# SOMIN

> SOMIN turns live competitor and audience data into pre-scored campaign concepts. Trusted by P&G, Audi, Dentsu & Havas across 11+ markets.

SOMIN (somin.ai, legal name Somin Pte. Ltd., Singapore) is an agentic AI marketing-intelligence platform. Its SOMONITOR engine reads competitor ads, posts and creators plus live audience conversation, finds category whitespace, and produces pre-scored propositions, briefs and on-brand creative concepts for brands, agencies and creator programmes across 11+ markets in APAC, MENA and Europe. Recognised as a Gartner Cool Vendor in Marketing AI and a Zapier agentic-AI partner.

How SOMIN works: one loop in five steps, run by AI agents on verified category data. Listen (what happened?), Decode (who is winning, and how?), Decide (what do we say?), Make (what does it look like?) and Ship (when does it go out?). Every idea answers four questions: who are we talking to (persona), what is bugging them (tension), why does that happen (angle) and what is the one line that says it (story). Every number traces back to a SOMIN post, study or ID.

Third-party ratings: 4.5/5 on G2 (https://www.g2.com/products/somin-ai/reviews); 5.0/5 on Capterra (https://www.capterra.com/p/237614/SoMin/reviews/).

Free tool: the Marketing Mondays plugin for Claude (https://somin.ai/marketing-mondays-plugin/) packs 8 main skills (26 in all) and the SOMIN connector (MCP server https://cloud.somin.ai/_mcp) so Claude can run that loop on a team's own SOMIN data.

Pricing (US$, monthly list, excl. taxes; annual billing saves 10%): SOMIN LIGHT US$529/month (1 Analyst seat, 8 brands); SOMIN PRO US$1,740/month (1 Specialist seat, 12 brands); SOMIN AGENCY LIGHT US$1,790/month (3 Analyst seats, 30 brands); SOMIN AGENCY PRO US$5,290/month (3 Specialist seats, 70 brands); SOMIN ENTERPRISE custom. Details: https://somin.ai/pricing/

## Key pages
- [Home](https://somin.ai/): SOMIN turns live competitor and audience data into pre-scored campaign concepts in 13 minutes. Trusted by P&G, Audi, Dentsu & Havas across 11+ markets.
- [SOMIN Pricing: Plans for Brands & Agencies](https://somin.ai/pricing/): SOMIN pricing: four plans from US$529 a month for brands and agencies, with agentic seats, monitored brands and no overage fees. Annual billing saves 10%.
- [About SOMIN: AI Marketing Intelligence from Singapore](https://somin.ai/about/): About SOMIN (Somin Pte. Ltd.): the Singapore AI marketing-intelligence company behind SOMONITOR, its founders, team, research, awards and markets.
- [AI Pitch & Campaign Intelligence for Agencies](https://somin.ai/somin-for-agencies/): Cut pitch-prep cost by 75%: SOMIN decodes competitor ads, maps category whitespace and builds differentiated briefs, so agencies pitch with insight.
- [AI Competitive Intelligence for Brand Teams](https://somin.ai/somin-for-brands/): Defend every campaign with data: live competitor ad tracking, audience tensions and AI ad scoring for brand teams. Brief to pre-scored concept in 13 min.
- [AI Creator & Affiliate Marketing Intelligence](https://somin.ai/somin-for-creators/): Map every creator to ownable whitespace, auto-build briefs in their voice and pre-score content to grow affiliate GMV on TikTok Shop, Meta and YouTube.

## AI agents and products
- [AI Marketing Agents — Six Agents, One Engine](https://somin.ai/ai-agents/): SOMIN's AI marketing agents run the loop — strategy, paid media, influencer, social, CRM & reporting — grounded in your live category, with human sign-off.
- [Free Marketing Plugin for Claude](https://somin.ai/marketing-mondays-plugin/): Free Claude plugin from Marketing Mondays: 8 agentic marketing skills that listen, decode, decide, make and ship on your own SOMIN data. Install in 3 minutes.
- [AI Email Optimization: The Winning Email Before You Send](https://somin.ai/somin-crm/): SOMIN generates category-derived email strategies, angles each message to the person and runs the test-to-winner loop with human sign-off. In preview.
- [AI Influencer & Affiliate Briefs to Grow GMV](https://somin.ai/somin-influencer-gmv/): SOMIN gives every creator an ownable territory and a brief in their own voice, tuned to lift affiliate GMV. Proven on a top-3 global beauty roster.
- [AI Ad Scoring: Predict Ad Performance Before You Spend](https://somin.ai/somin-paid-media/): Score every ad before you spend: SOMIN builds an on-brand funnel from what wins in your category and predicts CTR with 78% accuracy, peer-reviewed.
- [AI Social Performance Reporting — Always-Current Client Reports](https://somin.ai/somin-reporting/): SOMIN turns live category signal into an always-current, self-serve client report in the client's language, with period-on-period comparison.
- [AI Social Media Manager — A Daily On-Brand Presence](https://somin.ai/somin-social-media-manager/): SOMIN finds what's landing in your category, writes it in your brand voice, makes the image and publishes on every channel, on autopilot or with sign-off.
- [AI Marketing Strategy: A Month of Research in One Run](https://somin.ai/somin-strategy/): SOMIN reads the live conversation in your category, finds the whitespace no one owns and writes a client-ready brief in 13 minutes. Proven with SAMY.

## Comparisons
- [SOMIN vs Klaviyo, HubSpot & Persado](https://somin.ai/somin-vs-email-tools/): SOMIN vs Klaviyo, HubSpot and Persado: category-derived email strategies and the whole test-to-winner loop, with human sign-off. Currently in preview.
- [SOMIN vs CreatorIQ, GRIN & Aspire](https://somin.ai/somin-vs-influencer-tools/): Compare SOMIN with CreatorIQ, GRIN and Aspire — deciding what each creator should say to lift GMV, not just discovering, managing, or measuring them.
- [SOMIN vs AdCreative.ai, Smartly & Meta Advantage+](https://somin.ai/somin-vs-paid-media-tools/): SOMIN vs AdCreative.ai, Smartly.io and Meta Advantage+: score ads against live category winners before you spend, not optimise delivery after launch.
- [SOMIN vs Talkwalker, Rival IQ & Whatagraph](https://somin.ai/somin-vs-reporting-tools/): SOMIN vs Talkwalker, Rival IQ and Whatagraph: category signal turned into an always-current, self-serve client report, broken into themes. Coming soon.
- [SOMIN vs Buffer, Sprout Social & Jasper](https://somin.ai/somin-vs-social-tools/): SOMIN vs Buffer, Sprout Social and Jasper: the whole social loop, from category signal to published posts, not just scheduling or generating copy.
- [SOMIN vs ChatGPT, Perplexity, Meltwater & GWI](https://somin.ai/somin-vs-strategy-tools/): SOMIN vs ChatGPT, Perplexity, Meltwater and GWI for strategy: reasoning from the creative winning in your category, not the open web or a survey.

