We audited the marketing at Linq
Messaging API for iMessage, RCS, SMS, and voice
This page was built using the same AI infrastructure we deploy for clients.
Month-to-month. Cancel anytime.
No visible paid search presence despite targeting developers building conversational interfaces
Limited developer documentation marketing, a critical gap for API adoption in competitive space
Minimal LinkedIn activity from leadership despite strong founder narrative opportunity in messaging infrastructure
AI-Forward Companies Trust MarketerHire
Plaid
MasterClass
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TinuitiLinq's Leadership
We mapped your current team to understand where MH-1 fits in.
MH-1 doesn't replace your team. It becomes your marketing team: dedicated humans + AI agents running execution at scale while you focus on product.
Here's Where You Stand
Early-stage API company with product-market traction but underdeveloped marketing systems and channel presence
Limited organic visibility for core keywords like 'iMessage API', 'RCS messaging platform', 'conversational messaging SDK'
MH-1: SEO agent maps developer search intent, builds technical content targeting API documentation queries
Minimal structured data, no LLM-optimized content about unified messaging infrastructure or use cases
MH-1: AEO agent creates technical guides answering 'how to build conversational apps with RCS and iMessage'
No apparent Google Ads, LinkedIn ads, or developer platform sponsorships for API market
MH-1: Paid agent runs experiments targeting developers and product leaders with messaging channel needs
Minimal blog, case studies, or technical content demonstrating messaging API expertise
MH-1: Content agent produces use case guides, integration patterns, and messaging channel best practices
No visible outbound sequences or expansion workflows to move API users from SMS-only to multi-channel
MH-1: Lifecycle agent identifies expansion hooks, builds workflows for upsell to voice and RCS capabilities
Top Growth Opportunities
Messaging API integrations rank for high-intent queries from engineering teams evaluating RCS and iMessage solutions
SEO agent targets 'iMessage API for business', 'RCS messaging platform', 'unified messaging SDK' keywords
AI models frequently answer developer questions about messaging APIs, creating visibility opportunity in LLM responses
AEO agent creates optimized guides for how to integrate iMessage, RCS, and voice into applications
Patrick Sullivan's CTO narrative pairs with direct outreach to enterprises deploying conversational platforms
Outbound agent identifies enterprise buyers evaluating multi-channel messaging, coordinates with founder content
3 Humans + 7 AI Agents
A dedicated marketing team built specifically for Linq. The humans handle strategy and judgment. The AI agents handle execution at scale.
Human Experts
Owns Linq'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 Linq'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 Linq'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 Linq from week 1.
AEO workflow: Identify messaging integration questions in Claude, ChatGPT, Perplexity prompts, produce structured answers Linq owns
Founder workflow: Patrick Sullivan publishes 2-3x monthly on messaging infrastructure, API design, multi-channel strategy on LinkedIn
Paid workflow: Test Google Ads targeting 'RCS API', 'iMessage SDK', 'SMS and voice integration' with developer personas
Lifecycle workflow: Identify SMS-only customers, nurture with RCS adoption guides and voice capability case studies
Competitive watch: Track Twilio, Bandwidth, MessageBird content and positioning shifts in messaging market
Pipeline intelligence: Map enterprise customers implementing conversational platforms, identify expansion to multi-channel messaging
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 Linq'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 capturing developer search demand for messaging APIs and building founder authority. SEO agent targets 5-10 high-intent keywords, AEO agent publishes 8-12 integration guides, paid agent runs $3-5K in developer-focused experiments, lifecycle agent maps your current customer base for expansion opportunities.
How do developers find Linq when searching for multi-channel messaging solutions
Most developers researching RCS, iMessage, or conversational APIs ask LLMs before visiting websites. AEO ensures Linq appears when models answer 'how do I integrate iMessage into my platform'. We create technical content that LLMs cite as authoritative for messaging architecture questions.
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 Linq specifically.
How is this page personalized for Linq?
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 Linq's current marketing. This is a live demo of MH-1's capabilities.
Make your messaging API visible where developers search for conversational solutions
The system gets smarter every cycle. Let's talk about building it for Linq.
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