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today we're joined by Wharton marketing Professor Jonah berer to talk about his
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latest research on how language impacts Word of Mouth thanks for joining us Jonah thanks for having me so your
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previous work has looked at uh how things go viral and your latest book uh invisible influence looks at how in
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Hidden influences affect our decision-making processes yeah could you summarize what you and your co-author
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looked at in this paper we've all seen the power of Word of Mouth uh whether
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we're making a simple decision like what breakfast cereal to buy or more important one like which house to choose
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we use online reviews and word of mouth all the time to help us make those decisions but is that word of mouth
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always helpful uh and that's really what this with this research looks at so
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imagine you're at a party for example or at a conference uh and you're talking to
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people about movies to two people you haven't really met before one person says they like movie A and another
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person says they recommend movie B which of those movies are you more likely to see as a result and are you going to be
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happy with your choice and what we find I don't think so surprisingly uh is that
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people are more likely to follow recommendations you're more likely to movie be cuz you think the other person
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liked it more and it's a better movie but actually you might end up not liking
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that movie so much you might end up making a worse choice because the type of people that tend to use the word I
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recommend it's a a language uh device I recommend something that suggests not
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only you like something but you're making inference about what someone else likes and it turns out that people that
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say I recommend something whether we've looked at books or wine or hotels across
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range of domains it ends up that novices are more likely to say that they recommend something than experts experts
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aren't as willing to use use that recommend language they're more willing
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to say I like something sure I like this thing but they're less willing to make a
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guess about what you're going to like and so as a result if people end up listening to recommendations as they
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often do we might sometimes end up making worse choices so what were the key takeaways from from your study yeah
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so we look at we look at two things one how people endorse things so sometimes people say I like something sometimes
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say I recommend something those might seem like really subtle differences in language but they have a big impact on
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two things first of all whether we're persuaded by that language do we take that person's endorsement and end up
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going to see that movie or that restaurant uh and also whether we end up making a good choice as a result lots of
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research shows that word of mouth is really helpful and indeed often it is but in some cases where we don't know if
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someone's an expert or not like two people we meet at a conference that we've never met before should we take
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their advice or not and when we can't tell if someone's an expert or they're
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not our best friend who knows a lot about movies sometimes we use what they say and the way they say it as a CU to
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whether they're an expert or not so we assume that if someone says I recommend
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something they actually know a lot about movies for example where if they just say I like it we assume they don't know
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as much what's dangerous there though is that the opposite is actually true novices people that don't know a lot
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about movies are more willing to say they recommend something same thing happens with restaurants or other
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domains because they don't think about the fact that others may have different
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preferences than them so if you're an expert you're not really willing to say
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I recommend something because if we don't know each other well I don't know
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your taste I don't know if you'd like the same movies that I liked so I'm not
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as willing to recommend it for you but if I'm a novice I'm very willing to use
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that strong recommendation to say I recommend this movie whereas you as a listener might end up seeing it and be
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dissatisfied as a result so so my saying I recommend this might actually mislead
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some mislead somebody exactly yeah and and um you know in general if we follow experts that's a good thing right when
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we look online we follow the wine experts when we're picking wine we look for reviewer badges to figure out who
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knows a lot but there are many cases in our lives where we don't know whether
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someone knows a lot or not and so we use their language as a cue to whether they
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have expertise but that cue May sometimes lead us to did the finding surprise you definitely
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yeah so uh we sort of thought uh that recommendations would be more impactful than likes uh that someone saying I
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recommend this movie it seems stronger uh it suggests one that they know a lot about the domain but also they just
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plain liked it more um and so that didn't surprise us so much what did surprise us a little bit is the type of
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people that use these different types of language and I've done a lot of work on
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Word of Mouth and in general I think word of mouth is a good thing but but in this case sometimes Word of Mouth can
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actually lead us astray because different people tend to use different types of language right and what do you
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think the key takeaways of your study uh which you co-authored with um with Grant
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Packard yeah uh what do you think the key takeaways would be for marketers for marketers I think it's interesting you