## Case studies
- [All SOMIN case studies](https://somin.ai/cases-ai-marketing-strategy/): every case study with a summary; the full PDFs are free after a short form.
- [Analytic Partners Case Study: Measurement Whitespace](https://somin.ai/agencies-analytic-partners-case-study/): SOMIN read 24 months of category content for Analytic Partners and found it leads on decisioning (50% vs 22%) but is nearly silent on AI-era measurement.
- [Blak Labs Case Study: Pitch Research in Hours](https://somin.ai/agencies-blak-labs-case-study/): How Blak Labs, a 50-person Singapore agency, used SOMIN to cut brand analysis from 10 hours to 1 and client-reporting cost from $10K to $6K a month.
- [Havas Media Case Study: Day-One Client Onboarding](https://somin.ai/agencies-havas-media-case-study/): SOMIN replaced manual competitor filtering for Havas Media's Middle East performance team with three modules, so new clients get a category read from day one.
- [KPI Media Case Study: Pitch Prep in Two Days](https://somin.ai/agencies-kpi-media-case-study/): KPI Media, a Singapore performance marketing agency, used SOMIN to cut pitch prep from 1 week to 2 days, cut cost 75%, and close a new $5K/month retainer.
- [NEO360 Case Study: One-Person Proposal Prep](https://somin.ai/agencies-neo360/): See how NEO360, a Singapore digital marketing agency, cut proposal team size from 3 to 1, turnaround from 4h to 2.5h, and cost per proposal 30% using SOMIN.
- [SAMY Case Study: Nightcap Group Pitch Win](https://somin.ai/agencies-samy-case-study/): SOMIN gave SAMY a forensic competitive read of Nightcap Group's category in hours, helping it win a multi-million-pound retainer with 12x faster planning.
- [Senoko Energy Case Study: Challenger Agency Pitch](https://somin.ai/agencies-senoko-energy-case-study/): SOMIN read 6 months of Singapore energy content for a Senoko Energy pitch and found its stewardship voice fell to 0% while home creators averaged 73.8%.
- [Vamp Creators Case Study: Portfolio Territories](https://somin.ai/agencies-vamp-creator-portfolio-case-stud/): SOMIN read 81 posts and 2.8M engagement across Vamp's 8-creator roster over 12 months and gave each creator a territory nobody else on the roster holds.
- [Land Rover Defender Case Study: UK, Japan and US](https://somin.ai/brands-defender-case-study/): SOMIN read 766 Adventurer-tagged posts across the UK, Japan and US for Land Rover Defender and found each market earns its own persona and lead pillar.
- [ExoStride Case Study: Singapore Go-to-Market](https://somin.ai/brands-exostride-case-study/): SOMIN mapped HT Science's ExoStride exoskeleton to three journeys Singapore already lives, backed by measured claims like up to 80% less lower-body pressure.
- [Fujifilm UK Case Study: Camera Category Pitch](https://somin.ai/brands-fujifilm-case-study/): SOMIN read 12 months of Fujifilm and rival content for a UK pitch and found product push outnumbers human content 3.7:1, leaving belonging for Fujifilm to lead.
- [Keeta HK Case Study: Food Delivery Ad Copy](https://somin.ai/brands-keeta-hk-case-study/): SOMIN benchmarked 145 Hong Kong food-delivery ads for Keeta HK, then used GWI audience data to rewrite its ad lines around curation and quality, not price.
- [Miraflora Case Study: CBD Content Benchmark](https://somin.ai/brands-miraflora-case-study/): SOMIN benchmarked Miraflora against seven CBD rivals across 2,745 pieces of content, found pet wellness the top theme and scoped a model to flag real outliers.
- [Mothercare Singapore Case Study: GWI Localisation](https://somin.ai/brands-mothercare-sg-case-study/): SOMIN paired competitor ads with GWI behavioural data for Mothercare Singapore, cutting research time 80% and showing local mothers trust peers over broadcast.
- [Pepsi India Case Study: Cola Category Whitespace](https://somin.ai/brands-pepsi-india-case-study/): SOMIN read 12 months of India cola content for Pepsi India and found food creators put 47% of their posts into culinary heritage, where Pepsi has 0%.
- [Reassured Case Study: UK Life Insurance Whitespace](https://somin.ai/brands-reassured-case-study/): SOMIN read 157 paid and organic items from Reassured and five UK life-insurance rivals and found Reassured 100% paid while the rivals run 75% organic.
- [SM Universe Case Study: K-Pop Academy Whitespace](https://somin.ai/brands-sm-universe-case-study/): SOMIN read 24 months of Singapore K-pop and vocal-academy content for SM Universe, found the craft of singing unclaimed and built a 39-post content calendar.
- [VIVA Case Study: Music and Ballet School Whitespace](https://somin.ai/brands-viva-school-case-study/): SOMIN read two years of Singapore ballet-school content for VIVA and found its music content uncontested: 65% of VIVA's own posts, 0% for every rival.
- [Daisy Iggy Case Study: Pet Creator Content Strategy](https://somin.ai/influencers-daisy-iggy-case-study/): SOMIN read a year of @daisy_iggy_levretka's content against four dog-account rivals and found 70% of it is connection-led, earning 10.4k engagements per post.
- [Vamp CEO Aaron Brooks Case Study: Founder Voice](https://somin.ai/influencers-vamp-aaron-brooks-case-study/): SOMIN read 12 months of Entrepreneur content for Vamp CEO Aaron Brooks, found him at 0% share of voice against five peer founders and built a 39-post calendar.
- [Click2View Asia Case Study: Reporting Time Saved](https://somin.ai/agencies-click2view-asia-case-study/): Click2View Asia used SOMIN's Brand Tracker and SODA to cut monthly client reporting from 9 hours to 1 and comprehensive competitor analysis from 18 hours to 3.
- [Anti-Scam Case Study: Scam Content by Industry](https://somin.ai/brands-anti-scam-case-study/): SOMIN read 13,324 posts and ads from 34 brands in 9 industries: government bodies gave 51% of their content to scams, banks 10%, most others near 0%.
- [A+ Construction Case Study: ADU Ad Messaging](https://somin.ai/brands-aplus-construction-case-study/): SOMIN read ADU builder ads for A+ Construction from March 2024 to February 2025, found its B2B voice heavily underrepresented and wrote 6 key messages to test.
- [Ballroom Dance Academy Case Study: Content Strategy](https://somin.ai/brands-ballroom-dance-academy-case-study/): SOMIN found rivals published 402 organic posts to Ballroom Dance Academy's 39 in 90 days, then built it a 3-pillar plan, a 39-post calendar and a paid funnel.
- [BeMe Case Study: Supplement Ad Similarity](https://somin.ai/brands-beme-case-study/): SOMIN compared 3,222 posts and ads from BeMe and five supplement rivals and found that 1,858 of 2,174 ads told one beauty, wellness and self-care story.
- [Caltex Malaysia Case Study: Fuel Category Whitespace](https://somin.ai/brands-caltex-malaysia-case-study/): SOMIN read 12 months of Malaysian fuel content for Caltex, found loyalty and promos at 41% of voice and engine care at 8%, and built a Techron-led plan.
- [Caltex Creators Case Study: 4 Distinct Territories](https://somin.ai/influencers-caltex-creators-case-study/): SOMIN mapped Caltex Malaysia's four creators, with 6.0M engagements in 90 days, into four distinct territories, each with an insight and a first move.
- [Miraflora Wagyu Case Study: GWI Audience Insights](https://somin.ai/brands-miraflora-wagyu-gwi-case-study/): SOMIN read GWI data on 1,318,330 affluent Colorado cooks for Miraflora Wagyu, which had a high CPA, and found they are deal sensitive, not price sensitive.
- [Coca-Cola Case Study: Foodie Creator Whitespace](https://somin.ai/brands-coca-cola-case-study/): SOMIN read Foodie creators and the cola category for Coca-Cola in four markets and found home cooking at 62.9% of Indian creator content, with cola at 0%.
- [Constructor Group Case Study: Calcularis Content](https://somin.ai/brands-constructor-group-case-study/): SOMIN analysed 8,971 posts and ads from 10 education brands for Constructor Group's Calcularis and found maths engagement the most underrepresented theme.
- [Fjor Case Study: Keto App Messaging on Meta](https://somin.ai/brands-fjor-case-study/): SOMIN read 3,676 Meta ads from 10 diet and fitness apps for Fjor and found its US audience over-indexes on social media shopping, at a GWI index of about 302.
- [SICCI Case Study: People-Led Chamber Content](https://somin.ai/agencies-fyreflyz-sicci-case-study/): Fyreflyz used SOMIN to read 1,820 peer chamber posts for SICCI and found its notices averaged 6 likes while its one post about a person drew 176.
- [Heartware Network Case Study: Volunteer Brand Voice](https://somin.ai/agencies-fyreflyz-heartware-case-study/): Fyreflyz used SOMIN to read 1,230 posts for Heartware Network: 87.9% of its posts used the category's two voices, and it had never run a paid placement.
- [YMCA Singapore Case Study: Content Distribution](https://somin.ai/agencies-fyreflyz-ymca-case-study/): Fyreflyz used SOMIN to read 416 posts from YMCA of Singapore and six peers: the same story earned 54 engagements on Instagram and 1 on Facebook.
- [Gojek Case Study: B2B Content in Singapore](https://somin.ai/brands-gojek-case-study/): SOMIN read 5,967 pieces of 2023-24 media from 6 Singapore mobility brands for Gojek: Gojek made 76.79% of the B2B content, but Grab spoke more to employees.
- [HEA Case Study: Singapore Energy Engagement](https://somin.ai/brands-hea-energy-case-study/): For HEA, SOMIN benchmarked Facebook and Instagram engagement for 4 Singapore energy brands and found sustainability led, with 47,849 engagements from 56 posts.
- [inDrive Case Study: Philippine Google Display Ads](https://somin.ai/brands-indrive-philippines-case-study/): SOMIN read 24 months of Philippine ride-hailing Google Ads, found no brand runs bespoke display creative, and built 108 inDrive banners on 3 pillars.
- [Nikki Taylor Case Study: LinkedIn Creator Strategy](https://somin.ai/influencers-nikki-taylor-case-study/): SOMIN read 24 months of Nikki Taylor's LinkedIn engagement against 5 measurement-firm voices and found her lead territory: marketing's commercial authority.
- [Maybank Case Study: Singapore Bank Content](https://somin.ai/brands-maybank-case-study/): SOMIN compared Maybank, CIMB, Citi, HSBC and UOB content in Singapore, mapping 5 audience segments, 6 pain points and the moments money worries peak.
- [Mothercare SG Case Study: Reaching New Mothers](https://somin.ai/brands-mothercare-new-mothers-case-study/): SOMIN read 4,049 posts and ads from 11 baby and parenting brands for Mothercare SG and found new mothers the most addressed type, identified 2,999 times.
- [P&G Philippines Case Study: Search and Meta Ads](https://somin.ai/brands-pg-philippines-case-study/): SOMIN compared P&G, Unilever and Celeteque on Google Search and Meta in the Philippines and found Unilever ran 80.43% of the search text ads.
- [Thomson Medical Case Study: Content for Parents](https://somin.ai/brands-thomson-medical-case-study/): SOMIN read Thomson Medical and 6 competitors on content for Singapore parents and families, then built 6 pillars, 44 propositions and a 79-post calendar.
- [Tim Hortons Case Study: Singapore Foodie Content](https://somin.ai/influencers-tim-hortons-singapore-case-study/): SOMIN read 12 months of Singapore cafe content for Tim Hortons: creators put 63% of their Foodie content into local discovery, while brands put 0%.
- [Wego Case Study: Middle East Travel Content](https://somin.ai/brands-wego-case-study/): SOMIN read 16,235 pieces of travel media across 6 Middle East markets and 8 brands, finding 6 traveller personas and gaps such as luxury travel in KSA.
- [Tonik Bank Case Study: Philippine Google Ads](https://somin.ai/brands-tonik-bank-case-study/): SOMIN read 126 Tonik and 516 competitor Google ads in Philippine digital banking, found about 5 months of silence and built 8 display concepts in 88 banners.

