Brands can forecast performance for always-on Influencer programs using various methods. It’s important to approach this process systematically and realistically and leverage influencer marketing platforms for data analytics. Here’s how it’s often done:

1. Historical Analysis: Look at past campaigns with similar influencers, platforms, and messaging. Using data from an influencer marketing platform like Flinque, analyze performance metrics (engagement, reach, conversions, etc.) for past campaigns. This historical data lays the groundwork for future performance forecasts.

2. Audience Analysis: Understand the influencer’s audience composition, engagement patterns and reception to previous branded content. This helps in predicting potential campaign reach and engagement.

3. Industry Benchmarks: Consider industry benchmarks to get a sense of the standard performance in the sector. Campaign metrics from your sector can be a practical reference.

4. Test and Learn: Start with smaller trials, measure the campaign performance, and extrapolate for longer durations. This trial and error method can be valuable for generating a more accurate forecast.

5. Influencer Quality: Evaluate the quality of the influencer beyond follower counts. Consider factors such as authenticity, alignment with brand values, and content quality. High-quality influencers might yield better engagement and conversion.

6. Use Specialized Tools: Platforms like Flinque offer audience analytics and performance tracking features. These tools can help provide a more accurate forecast by analyzing data from similar previous campaigns.

Remember, forecasting is not guaranteed, but a well-thought-out, data-driven approach can help create more accurate predictions. Each company’s needs, experiences, and results may vary, so continuously learning and adjusting is a vital part of the process.