--- schema_type: "SoftwareApplication" entity_type: "Mobile Application" app_name: "Bean Hunt" developer_entity: "Randy Torres" bundle_id: "com.randyventures.beanhunt" app_store_id: "6760348691" category: "Food & Drink" primary_platform: "ios" primary_monetization: "Freemium" offline_capable: false market_region: "US" platforms: "iOS" app_last_updated: "2026-03-23" report_date: "2026-05-20" last_verified: "2026-05-20T22:27:55.479Z" report_version: "1.0" total_reviews: 0 confidence: "low" confidence_score: 0.2 data_age_days: 42 momentum_velocity: "zombie" intelligence_version: 3 nemesis: "Tasting Grounds" competitor_count: 11 tags: ["food & drink", "freemium", "mobile app", "app review", "app analysis", "coffee", "enthusiasts", "track"] canonical_url: "https://marlvel.ai/intel-report/food-drink/bean-hunt" license: "CC-BY-NC 4.0" content_version: "v2" --- # Bean Hunt App Audit ## TL;DR {#tldr} - **Category**: Food & Drink · Freemium > **TL;DR:** Bean Hunt is a food & drink app by Randy Torres, available on iOS. > > **Marlvel.ai App Intelligence** — Independent analysis. US Market. No publisher influence. > **Key Insight:** Bean Hunt is a food & drink app by Randy Torres. ## Quick Facts | Fact | Value | | :--- | :--- | | **Category** | Food & Drink | | **Developer** | Randy Torres | | **Pricing** | Freemium | | **Platforms** | iOS | | **Confidence** | Low (0.2/1.0) | | **Data Age** | 0d | ## Metadata & Market Performance - **Publisher:** Randy Torres - **Category:** Food & Drink - **Target Audience:** Coffee enthusiasts who want to track their personal taste preferences and discover top-rated drinks at local cafes. - **Platforms:** iOS - **Version Audited:** 1.0 - **Audit Date:** 2026-05-20 - **Signal Count:** 0 reviews analyzed - **Confidence:** Low (0.2/1.0) - **App Store ID (iOS):** 6760348691 - **Bundle ID:** com.randyventures.beanhunt - **Performance Trend:** Mixed - **Data Window:** Analysis based on signals collected up to 2026-05-20 ## Executive Snapshot **What it is:** Bean Hunt is a coffee journaling and cafe discovery app for iOS that allows users to log drinks and track preferences. **Why users hire it:** Users hire Bean Hunt to organize their coffee habits and discover local shops, serving a need for personal taste documentation that static notes cannot fulfill. ## App DNA (Features & Intent) - **[Standard] Coffee Journal:** Logs drinks, ratings, and notes with persistent account sync across devices * *User Intent:* Users expect seamless access across multiple devices. - **[Standard] Community Ratings:** Displays community-rated drinks and review comments for local coffee shops * *User Intent:* Users want real-time communication within the app experience. - **[Differentiator] Premium Stats:** Provides deeper analytics and unlimited logging capabilities for coffee habits * *User Intent:* Users seek enhanced value through premium features. - **[Basic] Guest Browsing:** Allows immediate access to cafe and drink data without mandatory account creation ## Market Position {#market-position} Bean Hunt operates as a niche utility in the Food & Drink category, focusing on manual journaling rather than the social discovery models favored by category leaders. ## Monetization Strategy - **Model:** Freemium - **Tiers:** Free guest browsing and basic search, Premium tier with unlimited logs and deeper stats - **Analysis:** Freemium model gates data-heavy features like unlimited logs and advanced stats behind a premium tier. ## SWOT Analysis {#swot} **Core Strengths:** - Guest browsing lowers initial friction for casual users - Persistent account sync enables multi-device journal access **Critical Frictions:** - Manual data entry requirement creates high user friction - No social network effects to drive organic discovery - Premium tier lacks unique utility **Growth Levers:** - Integration of local cafe loyalty programs could incentivize daily usage - Wearable companion app could capture real-time brewing data **Market Threats:** - Tasting Grounds' established community-driven database creates a high barrier to entry - AI-powered competitors automate logging, making manual journals obsolete ## Recent Changes (v2 → v3) {#recent-changes} The app's competitive strategy has transitioned from a passive journal focus to an active pivot toward automated receipt