Marketing ops · Production
How Soap went from 25% to 73% email open rate with Landbot
The problem
Soap, a small eCommerce company competing against giants like Henkel, P&G, and Unilever, faced low landing page conversion rates and depended on paid ads for traffic, with no mechanism for real-time customer interaction.
Workflow diagram · grounded in source
1
Chatbot conversation initiated
trigger
“to build any relationship, you need a conversation, and Marco knew that right from the start”
2
Visitor engagement reduces bounce
ai_action
“when they're engaged in a conversation, they're less likely to bounce”
3
Email open rate improvement
output
“How Soap went from 25% to 73% of email open rate with Landbot”
Reported outcome
Using Landbot, Soap grew its email open rate from 25% to 73%.
Reported metrics
Email open rate (starting)25%
Email open rate (achieved)73%
Average landing page conversion rate (industry benchmark)2% or 3%
Consumers preferring chatbot interaction (industry benchmark)85%
Reported stack
Landbot
Frequently asked questions
What did this team achieve with this AI workflow?
Using Landbot, Soap grew its email open rate from 25% to 73%.
What tools did this team use?
Landbot.
What results were reported?
Email open rate (starting): 25%; Email open rate (achieved): 73%; Average landing page conversion rate (industry benchmark): 2% or 3%; Consumers preferring chatbot interaction (industry benchmark): 85% (source-reported, not independently verified).
How is this marketing ops AI workflow structured?
Chatbot conversation initiated → Visitor engagement reduces bounce → Email open rate improvement.