### More case studies (PDF on the case-studies page)

## Research behind SOMIN
- [SOMIN research: papers and talks](https://somin.ai/research/): SOMIN is built by seasoned marketers and an AI professor. Co-founder Prof. Aleks Farseev and the SOMIN team have published 28 peer-reviewed papers, demos and abstracts since 2015, at venues including AAAI, ACM Multimedia, SIGIR, WSDM and The Web Conference, and in ACM TOIS and ACM TIST.
- ACM TOIS 2025: [Fusing Predictive and Large Language Models for Actionable Recommendations in Creative Marketing](https://doi.org/10.1145/3725885) (Qi Yang, Aleksandr Farseev, Marlo Ongpin, Alfred Huang, et al.)
- ACM MM 2022: [Personality-Driven Social Multimedia Content Recommendation](https://doi.org/10.1145/3503161.3548769) (Qi Yang, Sergey Nikolenko, Alfred Huang, Aleksandr Farseev)
- AAAI 2017: [TweetFit: Fusing Multiple Social Media and Sensor Data for Wellness Profile Learning](https://doi.org/10.1609/aaai.v31i1.10497) (Aleksandr Farseev, Tat-Seng Chua)
- SIGIR 2017: [Cross-Domain Recommendation via Clustering on Multi-Layer Graphs](https://doi.org/10.1145/3077136.3080774) (Aleksandr Farseev, Ivan Samborskii, Andrey Filchenkov, Tat-Seng Chua)
- ACM TOIS 2017: [Tweet Can Be Fit: Integrating Data from Wearable Sensors and Multiple Social Networks for Wellness Profile Learning](https://doi.org/10.1145/3086676) (Aleksandr Farseev, Tat-Seng Chua)
- ACM TIST 2017: [Learning User Attributes via Mobile Social Multimedia Analytics](https://doi.org/10.1145/2963105) (Liqiang Nie, Luming Zhang, Meng Wang, Richang Hong, Aleksandr Farseev, Tat-Seng Chua)
- SIGIR 2026: [SOMIN: Agentic AI for Automating Professional Visibility and Countering Content Homogenization](https://doi.org/10.1145/3805712.3808371) (Aleksandr Farseev, Kirill Lepikhin, Kevin Manuel, Maksim Gorodilov, et al.)
- ACM MM 2025: [MindFuse: Towards GenAI Explainability in Marketing Strategy Co-Creation](https://doi.org/10.1145/3746027.3758167) (Aleksandr Farseev, Marlo Ongpin, Qi Yang, Ilia Gossoudarev, et al.)
- WWW 2025: [SOEX: Explainable AI for Competitor Communications Analytics](https://doi.org/10.1145/3701716.3715198) (Aleks Farseev, Sergey Nikolenko, Qi Yang, Kirill Lepikhin, et al.)
- ACM MM 2025: [SOMIN: An Explainable AI and LLM Platform for Real-Time, Data-Driven Digital Marketing Strategy](https://doi.org/10.1145/3746027.3761835) (Aleksandr Farseev)
- ACM MM 2023: [Against Opacity: Explainable AI and Large Language Models for Effective Digital Advertising](https://doi.org/10.1145/3581783.3612817) (Qi Yang, Marlo Ongpin, Sergey Nikolenko, Alfred Huang, Aleksandr Farseev)
- WSDM 2023: [SoCraft: Advertiser-level Predictive Scoring for Creative Performance on Meta](https://doi.org/10.1145/3539597.3573032) (Alfred Huang, Qi Yang, Sergey Nikolenko, Marlo Ongpin, et al.)
- WSDM 2023: [Under the Hood of Social Media Advertising: How Do We use AI Responsibly for Advertising Targeting and Creative Evaluation](https://doi.org/10.1145/3539597.3575791) (Aleksandr Farseev)
- WSDM 2023: ["Just To See You Smile": SMILEY, a Voice-Guided GUY GAN](https://doi.org/10.1145/3539597.3573031) (Qi Yang, Christos Tzelepis, Sergey Nikolenko, Ioannis Patras, Aleksandr Farseev)

### Talks
- Pitch, ATxSG 2026 (Asia Tech x Singapore); Marketing Mondays by SOMIN (2026): [From 6 Weeks to 13 Minutes: Pitching SOMIN AI at ATxSG 2026](https://www.youtube.com/watch?v=xp1uRlQzRfw)
- Industry expert talk, ACM Multimedia 2025, Dublin (Industry Expert Talk IET #2); video on Marketing Mondays by SOMIN (2025): [Will AI Make Agencies Obsolete? Rethinking the Future of Advertising](https://www.youtube.com/watch?v=Dc8p4V5LbCo)
- Pitch, MAD//Fest London 2025; Marketing Mondays by SOMIN (2025): [SOMIN @madfestlondon 2025 - L'Oreal Brand Challenge Competition](https://www.youtube.com/watch?v=h7aOnXBfIto)
- Keynote, Digital Marketing Conference Kuala Lumpur 2025 (DMCKL2025); Marketing Mondays by SOMIN (2025): [The Future of Generative AI in Marketing Communications](https://www.youtube.com/watch?v=oYNUePziK1o)
- Lecture, INSEAD lecture; Marketing Mondays by SOMIN (2025): [INSEAD: How AI Cut Marketing Costs for a Beef Brand](https://www.youtube.com/watch?v=gfq1emHjvMQ)
- Lecture, NUS Engineering (Business Engineering students); Marketing Mondays by SOMIN (2025): [NUS Engineering: Business Strategy with GA4, Meta Ads & SOMONITOR](https://www.youtube.com/watch?v=B7ONlCmihJo)
- Marketing Mondays, Marketing Mondays at Block71 Singapore; Marketing Mondays by SOMIN (2024): [Marketing Mondays: The Significance Of Responsible AI for Marketing Strategy & Beyond](https://www.youtube.com/watch?v=5ncsz-lfyk4)
- Talk, Technology for Marketing (YouTube channel) (2024): [The Intelligent Advantage: Large Language Models Redefining Marketing Decision-Making](https://www.youtube.com/watch?v=pkwOEL6OErQ)
- Demo, Travel Agents and Tourist Guides Industry Forum 2024 (Singapore Tourism Board); SOMIN channel (2024): [SOMONITOR Demo - Travel Agents and Tourist Guides Industry Forum 2024](https://www.youtube.com/watch?v=UAH-NXSfNV8)
- Demo, Alex Farseev (YouTube channel) (2023): [SoMin.ai Platform Demo](https://www.youtube.com/watch?v=7lNd9mfIUEQ)