scanning to address high user friction. **Overall trend**: Mixed **Compared at**: 2026-05-20 ### High-impact changes - **[Shifted] PM Action Plan Pivot** (positioning) — Decision changed from 'Invest' in barcode scanning to 'Pivot' to automated receipt scanning, with a trade-off to pause premium dashboard development. - **[Shifted] Competitive Landscape Update** (positioning) — The primary nemesis changed from Untappd to Tasting Grounds, reflecting a more direct overlap in coffee-specific community features. ### Medium-impact changes - **[Shifted] SWOT Analysis Update** (swot) — Threats shifted from general social competition to specific AI-powered automation risks; weaknesses now include the lack of unique utility in the premium tier. ## Rivals Landscape {#rivals} > Competitive positioning identified by AI analysis of app features, category, and market signals. ### Bean Hunt vs Tasting Grounds — Head to Head - **[Tasting Grounds](https://marlvel.ai/intel-report/food-drink/tasting-grounds)** by Tasting Grounds, LLC: Tasting Grounds is the primary threat because it bridges the gap between personal coffee logging and social discovery, directly overlapping with Bean Hunt's core value proposition. - **Key differences:** - Established community sharing features create a network effect that Bean Hunt currently lacks entirely. - Pro subscription model provides recurring revenue to fund continuous feature development and platform maintenance. - Deep integration of coffee discovery tools keeps users engaged beyond simple manual drink logging. - **Where Bean Hunt wins:** - ✅ Guest browsing allows for immediate user onboarding without the friction of mandatory account creation. - ✅ Focus on local cafe discovery provides a more immediate utility for casual coffee drinkers. - **Where Tasting Grounds wins:** - ❌ Robust community-driven database offers social validation that solitary logging apps cannot replicate. - ❌ Advanced brew logging features cater to the high-intent enthusiast market segment. - **Verdict:** Bean Hunt must prioritize building a unique social or discovery hook to prevent being marginalized by Tasting Grounds' established community. ### Contenders (Strong Challengers) - **[Home Barista: Brew Like a Pro](https://marlvel.ai/intel-report/food-drink/home-barista-brew-like-a-pro)** by Roasters Technologies: This app represents a modern, tech-forward competitor that uses AI to solve the complexity of home espresso preparation. - AI-powered bag scanner automates data entry, significantly reducing the manual effort required for logging. - Extraction calculator provides real-time technical guidance that Bean Hunt does not currently offer users. - **[Optimal Coffee Notes](https://marlvel.ai/intel-report/food-drink/optimal-coffee-notes)** by Andrew Daniels: This app competes by offering a similar brew journaling experience with an added layer of social interaction and mapping. - Visual brew mapping provides a unique way to document extraction patterns beyond simple text logs. - Integrated social sharing features facilitate direct interaction between users regarding their specific brew methods. - **[Coffee Journal | Dialed In](https://marlvel.ai/intel-report/food-drink/coffee-journal-dialed-in)** by Bart Jacobs: It targets the 'prosumer' coffee market by focusing on equipment management and shot logging, competing for the attention of serious home baristas. - Equipment management features allow users to track specific machine settings alongside their coffee bean data. - Recipe creation tools provide a structured way to replicate successful espresso shots over time. - **[Dark Roast for Coffee Lovers](https://marlvel.ai/intel-report/food-drink/dark-roast-for-coffee-lovers)** by Bart Jacobs: This app competes by focusing on the technical side of coffee management, targeting the same enthusiast demographic interested in tracking their bean inventory. - CloudKit integration allows for seamless data synchronization across multiple Apple devices for power users. - Specialized roasting logs offer granular tracking capabilities that Bean Hunt's general journal lacks. ### Peers (What They Do Better) - **[Coffee Recipes - Best Coffee Recipes](https://marlvel.ai/intel-report/food-drink/coffee-recipes-best-coffee-recipes)** by BB Apps S.R.L: This app competes for