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know the first thing that comes to mind probably when people listen to this when
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they think of likes versus recommendations is they think of Facebook right where we say hey I like
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this well if they instead change it to I recommend this it'd probably have more
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impact right knowing that a given movie or a given brand has a certain number of
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likes isn't as impactful as knowing it has a certain amount of recommendations
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so by subt changing the language you as a marketer use you can impact whether people follow that language or not that
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said you need to be careful right because what you don't want to encourage people to follow the wrong information
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we actually did a study where we show that uh novices end up picking worse wine for example end up being more
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likely to recommend that wine and then following their Word of Mouth leads people to be more likely to choose bad
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wine over good wine if they don't know the difference um and so to be careful
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there you know marketers need to think about well are we allowing people to use other cues as well are we just put
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putting the language out there are we giving information about how many books that person has reviewed how many uh
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other bottles of wine they've talked about before uh or potentially other cues that will allow people to get a
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better sense is this good for this person or might it be particularly good for me okay and what um what about the
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consumer side what are the implications for people who are trying to get information about what they like or what
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they might want to buy y uh how do they how can they judge a source next time someone tells you they recommend
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something be very very careful uh first thing think about you know do you know them or or not uh if it's someone you
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know and you know their preferences and they know your preferences the fact that
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they're recommending something is probably a good signal but if you don't
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know them if youve just met them if you don't know whether they know a lot about
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a domain a red flag should go off if someone's saying they recommend something be a little bit more careful
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figure out do they actually know something about that domain or not do they know something about me or not um
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and make sure they know enough about your preferences before you actually go ahead and take that recommendation I can
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imag I mean I could see this playing out all the time on Facebook for example certainly and I guess when it's your
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close circle of friends it makes perfect sense in some ways to accept a re an explicit recommendation as you describe
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it but I guess the the caution comes in when it's someone you may not know yeah
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and I think uh you know a lot of times when we're talking face to face it's
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pretty clear online the boundaries blur a little bit you know we we talk to our good friends but we also talk to a lot
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of people we don't know uh as well and we often assume those people know a lot
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about what they're talking about they may not necessarily and so that I think
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is is what's important here you know lots of work has been done on online reviews the power of online reviews
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they're certainly a valuable tool to often help us make better and faster and
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easier decisions but on the margin there's some cases where it can can lead us astray and that's what I think this
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this research points out great well what is it that you want to look at next research-wise yeah you know I think one
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thing this paper starts to do um and researchers starting to look in this area more generally is the language
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people use when they describe things you would think in marketing we thought a lot about language right uh the language
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that works in advertisements or why certain language would be more effective in Word of Mouth and not really haven't
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uh that much um and so there's a lot of work now bridging uh marketing as well
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as computer science called natural language processing that's starting to look at not just well did people
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recommend something but what did they say in that recommendation even saying I recommend something I can say I strongly
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recommend this I recommend this for people who like this type of other thing and the words I'm using there can be
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quite important and so while a lot of research just looks at the number of stars for example saying you know a
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five-star review on Amazon leads to about 20 more books being sold what's also important to say is well what's the
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language being used in that review and how does certain types of language affect others uh more more importantly
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so we're doing a bunch of research on this we're looking at the language of
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customer service calls looking at if you call up uh let's say a retailer and you
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say I'm really unhappy you know what words do they use that might make you happier or not as happy uh we're doing
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some work on the language used in movies uh for example might the certain words people use over time in movies lead
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those movies to be more or less successful and can we predict that based on the language
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of those movies even song lyrics can we predict how successful a song's going to
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be by the lyrics contained in that song There's a a lot of interesting data out
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there that's texturally based and we're trying to understand it better really
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fascinating a lot to explore there yeah yeah well thanks very much for giving us
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your time no problem thank [Music] you [Music]