The #3 edition of 8percent.
The #3 edition of 8percent.
Your weekly growth and product upskill, in 8 minutes.
Here’s what we have for you this week.
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Growth
💻 Tools: Tech lookup and Tracked emails.
🧠 Persuasion: Put things in the center.
📰 Article: Product-Market-Fit, by Superhuman.
🤖 Automation: Upskill daily, for real.
Product
💻 Tools: Have answers from users all around the world in 2 hours, for 10$.
🧠 Persuasion: Should you buy Tulip’s bulbs?
📰 Article: No A/B testing for you ? Try this!
💰 My 2 cents: Is AI always your best friend?
Growth.
Tools 👇
BuiltWith → Look up what tech any website is using. (free)
Need information on a website?
Click on the extension, and you’ll instantly know what tech they’re using, if they have a premium plan or not, and since when.
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Snov.io → Track your sent emails. (free)
Want to know who’s been seeing your emails? How many times have they opened it? Or click the links inside?
Use this extension.
Persuasion Technique 👇
Your eyes move faster than your brain.
Center-Stage Effect: When faced with a range of products presented side by side, we tend to be drawn towards the one situated in the middle. 🧠
This effect plays on the natural tendency of humans to attribute greater value to that which is physically or metaphorically in the 'center stage.'
Marketers, retailers, and even social influencers use this strategy to draw attention and sway choices by positioning products or ideas in a central, prominent position.
It looks like this 👇
Article 👇
There are a lot of articles on Product-Market-Fit, here’s one you should read:
How Superhuman Built an Engine to Find PMF?
Introduction: Superhuman's CEO Rahul Vohra has charted a course that's both analytical and unconventional. This approach redefines the startup playbook pre-PMF, blending data-driven strategies with a keen understanding of user satisfaction.
Traditional Startup Metrics: Traditionally, startups have been guided by metrics like daily active users or monthly growth rates. These numbers, while important, don't always paint a complete picture of user engagement or satisfaction. Vohra recognized this gap and sought a more telling metric.
The Superhuman Method: Vohra's methodology pivots on a singular, powerful question: "How would you feel if you could no longer use the product?" The responses to this question, categorized as "very disappointed," "somewhat disappointed," or "not disappointed," became the cornerstone of Superhuman's product-market fit engine. This metric, combined with a targeted user percentage, set a clear benchmark for success.
Practical Applications: Superhuman's approach goes beyond mere surveys. The team dives deep into qualitative feedback, identifying what users love and what's missing. This data informs targeted improvements, iterating the product until the "very disappointed" category hits its threshold of 40%. It's a blend of quantitative data and qualitative insights, a strategy that's as meticulous as it is effective.
Limitations & Future Prospects: While Superhuman's strategy is robust, Vohra acknowledges that it's not without its challenges. The model requires constant iteration and a willingness to pivot based on user feedback. Looking ahead, he envisions a dynamic where this method not only shapes products but also molds entire companies around genuine user needs.
Conclusion: Rahul Vohra's approach, detailed in his insightful blog post, is a testament to the power of user-centric metrics in achieving product-market fit. It's a must-read for any entrepreneur looking to make their mark in a crowded marketplace, and it can be found at the heart of Superhuman's success story.
Here is the article, read it!
Automation 👇
Let’s say you want to listen to more audiobooks or podcasts.
But you never find the time… or actually, you don’t think about it when you actually have time.
This will help you.
I found that when leaving my place to go somewhere, is the best time to focus on something, so I’ve put this really simple location-based automation on my phone.
As soon as you leave my place, it opens Blinkist, or whatever app I want.
Product.
Tool 👇
Lyssna → The easiest way to test things with real users, or anonymous panels.
Lyssna, formerly known as Husability Hub, is one of the most powerful and easy-to-use platforms, for user research.
Five-second testing, First-click testing, Prototype testing… and the main feature in my opinion: Research panels.
