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Slide 1: Word of Mouth: Insights, drivers, and measurement WOMMA Webex June 2010 CONFIDENTIAL AND PROPRIETARY Any use of this material without specific permission of McKinsey & Company is strictly prohibited
Slide 2: Contents Word of mouth importance and drivers How to manage WOM Our recent experiences McKinsey & Company |1
Slide 3: Word of mouth has significant impact on sales across categories and markets Percent of sales driven by Word of mouth 65 35 26 19 WOM appears to plays a more significant role in purchase decision-making for big ticket items and when consumers are new to the category Car insurance Emerging market mobile Mature Skin Care market Mobile SOURCE: McKinsey McKinsey & Company |2
Slide 4: WOM is a important across the consumer’s purchase ‘journey’ Impact of TPs along purchase journey, Percent A Mature markets 1 Drivers of inclusion in initial consideration set1 1. 2. 3. 4. 5. 6. Advertising Previous usage WOM Internet information Contacted provider Magazine/review 30 26 18 17 4 3 B Developing markets 1 Drivers of inclusion in initial consideration 1. 2. 3. 4. 5. 6. WOM Advertising Previous usage Magazine/Review Contacted provider POS reco 18 17 15 11 8 6 2 2 Drivers of inclusion in consideration set during active evaluation 1. 2. 3. 4. 5. 6. 7. Internet information WOM Shop Advertising Magazine/review Promotions Contacted provider 29 20 19 19 9 2 1 1 3 2 Drivers of inclusion in active evaluation 1. 2. 3. 4. 5. 6. WOM Advertisement Past usage Magazine/Review POS reco Operator contacted 28 26 13 7 7 6 4 3 Drivers for final selection 3 Drivers of final selection at moment of purchase 1. 2. 3. 4. 5. Internet information Shop WOM Advertising Contacted provider 65 20 10 3 2 1. 2. 3. 4. 5. 6. WOM Advertising Magazine/Review POS reco Contacted operator Past usage 46 40 9 3 1 1 1 Excludes contact by provider to extend contract after expiration (20% of consumers) SOURCE: CDJ "Mobile 2009" McKinsey & Company |3
Slide 5: WOM is generated by direct experiences and company driven activity Percentage 100% 35 28 40 32 65 72 60 68 65 Company triggered WOM Experience based WOM Split of experience based WOM - product vs. service experience Experience with customer service 44 56 Experience with product Market average 35 SOURCE: McKinsey WOM telco survey 2009 McKinsey & Company |4
Slide 6: WOM is predominantly triggered by experiences that deviate from expectations Average number of messages sent per respondent per KBF Telco Negative experience relative to expectations 1.0 Skincare 0.6 Experience as expected 0.3 0.5 Positive experience relative to expectation 1.2 2.2 Positive experiences most likely to trigger WOM Very low levels of negative experience vs. expectations possibly category related SOURCE: McKinsey McKinsey & Company |5
Slide 7: Some messages are more important than others – exceeding expectations is key to driving WOM 100 Functions MOBILE HANDSETS Highest likelihood to trigger and sustain impactful WOM @ @ @ @ @ @ 0 -5 -4 -3 -2 -1 0 ¥ © © ¥ ¥ © @ 1 2 Design © ¥ @ Brand A ¥ Brand B © Brand C Attractiveness of contract Importance Voice clarity of messages ¥ © © ¥ ¥ © McKinsey & Company Battery time Brand Ease of use 3 4 5 Deviation from expectations |6 SOURCE: McKinsey
Slide 8: Messages that “travel” in social networks should be understood and prioritised Positive WOM MOBILE OPERATORS Positive WOM Negative WOM Negative WOM Y Axis Percentage of WOM by WOM by content Percentage of content Percentage of WOM by content 20% 19% 18% 17% 16% 15% 14% 13% 12% 11% 10% 9% 8% 7% 6% 5% 4% 3% 2% 1% 0% 20% 19% 18% 17% 16% 15% Positive POS experience 14% Size of customer franchise Widest network 13% Lowest price Lowest price 12% 11% Good voice clarity Brand status in social network Good voice clarity Best brand 10% 9% Simple plans 8% call dropscall drops Min Min 7% Simplest tariffs Simplest tariffs 6% Best VAS 5% Specific, attractive offers Attractive schemes 4% Call in first Simple SIM attempt 3% purchase 2% 1% 0% 0% 50% 0% 50% 55% 55% 60% 65%65% 70% 17% 16% 15% 14% 13% 12% 11% 10% 9% 8% 7% 6% 5% 4% 3% 2% 1% 0% 70% 0% 2% 4% 6% 8% 10% 12% 14% 16% 18% 20% 22% 24% 26% 28% 30% 32% Likelihood of message being retold Complex processes Worst brand Network congestion Poor clarity High price Frequent call drops Poor customer care Poor coverage Poor network related WOM have the maximum negative impact Customer care related issues have the least impact on final purchase Poor VAS Not available Erroneous billing No complaint resolution Less offers Fewer plans Unavailability and –ve reco Not preferred by POS can completely shy by POS away potential customers Likelihood of message being retold Selection of message/themes also based on message impact on sales or brand ▪ ▪ Negative WOM can be triggered by negative customer experience Judgment call if communications are used to mitigate this SOURCE: McKinsey McKinsey & Company |7