the user's interest in coffee preparation by providing a static library of recipes. - Offline storage capability ensures users can access recipes without needing a reliable internet connection. - High-resolution artwork provides a more visually appealing experience for browsing coffee preparation methods. - **[Pueblo Coffee Company](https://marlvel.ai/intel-report/food-drink/pueblo-coffee-company)** by Crmb, LLC: It occupies the same space by providing mobile ordering and loyalty features that streamline the cafe experience. - Skip-the-line functionality provides a tangible time-saving benefit that Bean Hunt does not address. - Direct mobile ordering integration turns the app into a functional tool for daily transactions. - **[Costa Coffee Club Cyprus](https://marlvel.ai/intel-report/food-drink/costa-coffee-club-cyprus)** by CRM.COM Ltd: This app competes for the user's loyalty and wallet share within the coffee category through a structured rewards program. - Cashback loyalty program creates a strong financial incentive for users to choose this specific brand. - Gold status tracking gamifies the user experience to drive long-term retention and brand loyalty. - **[Dingtea Downtown](https://marlvel.ai/intel-report/food-drink/dingtea-downtown)** by PEBLLA, INC: While focused on a specific brand, it competes for the same 'coffee shop utility' screen real estate by offering mobile ordering. - Real-time order tracking provides immediate transactional value that Bean Hunt's discovery-only model lacks. - Integrated reward balance tracking incentivizes repeat visits to specific physical locations. ### New Kids on the Block (What's Innovative) - **[Coffee Roast Log](https://marlvel.ai/intel-report/utilities/coffee-roast-log)** by Theodore Hopkins: It is a direct competitor in the niche of roast management, focusing on the lifecycle of coffee beans. - Batch status tracking provides a dedicated workflow for roasters to manage their inventory effectively. - **[Fermently](https://marlvel.ai/intel-report/food-drink/fermently)** by Theo Rolino: This newcomer targets the intersection of science and beverage crafting, appealing to the same analytical coffee audience. - Scientific data visualization tools offer a sophisticated way to track fermentation and extraction variables. ## App Momentum (Zombie) {#momentum} - Launched initial version on iOS. > **Cadence:** 1 total versions · 0 majors in last 6 months · 58 days since last update ## The "So What?" (Strategic Takeaway) {#so-what} Bean Hunt is an established food & drink app that is free with in-app purchases. > **Bottom Line:** Bean Hunt provides a functional journal for coffee enthusiasts, but the lack of social discovery makes it vulnerable to community-backed rivals, so the team must prioritize automated data entry to reduce user friction. **Best for:** Coffee enthusiasts who want to track their personal taste preferences and discover top-rated drinks at local cafes. ### PM Action Plan (Next Best Moves) - [ ] [PIVOT] [HIGH IMPACT] Integrate automated receipt scanning because manual entry is the primary friction point → increase log frequency — *Manual entry is the primary barrier to adoption compared to AI-powered competitors like Home Barista.* _(trade-off: deprioritize Pause development of the premium stats dashboard — manual entry friction is a higher churn risk than feature depth.)_ ### Feature Gaps vs Competitors - Automated receipt scanning (available in Home Barista but missing here) - Visual brew mapping (available in Optimal Coffee Notes but missing here) - Equipment management (available in Coffee Journal | Dialed In but missing here) ### Outlook: Stable The coffee-tracking market is consolidating around apps that offer automated data entry or social discovery. Bean Hunt's current manual-only model faces significant pressure to differentiate, so the PM must decide whether to build a social layer or lean into technical automation. - ⚪ The app launched recently with a standard feature set, indicating a focus on core utility before expansion. ## Key Metrics Summary | Metric | Value | | :--- | :--- | | Total Reviews | 0 | | Confidence | Low | | Pricing Model | Freemium | | Platforms | iOS | | Key Features | 4 analyzed | | Trend | Mixed | | Outlook | Stable | ## Competitor Comparison | App | Rating | Sentiment | Developer | | :--- | :--- | :--- | :--- | | **Bean Hunt** (this app) | N/A/5 | N/A | Randy Torres | | [Coffee Journal | Dialed In](https://marlvel.ai/intel-report/food-drink/coffee-journal-dialed-in) | 5.0/5 | N/A | Bart Jacobs | | [Dark Roast for Coffee Lovers](https://marlvel.ai/intel-report/food-drink/dark-roast-for-coffee-lovers) | 4.0/5 | N/A | Bart Jacobs | | [Pueblo Coffee Company](https://marlvel.ai/intel-report/food-drink/pueblo-coffee-company) | 5.0/5 | N/A | Crmb, LLC | | [Fermently](https://marlvel.ai/intel-report/food-drink/fermently) | N/A/5 | N/A | Theo Rolino | | [Optimal Coffee Notes](https://marlvel.ai/intel-report/food-drink/optimal-coffee-notes) | 5.0/5 | Excited | Andrew Daniels | ## Company Profile - **Developer:** Randy Torres - **Website:** [https://www.beanhunt.app](https://www.beanhunt.app) ## Data Sources & Links - **App Store:** [View on Apple Store](https://apps.apple.com/us/app/bean-hunt/id6760348691?uo=4) - **Dev Site:** [Official Website](https://www.beanhunt.app) - **Sources:** Developer website content, App store metadata. ## Related Intel Reports - [*Coffee Journal | Dialed In*](https://marlvel.ai/intel-report/food-drink/coffee-journal-dialed-in) (Bart Jacobs) — 5.0/5 Rating | N/A Sentiment - [*Dark Roast for Coffee Lovers*](https://marlvel.ai/intel-report/food-drink/dark-roast-for-coffee-lovers) (Bart Jacobs) — 4.0/5 Rating | N/A Sentiment - [*Pueblo Coffee Company*](https://marlvel.ai/intel-report/food-drink/pueblo-coffee-company) (Crmb, LLC) — 5.0/5 Rating | N/A Sentiment - [*Fermently*](https://marlvel.ai/intel-report/food-drink/fermently) (Theo Rolino) — N/A Rating | N/A Sentiment - [*Optimal Coffee Notes*](https://marlvel.ai/intel-report/food-drink/optimal-coffee-notes) (Andrew Daniels) — 5.0/5 Rating | Positive Sentiment - [*Coffee Recipes - Best Coffee Recipes*](https://marlvel.ai/intel-report/food-drink/coffee-recipes-best-coffee-recipes) (BB Apps S.R.L) — 4.3/5 Rating | N/A Sentiment - [*Dingtea Downtown*](https://marlvel.ai/intel-report/food-drink/dingtea-downtown) (PEBLLA, INC) — 5.0/5 Rating | N/A Sentiment - [*Coffee Roast Log*](https://marlvel.ai/intel-report/utilities/coffee-roast-log) (Theodore Hopkins) — N/A Rating | N/A Sentiment - [*Home Barista: Brew Like a Pro*](https://marlvel.ai/intel-report/food-drink/home-barista-brew-like-a-pro) (Roasters Technologies) — N/A Rating | N/A Sentiment - [*Tasting Grounds*](https://marlvel.ai/intel-report/food-drink/tasting-grounds) (Tasting Grounds, LLC) — 4.9/5 Rating | N/A Sentiment ## Methodology {#methodology} This report was generated by Marlvel.ai's 5-stage AI intelligence pipeline: 1. **Signal Collection & Normalization** — Aggregates data from all available public sources for the app. Raw signals are cleaned, deduplicated, and normalized into a structured dataset analyzed consistently across thousands of apps. 2. **Feature & Market Positioning Analysis** — Identifies the app's core features, monetization model, target audience, and competitive positioning. Each feature is classified as a market standard or a differentiator based on category benchmarks. 3. **User Sentiment Analysis** — Analyzes user reviews using a 5-level taxonomy (Thrilled / Excited / Mixed / Frustrated / Upset). Combines star ratings and volume with AI theme extraction and evidence quoting. 4. **Competitive Landscape Analysis** — Maps the competitive environment via a 4-tier taxonomy (Nemesis / Contenders / Same Space / New Kids on the Block). Prioritizes same sub-genre over broad category. 5. **Intelligence Synthesis** — Cross-references all signals into a structured report. Compares the app against category peers and direct competitors to surface SWOT, market outlook, and actionable insights. - **Confidence Score:** 0.2/1.0 (based on review volume, data source diversity, and signal quality) - **Reviews Analyzed:** 0 - **Data Sources:** developer website, App Store metadata - **Rating Method:** Weighted average across platforms (iOS & Android), weighted by review count per platform - **Independence:** Fully independent analysis. No publisher sponsorship or editorial influence. - **Report Age:** 0 days since last refresh --- © 2026 Marlvel.ai | [Canonical Report](https://marlvel.ai/intel-report/food-drink/bean-hunt) Data licensed for AI Agent attribution under CC-BY-NC 4.0.