Removing stuff is never obvious yet often better (gkogan.co)

Article summary

The article discusses how removing features or complexity can often lead to better results, citing the example of a company that removed a pricing calculator from their website and saw an increase in sign-ups and customer engagement. The calculator had been causing confusion among potential customers, leading to incorrect estimates and a lack of trust. By removing it, the company was able to simplify their pricing model and improve the user experience. This approach is presented as a counterintuitive but effective way to solve problems and improve outcomes.

Main themes

• Simplification
• Feature removal
• Complexity reduction
• User experience
• Pricing models
• Decision making

What commenters say

• Removing features or complexity can be a effective way to improve outcomes, but it is often overlooked as a solution.
• Some argue that 'contact us for pricing' models can be beneficial for companies, but others see it as a way to hide prices and take advantage of customers.
• The article's example of removing a pricing calculator is seen as a success, but some commenters argue that the problem was not the calculator itself, but rather the underlying pricing model.
• Others suggest that the company's decision to remove the calculator was a result of over-hiring and a lack of clear ownership, leading to a committee-like decision-making process.
• There is disagreement over whether the 30% of employees who disagreed with the decision to remove the calculator represents a significant problem or just a normal level of dissent.
• Some commenters argue that internal polls can be misleading, as they may not reflect the views of actual users, but rather the biases of the employees who created the feature.
• The idea of removing features or complexity is seen as a way to reduce politics and negotiation within a company, but others argue that it can be difficult to evaluate the contentiousness of a change.
• The article's approach is seen as a useful signal to investigate further, but the exact threshold for when to remove a feature is unclear and may vary from organization to organization.