How To Use SAP CoPilot with Local Falcon: A Complete No-Code Guide

Have you ever wished you could have natural conversations about your Local Falcon data with a fully custom AI assistant? Well, by integrating Local Falcon with SAP CoPilot (formerly SAP Start Assistant), you can! And the best part is that there's no coding required.

In this guide, we'll walk you through exactly how to connect your Local Falcon data to SAP's enterprise AI assistant using mostly point-and-click configuration.

Understanding What We're Building

Before we get started, let's make sure you're crystal-clear on exactly what we're aiming to do through this integration: create a custom AI assistant that can answer questions related to your local search performance, like, "How are our Chicago rankings trending?" or "What patterns do you see in our "emergency service" keyword performance?," by analyzing your Local Falcon data in real time.

This integration will allow you to:

• Perform natural language queries about your rankings
• Get AI-powered insights into local search performance
• Identify local search trends automatically
• Receive proactive alerts about ranking changes

Getting Started: The Basic Setup

First, let's get your Local Falcon data flowing into SAP's systems. Don't worry; this is all point-and-click!

Step 1: Connecting Your Data

Log in to SAP Analytics Cloud and follow these exact steps:

1. Click "Create" > "Connection"
2. Choose "REST API Connection"
3. In the configuration panel, enter:
   
   

Connection Name: Local Falcon Data Base URL: https://api.localfalcon.com/v1 Authentication Type: API Key

1. Add your Local Falcon API key
2. Test the connection

Pro Tip: Make sure to name your connection something descriptive like "Local Falcon Production." You'll thank yourself later if you add more connections down the road!

Step 2: Creating Your Models

This is where we tell SAP CoPilot how to understand your data. In SAP Analytics Cloud:

1. Navigate to "Modeler"
2. Click "Create New Model"
3. Choose "REST API Source"

Now here's the most important part; we need three separate models:

Locations Model:

• Select the "/connected-locations" endpoint
• Map these fields:
• Location Name
• Address
• Place ID
• Store Code
• Set refresh to "daily"

Rankings Model:

• Choose the "/scan-reports" endpoint
• Map these critical fields:
• Place ID
• Keyword
• Ranking
• Grid Size
• Scan Date
• Enable real-time refresh

Trends Model:

• Use the "/trend-reports" endpoint
• Include these fields:
• Historical Rankings
• Date Range
• Location Details
• Keywords

Making it Talk: SAP Copilot Configuration

Now comes the fun part; teaching SAP CoPilot to understand questions about your data.

Setting Up Your AI Assistant

1. Open SAP CoPilot administration
2. Create a new skill called "Local Falcon Analytics"
3. Connect your data models
4. Add training phrases

Here's where many people go wrong; don't skip adding the training phrases. Add plenty of variations, like:

Location Questions: - "How is [location] performing?" - "Show me rankings for [city]" - "Compare [location1] and [location2]" - "Which locations need attention?" Ranking Questions: - "What's our average ranking in [city]?" - "Show trending keywords in [location]" - "Where are we losing rankings?" - "What patterns do you see in our data?"

Pro Tip: Add location-specific phrases for your actual business locations. It makes the responses much more natural.

The Magic Happens: Example Conversations

Next, let's look at how your new AI assistant will actually work. These are real examples from a production setup:

Basic Performance Check

You: "How are our Chicago locations performing?" Copilot: "I've analyzed your Chicago locations. Here's what I found: Overall Performance: - 6 locations actively tracked - Average ranking: 3.2 (up from 3.8 last month) - 85% of keywords in top 5 positions Standout Location: Michigan Avenue - Leading in 15 of 20 tracked keywords - Improved 22% since last month - Strong performance in service-related terms Attention Needed: West Loop - Dropped from position 2 to 4 on average - 3 key terms falling behind competitors - Grid coverage shows gaps in northwest area Would you like a detailed report for any specific location?"

Trend Analysis

You: "What patterns do you see in our emergency keywords?" Copilot: "I've analyzed trends in your emergency service keywords: Key Findings: - Rankings improve 30% during business hours - Weekend performance lags by 2.3 positions - Mobile searches show better results (+1.2 positions) Keyword Breakdown: 1. "emergency plumber" - Average position: 2.1 - Peaks at 8am and 5pm - Strong in northern suburbs 2. "24/7 repair service" - Average position: 3.4 - Most stable performance - Room for improvement in south region 3. "emergency HVAC" - Average position: 2.8 - Trending up (+15% this month) - Outperforming competitors Would you like me to generate an optimization plan for any of these terms?"

Making It Work Better: Best Practices

After setting up dozens of these integrations, here are the key things that we've found make the difference between a good setup and a great one:

Data Refresh Strategy

Don't just set it and forget it. Configure your refresh schedules like this:

• Location data: Daily refresh
• Rankings: Real-time during business hours
• Trends: Daily with weekly aggregation

Effective Queries

Teach your team to ask better questions:

• Be specific about locations
• Mention time periods when relevant
• Ask follow-up questions
• Use comparison requests

Regular Maintenance

Set up a simple maintenance schedule:

1. Daily: Check data freshness
2. Weekly: Review accuracy
3. Monthly: Update location lists
4. Quarterly: Full system review

When Things Go Wrong: Troubleshooting

Even the best setups occasionally have issues. Here's how to handle the most common ones:

Data Not Updating

• Check API key validity
• Verify connection settings
• Review rate limits
• Check error logs

Slow Responses

• Review data model optimization
• Check scheduling conflicts
• Clean up old data
• Verify index settings

Poor Quality Answers

• Add more training phrases
• Review data mapping
• Check permission settings
• Clear system cache

Taking It Further: Leveraging Advanced Features

Once you're comfortable with the basics, try using these advanced features:

Custom Alerts

Set up notifications for:

• Ranking drops over 3 positions
• New competitors appearing
• Grid coverage gaps
• Performance anomalies

Automated Reports

Schedule regular insights, including:

• Weekly performance summaries
• Monthly trend analysis
• Competitor movement reports
• Optimization recommendations

Conclusion: Your Next Steps

Integrating Local Falcon with SAP CoPilot provides you and your team with an additional tool that can help make your local SEO data more accessible and actionable.

Here's a summary of the basic steps needed to start using this powerful integration:

1. Set up your data connection
2. Create your models
3. Configure basic queries
4. Test thoroughly
5. Train your team

Keep in mind that the AI gets smarter the more you use it! So start with simple queries and gradually move on to more complex analyses as you and your team become comfortable with its capabilities to get even more out of this integration.

Ready To Get Started?

Begin with the data connection setup and work your way carefully and patiently through each step, making sure to take your time when adding the training phrases, as they're the foundation of good AI interactions. And remember, you can always come back to this guide as you build out your system!

If you need any additional assistance, SAP Support can help with CoPilot issues, while Local Falcon support can help with API-related questions. Don't hesitate to reach out if you have any questions or need a helping hand; this integration is powerful enough to be worth getting right!

Lastly, if you're looking for instant AI-powered insights into your local search performance, you can always try talking about your data with Falcon Assist, Local Falcon's built-in AI copilot for all things local SEO.