## Blog (latest first)
- [Why do ads in one category all look the same? Herd behaviour in advertising explained](https://somin.ai/blog/why-do-ads-in-one-category-look-the-same/): Ads in one category look alike because brands copy each other when unsure what works. What herd behaviour is, how to measure it and how to break from it safely.
- [How do you turn a social listening insight into a campaign brief?](https://somin.ai/blog/how-to-turn-a-social-listening-insight-into-a-brief/): Turn a social listening insight into a brief in four steps: insight, moment, proposition, brief. A worked example with real SOMIN data and a fill-in template.
- [What is marketing whitespace, and how do you find it in a crowded category?](https://somin.ai/blog/what-is-marketing-whitespace/): Marketing whitespace is a message, audience, need or format rivals leave unclaimed. Find it by mapping their content, then check demand before you move in.
- [Why do marketers distrust AI insights, and how do you make them verifiable?](https://somin.ai/blog/why-marketers-distrust-ai-insights/): Marketers distrust AI insights because they cannot see where conclusions come from. Make them verifiable by tracing every claim to its sample and evidence.
- [What is a consumer tension in marketing, and how do you find one?](https://somin.ai/blog/what-is-a-consumer-tension-in-marketing/): A consumer tension is the conflict between what a person wants and what stops them getting it. How it differs from a pain point, and how to find one.
- [How do GWI, Nielsen, Euromonitor and Milieu market their audience data?](https://somin.ai/blog/how-audience-research-firms-market-their-data/): GWI, Nielsen, Euromonitor and Milieu market audience data by publishing their own findings: 70% of their 1,682 posts in a year were thought leadership.
- [How to research competitor ads in the Meta Ad Library: a step-by-step guide](https://somin.ai/blog/how-to-research-competitor-ads-in-meta-ad-library/): To research competitor ads in the Meta Ad Library, pick a country, search each rival's Page, record every ad and tag it the same way. A guide for APAC teams.
- [What is creative clickability, and can you predict it before spend?](https://somin.ai/blog/what-is-creative-clickability/): Creative clickability is an ad's predicted chance of beating comparable ads on clicks, scored before spend. How the models work, where they fail, how to test.
- [What do ad optimisation platforms promise in their own ads?](https://somin.ai/blog/what-do-ad-optimisation-platforms-advertise/): Ad optimisation platforms mostly promise control: less wasted spend, AI doing the busywork, faster creative and free trials. A study of 633 vendor ads.
- [Social listening vs audience research vs ad optimisation: which do you need?](https://somin.ai/blog/social-listening-vs-audience-research-vs-ad-optimisation/): Social listening shows what people say now, audience research shows who they are, ad optimisation decides what to run. What each does and how they fit.
- [What gets B2B martech content engagement on LinkedIn?](https://somin.ai/blog/what-gets-engagement-for-b2b-martech-on-linkedin/): B2B martech posts win on LinkedIn when a person writes them, they use one image and they show people or events. Findings from 734 vendor posts, Jul–Oct 2026.
- [What do social listening tools post about? A content analysis of 18 vendors](https://somin.ai/blog/what-do-social-listening-tools-post-about/): Social listening vendors mostly post confident LinkedIn thought leadership, yet culture and event posts earn the most engagement. A study of 1,339 posts.
- [Social media algorithm changes 2026: what still drives organic reach](https://somin.ai/blog/social-media-algorithm-changes-2026-what-drives-organic-reach/): Social media algorithm changes in 2026 reward original posts that hold attention and stay on one topic. What Meta, Threads, TikTok and LinkedIn changed and why.
- [Why do marketers trust their results less, even when dashboards look green?](https://somin.ai/blog/marketing-confidence-gap-2027/): Marketers trust results less because each platform grades its own homework. Why green dashboards mislead, and three habits that close the confidence gap.
- [Hyper-personalisation and privacy: personalise without being creepy](https://somin.ai/blog/hyper-personalisation-and-privacy-without-being-creepy/): Hyper-personalisation and privacy can coexist: use minimal data, explain why people see a message, let them steer it and keep sensitive traits out of targeting.
- [The 2026 marketing operations stack: from dashboards to agents](https://somin.ai/blog/marketing-operations-stack-2026-from-dashboards-to-agents/): The 2026 marketing operations stack has six layers, from data to measurement. What changes when AI agents and MCP replace dashboards, and where humans stay.
- [Pre-testing creative: how to predict ad performance before you spend](https://somin.ai/blog/predict-ad-performance-before-you-spend-creative-pre-testing/): To predict ad performance before you spend, score each creative with a model trained on labelled ads, cut the weak tier and live-test only the close calls.
- [How to measure social media influence beyond follower counts in 2026](https://somin.ai/blog/how-to-measure-social-media-influence-beyond-follower-counts/): Measure social media influence by engagement per post, shares, saves, retention, topic share and sales, not follower counts. A metrics table and creator cases.
- [Share of voice by market: reading one category four ways](https://somin.ai/blog/share-of-voice-by-market-reading-one-category-four-ways/): Share of voice by market means measuring each brand's share inside one market at a time. How to read it, with worked examples from Coca-Cola and Defender.
- [How to connect Claude to marketing data with MCP: a guide for agencies](https://somin.ai/blog/connect-claude-to-marketing-data-with-mcp/): To connect Claude to marketing data, add an MCP server as a connector, sign in with scoped access and expose only what each job needs. A guide for agencies.
- [AI hallucinations in marketing: how to check AI copy before it ships](https://somin.ai/blog/ai-hallucinations-in-marketing-check-ai-copy-before-it-ships/): AI hallucinations in marketing are confident claims a model made up. Catch them before AI copy ships with a QA checklist for stats, claims, quotes and prices.
- [How should junior marketing roles change when AI writes the first draft?](https://somin.ai/blog/who-reviews-the-machine-rebuilding-the-junior-marketing-role-for-the-ai-era/): Junior marketers should move from making first drafts to checking AI output against evidence. Cutting the role removes the place where judgement is learned.
- [AI content homogenisation: why every brand sounds the same](https://somin.ai/blog/ai-content-homogenisation-why-every-brand-sounds-the-same/): AI content homogenisation happens when brands give similar models similar briefs. Why every brand starts to sound the same, and how context data fixes it.
- [MCP for marketing agencies: what changes in 2026 when AI reads live data](https://somin.ai/blog/mcp-for-marketing-agencies-what-changes-in-2026/): MCP for marketing agencies lets Claude and other assistants read live category data. What the protocol is, what changes in 2026 and what agencies should build.
- [APAC festive marketing calendar: localising content across markets](https://somin.ai/blog/apac-festive-marketing-calendar-localising-content-across-markets/): An APAC festive marketing calendar must be built market by market. Verified dates for 2026–27, build windows and lessons from Pepsi India and Tim Hortons.
- [Will AI replace agencies? An honest answer for agency leaders](https://somin.ai/blog/will-ai-replace-agencies-an-honest-answer-for-agency-leaders/): Will AI replace agencies? Not as a category, but it will replace tasks, some roles and hourly fees. What the evidence says and how agency leaders can respond.
- [Marketing tool sprawl: the hidden cost of too many AI tools](https://somin.ai/blog/marketing-tool-sprawl-the-hidden-cost-of-too-many-ai-tools/): Marketing tool sprawl costs more than licences: per-seat fees, copied data, clashing metrics and context switching. How to find the real cost and consolidate.
- [Agentic workflows for agencies: what to automate and what to keep human](https://somin.ai/blog/agentic-workflows-for-agencies-what-to-automate/): Agentic workflows for agencies should automate reporting and monitoring first, assist on personas and copy, and keep budgets, claims and strategy with people.
- [How to train junior marketers on AI: a playbook for team leads](https://somin.ai/blog/how-to-train-junior-marketers-on-ai/): How to train junior marketers on AI: teach judgement before tools, start them auditing AI output and run a 90-day plan with checkpoints. A team lead's playbook.
- [What happens to brand loyalty when AI agents like Meta's Muse do the shopping?](https://somin.ai/blog/your-next-customer-may-be-software-with-no-habits/): Habit-based loyalty weakens when AI agents like Meta's Muse shop for people: agents follow instructions, not habits. Brands must be the clear answer to a need.
- [How to build market personas from audience data and competitor ads](https://somin.ai/blog/market-personas-from-audience-data-and-competitor-ads/): Build market personas from audience data by pairing panel data with competitor ads in each market, then validating the clusters. Lessons from two SOMIN cases.
