How does the Future Demand's attribution model work?

Future Demand utilizes an advanced attribution model to enhance our client's marketing strategies and efficiently allocate resources.

Future Demand seamlessly integrates with your Facebook Business account to collect key data related to your advertising campaigns. This includes user interactions such as ad clicks, impressions/reach, and various conversion metrics.

However, with the introduction of Apple's App Tracking Transparency (ATT) policy and similar privacy initiatives, there are severe limitations on what ad platforms can measure. This has led to major changes in the way conversions are calculated. The live entertainment industry was not alone in adapting to the challenges of ATT, shifting its focus from relying on third-party tracking to fostering direct relationships with attendees. Today, machine learning predicts how many conversions have taken place. Because it relies on huge data sets and statistical models, it only works reliably for advertisers with high weekly ad spend, which many promoters do not have due to the nature of their business.

Future Demand offers an alternative solution designed to enable smaller promoters to gain insight into the efficiency of their ad spend. By combining multiple data sources, such as ticketing data, conversion metrics, and aggregated behavioural data from ad platforms, and our custom industry-specific attribution models, Future Demand enables meaningful campaign measurement for performance marketing campaigns for almost any budget size (we tend to see limitations for campaigns with less than 250-300 EUR/USD ad spend).

Throughout the duration of a campaign, our algorithm continuously evaluates the effectiveness of your ads and allows our platform to make any necessary adjustments to improve performance. Tailor-made algorithms analyse campaign data to determine the impact of each campaign on ticket sales.

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Our attribution model also assumes that other marketing activities (e.g. email marketing campaigns, newsletters, group discounts, etc.) influence demand and need to be taken into account in any analysis. This means that when attributing credit to campaigns, the distinctive demand patterns of other marketing campaigns are excluded.

Excluding these other demand patterns removes potential noise or bias from the data analysis. This ensures that the insights from our attribution model are focused on the impact caused by Future Demand campaigns, ensuring that our platform's data-driven campaign optimization increases ticket sales for your event.

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We continually compare and evaluate our attribution model with other methods. The results show that our model is at least as accurate, and in some cases more specific because we have customized our model for the performing arts and live entertainment industry.