Company Profile
Company Type
Regional freight company
Team Size
50-250 employees
Industry
Logistics
Key Challenge
Struggling with inefficient manual social media processes that were slowing growth and increasing operational costs. Their primary concern was cost optimization.
Tools Connected
The Challenge
Manual social media was the biggest bottleneck in this regional freight company's operations. Their team of 50-250 employees processed hundreds of social media requests weekly, each requiring multiple steps, cross-referencing against logistics-specific requirements, and coordination between departments. The average social media request took 45 minutes to complete manually, and the backlog was growing by 15% each quarter.
Beyond the time drain, the quality of their social media output was inconsistent. Different team members followed different procedures, and there was no standardized way to handle edge cases that are common in logistics. A recent audit revealed that 12% of completed social media 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 logistics team needed. They deployed a multi-agent workflow that breaks the social media process into discrete, automated steps — each handled by a specialized AI agent. The first agent monitors triggers from ShipStation and Google Sheets. The second agent analyzes and processes incoming requests using logistics-specific business logic. The third agent executes actions across connected tools and notifies team members via Airtable.
The beauty of the no-code approach was speed of implementation. The team had their first agent live within 90 minutes, and the full social media workflow was operational within a single afternoon. They used Arahi AI's template for logistics social media 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 social media instances with 99%+ accuracy — more than the team typically handled in a month.
The Results
Measurable improvements across key logistics social media metrics.
Task Completion Time
97% faster
Before
2-3 hours average
After
< 5 minutes
Team Productivity
250% increase
Before
Baseline
After
3.5x output
Quality Score
26% improvement
Before
78% accuracy
After
98.5% accuracy
Monthly Cost
85% savings
Before
$8,200/month
After
$1,200/month
Customer Satisfaction
35% increase
Before
3.4/5
After
4.6/5
“The difference is night and day. Our logistics clients used to wait days for social media to be completed. Now it happens in minutes, and the quality is consistently higher than what we achieved manually. Customer satisfaction scores went through the roof.”
VP of Customer Success
Regional freight company
Key Takeaways
The most important lessons from this logistics social media automation project.
AI-powered social media automation eliminated 88% of manual processing time for this logistics 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 by over 90%, significantly improving data quality and downstream decision-making.
The ROI was realized within the first month, with the solution paying for itself multiple times over through cost savings and productivity gains.
Implementation Timeline
From zero to production in 90 minutes — here's how they did it.
Step 1: Mapped the existing social media workflow
Documented every step of the current manual social media 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 social media workflow: connected ShipStation and UPS API as data sources, configured AI decision logic for logistics-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 social media instances, with the 2% of edge cases automatically flagged for human review.
Setup Time
90 minutes
AI Agents
2 AI agents
Tools Connected
5 integrations
Frequently Asked Questions
Common questions about automating social media in logistics.
Related Case Studies
Explore more AI automation success stories.
More Logistics Case Studies
Social Media in Other Industries
This case study represents a typical customer scenario. Individual results may vary.