On-demand access to panelists with more than 35 demographic filters: age, country, job, shopping habits…
Persuasion Technique 👇
We’ve all seen this.
"Join the 10,000+ businesses that switched to our platform this year".
The Bandwagon Effect - “The tendency of people to adopt certain behaviors, styles, or attitudes simply because everyone else is doing it.” 🧠
It’s old news. But it’s damn efficient.
eg: In the 17th century, tulips became a status symbol in the Netherlands. More and more people purchased tulip bulbs, increasing prices exponentially.
It looks like this 👇
Article 👇
Last week, we discussed A/B testing and how it is not for everyone (bummer..). So, how do we evaluate a page’s immediate impact on users without any constraints like budget or traffic?
If you don’t have quantitative, try qualitative data…
The 5-Second Test: when A/B Testing isn’t an Option.
But first, what is a 5-Second Test, and why 5?
Studies have shown that users can make snap judgments about a site in as little as 50 milliseconds, and their first impressions are often related to design elements. And in a few seconds, users form a basic understanding and judgment of your value proposition, which determines whether they’ll stay or leave.
The article explains the concept and how to conduct a 5-Second Test.
Importance of First Impressions: initial impressions are crucial! What users feel, recall from the first exposure, and how comfortable they are with what they just saw.
Definition of a 5-Second Test: a 5-second test involves showing a design to users for a brief period (5 seconds… ;)) and then asking them questions to gauge their immediate reactions and recall.
What a 5-Second Test won’t help you with: it is not a good approach for testing flows or designs that have multiple interactions and tasks. You can only test the first understanding of a page.
When to use it in your process: after you’ve reached a point of preparing high-fidelity designs.
How to use it: the solution described in the article is too complicated. Here is how I do it :
Create an account on a tool like lyssna.com
Use your design: you can begin with a screen of your webpage or use a design from your favorite tool
Create a test on Lyssna, add the image, put your 2, or 3 questions, and choose to use their user panels. It’ll cost you around 10$ for ten users which is enough for the first round
My personal vision of this:
If you want to test if people understand your value proposition : I generally use these two simple questions: Which product or service does this page offer? What makes it unique?
If you want to test your page from a more general perspective: The author suggests: What do you recall from the page you just saw? What do you think is the purpose of the page? What is the most prominent element that you remember from the page?
Decide, and it’s a critical point of the process: What’ll be considered as a win or a fail for each answer. Otherwise, you won’t be able to analyze the results.
Wait a couple of hours and voilà! You have ten answers.
How to analyze the results: here again a too complicated solution in my opinion.
Here is how I do it :I extract the questions from the tool and import them into a Google sheet.
I rate each answer: Full (100% accurate), Partial, Erroneous, None (no understanding).
I should have at least 80% of Full after several rounds (because, yes it’ll take you more than one round to figure this out).
Ux Collective writes the article on Medium. This is the link.
My 2 cents 👇
“Science sans conscience n’est que ruine de l’âme.”
Science without conscience is only a ruin of the soul.
Yes AI is such a revolution. And yes it can help you in many ways.
I will not discuss the philosophical issues around AI, but the misuse of it.
Three examples :
When it emphasizes gender bias
Amazon's AI-powered recruiting software preferred male candidates.
It was trained to vet applicants by observing patterns in resumes submitted to the company over ten years and … most came from men.
The system penalized phrases in the resume that included the word “women’s” like “women’s chess club captain” for instance.
Source: Reuters
When it makes you lose a case
An attorney used ChatGPT to research precedents for a lawsuit. However, at least six cases submitted in the brief did not exist, leading to a fine and dismissal of the lawsuit.
Source: Reuters
When it makes you lose a lot of money
Zillow used a machine learning algorithm to predict home prices. The algorithm leads Zillow to purchase homes at higher prices than its current estimates of future selling prices. This resulted in a $304 million loss in Q3 2021.
Source: insideBigData
We’ll see you next week.