AI Agents Guide

Automate your business intelligence with AI agents that continuously analyze your store, identify opportunities, and provide actionable insights - like having a team of analysts working 24/7.

What are AI Agents?

AI Agents are specialized artificial intelligence assistants that autonomously perform business intelligence tasks for your store. Unlike the AI Command Center where you chat with AI, agents work in the background, analyzing data, generating reports, and alerting you to opportunities without you having to ask.

What makes them special:

Autonomous Operation - Run on schedules (daily, weekly) without manual intervention
Specialized Expertise - Each agent focuses on one business area (analytics, inventory, marketing, etc.)
Actionable Insights - Don't just report data, provide specific recommendations
Continuous Monitoring - Track KPIs and alert you to important changes
Learning System - Improve recommendations based on what works for your store

Common use cases:

Daily sales analysis and trend identification
Inventory alerts (low stock, overstock, dead inventory)
Customer behavior insights (churn risk, VIP identification)
Marketing performance reports (what's working, what's not)
Product recommendations (what to promote, what to discontinue)
Pricing optimization opportunities
Competitor monitoring and alerts

How AI Agents Work

AI Agents operate in three stages:

1. Data Collection

Agents continuously gather data from:

Your Shopify store - Orders, products, customers, inventory
Analytics platforms - Google Analytics, Facebook Pixel
Marketing channels - Meta Ads, Google Ads, email campaigns
External sources - Competitors, market trends, search data

2. Intelligent Analysis

Using advanced AI, agents:

Identify patterns - Sales trends, customer behaviors, seasonal fluctuations
Detect anomalies - Sudden drops in traffic, unusual order patterns
Predict outcomes - Future sales, inventory needs, churn probability
Find opportunities - Underperforming products, untapped markets
Benchmark performance - Compare against industry standards

3. Actionable Reporting

Agents deliver insights through:

Daily/Weekly reports - Scheduled summaries in your inbox or dashboard
Real-time alerts - Immediate notifications for critical issues
Recommendations - Specific actions you can take to improve
Automatic actions - Some agents can make changes with your approval

Example flow:

Inventory Agent runs at 6 AM daily
↓
Analyzes: 247 products, 14-day sales velocity, supplier lead times
↓
Identifies issues:
- 12 products will stock out in < 7 days
- 8 products haven't sold in 90 days (dead inventory)
- 3 products selling 3x faster than forecast
↓
Generates report with recommendations:
- Reorder: "Blue Running Shoes" (7 days of stock left, order 50 units)
- Discount: "Winter Jacket" (90 days no sales, recommend 30% off)
- Increase inventory: "Yoga Mat" (selling fast, risk of stockout)
↓
Sends to your dashboard + email at 7 AM
↓
You review and approve actions (one click)

Available AI Agents

Synton offers 100+ specialized AI agents:

Sales & Analytics Agents

Sales Analyzer

Daily/weekly sales reports
Trend identification (growing/declining products)
Revenue forecasting
Goal tracking

Performance Monitor

KPI dashboard (conversion rate, AOV, traffic)
Anomaly detection (sudden drops/spikes)
Benchmark comparisons
Alert system

Customer Analytics Agent

Customer segmentation (VIP, at-risk, new)
Lifetime value calculation
Churn prediction
Retention recommendations

Inventory Agents

Inventory Optimizer

Stock level monitoring
Reorder recommendations
Dead inventory identification
Seasonal demand forecasting

Supplier Performance Agent

Supplier reliability tracking
Lead time analysis
Quality issue detection
Alternative supplier suggestions

Marketing Agents

Marketing Performance Agent

Channel ROI analysis (Meta, Google, Email)
Campaign effectiveness scoring
Budget allocation recommendations
A/B test analysis

Content Strategy Agent

Blog post topic suggestions
SEO keyword opportunities
Social media content ideas
Email campaign recommendations

Email Marketing Agent

List health monitoring
Segmentation suggestions
Send time optimization
Subject line recommendations

