Vista Intelligence is the shared AI layer in Vista software that transforms moviegoer, operational, and market data into actionable predictions, insights, and recommendations. These insights power Vista Cloud applications and workflows, allowing you to operate more efficiently and effectively across your organisation while delivering outstanding entertainment experiences to your guests.
Vista Intelligence powers features in Movio EQ, Horizon, Film Manager, React, and other Vista Cloud solutions.
Vista Intelligence models
Currently, the following models (systems that use data to generate insights or predictions) make up Vista Intelligence.
Projected CLV
Projected CLV (customer lifetime value) forecasts how much a moviegoer is likely to spend over the next three months. This helps you identify high-value guests and better understand the future value of your audience.
Data source and locations
Projected CLV is generated from Movio data and surfaced in Movio EQ and under Forecasts in the Members tab in Oneview.
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Moviegoer personas
Moviegoer personas group guests according to shared behavioural characteristics. Personas help you understand different audience types and tailor marketing, loyalty, and engagement activities to those audiences.
Data source and locations
Moviegoer personas are generated from Movio data and surfaced in Movio EQ and Film Manager forecasting reports.
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Propensity Algorithm™
Propensity Algorithm™ predicts which films a moviegoer is most likely to be interested in based on their historical behaviour and preferences. This information can be used to improve your targeting and personalisation.
Data source and locations
The Propensity Algorithm™ is calculated and surfaced in Movio EQ, contributes to forecast signals in Film Manager, and is surfaced as audience insights in Oneview.
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Projected churn
Projected churn estimates the likelihood that a moviegoer will not make a purchase within the next three months. This helps you identify guests who may benefit from re-engagement campaigns.
Data source and locations
Projected churn is generated from Movio data and surfaced in Movio EQ and under Forecasts in the Members tab in Oneview.
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Forecast signals
Forecast signals are behavioural, demographic, presales, and film-similarity information used to improve attendance forecasting. These signals support more accurate demand predictions.
Location
Forecast signals are used to generate the box-office forecast in Film Manager.
Schedule optimisation
Schedule optimisation recommends the allocation of screens and sessions using predicted demand and operational constraints. This helps you build schedules that better match expected attendance.
Location
Schedule optimisation is used in the assisted-scheduling feature in Film Manager.
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Movie similarity
Movie similarity measures how closely two films resemble each other using factors such as metadata, content characteristics, and visitation patterns. This is used by Movio EQ’s Propensity Algorithm™ for audience analysis and to support box-office forecasting.
Data source and locations
Movie similarity is calculated using film metadata and moviegoer data from Movio EQ and contributes to the Propensity Algorithm™ in Movio EQ and forecast signals in Film Manager’s box-office forecast.
Audience similarity
Audience similarity identifies how closely the audiences of two films align based on actual moviegoing behaviour, helping you understand audience overlap.
Data source and locations
Audience similarity is calculated using moviegoer-behaviour data from Movio EQ and is surfaced in Movio Research and Numero Audience.
On the roadmap
The following models are in development or planned and are represented by public-roadmap items.
Audience intelligence
Audience intelligence identifies likely audience segments for a film using presales information, behavioural data, and demographic trends. This helps you understand who is most likely to attend a particular title.
Data source and location
Audience intelligence uses Movio data and will be surfaced in Movio EQ.
Related roadmap item
Concession recommender
Concession recommender predicts which food and beverage items a guest is most likely to purchase based on previous purchasing behaviour. This model supports personalised concession recommendations and suggestive selling.
Data sources and locations
Concession recommender will be used across Lumos and digital guest experiences. Recommendations are generated from moviegoer purchasing behaviour from Lumos sales channels and Digital Platform.
Related roadmap item
Conversational analytics
Conversational analytics allows you to ask business questions using natural language and receive data insights and visualisations in response.
Locations
Conversational analytics is used in Horizon.
Related roadmap item
Guest sentiment insights
Guest sentiment insights are an analysis of moviegoer feedback to identify sentiment, recurring themes, and other patterns within survey responses and guest comments. This helps you understand guest experiences and identify opportunities for improvement or targeted campaigns.
Data source and location
Guest sentiment insights are generated from open feedback responses collected through React and surfaced as response summaries in Oneview.
Related roadmap item
Movie intelligence
Movie intelligence summarises a movie's circuit-wide performance and audience profile over its entire season.
Data sources and location
Movie intelligence will be generated using data from Vista, React, movieXchange and Movio EQ, and surfaced in Movio EQ.
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