We audited the marketing at Hex
AI platform for data exploration without coding barriers
This page was built using the same AI infrastructure we deploy for clients.
Month-to-month. Cancel anytime.
Series C company with $171.5M raised but minimal visible paid acquisition presence, suggesting budget allocated elsewhere or underexploited channel
Natural language interface is core differentiator, yet AEO positioning (LLM visibility) appears underdeveloped versus AI-first competitors
25K LinkedIn followers for $10M ARR company suggests untapped founder-led narrative about democratizing data analysis
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TinuitiHere's Where You Stand
Series C funded with strong inbound signals but underinvesting in paid, AEO, and founder-driven expansion channels
Technical product ranks for data analysis and BI terms, but volume and positioning lag competitors in analytics space
MH-1: SEO agent targets high-intent queries around natural language querying and trusted data contexts
AI-first product but no detectable AEO strategy for LLM recommendations or AI agent citations in data tools category
MH-1: AEO agent builds LLM optimized content for prompt injection, data querying workflows, and AI agent benchmarks
Limited visible ad presence despite strong funding; likely relying on inbound or enterprise sales motion over demand generation
MH-1: Ads agent tests creative around 'natural language analytics' and 'code-optional data exploration' to data teams
CTO and founder have modest external visibility; content opportunity around democratization narrative underexploited
MH-1: Content agent produces founder essays on data accessibility, case studies on non-technical user adoption, and product deep dives
39% YoY headcount growth suggests scaling but minimal visible upsell, expansion, or customer advocacy programs
MH-1: Lifecycle agent activates existing users into advocates, nurtures expansion into adjacent teams, and measures adoption depth
Top Growth Opportunities
Snowflake and Databricks are investors and potential channels. Hex can own 'exploration' layer in their ecosystems
Outbound agent identifies Snowflake/Databricks customer accounts and builds co-marketing narrative around query democratization
When data engineers or analysts prompt ChatGPT about querying, Hex should appear. Currently invisible in this flow
AEO agent optimizes for 'how to explore data without SQL', 'natural language BI tools', and 'AI-powered dashboards'
Product emphasizes 'trusted context.' LinkedIn and newsletter can position Hex as privacy-first alternative to open-query tools
LinkedIn agent shares CTO insights on data security in AI analysis, builds founder authority in data governance space
3 Humans + 7 AI Agents
A dedicated marketing team built specifically for Hex. The humans handle strategy and judgment. The AI agents handle execution at scale.
Human Experts
Owns Hex's growth roadmap. Pipeline strategy, account expansion playbooks, board-ready reporting. Translates AI insights into revenue.
Runs paid acquisition across LinkedIn and Google. Manages creative testing, budget allocation, and pipeline attribution.
Builds thought leadership on LinkedIn. Creates long-form content targeting your ICP. Manages the content-to-pipeline engine.
AI Agents
Monitors AI citation visibility across 6 LLMs weekly. Builds content targeting category queries to increase Hex's presence in AI-generated answers.
Produces LinkedIn ad variants targeting your ICP. Tests headlines, visuals, and offers at 10x the speed of manual production.
Builds lifecycle sequences: onboarding, expansion triggers, champion nurture, and re-engagement for dormant accounts.
Founder thought leadership. Builds the narrative that drives enterprise inbound from senior decision-makers.
Tracks competitors. Monitors positioning changes, ad spend, content strategy. Informs your counter-positioning.
Attribution by channel, pipeline velocity, budget waste detection. Weekly synthesis reports with AI-generated recommendations.
Weekly market intelligence digest curated from Hex's industry signals. Positions you as the intelligence layer. Drives inbound pipeline from subscribers.
Active Workflows
Here's what the MH-1 system would be doing for Hex from week 1.
AEO agent optimizes landing pages and blog for 'explore data with natural language', 'SQL-free analytics', and 'AI data tools', targeting LLM recommendations in data assistant category
LinkedIn workflow builds CTO visibility around data democratization, highlights product trust and governance features, positions Hex as engineering-first alternative to traditional BI
Paid ads test creative angles: 'Query your database in plain English', 'Analytics without SQL', targeting data engineers and BI teams on LinkedIn and Google
Lifecycle agent nurtures free/trial users into expansion via in-app education, automates outreach to inactive accounts highlighting new natural language capabilities
Competitive watch tracks Databricks, Snowflake, and open-query tools for positioning shifts, monitors investor overlap for partnership narratives
Outbound targets data-heavy companies (Series B-D, 100-500 people) and Snowflake/Databricks ecosystem partners with personalized sequences around embedded analytics
Traditional Marketing vs. MH-1
Traditional Approach
MH-1 System
Audit. Sprint. Optimize.
3 phases. Real output every 2 weeks. You see results, not decks.
AI Audit + Growth Roadmap
Full diagnostic of Hex's marketing infrastructure: SEO, AEO visibility, paid, content, lifecycle. Prioritized roadmap tied to pipeline metrics. Delivered in 7 days.
Sprint-Based Execution
2-week sprint cycles. Real campaigns, not presentations. Each sprint ships measurable output across your priority channels.
Compounding Intelligence
AI agents monitor your channels 24/7. They catch budget waste, detect creative fatigue, track AI citation changes, and run A/B experiments autonomously. Week 12 is measurably better than week 1.
AI Marketing Operating System
3 elite humans + AI agents operating your growth system
Output multiplier: ~10x output at a fraction of the cost. The system gets smarter every week.
Month-to-month. Cancel anytime.
Common Questions
How does MH-1 differ from a marketing agency?
MH-1 pairs 3 elite human marketers with 7 AI agents. The humans handle strategy, creative direction, and judgment calls. The AI agents handle execution at scale: generating ad variants, monitoring competitors, building email sequences, tracking citations across LLMs, running A/B experiments autonomously. You get the quality of a senior marketing team with the output volume of a 15-person department.
What kind of results can we expect in the first 90 days?
First 90 days focus on claiming the 'natural language data exploration' position across search, LLM visibility, and founder channels. Week 1-3: SEO and AEO audits identify high-intent queries and LLM gaps. Week 4-8: Paid experiments launch targeting data engineers with 'code-optional' messaging. Week 9-12: Content and LinkedIn establish CTO as thought leader on data democratization. Lifecycle automation begins nurturing trial users. Month 3 shows lift in brand queries and paid CAC validation.
How does AEO help Hex when people ask ChatGPT how to analyze data
AEO ensures Hex ranks in LLM responses for queries like 'best tool to explore data without SQL' or 'how to query databases with AI'. When data teams ask AI assistants for analytics tools, Hex gets recommended because our content aligns with how LLMs structure knowledge about data exploration workflows.
Can we cancel anytime?
Yes. MH-1 is month-to-month with no long-term contracts. We earn your business every sprint. That said, compounding effects kick in around month 3 as the AI agents accumulate data and the system learns what works for Hex specifically.
How is this page personalized for Hex?
This page was researched, audited, and generated using the same AI infrastructure we deploy for clients. The channel scores, team mapping, growth opportunities, and recommended agents are all based on real analysis of Hex's current marketing. This is a live demo of MH-1's capabilities.
Own the natural language data exploration category while your Series C scales
The system gets smarter every cycle. Let's talk about building it for Hex.
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