Product Agents

Product Performance Agent

Best/worst sellers identification
Pricing optimization suggestions
Bundle opportunities
Cross-sell recommendations

Review Monitor Agent

Review sentiment analysis
Negative review alerts
Review response suggestions
Rating trend tracking

Customer Service Agents

Support Ticket Analyzer

Common issue identification
Response time monitoring
Customer satisfaction tracking
Knowledge base gap detection

Refund Risk Agent

High-refund product alerts
Refund pattern analysis
Quality issue detection
Prevention recommendations

Operations Agents

Fulfillment Agent

Shipping time monitoring
Carrier performance analysis
Shipping cost optimization
Delivery issue alerts

Fraud Detection Agent

Suspicious order flagging
Fraud pattern detection
Risk scoring
Chargeback prevention

Deploying AI Agents

Step 1: Deploy via AI Chat

Open the AI Command Center and say:

You: "Set up AI agents for my store"

AI: "I'll help you set up AI agents to automate your business intelligence. Let's start by understanding what insights you need most.

Which areas would you like agents to monitor?

Sales & Revenue - Daily performance, trends, forecasting
Inventory Management - Stock alerts, reorder recommendations
Marketing Performance - ROI analysis, campaign effectiveness
Customer Insights - Behavior, churn risk, segmentation
Product Performance - Best sellers, pricing optimization
All of the above - Complete business intelligence suite

What would you like?"

You: "All of the above"

AI: "Perfect! I'll deploy a comprehensive AI agent suite for your store.

Agents I'm deploying:

Daily Reports (Run at 7 AM):

✅ Sales Analyzer - Yesterday's performance + trends
✅ Inventory Optimizer - Stock alerts + reorder recommendations
✅ Customer Analytics - New customers, churn risks, VIPs

Weekly Reports (Run Monday 8 AM):

✅ Marketing Performance - Last week's campaign results
✅ Product Performance - Best/worst sellers + recommendations
✅ Support Ticket Analyzer - Common issues + satisfaction

Real-Time Alerts:

✅ Fraud Detection - Suspicious orders (immediate alerts)
✅ Inventory Alerts - Critical low stock (< 3 days)
✅ Review Monitor - New negative reviews (< 3 stars)

Delivery:

📧 Email reports to: [your email]
📱 Dashboard: app.synton.ai/app/agent-results
🔔 Push notifications for critical alerts (optional)

Should I deploy these agents?"**

You: "Yes, deploy them"

AI: "✅ Deploying 9 AI agents for your store...

Setup complete!

First reports:

Daily agents: Tomorrow at 7 AM
Weekly agents: Next Monday at 8 AM
Real-time alerts: Active immediately

You'll receive:

Welcome email with setup confirmation
Guide to reading your first report
Dashboard access to all agent results

Tip: Agents learn from your feedback. Mark insights as 'helpful' or 'not helpful' to improve future recommendations."

Step 2: Configure Agent Settings

Customize how agents work:

You: "Change the Sales Analyzer to run at 9 AM instead of 7 AM"

AI: "✅ Updated Sales Analyzer schedule to 9 AM daily.

Current schedule:

9:00 AM - Sales Analyzer
7:00 AM - Inventory Optimizer
7:30 AM - Customer Analytics

Would you like all daily reports at the same time, or staggered like this?"**

You: "All at 9 AM"

AI: "✅ All daily agents now run at 9 AM. You'll receive one consolidated email with all reports."

