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Posts Tagged ‘Medium’

“Good service design is important for the overall user experience. Yet, it is even more important at the end of an experience (or exposure to a brand) due to the Peak-End Rule and Recency Effect. Placing the business needs before the user’s needs, breaking the user’s flow and not addressing a user’s need at the point of their need are primary culprits in designing a poor experience.”

Chris Kiess writes in his article “Service Design — How to Fail at the Checkout and Ruin Your User’s End Experience” appearing here.

While he talks about “8 ways I see retail merchants like Target, Walmart or Meijer fail in service design as it relates to the end of the customer experience and the final impression they make with consumers,” there’s an interesting snippet about a negative perception and how it could be turned around.

First about the perception:

“The biggest faux pas of superstores is having too many checkout registers and not enough cashiers. Most people would probably not be concerned during the holidays (or any other time) if they sauntered over to the checkout and there were ten cashiers at all ten registers with lines behind each. This would give the customer the illusion the store is busy and they are doing everything they can to help customers move through the checkout process. But, what generally happens instead is you walk up to the checkout area after finding everything you need and there are thirty registers with only five in service. This, I cannot understand. On the surface, it gives the impression the store could do more. After all, there are twenty-five more registers and surely they could open one or two more of them. It boggles the mind that a store would feel the need to install thirty checkout lanes and never use them all at one time.”

He suggests:

“This is largely about human perception. The simple fix is to cut the number of registers installed and use a greater percentage of them during busy times. This would give the impression (and shape perceptions) a greater effort is being employed to move people through the lines.”

A thought:

The suggestion could still leave at times a few unattended counters. So why not have counters that could be rolled in from back of the store on need basis and wheeled away when done? Just as many as needed, leaving no visibly unattended counters at any time.

Also could the stores do like the airlines doing in-line check-in with staff going around with their special devices? Of course, it needs some adaption to allow for handling the purchases in the cart.

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Image from here.

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From Jason Fried’s blog here (minimally edited) pointed to by Wally Bock .

It’s Bezos expressing himself in Q&A session conducted years ago about people who are “right a lot” and those who aren’t

His observation about people who are “right a lot”:

Bezo Says

People who were right a lot of the time were people who often changed their minds. He doesn’t think consistency of thought is a particularly positive trait. It’s perfectly healthy — encouraged, even — to have an idea tomorrow that contradicted your idea today.

The smartest people are constantly revising their understanding, reconsidering a problem they thought they’d already solved. They’re open to new points of view, new information, new ideas, contradictions, and challenges to their own way of thinking.

This doesn’t mean you shouldn’t have a well formed point of view, but it means you should consider your point of view as temporary.

And what trait signified someone who was wrong a lot of the time? Someone obsessed with details that only support one point of view. If someone can’t climb out of the details, and see the bigger picture from multiple angles, they’re often wrong most of the time.

 

 

 

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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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nobody-wants-to-use-software

 

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Source: medium.freecodecamp.com/nobody-wants-to-use-software-a75643bee654

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