Understanding and using Lookout predictions

Accurate forecasting requires continuous learning and adaptation. In this article, we'll explore how to get the most out of the forecasts with Future Demand Lookout.

Lookout predictions consider similar events, locations, and timeframes from millions of historical data points analyzed by the algorithm. Based on a number of relevant parameters, the algorithm calculates how sales of a specific future event will be affected by these parameters.

Important points to consider:

• Avoid Assumptions on Predicted Occupancy Rates:

  • One common pitfall in prediction is assuming that an event will definitely achieve the calculated occupancy rate. It's crucial to understand that predictions are based on a set of assumptions, and real-world factors may deviate over time from these assumptions.
  • Think of Lookout as a dynamic forecast that constantly adjusts based on real-time data such as your rolling sales forecast.

Decisive Factors:

• The accuracy of the prediction crucially depends on the availiability of relevant data points.
• Regularly updated sales data is a key component in this process. Ensure that the data reflects the most recent facts, allowing Lookout to make more accurate predictions.
• If sales data is only received towards the end of a campaign, this will affect the accuracy of the prediction.
• Modelling is based on historical information and marketing efforts. Material changes to how you usually market similar events can impact prediction accuracy. 

Conclusion:

By avoiding misleading assumptions, focusing on decisive factors, adjusting for timing differences in sales data, and conducting regular data maintenance, you can make optimal use of Future Demand's prediction. Lookout is a powerful tool, and with continuous training and attention to data quality, you'll unlock its full potential in predicting future demand. If you have any further questions or need assistance, feel free to reach out to our support team. Happy forecasting!