Step 3: Review First Report

Check your email or dashboard the next day:

Sample Agent Report (Sales Analyzer):

📊 Daily Sales Report - January 19, 2024

**Yesterday's Performance:**
Revenue: $2,847 (+18% vs. Wed) ⭐
Orders: 34 (+6 vs. Wed)
AOV: $83.74 (+11% vs. Wed)
Conversion: 3.2% (↔️ flat)

**Key Insights:**

✅ Strong Day! Revenue up 18% vs. same day last week
⚠️ Conversion rate flat despite higher traffic - check checkout flow

**Trending Products (Last 7 Days):**
1. "Blue Running Shoes" - 47 sales (+34% WoW) 🔥
2. "Yoga Mat Premium" - 29 sales (+18% WoW)
3. "Protein Powder" - 23 sales (-8% WoW) ⚠️

**Recommendations:**
1. Promote "Blue Running Shoes" (high demand, good margin)
   → Action: Feature in homepage banner

2. Investigate "Protein Powder" decline (usually top seller)
   → Check: Are competitors running promotions?

3. Create bundle: Running Shoes + Gym Socks ($89 value for $79)
   → Potential: +$400/week in bundle sales

**Click to approve recommendations** [View in Dashboard]

Managing AI Agents

Viewing Agent Results

Check all agent reports:

You: "Show me my AI agent reports"

AI: "Here are your latest AI agent reports:

Today (Jan 19):

Sales Analyzer (9:00 AM) - Revenue +18%, 3 recommendations
Inventory Optimizer (9:00 AM) - 4 low stock alerts, 2 reorder suggestions
Customer Analytics (9:00 AM) - 12 new customers, 3 churn risks identified

This Week:

Marketing Performance (Mon 8 AM) - Meta ads ROI 3.2x, Google 1.8x
Product Performance (Mon 8 AM) - 8 winners, 5 losers, pricing suggestions
Support Tickets (Mon 8 AM) - Avg response time 4.2h, top issue: shipping delays

Real-Time Alerts (Last 24h):

🔴 Fraud Detection: 1 suspicious order flagged (review needed)
⚠️ Inventory Alert: "Blue Running Shoes" - 3 days of stock left

Which report would you like to see in detail?"**

You: "Show me the Product Performance report"

AI: "Product Performance Report - Week of Jan 15-21

🏆 Top Performers (Promote These):

Blue Running Shoes - $3,847 revenue (34% growth)
- Profit margin: 42%
- Inventory: ⚠️ Low (3 days)
- Recommendation: Restock ASAP + feature in ads
Yoga Mat Premium - $2,116 revenue (18% growth)
- Profit margin: 55%
- Inventory: ✅ Good (45 days)
- Recommendation: Upsell with yoga blocks
Protein Powder Vanilla - $1,923 revenue (12% growth)
- Profit margin: 38%
- Inventory: ✅ Good (32 days)
- Recommendation: Create subscription offer

⚠️ Underperformers (Take Action):

Winter Jacket Blue - $0 revenue (90 days no sales)
- Inventory: 47 units (dead stock!)
- Recommendation: Discount 40% to clear, or return to supplier
Running Socks Pack - $124 revenue (-45% vs. last week)
- Issue: Price increase on Jan 12 ($19.99 → $24.99)
- Recommendation: Revert to $19.99 or bundle with shoes

💡 Opportunities:

Bundle: Running Essentials (Shoes + Socks + Water Bottle)
- Estimated demand: 15 bundles/week
- Bundle price: $119 (vs. $139 separate)
- Projected revenue: +$1,785/week
Cross-sell: Gym Bag
- 78% of running shoe buyers also buy bags
- You don't sell gym bags (missed opportunity)
- Recommendation: Add gym bag to catalog

Should I implement any of these recommendations?"

Approving Agent Recommendations

Agents can take actions with your approval:

You: "Approve the running essentials bundle"

AI: "✅ Creating Running Essentials Bundle:

Bundle includes:

Blue Running Shoes ($89.99)
Running Socks 3-Pack ($19.99)
Water Bottle ($12.99)

Bundle pricing:

Individual total: $122.97
Bundle price: $109.99 (save $12.98)

Marketing:

Featured on homepage
Discount code: RUNMORE (auto-applied)
Meta ad campaign ($50/day budget)

Created! Bundle is live on your store. I'll track performance and report back in 7 days."

