Using AI to Adjust Strategy in Real Time Based on Company Performance #S13E9

ChatGPT Masterclass - AI Skills for Business Success

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15d ago 8:30

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This is Season 13, Episode 9 of the ChatGPT Masterclass: AI Skills for Business Success.

In the last episode, we explored how to use AI for performance reviews and strategy-driven employee feedback. We discussed how AI can track individual and departmental performance in real time, generate automated reports, and provide actionable coaching.

Today, we’re focusing on how to use AI to adjust strategy in real time based on company performance.

Many businesses struggle because strategic decisions are based on old data. If you wait until a quarterly review to adjust your strategy, you’re already too late. AI allows you to track performance continuously and make data-driven decisions on the fly.

By the end of this episode, you’ll know how to get real-time business data into AI, set up AI-driven monitoring systems, automate recommendations, and make proactive strategy adjustments based on real-time insights.

Step 1: Getting Real-Time Data into AI – The Easiest Methods

Before AI can help you adjust strategy, it needs real-time business data. There are several ways to get this data into AI, depending on your setup. Let’s go over the easiest and most practical methods.

Option 1: Manually Export Data from Business Tools and Feed It into AI

If you’re just starting, the simplest way to get real-time insights is by manually exporting key reports from your CRM, sales platform, or marketing dashboard and pasting the data into AI.

For example:

Export a CSV from your CRM with sales data.
Copy the latest performance report from Google Analytics.
Download your marketing campaign data from Facebook Ads or LinkedIn Ads.

Once you have this data, you can paste key figures into AI and ask for strategic insights:

"Analyze this sales report. Identify any major trends, unexpected drops, or opportunities for strategic adjustments."

This is the easiest way to start without setting up automation.

Option 2: Automate Data Flow with Zapier or Make (formerly Integromat)

If you want automatic updates without manual work, tools like Zapier or Make can send real-time business data directly to AI.

For example:

Sync sales data from HubSpot or Salesforce into Google Sheets automatically.
Pull marketing performance metrics from Facebook Ads every hour and update a report.
Send customer service trends from Zendesk or Intercom into a tracking dashboard.

Once the data is collected, AI can analyze it without requiring you to copy-paste manually.

You can set up AI to automatically check the latest numbers: "Every Friday, summarize the last seven days of sales and marketing performance. Identify any deviations from strategy and suggest potential adjustments."

This method saves time and ensures that AI always works with the most recent data.

Option 3: Connect AI Directly Using an API

For advanced users, connecting AI directly via an API allows real-time insights with zero manual effort.

For example:

Use OpenAI’s API to pull customer feedback and generate automated reports.
Connect your AI to Stripe or PayPal to monitor revenue trends and cash flow in real time.
Automatically analyze competitor activity using AI-driven web scraping.

If you work with a developer or no-code tools like Retool or Bubble, you can create a fully automated AI-powered business intelligence system.

This method is more advanced but allows instant strategic adjustments based on live business data.

Step 2: Set Up AI-Powered Strategy Monitoring

Once you’ve set up a way to get real-time business data into AI, the next step is to automate monitoring and detection of key trends.

Ask AI to monitor your key performance indicators (KPIs):

"Analyze sales, marketing, and financial data daily. Compare actual performance with strategic targets and alert me when adjustments may be needed."

For example, AI can flag issues like:

Sales dropping in a key market.
Marketing campaigns underperforming.
Customer churn increasing.

If AI detects a deviation from expected performance, it can automatically generate a strategy adjustment alert.

For example, if customer engagement is lower than expected, AI might generate an insight like:

"Customer engagement in the last 30 days is 25 percent lower than forecast. Consider adjusting content strategy, increasing ad spend, or refining targeting parameters."

This ensures that you don’t wait until a quarterly meeting to realize something isn’t working.

Step 3: Automate AI-Generated Strategy Adjustments

Once AI detects a performance issue, it can generate actionable strategy adjustments.

For example, if new customer conversions are lower than expected, AI can analyze data and provide recommendations:

"Sales conversions have dropped by 15 percent in the last month. Based on competitor analysis, consider adjusting pricing by 5 percent, launching a limited-time offer, and refining your value proposition."

For a marketing campaign, AI might generate:

"Email open rates are down by 20 percent. Consider adjusting subject lines, A/B testing headlines, and increasing personalization."

By automating AI-generated strategy recommendations, businesses can quickly adapt and stay competitive.

Step 4: AI-Powered Scenario Planning – Test Strategy Adjustments Before Implementing

Before making changes, AI can simulate potential outcomes and help predict which strategy adjustment is most effective.

For example, if you’re considering a price change, AI can analyze different scenarios:

"Simulate the impact of increasing or decreasing prices by 5 percent, 10 percent, and 15 percent. Identify which strategy is likely to maximize revenue while maintaining profitability."

For marketing strategy changes:

"Compare three different content marketing approaches and predict which one is likely to generate the highest return on investment based on past performance."

By testing adjustments before implementing them, businesses reduce risk and make smarter strategic decisions.

Step 5: Automate AI-Powered Strategy Reports and Alerts

AI can also be used to send regular strategy reports and alerts so you always stay updated on necessary adjustments.

For example, you can automate an AI-generated weekly strategy summary:

"Every Monday, generate a strategy insights report highlighting key business performance trends, potential strategy risks, and recommended adjustments."

Or set up real-time alerts when key metrics shift:

"Alert me immediately if revenue drops by more than 10 percent in a 30-day period or if customer churn rate increases unexpectedly."

By setting up automated AI reports and alerts, you ensure that you always stay ahead of potential business risks and opportunities.

Pro Tips and Common Mistakes

✔ Pro Tip: Use AI to Identify Strategy Risks Before They Happen
AI can identify warning signs before they become major problems.

Try this:
"Analyze the top three risks to our current strategic plan. Identify potential threats based on customer behavior, market trends, and competitor activity."

❌ Common Mistake: Only Looking at AI Insights Without Taking Action
AI should not just be a reporting tool—it should help drive actual decisions.

Try this:
"Every Friday, generate a decision-making summary based on AI-generated strategy insights and propose specific actions."

Practical Takeaway

Your challenge for today:

Set up a system to get real-time business data into AI. Choose manual exports, Zapier, or an API connection.
Define the key performance indicators AI will track for real-time strategy adjustments.
Automate AI-generated strategy recommendations based on business performance data.
Use AI-powered scenario planning to test adjustments before making changes.
Implement AI-powered strategy reports and alerts to track ongoing progress.

By following these steps, you’ll ensure that your strategy is continuously optimized and adjusted in real time based on business data.

Call-to-Action

If you found this episode useful, subscribe to the podcast so you don’t miss the final episode of this season, where we’ll bring everything together and discuss how to run a fully AI-optimized strategy execution process.

See you in the next episode!

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