Slide 9: ~8-10% of consumers are influential – they create more WOM with higher impact Number of messages sent per month Impact WOM Positive Negative Influentials1 Non-influentials 19 1.0 -2.3 5-9x 5 Most important characteristics of influentials1 Percentage of respondents Is technology-savvy I value his/her opinion Is an expert in this topic He/she is close to me He/she understands my needs He/she has independent views and tastes Has a high education 44 36 35 29 24 21 16 -1.1 Influentials in telco tend to… Have a higher education (schoolleaving exam, university studies) Watch more TV and listen more to the radio Read more newspapers and magazines 1 Influentials are senders who are considered very trustworthy and competent. Their tips are regarded highly relevant. Influentials have a bigger network and pass on a higher number of messages than the rest of the population. Influentials constitute ~10% of the population SOURCE: McKinsey McKinsey & Company |8
Slide 10: Influentials are not the same across categories Most important characteristics of influentials1 Percentage of respondents Is technology-savvy I value his/her opinion Is an expert in this topic He/she is close to me He/she understands my needs He/she has independent views and tastes Has a high education Is male He/she is first to buy new mobile phone products Is young Influentials in telco tend to… Have a higher education (school-leaving exam, university studies) Watch more TV and listen more to the radio Read more newspapers and magazines Most important characteristics of influentials1 Percentage of respondents 45 69 38 44 49 31 6 44 Is very interested in beauty 36 35 29 24 21 16 14 13 8 I value his/her opinion Is an expert in this topic He/she is close to me He/she understands my needs He/she has independent views and tastes Has a high education Is female He/she is first to buy new skincare products Is young Influentials can be identified by – Demographics – Attitudes and behaviors 38 31 3 – Preferences Who talks depends on the sector Influentials in skincare tend to… Have an intermediate education (no university studies) Listen less to the radio Read more magazines, but not newspapers 1 Now think about the latest recommendations you received for [product] and that influenced your thinking. Please select the most important characteristics of the people whose advice you would follow. [max. 5] SOURCE: McKinsey McKinsey & Company |9
Slide 11: WOM most effective if aimed at personal interactions with trusted individuals and experts Share of messages sent Percentage Experts Family Online 17 Impact positive WOM1 83 Face-to-face 1.4 1.0 0.9 0.8 0.7 Friends Internet users Colleagues 1 Impact coefficients from logistic regression were transformed into impact weights by applying weight factor 1.12. SOURCE: WOM telco 2009 McKinsey & Company | 10
Slide 12: Selected media vehicles can be used identified to trigger WOM (beyond product/service experience) Scale 1 to 100 percent Channel 1 Cinema 2 TV 3 Online specials 4 Outdoor specials 5 Promotion-stand 6 Flyer 7 Online ads 8 Radio 9 Events 10 Outdoor ads 11 Magazines 12 CRM newsletter … 25 … Newspaper Suitability to trigger WoM effects DISGUISED CASE EXAMPLE 90 80 75 75 70 65 55 50 50 45 45 45 … 25 Source: McKinsey McKinsey & Company | 11
Slide 13: WOM performance can be managed at brand level by understanding “WOM Equity” High impact on purchase Low impact on purchase Volume Impact WOM Sender: “Who is talking” ▪ Influential ▪ Non-Influential WOM Network: “Where are they talking” WOM Content: “What are they saying” ▪ Key buying factor (driver) ▪ Product attribute (ante) WOM equity Number of messages ▪ Close/ trusted Impact ∑ WOM equity Index ▪ Large/ dispersed WOM Source: “What is the trigger” ▪ Own experience ▪ Company triggered SOURCE: McKinsey McKinsey & Company | 12
