Launching Your Conversation Engine
You’ve got the strategy, the flows, the content, and the tech stack — now it’s time to go live.
But launching a conversation marketing engine isn’t like launching a static campaign. It’s not a “set it and forget it” process. It’s a living system — designed to listen, adapt, and improve.
This chapter will guide you through a successful launch: from preparing your team to promoting your channels and refining your flows post-launch.
1. Set Clear Objectives
Before you deploy anything, define what success looks like — for both the business and the customer.
Common launch goals:
- Reduce customer service response time
- Increase lead qualification through automation
- Drive more conversions from chat-based journeys
- Improve onboarding or product adoption
- Collect feedback and sentiment at scale
Tie each goal to measurable KPIs, such as:
- Time to first response
- Conversion rate from chat to action
- NPS or CSAT improvements
- Number of qualified leads or resolved issues
2. Train the Humans Behind the Machines
Even the most advanced system needs people behind it.
- Ensure your customer-facing teams know how to step in when needed
- Train your staff on tone, escalation protocols, and expectations
- Align support, sales, and marketing on conversation purpose and scope
- Create documentation and internal playbooks for common scenarios
Remember: conversational marketing blends automation and human empathy. That’s the winning combo.
Create a Conversational Style Guide
Define your brand’s tone of voice, preferred greetings, fallback language, and escalation phrases — so everyone sounds like one consistent brand.
3. Promote the Conversation Entry Points
A great chatbot or message flow won’t help anyone if no one sees it.
Make sure your conversation channels are:
- Visible: Add them to menus, footers, banners, emails, and landing pages
- Inviting: Use proactive messages to greet or guide visitors
- Contextual: Trigger the right message based on page, behaviour, or timing
- Integrated: Promote across your campaigns — "Have questions? Chat with us!"
Think of them like store entrances — clean, obvious, and welcoming.
4. Monitor and Iterate Fast
You won’t get everything perfect on day one — and that’s okay.
Track early signals:
- Drop-off points in flows
- FAQ triggers that get repeated
- Response speed or satisfaction ratings
- Unusual queries or sentiment spikes
Use this data to:
- Rewrite confusing responses
- Add missing branches or fallback logic
- Train AI models with new examples
- Escalate more efficiently
Weekly reviews in the first month are essential.
Real-World Example: ASOS Customer Assistant
ASOS rolled out a customer support chatbot to manage high-volume queries. But its real strength was in iteration — within the first 90 days, they’d added 500+ new queries, shortened wait times, and integrated product discovery into the flow.
They didn’t launch a perfect bot. They launched a learning one.
5. Close the Loop
Don’t just collect data — act on it. Share insights with product teams, UX designers, and leadership.
Conversation data is one of your richest sources of:
- Customer language and sentiment
- Objections and pain points
- Opportunities to improve your offer
Make it part of your continuous improvement process.
What This Chapter Really Means
Launching your conversational engine is a milestone — but it’s not the finish line.
It’s the beginning of a new kind of relationship: one where your brand doesn’t just speak, but listens, adapts, and evolves — every day.
“If you're not learning from your conversations, you're not really having any.”
— Jonny Bowker