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Posts Tagged ‘User Research’

From Clean Laffs here:

should-keep-in-your-fridge

Frozen Food Labeling

I have changed my system for labeling homemade freezer meals. I used to carefully note in large clear letters, “Meatloaf” or “Pot Roast” or “Steak and Vegetables or “Chicken and Dumplings” or “Beef Pot Pie.”

However, I used to get frustrated when I asked my husband what he wanted for dinner because he never asked for any of those things. So, I decided to stock the freezer with what he really likes.

If you look in my freezer now you’ll see a whole new set of labels. You’ll find dinners with neat little tags that say: “Whatever,” “Anything,” “I Don’t Know,” “I Don’t Care,” “Something Good,” or “Food.” Now no matter what my husband replies with when I ask him what he wants for dinner, I know that it is there waiting.

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Source: Image from wwonline.net

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…where to spend the bucks!

A lightly edited excerpt from an article by Josh Elman appearing here. Though dated, the anecdote and the concept are still relevant, I thought. And for companies not merely in the product space. Here we go:

twitter-bird-white-on-blue

Pretty much every new app has the following problem: lots of people sign up but don’t stick around.

I frequently get asked what are benchmarks for retention after one day or one week. My answer tends to be the same for products in the early days:

Ignore the benchmarks. Find the patterns in the stories of people who do get your product. Figure out what converted them and got them so excited to keep using your product every day or every week. In the early days, your main focus should be to attract and create more and more of those “core users” who deeply use your product. Over time you can try to increase averages, but first, you just need a core and strong base.

Most people look too much at the “big data” and try to draw conclusions. In the early days of a product you have to talk to people. You need anecdotes much more than data. You could say The plural of anecdote is data.

To collect anecdotes, you have to talk to actual users. The best users to call are ones who can help you understand why they tried your product and what hooked them. I like to look for bouncebacks. Bouncebacks are users that have tried your product, bailed immediately and didn’t find it useful, came back to try again for some reason (at least 1 week later, or even better, 1 month later), and then got hooked.

The first step is to identify some bounceback users to call…

From these patterns, you can invest in revising your marketing and improving your product and onboarding. Revamp your messaging to focus more on the messages that brought people back and got them engaged. Update your product and onboarding to simplify whatever the users did the second time to get fully engaged…

We learned from early users that many of them signed up for Twitter and thought it was just a megaphone. When they had nothing to say, and didn’t otherwise understand the product they bailed. When they later heard about how valuable Twitter could be if they followed their reverend or the food truck that broadcasts its location every day, they came back and tried again. But this second time they specifically sought out people to follow and had a good experience. We rapidly rebuilt our onboarding to focus much more on following and finding the right people which caused significant increases in how many users were activated after signing up. We revised our messaging to talk much more about finding and following the right people on Twitter instead of talking about tweeting and broadcasting.

I recommend doing this exercise of interviewing new bounceback users every 6 months. You’ll learn a lot about how to keep improving your adoption and activation.

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Source: Image from publiclibrariesonline.org

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