360: Product feature prioritization & methods – with András Juhász
Product Mastery Now for Product Managers, Leaders, and Innovators - A podcast by Chad McAllister, PhD - Mondays
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Four feature prioritization methods product managers should know Today we are talking about methods for prioritizing product features. Joining us is András Juhász, a product manager for Smartly.io, a social media advertising company. He wrote an article on six methods to prioritize product features, and we’ll talk through some of them. Summary of some concepts discussed for product managers [1:30] What caused you to explore different ways to prioritize features? I think feature prioritization is an interesting topic on the product level and organization level. We ask, What problems are worth solving? What are the next best features? [3:17] How does the Kano Model work? The Kano Model uses two axes—satisfaction and execution—and shows how customer satisfaction depends on execution for each feature. It divides customer preferences into five different categories: * Basic functionality—features customers expect, e.g., voice calling capability on a mobile phone. Poor execution decreases customer satisfaction, but great execution does not amaze customers. * Performance—more is better, e.g., an electric car’s range. The more you provide, the more customer satisfaction you get. * Excitement—positive surprises, e.g., fireworks appear when you complete a task on a to-do app. Customers don’t expect these features, but they are pleasantly surprised by them. * Indifferent—features that don’t affect customers’ satisfaction, e.g., the thickness of a carton of milk. * Reverse—more is worse, e.g., longer scripts at a call center. The more you provide, the less customer satisfaction you get. This model helps you prioritize features so you don’t underbuild or overbuild the product. [9:12] Tell us about the RICE Method. The RICE Method scores your product in four categories: * Reach—how many users will be affected if you release the feature * Impact—the value the feature creates, measured as a subjective score from 1 -5 or 1-10 * Confidence—how much data is backing the feature, measured from 1-5 * Effort—the time it will take to develop the feature, measured in hours, days, weeks, or months To calculate your total RICE score, multiply reach, impact, and confidence, and then divide by effort. [16:24] What’s the Effort vs. Impact Matrix? The Effort vs. Impact Matrix is a two-by-two matrix of effort and impact, which can each be either low or high. * Low-impact, low-effort tasks are fill-ins for when the team is idle, e.g., component improvement. * Low-impact, high-effort tasks are thankless tasks that are not providing much customer value but may still be necessary, e.g., security tasks. * High-impact, low-effort tasks are the low-hanging fruit that provide immediate value. * High-impact, high-effort tasks are major projects and functionalities that provide high customer value. [19:34] How does MoSCoW work? MoSCoW is an abbreviation for Must have, Should haves, Could haves, and Won’t haves. * Must haves are the essential features your solution must deliver, the minimum valuable product; they are in your first iteration. * Should haves are important but not essential features; they might be part of the first iteration or version 1.2. * Could haves are small enhancements, adding color to your product; they might be in version 1.5. * Won’t haves are functionalities you plan to exclude. Action Guide: Put the information András shared into action now. Click here to download the Action Guide. Useful links: * Read András’ article on