Dating Apps Drive Users to DIY Solutions: The Spreadsheet Symptom
·6 min read
78% of dating app users report burnout severe enough to register as emotional, mental, or physical exhaustion according to Forbes Health's 2025 survey
Developer Sampson Ezieme launched Spread in January 2025, an app purpose-built to log dates and auto-rank prospects by red, beige, and green flags
Etsy sellers now offer pre-built dating tracker templates with tabs for flag weighting and preference logging
Women appear disproportionately drawn to spreadsheet systems, frequently citing safety concerns and the need to manage rejection's psychological toll
Dating app fatigue has spawned an unexpected coping mechanism: singles are turning themselves into relationship analysts, armed with spreadsheets, colour-coded rankings, and metrics for everything from kiss quality to conversational humour. According to reporting in Cosmopolitan, women in particular are logging their romantic encounters in Google Sheets, tracking potential partners across variables like appearance, personality traits, red flags, and date outcomes—then using the data to optimise their approach to finding a relationship.
One user identified a pattern of failed connections with matches who lacked humour, leading her to prioritise wit in future interactions. Another developed comparison graphs and slide decks to evaluate prospects, ultimately choosing a partner who scored highest across her weighted metrics. The approach has generated enough commercial interest that Etsy sellers now offer pre-built dating trackers, whilst in January 2025, developer Sampson Ezieme launched Spread, an app purpose-built to log dates, categorise them by red, beige, and green flags, and auto-rank prospects for comparison.
Person analysing data on laptop with spreadsheets
The DII Take
When 78% of dating app users report burnout severe enough to register as emotional, mental, or physical exhaustion, the fact that singles are building their own infrastructure to manage the cognitive load tells you everything about where platforms are falling short.
This isn't quirky Gen Z content fodder—it's a symptom of product failure at scale. The spreadsheet phenomenon shares DNA with the recent surge in traditional matchmaking interest: both represent users trying to offload the labour that apps promised to automate but instead amplified. If your product drives customers to build competitor tooling in Excel, you've got a retention crisis masquerading as a feature gap.
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When swiping becomes project management
The professionalisation of romance reflects what Luke Brunning, co-director of the University of Leeds' Centre for Love, Sex, and Relationships, describes as a blurred line between personal and professional domains. Dating app profiles increasingly resemble CVs, he notes, creating 'lots of work' in the decision-making process. The spreadsheet response simply makes that work visible—and systematic.
Women appear disproportionately drawn to these systems, frequently citing safety concerns, mismatched emotional labour, and the need to manage rejection's psychological toll. Tracking data rather than dwelling on individual outcomes provides emotional distance. Patterns emerge: incompatible communication styles, recurring dealbreakers, the types of profiles that correlate with disappointing interactions. The spreadsheet becomes both analytical tool and psychological buffer.
That gendered dimension matters for operators. If your female user base is experiencing dating as a risk management exercise requiring bespoke tracking systems, your matching algorithms and safety features aren't delivering the cognitive relief you're selling. The effort required to filter, assess, and protect hasn't decreased—it's just migrated from your interface to theirs.
Woman using smartphone dating app
The monetisation question
Commercial interest arrived quickly. Etsy's dating tracker templates offer tabs for flag weighting and preference logging, positioning what was organic user behaviour as purchasable infrastructure. Spread's January launch takes the concept further, packaging the spreadsheet logic into dedicated software that promises to 'take the guesswork out of dating'.
The market validation is instructive. These products exist because dating platforms haven't solved the core problem: too many options, insufficient signal, and no memory layer that helps users learn from past interactions. Match Group (MTCH) and Bumble (BMBL) both invest heavily in AI-powered matching, yet users still feel compelled to build their own decision-support systems outside the app. That gap represents either a product opportunity or evidence that the swipe model itself can't be optimised away from exhaustion.
What platforms haven't provided is pattern recognition that genuinely reduces work. Recommendation engines surface profiles, but they don't help users understand why the last twelve conversations fizzled or which green flags actually correlated with second dates. The spreadsheet users are doing that analysis themselves because the apps won't—or can't.
The quantified self meets the intimacy crisis
This trend shares the philosophical underpinnings of broader quantified self culture: the belief that measurement drives improvement, that data reveals truth, that optimisation applies to everything. Brunning's warning is worth considering: 'At some point, you have to start actually relating to people as human beings, and all the complexity, messiness, and ways in which they likely fall short of your ideals.'
The spreadsheet isn't meant to capture everything; it's meant to impose order on chaos that platforms created but won't manage.
The tension is real. Reducing romantic prospects to weighted scores risks mistaking correlation for causation, confusing what's measurable with what actually matters. A partner who rates highly on predetermined metrics might still lack chemistry; someone who scores poorly on paper might surprise you. Human connection has irreducible elements that resist quantification.
But that critique, however philosophically sound, misses what's driving adoption. These users aren't confused about romance's complexities—they're drowning in abundance without tools to navigate it. The spreadsheet isn't meant to capture everything; it's meant to impose order on chaos that platforms created but won't manage. Whether that order helps or hinders genuine connection is secondary to the immediate need for cognitive relief.
Person reviewing notes and data on desk
The 78% burnout figure suggests this isn't a fringe response. It's emerging infrastructure built by users who've lost faith that the platforms will solve their decision paralysis. Some will spreadsheet their way into relationships—the success stories exist. Others will discover that no amount of data fixes misaligned intentions or bad faith actors. Either way, the behaviour reveals where product gaps have grown wide enough that users are willing to do the engineering themselves.
Operators watching this trend should ask what's missing from their own feature sets. The spreadsheet users aren't failing to engage with dating apps—they're engaging so intensively that they need external tools to process the volume. That's a retention risk dressed up as user dedication. If singles are building relationship CRMs in Google Sheets, perhaps it's time to consider what a native version would look like—or whether the entire match-volume-first model needs rethinking before more users decide the cognitive overhead isn't worth it.
The spreadsheet trend signals a fundamental product failure: dating platforms have created cognitive overload rather than reducing it, forcing users to build their own decision-support infrastructure
Commercial validation through Etsy templates and dedicated apps like Spread reveals an addressable gap in native platform features around pattern recognition and learning from past interactions
Watch whether major operators respond with memory-layer features or whether the match-volume-first model proves incompatible with reducing user burnout—retention will depend on which path they choose