Slide 14: Optimizing impact drivers is more important than managing volume Impact of WOM driver group elements on purchase Factor1 Sender 1.3x High Low Influentials Noninfluentials Content 10x Functionality Battery time Source 1.6x Own experience Other sources (e.g. stories from other people) 5x Own experience Network 2x Experts Colleagues Total 42x 1.2x High Influentials 2.2x Based on science/advanced ingredients Good value for money 2.4x Experts 32x Low Noninfluentials “What I heard in the news Others (e.g. experts) 4x High Influentials 1.6x Interest rates Modernity, International presence of bank 2.6x Own experience as customer Indirect 2.2x Family 39x Low Noninfluentials Coworker 1 Highest/lowest impact SOURCE: McKinsey McKinsey & Company | 13
Slide 15: WOM Equity metric combining volume and impact WOM scorecard Message volume as share of total messages in sample1 Brand A 15 x Average impact per message on purchase per brand, score2 -0.26 = -3.90 WOM equity Index Brand B 10 0.49 4.90 Brand C 29 0.13 3.70 Similar volumes for brand A, D, & F, but huge differences in WOM impact Brand D 16 0.45 7.30 Brand E 16 0.03 0.50 Brand F 7 -0.19 -1.30 1 Percentage of total number of messages in the sample 2 For each brand this was calculated by taking the average of impact weights for positive and negative messages (Betas from logistic regression*weight factor) which had been weighted with the volume of positive and negative messages for each brand. SOURCE: McKinsey CDJ telco 2009 McKinsey & Company | 14
Slide 16: Contents Word of mouth importance and drivers How to manage WOM Our recent experiences McKinsey & Company | 15
Slide 17: What matters in executing a successful strategies ▪ ▪ ▪ Develop insights around WOM equity drivers at category and brand level – these should be tracked whilst understanding impact on business A great story built around messages and themes which have intrinsic impact and velocity The ability to engage the most influential consumers in the category by either – Vivid and unusual/exclusive experiences which can be related – or Disruptive marketing campaigns Apply a multi-channel mix which enables engagement, co-creation and sharing Multi-agency collaboration key to build integrated and holistic campaigns which make sense and can be sustained ▪ ▪ McKinsey & Company | 16
Slide 18: Three distinct ways to harness WOM in marketing strategies/ campaigns Actions to harness WOM sources Use word of mouth insights to optimize traditional marketing - Maximize return on traditional marketing optimizing for both direct effects and pass on effects through word of mouth (reach and impact) Relevant cases 1 2 3 Consequential WOM Develop comprehensive intentional WOM strategies – Leverage CLM, events and online to deliberately trigger WOM Intentional WOM Use WOM insights to optimize the customer experience and to develop new products – Over-deliver on product and service dimensions that matter to the customers and that consumers naturally talk about – Enable consumer to share experiences with other Experiential WOM McKinsey & Company | 17
Slide 19: Traditional marketing campaigns can be powerful WOM triggers if executed with creativity and engage consumers Cadbury advertisement campaign £6.2m campaign to increase sales and brand engagement Bizarre Gorilla advertisement on television and cinema at heart of campaign Additional appearances on billboards, print media, and event sponsorships Online buzz via YouTube Video was uploaded on YouTube and generated great number of unpaid contacts ─ 500,000 views in the first week ─ 6 million views within 3 months Perpetuating effect: Video was copied/parodied by other brands Sales for Dairy Milk increased by 9% YOY Public perception of brand improved by 20% Cadbury’s Gorilla ad campaign gathered exponential momentum through WOM online channel YouTube SOURCE: Cadbury website, YouTube McKinsey & Company | 18
Slide 20: First Direct launched a WOM-embedded online marketing campaign enabling customers to share experiences Situation/Objectives Situation ▪ First Direct is a direct bank in the UK offering banking services via internet and phone ▪ Bank with the highest customer satisfaction in the UK, top 10 across industries Objectives ▪ Wanted to leverage high customer satisfaction to raise brand awareness and encourage people to switch Approach Impact ▪ Conducted a survey with the credible newspaper Guardian on ‘trust in the digital age’. Over 750 participants, results can be read on Guardian homepage Main findings ▪ Consumers mainly trust expert advice websites, consumers’ recommendations on the internet and independent experts ▪ 65% visit customer review websites ▪ 85% do online research before choosing a financial product ▪ “Our research clearly shows that customers expect openness and honesty in the businesses they trust and recommend. We want to take the next step and utilise this