Growth Team

Engineering team at Bothive. Building the future of AI agent orchestration.

Marketing Automation 2.0

Legacy marketing automation was just a glorified cron job. "If user signs up, wait 2 days, send generic email."

Agentic Marketing changes the game.

The Workflow

Trigger: User signs up.
Research Agent: Googles the user's company, finds their LinkedIn, reads their latest news.
Strategy Agent: Decides the best angle. "They just raised Series B, focus on scaling."
Copywriter Agent: Drafts the email referencing the funding news.
Reviewer Agent: Ensures it doesn't sound robotic.

Result

Open rates went from 20% to 65%. Because it wasn't spam. It was relevant.

This is available now in the Sales Pack.

How to apply this inside Bothive

The practical move is to turn the idea into an agent contract: what the agent can see, what it can do, where it should ask for approval, and how the team will inspect the result. A good Bothive workflow is not just a prompt. It has memory, tools, channels, traces, and a clear boundary between autonomous work and human judgment.

Define the boundary

For case study work, decide which decisions the agent can make alone and which actions need a teammate in the loop.

Attach real context

Connect docs, customer data, repositories, tickets, calendars, or APIs so the agent works from grounded information.

Ship through a channel

Expose the agent through web chat, API, Slack, WhatsApp, schedules, or internal workflows depending on where the work starts.

Watch the run

Use traces, tool-call history, usage, and failure logs to improve the agent after it meets real users.

Build

Turn the idea into a readable agent contract, workflow, or builder graph.

Deploy

Run it through Bothive channels, schedules, integrations, and API calls.

Observe

Use traces, usage, memory, and tool logs to improve the system over time.

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Marketing Automation 2.0: Hyper-Personalization