Joining Sally Field’s “like me” revolution
In 1985, a few eyebrows were raised (and many eyes rolled) when Sally Field gave her “You like me!” Academy Award acceptance speech.
That speech has always been like fingernails on a chalkboard to me (and a lot of other people, too). But guess what: 26 years later, “like me” has become integral to the marketing and business plans for many companies.
“Like” is all over Facebook. One new startup, Babelverse, is applying the “like me” model to its real-time voice translation via smartphone. Instead of relying on machines to do the translation, Babelverse uses a pool of human interpreters who offer their services for bid through Babelverse. The company guarantees the quality of services by requiring users to rate interpreters:
To ensure high quality, listeners must rate their interpreter after each session. Upon making a request, they will be assigned a personalised ranking of interpreters that are the best fit (automatically taking into account language pair, availability, ratings, expertise, accent…). Users will also be able to re-employ their favourite interpreters.
If an interpreter does a good job, users of Babelverse can request that interpreter again. Reading between the lines, I suspect that Babelverse would no longer work with interpreters who didn’t get consistently acceptable ratings.
This kind of ranking model has made its way into technical communication—like it or not. Comments on web pages and stats on web traffic indicate what information people find valuable (and not so valuable). Twitter, wikis, and other social media technologies are making it easier and easier to send and receive feedback on technical content.
I do wonder if everyone in tech comm is actively seeking feedback on their content. I bet not. Granted, it can be very uncomfortable to find out that responses to your work aren’t as sparkling and happy as you expected. However, unless you gather metrics to verify how useful (and how often used) your content is, you might as well be writing for yourself in a pointless and costly exercise.
Even if you do not have a lot of time or money to set up methods for soliciting feedback, there are small, low-cost steps you can take to get the feedback loop started:
- Adding links to help systems for emailing comments
- Enabling commenting on web content
- Using Google Analytics to gather metrics on web traffic
Also, if your company’s online user assistance consists exclusively of static PDF files up on a web site, you may need to rethink how you deliver content. From a use metrics standpoint, having a bunch of content in just one PDF file makes it impossible for you to gather metrics on what bits of information are used most often. (It’s also worth noting that PDF files are more difficult for users to search, have many accessibility pitfalls, and are harder to view on the smaller screens of mobile devices, but evaluating the pros and cons of the PDF format are another discussion entirely.)
It is time for everyone in tech comm to join the “like me” revolution. But please don’t make an irritating speech in front of millions of your users.
We need to draw a distinction between measuring the usefulness of content (web analytics, surveys) and simply measuring popularity (likes). I’m surprised to see that Babelverse is equating popularity with quality, with apparently no thought given to whether the translation is true to the writer’s original intent.
I’m not saying we should ignore the crowd. But we mustn’t blindly trust the crowd to do our thinking for us. A while back I wrote about this, citing the distinction James Surowiecki made between wise crowds and irrational crowds.
Sally Field is a good actress, but on Oscar night in 1985 she acted pretty irrationally. We can be wiser than that.
Babelverse is requiring users to rate the quality of interpreters’ work, so it’s not just a matter of popularity, from what I can tell.
In any context, popularity doesn’t necessarily (and shouldn’t) equate quality. However, if you’ve got content and nobody has found it or used it, you’ve got a problem. I’d argue that technical content can’t be considered high quality if no one is using it.
Larry is right though. Just because several people rate a topic highly does not mean it is perfection. There may be other users who found it less helpful but did not add comments. As is suggested, “liking” is just one tool in our arsenal.
Alan – You make a really good point about the word “like” and what it means. When I go out to Yelp to research something new (restaurant, yoga class, whatever) I notice that there are two kinds of ratings: Incredibly wonderful and Terribly awful. And that’s because people have to feel passionate about something to take the time to rate it. (And truth be told, most people would take the time to complain, rather than take the time to compliment.)
Another point I’d like to make (while I’m at it!), has to do with “quality work”. I have seen situations where the consultant creates amazing content, but does not get along well with the customer. Brusque consultants doing stellar work doth not necessarily make the customer happy.
On the flip side, I have had occasions where the consultant really wasn’t delivering the best goods, but got along famously with the customer. And the customer was happy – even though I wanted to switch out the consultant. “Quality work” was part experiential and part the work itself.
Perhaps the difference is rating the quality of the content versus rating the experience of working with the person who wrote/translated it. Those two things are not necessarily the same. So if we ask for ratings, we need to be very specific. It’s not that we can’t ask for both – we should – but we need to make sure we keep those things separate.
Val, I *completely* relate to your point about consultants and “quality work.” I have experienced the same situations you describe.
The comments are becoming more interesting than the post itself! I think we all agree that we have to gather metrics about our content/work–and those metrics include quality and popularity.
Tech comm has to get away from this notion that we create content, publish it, and then move on to the next release or project. A lot of companies understand the importance of metrics and have acted accordingly, but there are quite a few departments still in the “publish and move on” cycle.