How a Mid-market SaaS provider Automated Customer Retention with Arahi AI
See how a mid-market saas provider automated customer retention with Arahi AI. Results: Major reduction monthly churn rate, Proactive vs. reactive at-risk detection lead time. Read the full case study.
Company Profile
Company Type
Mid-market SaaS provider
Team Size
50-200 employees
Industry
SaaS
Key Challenge
Struggling with inefficient manual customer retention processes that were slowing growth and increasing operational costs. Their primary concern was trial-to-paid conversion.
Tools Connected
The Challenge
Manual customer retention was the biggest bottleneck in this mid-market saas provider's operations. Their team of 50-200 employees processed hundreds of customer retention requests weekly, each requiring multiple steps, cross-referencing against saas-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 saas. 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 saas 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 HubSpot and Slack. The second agent analyzes and processes incoming requests using saas-specific business logic. The third agent executes actions across connected tools and notifies team members via Notion.
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 saas 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 high accuracy — more than the team typically handled in a month.
The Results
Measurable improvements across key saas customer retention metrics.
Monthly Churn Rate
Major reduction
Before
Elevated
After
Significantly lower
At-Risk Detection Lead Time
Proactive vs. reactive
Before
After cancellation
After
Weeks before churn
Retention Intervention Success
Significant improvement
Before
Low
After
Much higher
Annual Revenue Saved
Meaningful impact
Before
No proactive program
After
Significant recovery
NPS Score
Major improvement
Before
Below target
After
Above target
“What impressed me most was the setup speed. I expected a months-long implementation, but we had AI agents handling our saas customer retention workflow within a single afternoon. The no-code approach meant our team could configure everything themselves without waiting on IT.”
Director of Business Operations
Mid-market SaaS provider
Key Takeaways
The most important lessons from this saas customer retention automation project.
AI-powered customer retention automation dramatically reduced manual processing time for this saas team, freeing staff to focus on high-value strategic work.
Implementation took less than a day — the no-code approach meant no IT bottleneck or months-long development cycle.
Error rates dropped significantly, improving data quality and downstream decision-making.
The ROI was realized quickly, with the solution paying for itself through cost savings and productivity gains.
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 HubSpot and Stripe as data sources, configured AI decision logic for saas-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 the vast majority of customer retention instances, with edge cases automatically flagged for human review.
Setup Time
Half a day
AI Agents
2 AI agents
Tools Connected
5 integrations
Frequently Asked Questions
Common questions about automating customer retention in saas.
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This case study represents a typical customer scenario. Individual results may vary.