Agent Scheduling

Control when agents run:

You: "Change the Marketing Performance agent to run daily instead of weekly"

AI: "Are you sure you want Marketing Performance to run daily? Here's what to consider:

Weekly (current):

✅ Gives enough data for meaningful insights
✅ Less noisy (filters out daily fluctuations)
❌ Slower to detect issues

Daily:

✅ Faster issue detection
❌ More volatile data (harder to spot real trends)
❌ May lead to over-reaction to normal fluctuations

My recommendation: Keep weekly for overall performance, but add a separate 'Marketing Alerts' agent for daily anomaly detection.

Should I:

Keep weekly + add daily alerts
Switch to daily (not recommended)
Keep as-is"**

You: "Option 1 - keep weekly + add daily alerts"

AI: "✅ Created Marketing Alerts agent:

Runs: Daily at 10 AM Monitors:

Ad spend anomalies (>20% increase without approval)
Campaign performance drops (>30% decrease in conversions)
Budget exhaustion (90% of daily budget spent by noon)

Alerts only - no full report. You'll get notifications only when something needs attention.

Your weekly Marketing Performance report continues as before."

Advanced Agent Features

Custom Agents

Create specialized agents for your needs:

You: "Create a custom agent to monitor my wholesale customers"

AI: "I'll create a Wholesale Customer Agent for you.

What should this agent monitor?

Tell me what insights you need, for example:

Order frequency (are they ordering regularly?)
Order size trends (are orders getting bigger/smaller?)
Payment terms (overdue invoices?)
Reorder patterns (predict next orders?)
Price sensitivity (discount usage?)

What's most important for your wholesale business?"**

You: "Monitor order frequency, predict reorders, and alert me if a customer goes 30 days without ordering"

AI: "✅ Creating Wholesale Customer Agent:

Monitoring:

Order frequency per customer (baseline: last 90 days)
Reorder pattern prediction (AI learns typical cadence)
Inactivity alerts (30+ days since last order)

Reports:

Weekly: Reorder predictions for upcoming week
Real-time: Immediate alert when customer hits 30-day inactivity

First report: Next Monday with initial baseline analysis

Sample insight you'll get: 'ABC Company typically orders every 18 days. Last order was 28 days ago (2 days from alert threshold). Predicted next order: This week. Suggested action: Proactive outreach call.'

Agent deployed!"

Agent Learning & Feedback

Improve agents with feedback:

You: "The inventory agent keeps recommending I restock items that don't sell well"

AI: "Let me check the Inventory Optimizer's recent recommendations...

I see the issue. The agent is using simple 'days of stock remaining' but not considering:

Seasonal demand (winter items in summer)
Product lifecycle (discontinued items)
Your profit margins (low-margin items not worth restocking)

I'll retrain the agent with these criteria:

✅ Consider seasonal trends (don't restock winter coats in July)
✅ Exclude products you've marked 'discontinue'
✅ Prioritize high-margin items (>30% margin)
✅ Factor in sales velocity trend (declining items = lower priority)

Should I apply these improvements?"**

You: "Yes, improve it"

AI: "✅ Inventory Optimizer retrained with new criteria.

Changes you'll see:

Smarter seasonal recommendations
Focus on profitable inventory
Better prioritization (urgent vs. can wait)

Testing: I'll run a simulation on your last 30 days of recommendations and show you the difference. One moment...

Before vs. After:

Before: 47 restock recommendations (24 were poor choices)
After: 31 restock recommendations (all high-priority, high-margin)
Accuracy: +62%

The improved agent is now active. You'll see better recommendations starting tomorrow."

Multi-Agent Collaboration

Agents can work together:

You: "Can agents work together to find opportunities?"

