Return on A Share
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VP of Data Scientist at ShareThis, Dr. Yan Qu, recently presented at the Global Data Science Conference about our study on the Return on A Share. Here are her slides.
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Return on A Share
- 2. With the growth of the social web, we turn more often to friends and strangers for recommendations on where to go, what to eat, and what to buy. 2 SHARING IS THE CONNECTIVE THREAD OF THE SOCIAL WEB
- 3. 3 120 SOCIAL CHANNELS 95% OF ONLINE AUDIENCE ShareThis Sharing Solutions ShareThis is the largest sharing platform reaching 211 million people over 120 social channels on 2.8 MM sites. That’s 95% of the web! 2.8MM PUBLISHERS
- 4. YOUR AD AUDIENCE IDENTIFICATION DELIVERY HOW SHARETHIS WORKS 4 Jessica reads an article about budget bedroom ideas & decides to share it to her Facebook page using the ShareThis widget! This is Jessica! She’s busy chatting and browsing the web… ShareThis observes the share and can then target Jessica and her friends with advertising messages tailored to their interests All social actions are then cataloged and segmented to build out custom audience profiles based on social sharing behaviors. YOU R AD
- 5. 5 Sharing widgets across 120+ social channels Widget Stats
- 6. 6 THE IMPACT OF SHARING IS WELL- DOCUMENTED 73% of survey respondents process information more deeply, thoroughly, and thoughtfully when they share it. 70% of people trust consumer reviews they found online. 38% During a four-week test, Starbucks’ Facebook fans and “friends of fans” were 38% more likely to make a purchase.
- 7. 7
- 8. 8
- 9. 9 BUT HOW DOES IT ALL TRANSLATE TO MONETARY IMPACT?
- 10. SHARETHIS COMMISSIONED THE FIRST STUDY OF ITS KIND TO MEASURE THE IMPACT OF SHARING ON THE PURCHASE PROCESS PURCHASE INTENT RECOM- -MENDATION PRICE BRAND PREMIUM GENERIC LUXURY ECONOMY TYPE SOURCE STRENGTH Family Friend Acquaintance Stranger Professional Excellent Good Moderate Bad In-person Social Network Trade Publication
- 11. 11 LIKERT SURVEY METHOD DO NOT CAPTURE THE TRADEOFF IN REAL PURCHASE SITUATIONS
- 12. 12 CONJOINT METHODOLOGY USES STATISTICAL MODELING TO DETERMINE THE RELATIVE IMPORTANCE OF VARIOUS FACTORS AFFECTING THE CONSUMER PURCHASE DECISION http://sibmbaw11.blogspot.com/
- 13. BRAND PRICE TYPE STRENGTH SOURCE RECOMMENDATION WHICH OF THE FOLLOWING TWO PRODUCTS ARE YOU MORE LIKELY TO PURCHASE? 13 CONJOINT METHODOLOGY USES STATISTICAL MODELING TO DETERMINE THE RELATIVE IMPORTANCE OF VARIOUS FACTORS AFFECTING THE CONSUMER PURCHASE DECISION x Premium Brand 10% higher Facebook Post Friend Economy Brand 10% lower Car & Driver Review Professional Sample conjoint survey screen
- 14. 14 Study Details Three industries (consumer packaged goods, mini-tablets and automobile) Two studies (traditional Likert rating scales and conjoint analysis) Four types of prices (10% lower pricing, comparable pricing, 5% higher pricing, 10% higher pricing) Four types of brands (economy, generic, luxury, premium) Four recommendation strengths (bad, moderate, good, excellent) Six thousand responses (1,000 for each industry / study)
- 15. 15 RECOMMENDATIONS ARE MORE IMPORTANT TO THE CONSUMER PURCHASE DECISION THAN BOTH BRAND AND PRICE Recommendations account for 57% of the consumer purchase decision: RECOMMENDATIONS 57% PRICE 28% BRAND 15%
- 16. 16 SIMILAR PATTERN ACROSS DIFFERENT VERTICALS 58% 34% 8% 56% 24% 19% 56% 25% 19% CPG Electronics Autos Recommendations Price Brand
- 17. 17 6.3% 7.3% 9.5% 10.6% ONLINE SHARES ARE NEARLY AS VALUABLE AS IN-PERSON RECOMMENDATIONS Consumer Ratings Consumer Reviews In-Person Recommendations Online Shares Impact on purchase intent
- 18. 18 RETURN ON ‘EXCELLENT’ RECOMMENDATIONS Highly positive shares yield a return of 9.5% 6.3% 7.3% 9.5% 10.6% 10.2% Consumer Ratings Consumer Reviews Online Shares In-Person Recommendations Professional Reviews 6.0% 6.2% 11.2% 13.2% 7.1% 7.6% 8.1% 9.3% 10.5% 5.7% 8.1% 9.2% 9.3% 10.0% CPG Electronics Autos
