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Give your audience something to share

It doesn’t matter what you say, or what someone hears, the only thing that matters is what your audience repeats.

Give your audience something to share


It doesn’t matter what you say, or what someone hears, the only thing that matters is what your audience repeats.

If you send a Tweet, stop and think: will my followers want to pass this along? And what about my follower’s followers and the people who follow them? Give your audience something they will want to share.

The NYTimes reported in 2009:

People preferred e-mailing articles with positive rather than negative themes, and they liked to send long articles on intellectually challenging topics.
Perhaps most of all, readers wanted to share articles that inspired awe, an emotion that the researchers investigated after noticing how many science articles made the list.

What we share reflects back upon us. That’s why we tend to pass along inspiring, helpful, interesting or entertaining stories. What stories do you repeat to your friends or loved-ones? What conversation starters do you feel particularly happy to share on a first date? Helpful, useful, inspiring or good stories are the most socially successful messages.

If you are using social media to promote the story of your brand or business, package your message in a way that entices your audience to share it. Don’t just add a share button—construct your content so that it is eminently sharable. Give links to pictures, inspiring videos, articles, insights or information that your audience actually wants.

Match your content to your brand.

A brand is a promise delivered. I learned this the hard way at DreamWorks. We did an early test screening for Madagascar, when the content was a little more raw and racy. The audience roared. They loved it. The humor tested really well. People were laughing so hard they were crying. But our final question of the audience survey was:

“Would you recommend this film to the parents of your kid’s friends?”

…and the answer came back with a crystal clear “no.”

It didn’t matter that our message was well-crafted and well received and that our jokes were funny—what mattered was that no parent would recommend such a racy and inappropriate comedy to their kid’s friend’s parents. We iterated, watered down the content (and frankly the laughs) but we gained trust and landed the audience we wanted.

Imagine what would have happened if we had optimized for laughs instead of recommendations? There wouldn’t have been a Madagascar 2 or 3 and several hundred of us might have been out of a job.

If you go to a kid’s movie, you want to see a kid’s movie, not an adult comedy. Sometimes DreamWorks could walk the line to give you both, but the whole idea was to never cross the line so far that you can’t retreat back to the zone of parental recommendation.

DreamWorks made the right decision to optimize for repeatability (“Yes! that film is great. Your kids will totally love it.”) rather than the data-proven results of “the funniest jokes.”

For startups

If you are crafting data-driven decisions about your product, marketing or UX, make sure that you are testing the right thing. Don’t be fooled into thinking your goal is to make every number go up and to the right.

Deduction is an art.

You can’t just scan for anything that causes the numbers to jump (more funny, raunchy jokes!) and then think you’ve got the answer. You must instead work through the data to determine an actual thesis for growth, retention and delight. This type of work sometimes requires divergent, orthogonal, and truly creative thinking to uncover a idea hidden in plain sight. It’s the plot of every House episode, every Sherlock Holmes story, every inventive Artist’s biography, and every inventor’s artistry. Sometimes your big idea comes from a product visionary who concocts something out of the blue. Sometimes it will comes from a carefully constructed testing system. Usually it will come from someone who is able to offer an actual insight, not just another incremental optimization.

Data is not enough. You need a product thesis, and then your experimentation becomes a series of hypotheses that test against the your big idea.