information” (Head of Marketing, First Direct) ‘Live’ campaign (Sep 2009) ▪ Aggregated customers’ comments made about the brand in more than 5 million blogs and forums ▪ Posted these comments on a dedicated website, both positive and negative ▪ Visitors can share their experiences and feedback on the page and view visual summaries, quotes and statistics about the brand ▪ Over 2,000 customers shared their feedback within the first 2 weeks, a large majority being positive Voted as “most loved savings brand” and “best customer service” by independent online survey end of 2009 “We've had great success with our 'Live' campaign” (Marketing Communication Manager, First Direct) ▪ ▪ SOURCE: Company website, UK Customer Service Index, Guardian, lovemoney.com, press clippings McKinsey & Company | 19
Slide 21: XBOX use WOM as the core driver for product design Table of contents of the book of Xenon – Product vision document for XBOX 360 ▪ ▪ ▪ ▪ Vision of the digital entertainment lifestyle and the experiences and communities we will create for customers Stories from our customers - how they will describe the experience to their circle of friends [uses personas but focuses on stories - uses emotional language...] Technology quests on which we must succeed for our customers – Extraordinary visual rendering of imagined worlds – Capture of memories and sharing of experiences and accomplishments – Seamless integration to communications and communities – Effortless access to entertainment from multiple sources – Easy creation of online and in game identities – Simple integration with other devices/networks – Convenient one click payment for new content or capabilities What stories the world will tell about us when we win [press articles as if written about the team's success several years later] SOURCE: www.time.com/time/magazine/article/0,9171,1061497-5,00.html McKinsey & Company | 20
Slide 22: Contents Word of mouth importance and drivers How to manage WOM Our recent experiences McKinsey & Company | 21
Slide 23: Recent McKinsey experiences in WOM Strengthening brand sentiment ▪ Diagnostic: WOM only ▪ touchpoint capable of sentiment change Study developed WOM strategy e.g., messages, vehicle and senders capable of sentiment change Concrete campaigns developed and launched Driving trial for product launch ▪ Granular analytics ▪ revealing touch rate required to drive trial Detailed consumer engagement model developed across touch points to drive trial Result: industry leading trial rates ▪ ▪ Greenfield mobile carrier launch rates ( weighted by touch point) calculated to ensure WOM buzz at launch WOM equity diagnostic used to identify messages with high velocity Consideration % Marketing mix and message optimization ▪ Understand adjusted reach and Quality of WOM ▪ Adjust mix and messages to optimise RoI ▪ Required touch Launch trial consideration 120 100 80 60 40 20 0 -20 Key inflection point ▪ Touch rate (n) McKinsey & Company | 22
Slide 24: And finally…. What is Incite? What are the service offerings? ▪ ▪ Market leader in enterprise social media monitoring/analytics (Source: Forrester) Dataset: Billions of social media conversations per year across 120 million blogs, message boards and social networks Global: 13 markets now (US, UK, Germany, Spain, Italy, Australia, New Zealand, China, Japan, India, Brazil, Canada and Korea); 20 by EOY 2010; over 150 clients globally Sentiment accuracy is highest in the industry (source: Microsoft) Jointly owned by Nielsen and McKinsey; co-developing unique software, metrics, analytic services Proprietary technology for analyzing social media Dedicated analyst support with category expertise ▪ ▪ ▪ ▪ ▪ ▪ Service offerings 1 – Marketing effectiveness: Identify brand strengths/weaknesses for each stage of the consumer decision journey (from awareness to loyalty), based on unprompted, authentic consumer insights. Identify influencers and measure the reach of their buzz – Product development: Surface unmet needs and 2 perceived feature benefits for brands and competitors. Improve product launch success via rapid, marketdriven product, packaging, and messaging adjustments – Customer service: Turn customer service into a 3 marketing channel: detect and respond to buzz about positive and negative consumer experiences with your company; identify and engage with highly influential consumers Benchmarks for buzz volume, advocacy, reach Best practices for incorporating social media into core marketing, customer service, and product development processes ▪ ▪ McKinsey & Company | 23