Company Profile
Company Type
Ecommerce marketplace seller
Team Size
10-40 employees
Industry
E-Commerce
Key Challenge
Struggling with inefficient manual customer retention processes that were slowing growth and increasing operational costs. Their primary concern was cart abandonment.
Tools Connected
The Challenge
Manual customer retention was the biggest bottleneck in this ecommerce marketplace seller's operations. Their team of 10-40 employees processed hundreds of customer retention requests weekly, each requiring multiple steps, cross-referencing against e-commerce-specific requirements, and coordination between departments. The average customer retention request took 45 minutes to complete manually, and the backlog was growing by 15% each quarter.
Beyond the time drain, the quality of their customer retention output was inconsistent. Different team members followed different procedures, and there was no standardized way to handle edge cases that are common in e-commerce. A recent audit revealed that 12% of completed customer retention records contained errors that required rework — costing the organization an additional $50K annually in correction and remediation efforts. The leadership team recognized that continuing to throw people at the problem wasn't viable and began searching for an AI-powered solution.
The Solution
Arahi AI provided the automation backbone this e-commerce team needed. They deployed a multi-agent workflow that breaks the customer retention process into discrete, automated steps — each handled by a specialized AI agent. The first agent monitors triggers from Shopify and Mailchimp. The second agent analyzes and processes incoming requests using e-commerce-specific business logic. The third agent executes actions across connected tools and notifies team members via Zendesk.
The beauty of the no-code approach was speed of implementation. The team had their first agent live within 90 minutes, and the full customer retention workflow was operational within a single afternoon. They used Arahi AI's template for e-commerce customer retention as a starting point, customized the business rules to match their specific process, and connected their existing tool stack without writing a single line of code. Within the first week, the agents had processed over 200 customer retention instances with 99%+ accuracy — more than the team typically handled in a month.
The Results
Measurable improvements across key e-commerce customer retention metrics.
Monthly Churn Rate
60% reduction
Before
5.2%
After
2.1%
At-Risk Detection Lead Time
Proactive vs. reactive
Before
After cancellation
After
14+ days before churn
Retention Intervention Success
189% improvement
Before
18%
After
52%
Annual Revenue Saved
$340K impact
Before
$0 (no proactive program)
After
$340K recovered
NPS Score
142% improvement
Before
24
After
58
“Before Arahi AI, our customer retention process was the bottleneck that every e-commerce team complained about. Now it's our competitive advantage. We process faster, more accurately, and at a fraction of the cost. Our competitors are still doing this manually.”
Head of Strategy
Ecommerce marketplace seller
Key Takeaways
The most important lessons from this e-commerce customer retention automation project.
Automating customer retention in e-commerce delivered immediate, measurable results: faster processing, higher accuracy, and lower costs.
The key to success was connecting existing e-commerce tools to AI agents rather than replacing the entire tech stack.
24/7 automated processing eliminated backlogs and ensured consistent service quality regardless of volume fluctuations.
Starting with a pre-built template and customizing for e-commerce-specific requirements dramatically reduced time-to-value.
Implementation Timeline
From zero to production in Half a day — here's how they did it.
Step 1: Mapped the existing customer retention workflow
Documented every step of the current manual customer retention process, including decision points, exceptions, and handoffs between team members. Identified which steps could be fully automated versus those needing human oversight.
Step 2: Built the automation in Arahi AI
Used Arahi AI's no-code builder to create the customer retention workflow: connected Shopify and ShipStation as data sources, configured AI decision logic for e-commerce-specific requirements, and set up automated actions and notifications.
Step 3: Parallel run with manual process
Ran the AI agents alongside the manual process for one week to compare outputs. The AI matched or exceeded human accuracy on 98% of customer retention instances, with the 2% of edge cases automatically flagged for human review.
Setup Time
Half a day
AI Agents
3 AI agents
Tools Connected
5 integrations
Frequently Asked Questions
Common questions about automating customer retention in e-commerce.
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This case study represents a typical customer scenario. Individual results may vary.