- [Why AI adoption in agencies stalls, and how to fix it](https://somin.ai/blog/why-ai-adoption-in-agencies-stalls-and-how-to-fix-it/): AI adoption in agencies stalls on people, not technology: fear for roles, perfectionism, undervalued juniors and no time to learn. Five fixes that restart it.
- [Generative engine optimisation: how brands get cited by AI answer engines](https://somin.ai/blog/generative-engine-optimisation-how-brands-get-cited/): Generative engine optimisation gets brands cited by AI answer engines: answer questions early, make the entity clear, cite sources and publish original data.
- [Middle East travel marketing: personalising by market, from KSA to Kuwait](https://somin.ai/blog/middle-east-travel-marketing-personalising-by-market/): Middle East travel marketing works best per market: SOMIN read 16,235 posts and found luxury under-served in KSA, families open in Kuwait and thrift in the UAE.
- [What should you do when a buyer says your price is too high?](https://somin.ai/blog/when-a-buyer-says-your-price-is-too-high-check-your-story-first/): When a buyer says your price is too high, check your positioning first: in crowded categories, deals are lost on clarity and price is where confusion shows.
- [QA for AI marketing content: a practical checklist for brand teams](https://somin.ai/blog/qa-for-ai-marketing-content-checklist/): QA for AI marketing content checks six things before anything ships: facts, traceable numbers, brand voice, claims and legal, localisation and accessibility.
- [Why global brands need market-specific messaging in the AI age](https://somin.ai/blog/why-global-brands-need-market-specific-messaging/): Market-specific messaging works because each market has its own rivals, tensions and culture. Evidence from SOMIN's Defender and Coca-Cola market reads.
- [Context engineering for marketing: why the same prompt writes the same ad](https://somin.ai/blog/context-engineering-for-marketing/): Context engineering for marketing explains why the same prompt writes the same ad, and what to give AI: competitor ads, tensions, brand assets and results.
- [Does a faster AI agent make better marketing decisions?](https://somin.ai/blog/a-faster-agent-is-not-the-same-thing-as-a-smarter-one/): No. A faster agent acts on whatever signal it gets, so fragmented audience data just produces wrong decisions sooner. Unify the data before you automate.
- [Has open-source software made marketing mix modelling easy?](https://somin.ai/blog/the-marketing-mix-modelling-barrier-did-not-disappear-it-relocated/): Open-source tools and AI agents make building a marketing mix model easy, but knowing whether it is right still takes expertise, above all in Southeast Asia.
- [Why has AI changed product discovery in Southeast Asia but not buying decisions?](https://somin.ai/blog/southeast-asias-ai-marketing-blind-spot-why-discovery-has-changed-but-buying-decisions-havent/): About one in four Southeast Asian shoppers now use AI to discover products, but family, friends and reviews still decide purchases. Where AI budgets should go.
- [What is agentic commerce, and how do brands get chosen by AI shopping agents?](https://somin.ai/blog/beyond-the-click-thriving-in-the-era-of-agentic-commerce/): Agentic commerce is when AI agents search, compare and buy for people. Brands get chosen with machine-readable data, fast APIs and a focus on Share of Model.
- [Why are proprietary agency AI platforms a risk for brands?](https://somin.ai/blog/the-agency-ai-trap-why-proprietary-platforms-are-billion-dollar-paperweights/): Proprietary agency AI platforms lock brands into tools Gartner says half of will be obsolete by 2029. Ask for modular, vendor-neutral intelligence instead.
- [What can Meta's Manus agent do for performance marketers, and where does it fail?](https://somin.ai/blog/the-rise-of-autonomous-agents-in-performance-marketing-analyzing-metas-usdollar2b-manus-ai-investment/): Manus speeds up reporting, funnel analysis and creative audits in Meta, but misjudges awareness spend and sees little beyond Meta. A bakery audit shows both.
- [How is AI changing the role of the marketing scientist?](https://somin.ai/blog/the-strategic-translator-how-ai-is-redefining-the-marketing-scientist/): AI now handles most observational analytics, so the marketing scientist's job moves from building dashboards to explaining why, what it means and what to do.
- [Will AI agents like Manus replace dashboard SaaS in marketing?](https://somin.ai/blog/the-autonomous-agent-era-metas-manus-acquisition-and-the-death-of-dashboard-saas/): For execution, largely yes: agents like Manus monitor, create, optimise and report on their own, reading data through MCP. What stays valuable is clean data.
- [How do Meta's AI connectors let outside AI agents work in your ad account?](https://somin.ai/blog/breaking-the-walls-metas-strategic-shift-toward-open-ai-connectors/): Meta's AI connectors link ad accounts to outside AI tools through an ads MCP server, so agents can manage campaigns, pull diagnostics and organise catalogues.
- [What is the AI shadow ledger, and why does AI governance protect brand trust?](https://somin.ai/blog/the-shadow-ledger-why-ai-governance-defines-modern-brand-trust-and-enterprise-revenue/): The AI shadow ledger is the hidden record of commitments ungoverned AI agents make. A decision architecture with gates and audit trails removes it.
- [How can AI localise a global brand's message? Lessons from Land Rover Defender](https://somin.ai/blog/beyond-the-grid-how-ai-is-rewriting-the-global-playbook-for-land-rover/): AI localises a brand's message by reading each market's audiences, rivals and creators. For Land Rover Defender, the UK, Japan and US each needed its own story.
- [What happens to billable hours when AI agents run marketing execution?](https://somin.ai/blog/the-death-of-the-delivery-hour-why-strategic-brilliance-is-marketings-new-currency/): When AI agents run execution, billable delivery hours lose value and the premium moves to strategy. What Salesforce's agentic tools mean for agencies.
- [What did the Fable 5 shutdown reveal about Asia's AI platform risk?](https://somin.ai/blog/the-day-the-mind-went-dark-washington-just-exposed-asias-massive-ai-blind-spot/): The Fable 5 shutdown showed frontier AI access can vanish overnight. What it means for Asian businesses built on rented models, and how marketers can hedge it.
- [Why isn't more AI-generated content making campaigns better?](https://somin.ai/blog/why-more-ai-generated-marketing-content-is-not-making-your-campaigns-better/): More AI content isn't improving campaigns because the audience brief is weak, not the model. 88% of marketers make more creative; only 45% see better quality.
- [Why does your marketing stack need data foundations before AI agents?](https://somin.ai/blog/the-silent-cracks-in-the-ai-facade-why-your-marketing-stack-needs-a-data-revolution/): AI agents on fragmented data scale mistakes, which is why 88% of marketing leaders wish they had fixed content and data foundations before deploying them.
- [Why does AI integration matter more than model intelligence in 2026?](https://somin.ai/blog/the-great-ai-realignment-why-intelligence-is-taking-a-backseat-to-integration-in-2026/): In 2026 enterprises buy AI for secure integration with their own data, not raw intelligence. What the shift in enterprise AI share means for marketing teams.
- [What is agentic AI in marketing, and how is it different from automation?](https://somin.ai/blog/the-agentic-era-of-marketing-from-static-automation-to-real-time-reasoning/): Marketing automation follows fixed if-this-then-that rules; agentic AI reasons, adapts and optimises on live data. What the shift means for teams and agencies.
- [How do advertisers adapt when Meta's AI replaces the media buyer?](https://somin.ai/blog/meta-replaced-your-media-buyer-with-ai-how-to-survive-the-automation-takeover/): Make creative your targeting: with Meta's AI choosing who sees ads, win with genuinely different creative for each persona, grounded in market data.
- [Why should an agency pitch sell strategic intelligence instead of content?](https://somin.ai/blog/the-evolution-of-the-agency-pitch-why-strategic-intelligence-must-replace-content-execution/): Agency pitches should sell strategic intelligence because AI has made content execution a commodity and CMOs now buy revenue and pipeline, not volume.
- [Why is your go-to-market strategy failing, and how do you fix it?](https://somin.ai/blog/the-architecture-of-failure-why-your-go-to-market-strategy-is-broken-and-how-to-fix-it/): Most go-to-market failures are structural: systems never built to work together and nobody owning them. Fix it by treating marketing operations as strategy.
- [How do you choose an AI marketing agency that actually delivers growth?](https://somin.ai/blog/how-to-choose-an-ai-marketing-agency-that-actually-delivers-growth/): Choose an AI marketing agency on platform ownership, transparency, human oversight, data integration and test velocity. Ask seven questions before signing.
- [Agency business model in the AI era: from retainers to agents](https://somin.ai/blog/agency-business-model-ai-from-retainers-to-agents/): How AI changes the agency business model: why FTE retainers break when agents do production, which pricing models replace them and what clients still pay for.
