More in Growth & Experimentation — page 13
Minimum Detectable Effect: How Small a Change Can You See?
Minimum Detectable Effect (MDE) is the smallest change your A/B test can reliably see. You calculate it *before* a test to determine the sample size needed.
The RICE Scoring Model: Prioritize with Data, Not Feelings
RICE is a formula—(Reach × Impact × Confidence) / Effort—for scoring competing features. It replaces gut feelings with a data-driven framework for prioritizing product roadmaps. The biggest footgun is treating the score as gospel, not a conversation starter.
Five Whys: Find the Root Cause, Not Just the Symptom
Five Whys is a tool for digging past surface-level problems. By repeatedly asking "Why?", you trace a chain of causality back to the true root cause. It's used in post-mortems to find systemic issues, not just patch symptoms. The footgun is stopping too soon.
Hypothesis-Driven Development: Test Your Ideas Before You Build
Hypothesis-Driven Development treats product work as a series of experiments, not a to-do list. You state a testable belief ("If we build X, users will do Y") before writing code. This de-risks new features by validating ideas early.
The Endowment Effect: We Overvalue What We Already Own
We irrationally value things more simply because we own them. This appears in free trials that create a sense of ownership, making users less likely to cancel. The footgun is assuming users judge value objectively; they don't, and will resist switching.
The IKEA Effect: Why We Overvalue What We Build
The IKEA effect is our tendency to overvalue things we help build. It's used in products that let users customize profiles or dashboards, increasing their investment. The footgun: if the task is too hard or fails, users feel incompetent and abandon it.
Variable Rewards: The Engine of Habit
Variable rewards make products sticky by creating unpredictable payoffs, like a slot machine. This drives repeat actions in social feeds or games. The footgun is that overuse can feel manipulative and lead to user burnout or accusations of addictive design.
Nudge Theory: Shaping Choices Without Forcing Them
Nudge theory influences behavior by subtly redesigning the environment where choices are made. It's used in product design to guide users toward desired actions, like setting smarter defaults.
The Paradox of Choice: Why More Options Can Hurt
The Paradox of Choice argues that more options can decrease user satisfaction. Instead of empowering users, an explosion of choices in pricing tiers or feature settings can lead to decision paralysis. The footgun is assuming users want maximum choice.
The Peak-End Rule: Design for Memory, Not Averages
Users don't remember the average of an experience; they remember its most intense moment and its end. This shapes recall of onboarding, support calls, or checkout. The footgun is optimizing for overall 'goodness' while ignoring a painful peak or weak ending.
Anchoring Bias: The First Number You See Matters Most
The first number you see acts like a mental anchor, warping all subsequent judgments. This is used in pricing, where a high "original" price makes a sale price seem better, and in negotiations.
The Hook Model: Designing for Repeat Engagement
The Hook Model engineers user habits with a 4-step loop: Trigger, Action, Variable Reward, and Investment. It's a framework for building products people return to on their own, common in social media and games.
Fogg Behavior Model: Why Users Act (or Don't)
The Fogg Behavior Model states a behavior only happens when Motivation, Ability, and a Prompt converge (B=MAP). Use it to diagnose why a feature fails or to design new ones. The footgun is blaming low motivation when the real issue is low ability.
Social Proof: People Copy People
Social proof is the tendency to copy others' actions, assuming they reflect the correct behavior. It’s why we trust a product with thousands of positive reviews or a restaurant with a long line. The footgun: the crowd can be wrong or even faked.
Loss Aversion: Why Losing $10 Hurts More Than Gaining $10
Loss aversion is the bias where losing something feels twice as bad as gaining the same thing feels good. It drives user behavior in free trials and pricing. Don't confuse this emotional reaction to framing with rational risk aversion.
Schema-on-Read vs. Write: Pay for Structure Now or Later?
Schema-on-Write pays to structure data upfront for fast, consistent reads. Schema-on-Read defers this cost to query time for flexible ingestion. This choice underpins relational databases (write) vs. data lakes (read). The footgun is creating a data swamp.
Attribution Modeling: Who Gets Credit for a Conversion?
Attribution modeling decides how to credit different marketing channels for a conversion. It's like splitting a sales commission: does the first call, the final meeting, or everyone involved get credit? The footgun is using a simplistic model like last-touch.
Identity Resolution: Stitching User Profiles Together
Identity resolution stitches together scattered user data into a single profile. It's like a detective matching a phone number from your CRM and a cookie from your website to the same person.
The Data Layer: A Central Hub for Website Events
A data layer is a central JavaScript object acting as a message bus between your site and analytics tags. It passes event data, like button clicks or purchase values, in a structured way. The key footgun: never overwrite it; always use `dataLayer.push()`.
Event-based Analytics: Tracking User Actions, Not Page Views
Event-based analytics tracks specific user actions—clicks, purchases, signups—not just page views. This model powers product analytics tools to map user journeys and measure feature adoption. The footgun is tracking everything, creating noisy, unusable data.