AI: "Yes! Agents can collaborate. Here's an example of multi-agent intelligence:

Scenario: Product Launch Opportunity

Step 1: Product Performance Agent identifies:

"Yoga mats" selling 3x faster than forecast

Step 2: Customer Analytics Agent analyzes buyers:

78% are women age 25-45
45% also search for 'yoga blocks' on your site
32% bounce because you don't sell blocks

Step 3: Marketing Performance Agent checks competition:

Competitors selling yoga block sets at $29.99
Facebook ads for yoga blocks: 4.2% CTR (high intent!)

Step 4: Inventory Optimizer evaluates:

Supplier can deliver yoga blocks in 10 days
Estimated cost: $8/unit, sell for $29.99 (73% margin!)

Combined Recommendation: 'Launch yoga blocks product. High demand from existing customers, low competition, excellent margins. Estimated revenue: +$2,400/month.'

This is automatic! Agents collaborate behind the scenes. Should I enable multi-agent opportunities?"**

You: "Yes, enable it"

AI: "✅ Multi-agent collaboration enabled.

How it works:

Agents share insights in the background
When multiple agents identify the same opportunity from different angles, they collaborate
You receive combined recommendations (higher confidence)

You'll see reports like: '🔗 Multi-Agent Insight: Product Performance + Customer Analytics + Marketing Performance'

This ensures recommendations are backed by multiple data sources."

Agent Alerts & Notifications

Configure alert preferences:

You: "I'm getting too many alerts. Can you reduce them?"

AI: "Let me check your current alert settings...

Current: 47 alerts in last 7 days

Breakdown:

Critical (require immediate action): 8
Important (review within 24h): 23
Informational (FYI): 16

Problem: You're getting too many 'Informational' alerts (noise).

Recommendation:

Keep: Critical + Important alerts (31/week)
Consolidate: Informational → Daily digest email
Add: Smart batching (group similar alerts)

New alert policy:

🔴 Critical: Immediate (fraud, critical low stock, major issues)
⚠️ Important: Once per day digest (morning report)
ℹ️ Informational: Weekly summary only

This reduces alerts from 47/week to ~10-15/week (only urgent items).

Should I apply this?"**

You: "Yes"

AI: "✅ Alert preferences updated.

New alert flow:

Critical alerts: Real-time (SMS or push notification)
Important alerts: Daily digest at 9 AM
Informational: Weekly summary (Mondays)

You should see 70% fewer interruptions while still catching all critical issues."

Agent Performance & ROI

Measuring Agent Impact

Track the value agents provide:

You: "How much value have the AI agents provided?"

AI: "Here's your AI Agent ROI report since deployment (90 days ago):

Revenue Impact:

Implemented recommendations: 47
Revenue increase: +$23,847 (18% growth)
Estimated agent contribution: $14,320 (60% of growth)

Top Value Agents:

Product Performance Agent - $8,940 value
- Identified 3 winning products to promote
- Flagged 5 products to discount/discontinue
- Suggested 2 profitable bundles
Inventory Optimizer - $3,280 value
- Prevented 8 stockouts (missed sales avoided)
- Identified $2,100 in dead inventory to clear
- Optimized reorder timing (reduced holding costs)
Marketing Performance Agent - $1,870 value
- Found 3 underperforming ad campaigns to pause ($890 saved)
- Identified 2 high-ROI campaigns to scale ($980 additional revenue)

Cost Savings:

Ad spend optimization: $1,240 saved
Inventory holding costs: $680 saved
Prevented stockouts: $2,100 in missed sales avoided
Total savings: $4,020

Time Savings:

Manual reporting time: ~12 hours/week before agents
Current time: ~2 hours/week reviewing agent reports
Time saved: 10 hours/week (520 hours over 90 days)

ROI:

Investment: $79/mo Professional plan (agents included)
Returns: $14,320 revenue + $4,020 savings = $18,340
ROI: 7,300% over 90 days

Bottom line: Agents have paid for themselves 73x over."

Agent Success Metrics

Monitor agent performance:

You: "Which agents are performing best?"