- [Competitor ad analysis by market: finding whitespace in each country](https://somin.ai/blog/competitor-ad-analysis-by-market-finding-whitespace/): Competitor ad analysis by market: pull local rivals' ads from ads libraries, label and cluster them, and call whitespace only where the audience signal is real.
- [SEO, AEO and GEO: how do brands get discovered in AI answers?](https://somin.ai/blog/beyond-page-one-the-new-rules-of-brand-discovery-in-the-age-of-ai/): Brands get found in AI answers by layering SEO for rankings, AEO for direct answers and GEO for citations in AI assistants, all backed by original insight.
- [Agency proprietary data: why category data beats a better prompt](https://somin.ai/blog/agency-proprietary-data-why-category-data-beats-a-better-prompt/): Agency proprietary data is the category knowledge an agency owns and can query. Why it beats a better prompt, what to collect and what agency case numbers show.
- [Why do isolated marketing tools cost more than they earn?](https://somin.ai/blog/the-hidden-drain-on-modern-marketing-why-isolated-tools-cost-more-than-they-earn/): Isolated marketing tools cost more than they earn because of an integration tax: engineering hours, middleware fees, data drift and slower signals for AI.
- [How is agentic AI changing global beverage strategy in the cola wars?](https://somin.ai/blog/the-new-era-of-global-beverage-strategy-how-agentic-ai-redefines-the-cola-wars/): Agentic AI turns weeks of research into minutes. Across four markets it found food is half of the conversation, yet cola brands are almost absent from it.
- [How to measure AI ROI in agencies: hours, pitches and revenue](https://somin.ai/blog/how-to-measure-ai-roi-in-agencies/): To measure AI ROI in agencies, track hours saved, pitch cost and revenue won from redeployed time against a baseline. KPIs and real agency case numbers.
- [How do you solve Meta's creative differentiation problem at scale?](https://somin.ai/blog/automating-creative-differentiation-solving-the-meta-algorithmic-bottleneck-with-mindfuse/): Meta groups ads that look alike and limits their reach. MindFuse automates differentiation: it extracts content pillars, clusters personas and scores creative.
- [Why do 94% of AI marketing strategies fail at integration?](https://somin.ai/blog/the-integration-gap-why-94-percent-of-ai-marketing-strategies-fail/): Most AI marketing strategies fail because tools are bought but never integrated: only 6.3% of firms run AI in a fully governed, operational marketing stack.
- [Agency pitch competitor research: how to win new business with data](https://somin.ai/blog/agency-pitch-competitor-research-win-new-business-with-data/): Agency pitch competitor research wins new business when it finds the opening rivals miss. How to build that read in days, with SAMY and KPI Media results.
- [What does Meta's Manus acquisition mean for digital advertising and agencies?](https://somin.ai/blog/the-agentic-shift-meta-manus-ai-and-the-future-of-digital-advertising/): Meta's Manus deal puts an autonomous agent in Ads Manager, making reports fast and cheap and squeezing agency retainers. Data and human checks still decide.
- [Content localisation in Asia is not translation: three market lessons](https://somin.ai/blog/content-localisation-in-asia-is-not-translation/): Content localisation in Asia means rebuilding the message for each market's rivals and trust signals. Lessons from Hong Kong, the Philippines and Singapore.
- [How can brands close the AI trust gap with consumers?](https://somin.ai/blog/bridging-the-ai-trust-gap-why-creative-variety-and-personal-connection-define-the-future/): Brands close the AI trust gap by using AI for creative variety and relevance, not just cheaper output. Over 90% of marketers trust it; half of consumers do.
- [Authentic content with AI: why imperfect posts win and how to stay human](https://somin.ai/blog/authentic-content-with-ai-why-imperfect-posts-win/): Authentic content with AI works when AI does the research and drafting and people add real stories and voice. Why imperfect posts beat polished ones, with data.
- [Why did the generalist agency model collapse in 2026?](https://somin.ai/blog/the-strategic-pivot-why-the-generalist-agency-model-collapsed-in-2026/): The generalist agency model collapsed because AI made execution cheap and clients now pay for outcomes, not hours. Here is what replaces it.
- [Why is explainable AI becoming a B2B sales advantage?](https://somin.ai/blog/from-opaque-to-open-why-explainable-ai-is-the-new-b2b-sales-advantage/): Explainable AI wins B2B deals because buyers trust a price they can see the reasons for. How glass-box AI turns pricing from friction into a sales asset.
- [Is SEO dead? How brands stay visible when AI agents search for buyers](https://somin.ai/blog/the-end-of-seo-how-to-survive-the-rise-of-the-agentic-web/): The old SEO playbook of winning the click is fading as AI agents read the web for people. Brands stay visible by being machine-readable, citable and chosen.
- [SOMIN joins Meta's Llama Incubator in Singapore](https://somin.ai/blog/somin-joins-metas-llama-incubator-to-power-ai-driven-creative-diversification/): SOMIN was selected for Meta's first Llama Incubator in Singapore, a six-month programme run with the Singapore government for Southeast Asian AI startups.
- [Persona, tension, angle, story: an AI copywriting framework that works](https://somin.ai/blog/ai-copywriting-framework-persona-tension-angle-story/): An AI copywriting framework that stops generic copy: answer persona, tension, angle and story from real audience data before the model writes a single line.
- [SOMIN named among Echelon 2025's Top 10 Startups](https://somin.ai/blog/somin-named-among-echelon-2025s-top-10-startups/): SOMIN, the AI creative planning and competitive intelligence platform, was named one of Echelon 2025's Top 10 Startups after e27's TOP100 Program evaluation.
- [How is AI changing competitor and audience research? Lessons from Marketing Mondays](https://somin.ai/blog/ai-digital-marketing-competitor-audience-research/): AI joins competitor ad analysis with audience data, so marketers see what rivals say and what buyers value. A Marketing Mondays case study: Miraflora Wagyu.
- [What is the AIDA model, and how do you use it to attract and convert customers?](https://somin.ai/blog/a-beginners-guide-to-the-aida-marketing-model-how-to-attract-and-convert-customers/): AIDA stands for Attention, Interest, Desire and Action, the four stages a buyer goes through before acting. How to apply each one, with beginner examples.
- [Which social media advertising metrics matter, and how do you optimise them?](https://somin.ai/blog/an-expert-guide-to-social-media-advertising-key-metrics-and-strategies-for-effective-optimization/): The social ad metrics that matter most are CTR, the click-to-landing-page-view ratio, conversion rate and CRM-based cost per conversion. How to read each one.
- [Why do ad costs fluctuate, and how can you stabilise them?](https://somin.ai/blog/mastering-the-fluctuations-strategies-for-stabilizing-ad-costs-in-the-current-market/): Ad costs swing because AI auctions keep re-estimating who will respond to each ad. Stabilise them by balancing reach with targeting and watching key metrics.
- [How can businesses use large language models beyond chatbots?](https://somin.ai/blog/expanding-horizons-leveraging-large-language-models-for-business-innovation-beyond-chatbots/): Beyond chatbots, LLMs condense information and let people run complex tools in plain language, as the OpenAI Startup Fund's bets on Descript and Harvey show.
- [What are social listening tools, and which ones should marketers know?](https://somin.ai/blog/social-listening-tools-the-essential-guide-for-marketers-in-2024/): Social listening tools monitor and analyse online conversations about brands, keywords and hashtags. The 11 tools we reviewed in 2024, plus SOMONITOR.
- [How do you optimise ads on Meta and TikTok? A step-by-step process](https://somin.ai/blog/mastering-ad-optimization-in-the-dynamic-world-of-digital-advertising-a-strategic-guide-for-meta-and-tiktok-platforms/): Optimise Meta and TikTok ads in layers: a three-day KPI check per ad set, fixes to costly ads, a weekly review, budget scenarios and secondary metrics like CTR.
- [How do Google and Meta smart bidding algorithms differ?](https://somin.ai/blog/a-comparative-analysis-of-meta-and-google-smart-bidding-algorithms-optimizing-digital-advertising/): Google's Target ROAS bids for conversion value from campaign data; Meta's smart bidding ranks ads on predicted engagement from user data. How they compare.
- [SOMONITOR joins the first batch of Singapore's GenAI Sandbox](https://somin.ai/blog/somonitor-joins-the-elite-genai-sandbox-backed-by-singapores-visionary-ai-investment/): SOMONITOR, SOMIN's competitor intelligence platform, joined the first batch of Singapore's GenAI Sandbox in 2024, as Budget 2024 put over S$1 billion into AI.
- [How can LLM-backed startups stay defensible enough to win VC investment?](https://somin.ai/blog/unlocking-vc-investment-the-key-element-for-large-language-model-backed-startups/): LLM startups win VC backing by owning what rivals cannot copy: proprietary data, IP and in-house AI on top of the model, plus a team that goes beyond an API.

