
  29. 29. What Brand Did They Talk About? Handset Airtime PWOM NWOM PWOM NWOM Current brand 81 20 79 19 Brand before current brand 5 45 4 32 Owned before that 10 26 5 24 Never owned 5 9 12 26
  30. 30. Applications With a database – reduce NWOM by focusing on complainants, ex-customers and current customers (with different messages) (remember, the person who gives NWOM is also likely to be giving PWOM on another brand). – increase PWOM by targeting current and, usually, recently acquired customers Develop metric for WOM performance Identify the “talking points” used in PWOM and NWOM and how these can be transmitted in advertising on which media http://subaru.com.au/awd/
  31. 31. Finally If NWOM is “bad news”, the “good news” is that it is not that common and usually has less influence than PWOM when it occurs But it is a pity that this research has not been done before We need evidence-based marketing not marketing folklore

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