AI: "Here's your agent performance dashboard:

Top Performers (High Impact):

Sales Analyzer ⭐⭐⭐⭐⭐
- Accuracy: 94% (predictions vs. actual)
- Helpful rating: 4.8/5 (from your feedback)
- Recommendations implemented: 82%
- Status: Excellent, no changes needed
Inventory Optimizer ⭐⭐⭐⭐⭐
- Accuracy: 91%
- Stockout prevention: 15 instances
- Helpful rating: 4.7/5
- Status: Performing well
Customer Analytics ⭐⭐⭐⭐
- Churn prediction accuracy: 87%
- VIP identification: 100% accurate
- Helpful rating: 4.2/5
- Status: Good, improving over time

Underperformers (Need Attention):

Email Marketing Agent ⭐⭐⭐
- Subject line recommendations: 61% success rate (below 75% target)
- Helpful rating: 3.4/5
- Issue: Not adapting to your audience well
- Action: I'll retrain with your top-performing emails
Review Monitor ⭐⭐
- Sentiment analysis: 72% accurate
- Helpful rating: 2.9/5
- Issue: Too many false positives (flagging neutral reviews as negative)
- Action: Needs recalibration

Should I retrain the underperforming agents?"**

You: "Yes, retrain them"

AI: "✅ Retraining Email Marketing and Review Monitor agents...

Email Marketing Agent:

Analyzing your last 50 email campaigns
Learning from your best-performing subject lines
Adapting to your audience's preferences
ETA: Improved recommendations in 48 hours

Review Monitor Agent:

Recalibrating sentiment threshold (less sensitive)
Training on your product-specific language
ETA: More accurate alerts starting tomorrow

I'll report back in 7 days with performance improvements."

Troubleshooting

Agent Not Running

Problem: Agent didn't send scheduled report

Solutions:

You: "I didn't receive my daily sales report this morning"

AI: "Let me check the Sales Analyzer agent status...

Found the issue: The agent ran at 9 AM, but the email failed to send due to a temporary issue with your email provider.

Report was generated: Yes, available in dashboard Email status: Failed at 9:03 AM, retrying now...

✅ Email sent successfully! Check your inbox.

To prevent this:

I've added your backup email: [backup email]
Critical reports will now go to both addresses
Dashboard always has reports even if email fails

Would you like me to resend the last 3 days of reports?"

Inaccurate Recommendations

Problem: Agent recommendations don't make sense

Solutions:

You: "The inventory agent recommended I restock winter coats, but it's summer"

AI: "You're right - that's a poor recommendation. Let me investigate...

Issue found: The Inventory Optimizer is using last year's sales data without considering seasonality.

Why this happened:

Agent deployed 30 days ago (not enough data to learn seasonal patterns)
Using simple 'days of stock' calculation
Not factoring in current season

Fix:

I'll manually set seasonal rules for winter items
Agent will learn seasonal patterns over next 90 days
For now: winter items won't trigger restock recommendations in summer

✅ Applied fix. You won't see out-of-season recommendations anymore.

Learning: As agents gather more data, they'll automatically learn your seasonal patterns. For now, I've given them a head start with manual rules."

Too Many False Positives

Problem: Agent alerts that aren't useful

Solutions:

You: "The fraud detection agent flags almost every order as suspicious"

AI: "Let me check the Fraud Detection agent's sensitivity settings...

Issue: Agent is set to 'Very Strict' mode (flags 35% of orders)

Your store profile:

Average risk: Low (1.2% actual fraud rate)
Industry benchmark: 2.8%
Current setting: Appropriate for high-risk stores only

Recommendation: Lower sensitivity to 'Moderate'

Will flag 8-12% of orders (only genuine risks)
Reduces false positives by 70%
Still catches 95% of actual fraud

Should I adjust the sensitivity?"**

You: "Yes, use moderate sensitivity"

AI: "✅ Fraud Detection sensitivity adjusted to Moderate.