## Pricing
- SOMIN LIGHT (Core channels, one desk): US$529 a month, US$476.10 a month billed annually; 1 Analyst seat, 8 brands monitored, 8 handle swaps a month.
- SOMIN PRO (All ten channels, in depth): US$1,740 a month, US$1,566.00 a month billed annually; 1 Specialist seat, 12 brands monitored, 15 handle swaps a month.
- SOMIN AGENCY LIGHT (Your whole client roster): US$1,790 a month, US$1,611.00 a month billed annually; 3 Analyst seats, 30 brands monitored, 15 handle swaps a month.
- SOMIN AGENCY PRO (Depth at scale, plus API): US$5,290 a month, US$4,761.00 a month billed annually; 3 Specialist seats, 70 brands monitored, 25 handle swaps a month.
- SOMIN ENTERPRISE: custom multi-market private offers, handle pools (100+ brands), customer success manager.
- Add-ons: Analyst seat US$300/month, Specialist seat US$600/month, +10 brands US$190 (Light plans) or US$390 (Pro plans) a month. No overage fees. Full table: https://somin.ai/pricing/

## Authors
- [Prof. Aleks Farseev, Co-Founder and CEO](https://somin.ai/authors/aleks-farseev/)
- [Murtaza Hyder Magsi, Quality Assurance Engineer](https://somin.ai/authors/murtaza-hyder-magsi/)
- [Hsiao Yuh Tyng, SOMIN author](https://somin.ai/authors/hsiao-yuh-tyng/)
- [Dr. Yang Qi, Senior Data Scientist](https://somin.ai/authors/yang-qi/)
- [Joy Yu-Yi Chu, Data Analyst](https://somin.ai/authors/joy-yu-yi-chu/)
- [Phil Lugovoi, Business Development](https://somin.ai/authors/phil-lugovoi/)
- [Da-Min You, SOMIN team](https://somin.ai/authors/da-min-you/)
- [Egor Shevelev, Head of Development](https://somin.ai/authors/egor-shevelev/)
- [Kirill Lepikhin, Co-Founder and CTO](https://somin.ai/authors/kirill-lepikhin/)

