I love a good card trick. We can apply the illusion of choice to user interactions within our Product.
I love a good card trick.
In one of my favourite trick endings, I’ll lay 6 cards out on the table, facedown. I secretly know the position of your chosen card. Then I’ll ask you to point to 3 of the cards.
If your card is one of the 3 you pointed at, I’ll take away the three you didn’t choose, letting you assume I was asking you which cards to keep. Otherwise, I’ll do the opposite, letting you assume I was asking you which cards to remove.
Repeat this step by pointing at 2 cards, and then again (if required) for the very last card. In the end, you feel like you’ve chosen exactly which card was left on the table.
We can apply this illusion of choice to the user interactions within our Product. We often see this when an app asks us for our review, either “Now”, or “Later”.
This can be implemented in any number of ways to influence the behaviour of our customers.
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What user behaviour would you like to change? How can you use the illusion of choice, to help them make that change?
Data can mean anything, therefore it means nothing. How, then, can we extract meaning from a dataset?
Two shoe salesmen were sent into “darkest Africa” to feel out the potential shoe market. The first telegraphed home saying: it’s hopeless stop nobody here wears shoes. The second telegraphed back saying: it’s wonderful stop nobody has any shoes.
As Product Managers, we work with a lot of data. Sometimes we even hire a data scientist to go through our data and tell us what it means.
Framing is the lens through which we view data. Since we all have different brains (and hence different frames) the same data will always represent something different to different analysts. Data can be objective. Recommendations based on that data can never be.
Data can mean anything, therefore it means nothing.
How, then, can we extract meaning from a dataset? One very effective method is to look hidden assumptions.
Suppose your analytics show a temporary downtick in traffic during February. One might assume that this is simply a natural ebb, another may assume that February must be a low month in your industry, a third may assume that there was a technical error has since been resolved.
To extract meaning from these analytics, ask yourself:
What assumption am I making,
That I’m not aware I’m making,
That gives me what I see?
Challenging this assumption will help you learn something new about your product (a competitor launched, an industry event, a political influence), which you can then leverage to your advantage.
Most marketing campaigns, aim to reach as many eyes as possible. Here’s another approach: Minimum Viable Marketing.
We’ve all heard about lean product development principles: Create a Minimum Viable Product (MVP), measure its performance, and iterate.
We could apply this same principle to many Product disciplines. Take marketing, for example. Often, a Product team will hire a marketing manager or consultant and launch a campaign, aiming to reach as many eyes as possible.
Here’s another approach: A Minimum Viable Marketing (MVM) campaign.
Define a small campaign targeted only at the early adopters amongst your market segment, using words like Innovative, Pioneer, Breakthrough, Private, Limited, and Now. Choose just one channel to reach them on.
No need to build out every asset for every medium. No need to get the alignment just so. No need for pixel perfection. No need to wordsmith.
Since you’re starting small, take the time to get to know your audience. Talk with them, without any hint of self-promotion. Show them your marketing materials and gauge their thoughts and reactions.