Trendspotting
Observe mimetic user behaviours within the defined domain.
What is Trendspotting?
Trendspotting is a qualitative validation technique that involves systematically observing and analyzing mimetic behaviors within your target market or industry domain. This method focuses on identifying patterns in how users copy, adapt, or respond to emerging behaviors, products, or services that others in their peer group are adopting. By studying these imitative patterns, entrepreneurs can uncover hidden opportunities and validate demand signals before competitors recognize them.
This technique leverages the fundamental human tendency to follow social proof and copy successful behaviors from others. When users begin mimicking certain actions, purchasing decisions, or lifestyle changes within a specific domain, it often indicates an underlying shift in preferences, needs, or market conditions. Trendspotting helps startups identify these early signals by monitoring social media conversations, user-generated content, community discussions, and behavioral changes across various platforms and real-world environments.
The power of trendspotting lies in its ability to reveal opportunities that traditional market research might miss. While surveys and interviews capture what people say they want, observing mimetic behaviors shows what people actually do when they think no one is watching. This technique is particularly valuable for identifying emerging niches, understanding evolving user needs, and spotting gaps in the market before they become obvious to everyone.
When to Use This Experiment
• Early-stage opportunity identification when you're exploring potential markets but haven't yet defined a specific problem or solution • Before conducting expensive market research to identify promising areas worth deeper investigation • When entering established markets to find underserved segments or emerging sub-trends that incumbents haven't noticed • For B2C products where social influence and peer behavior strongly impact adoption decisions • When targeting younger demographics who are more likely to exhibit mimetic behaviors on social platforms • During market expansion to understand how your existing solution might be adapted for new user segments • For lifestyle, fashion, or social products where trends and social proof drive significant portions of demand • When you notice unusual activity in adjacent markets or among edge users of existing products
How to Run This Experiment
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Define your observation scope by identifying the specific domain, user segments, and geographic areas you want to monitor. Choose 3-5 platforms or environments where your target users are most active.
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Set up monitoring systems using free tools like Google Alerts, social media hashtag tracking, Reddit monitoring, and TikTok trend analysis. Create lists of relevant keywords, communities, and influencers to follow.
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Establish baseline patterns by spending 1-2 weeks observing normal behavior patterns within your chosen domain. Document typical conversation topics, popular content types, and standard user interactions.
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Identify mimetic signals by looking for behaviors that spread from user to user, including copied content formats, repeated phrases, similar product modifications, or parallel lifestyle changes. Pay attention to phrases like 'I saw someone doing this' or 'everyone is trying this now.'
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Document and categorize trends by creating a spreadsheet to track each observed pattern, including the source, spread rate, user types involved, and potential underlying needs or problems being addressed.
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Analyze trend drivers by investigating what motivates users to copy these behaviors. Look for common pain points, aspirations, or social pressures that make certain behaviors attractive to replicate.
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Validate trend significance by checking if the patterns appear across multiple platforms, user segments, or geographic areas. Strong trends typically show up in various forms across different environments.
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Extract opportunity insights by identifying gaps where users are trying to solve problems through makeshift solutions, workarounds, or suboptimal existing products, then formulate hypotheses about potential solutions.
Pros and Cons
Pros
• Zero financial cost - requires only time and attention, making it accessible for bootstrapped startups • Reveals authentic behavior - shows what users actually do rather than what they claim in surveys • Early opportunity detection - can identify trends before they become mainstream and competitive • Broad market insights - provides understanding of user psychology and social dynamics beyond specific product feedback • Continuous learning - can be performed ongoing to stay ahead of market shifts
Cons
• Time-intensive process - requires consistent daily monitoring and analysis to be effective • Subjective interpretation - distinguishing meaningful trends from noise requires experience and judgment • Limited actionability - observations must be combined with other validation methods to develop concrete solutions • Platform dependency - insights may be skewed by the specific platforms or communities you choose to monitor • Trend timing uncertainty - difficult to predict if observed behaviors will scale or fade quickly
Real-World Examples
Dollar Shave Club identified the opportunity for their subscription razor service by observing frustrated discussions in online forums where men complained about expensive razor prices and shared DIY solutions or bulk-buying strategies. The founders noticed users were already trying to 'hack' the traditional razor purchasing model, indicating demand for a more convenient, affordable alternative.
Instagram's founders originally created Burbn, a location-based check-in app, but through trendspotting realized users were primarily using just the photo-sharing features. They observed that people were mimicking professional photography techniques on mobile devices and sharing heavily filtered images across various platforms, leading them to pivot and focus solely on photo sharing with filters.
Peloton's opportunity emerged from observing the growing trend of people sharing indoor cycling workout experiences on social media, posting photos of expensive studio classes, and trying to recreate boutique fitness experiences at home. The founders noticed users were already attempting to combine high-end fitness equipment with social sharing and gamification, validating demand for a connected home fitness solution.