## Languages
172 of the pages above also exist in 16 other languages at /<language>/<path>/ (for example https://somin.ai/ja/somin-strategy/), linked with hreflang; the language sitemaps list them. Legal documents are English only. Language home pages and sitemaps:
- 简体中文 (zh-Hans): https://somin.ai/zh-hans/ · sitemap https://somin.ai/sitemap-zh-hans.xml
- 繁體中文 (zh-Hant): https://somin.ai/zh-hant/ · sitemap https://somin.ai/sitemap-zh-hant.xml
- 日本語 (ja): https://somin.ai/ja/ · sitemap https://somin.ai/sitemap-ja.xml
- 한국어 (ko): https://somin.ai/ko/ · sitemap https://somin.ai/sitemap-ko.xml
- ไทย (th): https://somin.ai/th/ · sitemap https://somin.ai/sitemap-th.xml
- Tiếng Việt (vi): https://somin.ai/vi/ · sitemap https://somin.ai/sitemap-vi.xml
- Bahasa Indonesia (id): https://somin.ai/id/ · sitemap https://somin.ai/sitemap-id.xml
- Bahasa Melayu (ms): https://somin.ai/ms/ · sitemap https://somin.ai/sitemap-ms.xml
- हिन्दी (hi): https://somin.ai/hi/ · sitemap https://somin.ai/sitemap-hi.xml
- Filipino (fil): https://somin.ai/fil/ · sitemap https://somin.ai/sitemap-fil.xml
- Español (es): https://somin.ai/es/ · sitemap https://somin.ai/sitemap-es.xml
- Français (fr): https://somin.ai/fr/ · sitemap https://somin.ai/sitemap-fr.xml
- Deutsch (de): https://somin.ai/de/ · sitemap https://somin.ai/sitemap-de.xml
- Português (pt): https://somin.ai/pt/ · sitemap https://somin.ai/sitemap-pt.xml
- العربية (ar): https://somin.ai/ar/ · sitemap https://somin.ai/sitemap-ar.xml
- Русский (ru): https://somin.ai/ru/ · sitemap https://somin.ai/sitemap-ru.xml

## Company & legal
- [About SOMIN](https://somin.ai/about/)
- [Our Vision](https://somin.ai/vision/)
- [Privacy Policy](https://somin.ai/privacy-policy/)
- [SaaS Agreement](https://somin.ai/saas-terms-general/)

## Contact
- Book a call: https://calendly.com/filipp-lugovoi/30min
- Try SOMIN: https://somin.ai/try-somin/
- Free Claude plugin: https://somin.ai/marketing-mondays-plugin/
- Platform login: https://cloud.somin.ai/auth/signin