- 19. 19 NEGATIVE RETURN ON ‘BAD’ RECOMMENDATIONS Negative shares lower purchase intent by 11.0% (11.3%) (11.2%) (11.0%) (11.2%) (10.2%) Consumer Ratings Consumer Reviews Online Shares In-Person Recommendations Professional Reviews (13.1%) (13.1%) (12.5%) (12.9%) (10.6%) (10.6%) (10.5%) (10.6%) (10.5%) (10.2%) (10.0%) (9.9%) (10.0%) (9.9%) CPG Electronics Autos
- 20. 20 THE SOURCE OF THE SHARE IS IMPORTANT 8.0% 7.7% 7.5% 12.7% 8.5% 9.0% 14.0% 9.6% 10.7%10.5% 11.7% CPG Electronics Autos Strangers Acquaintances Close Friends / Family Professionals
- 21. 21 FOR AUTO BRANDS, AN EXCELLENT SHARE IS WORTH $3,708 Consumer Ratings Consumer Reviews In-Person Recommendations Online Shares Professional Reviews $2,312 $3,277 $3,708 $3,766 $4,702
- 22. 22 Consumer Ratings Consumer Reviews In-Person Recommendations Online Shares Professional Reviews $22.09 $23.56 $24.91 $28.76 $32.44 FOR ELECTRONICS BRANDS, AN EXCELLENT SHARE IS WORTH $25
- 23. $0.42 $0.44 $0.92 $1.05 23 Consumer Ratings Consumer Reviews In-Person Recommendations Online Shares FOR CPG BRANDS, AN EXCELLENT SHARE IS WORTH $0.92 That’s how much more consumers are willing to pay for the average supermarket product if it was positively shared about by someone in their social network.
- 24. 24 Key Findings Recommendations have more impact on a consumer’s decision-making process than brand or price
- 25. 25 Recommendations have more impact on a consumer’s decision-making process than brand or price Highly positive online shares generate a 9.5% increase in purchase intent, while negative reviews can decrease intent by 11.0% Key Findings
- 26. 26 Recommendations have more impact on a consumer’s decision-making process than brand or price Highly positive online shares generate a 9.5% increase in purchase intent, while negative reviews can decrease intent by 11.0% Online sharing has a measurable effect on a product’s prices, driving incremental value by as much as $3,708 for automobiles Online shares are nearly as valuable as in-person recommendations Key Findings
- 27. 27 WHAT DOES IT ALL MEAN?
- 28. DRIVE EARNED MEDIA SUCCESS WITH SOCIAL INSIGHTS VIEW CURRENT CUSTOMERS AS MARKETING PARTNERS ENABLE CUSTOMER EVANGELISM MONITOR YOUR ONLINE PRESENCE THROUGH SHARING ADDRESS NEGATIVE REVIEWS OPENLY AND HONESTLY
- 29. Use social signals to determine where and when to spend media dollars UNLOCK THE VALUE OF SHARING WITH PAID MEDIA Use social data to identify users who shared relevant content IDENTIFY TARGET Align messaging with sharers’ interests and deliver media on the content with which they engage OPTIMIZE Heavy-up deployment around key events to drive conversion when conversations are abuzz Monitor sharing trends in real time and capitalize on user intent as quickly as possible throughout the purchase funnel
- 30. 30 THE VIRTUOUS CIRCLE OF SHARING SHARING INSIGHTS OPTIMIZATION EARNED MEDIA LARGER AUDIENCE
Editor's Notes
- Explosion of social networks, not just in terms of adoption, but also proliferation; from FB & Tw to 4Sq and Pinterest. What they all have in common is that they are a way for people to share things This has created an unprecedented amount of user curated content
- In fact, there has been so much new content that it has changed the way we make buying decisions. Effect is well documented; 70% of people trust the consumer reviews they find online – this didn’t exist 10 years ago!
- But what really is the monetary impact of all this and how can a brand manager plan for it?
- There are a number of factors that play into purchase decisions. Brand, price, recommendation, etc. Clustered within these are even more parameters (type, strength, etc.) How do we pick apart the impact of each of these? Can we ask people? Bias from what people say they do vs. what they actually do. Unconscious desires, Freud, etc. Traditional survey approach (likert) doesn’t effectively weigh the relative importance of all these variables. Moreover, what people say they do (i.e. survey response) is different from what they actually do.