What this means:

Fewer false alarms (expect 3-4 flags/week instead of 15-20)
Focus on high-confidence fraud indicators
You can manually flag additional orders if needed

I'll monitor fraud rates for 30 days to ensure we're still catching real fraud. If we miss any, I'll adjust."

Best Practices

Start Small, Scale Up

Don't deploy all agents at once:

Week 1: Deploy 2-3 core agents (Sales, Inventory, Customer)
Week 2-3: Learn to use their insights effectively
Week 4+: Add specialized agents as needed

Why: Prevents overwhelming yourself with reports

Review Reports Regularly

Set a routine:

Morning: Review daily agent reports with coffee (10 min)
Monday: Deep dive into weekly reports (30 min)
Monthly: Analyze agent performance and ROI

Consistency is key: Agents learn from your feedback and implemented recommendations

Provide Feedback

Train your agents:

Mark insights as "helpful" or "not helpful"
Explain why a recommendation doesn't work
Ask agents to adjust parameters

Example:

You: "This recommendation to discount yoga mats doesn't make sense - they're selling well"

AI: "You're right! Let me adjust the Product Performance agent's discount logic:

Current rule: Recommend discount if sales drop >20% WoW Your feedback: Don't recommend discounts for products with healthy sales

New rule: Only recommend discounts for products with:

Sales drop >40% WoW, AND
Inventory >60 days, AND
Margin >40% (can afford discount)

This prevents premature discounting of good sellers."

Implement Recommendations Quickly

Act on insights:

Agents identify opportunities with limited windows
"Hot product" recommendations are time-sensitive
Inventory alerts prevent stockouts (missed revenue)

Quick implementation = maximum value

Monitor Agent ROI

Track what works:

Which agent recommendations drive the most revenue?
Which reports do you actually use?
Which agents waste your time?

Optimize your agent suite based on results

FAQs

Q: How much do AI Agents cost? A: Included in Professional ($79/mo) and Enterprise ($249/mo) plans. Uses AI credits for analysis (typically $5-15/mo depending on usage).

Q: Can I pause agents? A: Yes! You can pause any agent at any time and resume later. No data is lost.

Q: How many agents can I run? A: Unlimited! But we recommend 5-10 agents to avoid report overload.

Q: Do agents make changes without approval? A: No. Agents only recommend actions. You must approve before any changes are made to your store (except optional auto-approve for specific actions).

Q: Can agents integrate with other tools? A: Yes! Agents can pull data from Google Analytics, Meta Ads, Klaviyo, and 20+ other platforms.

Q: How accurate are agent predictions? A: Accuracy varies by agent and data quality. Sales forecasts: 85-95%, inventory predictions: 88-92%, churn predictions: 82-90%. Accuracy improves over time as agents learn.

Q: What if an agent recommendation is wrong? A: Mark it as "not helpful" and explain why. The agent learns from your feedback and improves future recommendations.

Q: Can I create my own custom agents? A: Yes! Tell the AI what you need monitored, and it can create custom agents with specific logic for your business.

Q: Do agents work for new stores with limited data? A: Yes, but with caveats. Agents need 30-60 days of data for accurate insights. For new stores, agents provide more generic recommendations initially and improve as data accumulates.

Q: Can I export agent reports? A: Yes! All reports can be exported as PDF, CSV, or sent to Google Sheets/Excel automatically.

Next Steps

Now that you understand AI Agents:

Deploy core agents - Start with Sales, Inventory, and Customer agents
Review first reports - Understand what insights agents provide
Implement recommendations - Act on high-confidence suggestions
Provide feedback - Help agents learn your business
Scale up - Add specialized agents as needed

Quick start command: "Set up AI agents for my store"

Related guides:

Analytics - Manual data analysis with AI Chat
Competitor Intel - Competitive intelligence agents
Meta Ads - Advertising-specific agents

Need help? Ask the AI: "Explain AI agents" or "Which agents should I use?"