- Conjoint analysis is a statistical technique used in market research to determine how people value different attributes (feature, function, benefits) that make up an individual product or service. Therein lies the power of Conjoint methodology. Instead of asking questions like “Rate the importance of BRAND to your purchase on a scale of 1 to 10”, we lay out a series of choices (tradeoffs) broken out by purchase factor. With enough data points (~20 tradeoffs per respondent over 6,000 respondents) we can then statistically model the relative importance of EACH FACTOR. This has never been applied to the concept of online sharing. Respondents are all recent or active purchasers. Auto/tech: past 6 months CPG: primary supermarket shopper in household
- Therein lies the power of Conjoint methodology. Instead of asking questions like “Rate the importance of BRAND to your purchase on a scale of 1 to 10”, we lay out a series of choices (tradeoffs) broken out by purchase factor. With enough data points (~20 tradeoffs per respondent over 6,000 respondents) we can then statistically model the relative importance of EACH FACTOR. This has never been applied to the concept of online sharing. Respondents are all recent or active purchasers. Auto/tech: past 6 months CPG: primary supermarket shopper in household
- For consumer packaged goods pricing, we used $4 for a typical store brand grocery product, $6 for a typical standard brand, $8 for a typical quality brand and $10 for a typical premium item. For the mini-tablets, where we identified specific brands, we used actual prices of each mini-tablet. Apple’s mini iPad, Samsung Galaxy, Dell Venue and Google Nexus. The other adjustment we made for this test was to use specific price points ($189, $229, $309, $329 and $359). For the automobiles, we used Kelly Blue Book (www.kbb.com) to price a 2014 Kia Rio LX ($14,100), a 2014 Ford Taurus SE ($26,100), a 2014 Audi A6 ($42,200) and a 2014 Jaguar XK ($76,500).
- This chart plots relative importance of each factor. Recommendations (whether personal, online, etc.) drive 60% of a consumer’s purchase decision. A considerable weight.
- So we know recommendations are important. What about the type of recommendation. We were particularly interested in the online share
- Not all recs are the same. A recommendation, of course, is comprised of many components. We focused on the three most important components: the strength of the recommendation, who made the recommendation, and the source of the recommendation or share. Again, the results were surprisingly consistent across the three product areas: the strength of the recommendation (bad, moderate, good and excellent) is far more important than the source or even the familiarity of the person who made it. Online shares more valuable due to proximity of relationship. Social networks are usually friends and family. At the end of the day, being told something in person has more weight.
- Looking across the verticals, once again we see a similar pattern. The impact is particularly marked for CPG brands where the impact of ratings and reviews has been less
- For consumer packaged goods pricing, we used $4 for a typical store brand grocery product, $6 for a typical standard brand, $8 for a typical quality brand and $10 for a typical premium item. For the mini-tablets, where we identified specific brands, we used actual prices of each mini-tablet. Apple’s mini iPad, Samsung Galaxy, Dell Venue and Google Nexus. The other adjustment we made for this test was to use specific price points ($189, $229, $309, $329 and $359). For the automobiles, we used Kelly Blue Book (www.kbb.com) to price a 2014 Kia Rio LX ($14,100), a 2014 Ford Taurus SE ($26,100), a 2014 Audi A6 ($42,200) and a 2014 Jaguar XK ($76,500).
- For consumer packaged goods pricing, we used $4 for a typical store brand grocery product, $6 for a typical standard brand, $8 for a typical quality brand and $10 for a typical premium item. For the mini-tablets, where we identified specific brands, we used actual prices of each mini-tablet. Apple’s mini iPad, Samsung Galaxy, Dell Venue and Google Nexus. The other adjustment we made for this test was to use specific price points ($189, $229, $309, $329 and $359). For the automobiles, we used Kelly Blue Book (www.kbb.com) to price a 2014 Kia Rio LX ($14,100), a 2014 Ford Taurus SE ($26,100), a 2014 Audi A6 ($42,200) and a 2014 Jaguar XK ($76,500).
- To equate sharing with a dollar value, we multiplied the percentage impact attributed to shared recommendations by the average price of the products we were looking at. For example, we found that positive online shares drove a 9.2% increase in purchase intent among autos; so 9.2% x $39,000 (the average price of vehicles we surveyed) amounts to $3,708 in additional value. Of course, we can get even more granular with this data by breaking out these values across price points, recommendation source, and recommendation type. An online share from a close friend (11.2% increase in perception) about a luxury vehicle (avg price: $76,500) yields roughly $8,676 in additional value. For consumer packaged goods pricing, we used $4 for a typical store brand grocery product, $6 for a typical standard brand, $8 for a typical quality brand and $10 for a typical premium item. For the mini-tablets, where we identified specific brands, we used actual prices of each mini-tablet. Apple’s mini iPad, Samsung Galaxy, Dell Venue and Google Nexus. The other adjustment we made for this test was to use specific price points ($189, $229, $309, $329 and $359). For the automobiles, we used Kelly Blue Book (www.kbb.com) to price a 2014 Kia Rio LX ($14,100), a 2014 Ford Taurus SE ($26,100), a 2014 Audi A6 ($42,200) and a 2014 Jaguar XK ($76,500).
- For Brand Strategy & Social Media Teams – provides tangible metrics for earned media strategies. Valuate shares of brand content to better understand success of earned media strategies and optimize accordingly. Provides basis for understanding brand perception around the web, and generating new and shareable content to drive engagement and advocacy
- For Digital Media Planners – provides justification for identification, targeting, optimization based on sharing Recommendations drive a vast majority of the purchase decision, meaning sharing is an inherently powerful indicator of interest and consideration.