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TRU for Convenience Stores
Use existing Infrastructure to boost customer engagement and sales.
The TRU Recognition Platform can provide significant business value to convenience stores by improving safety, enhancing security, providing customer insights as well as improving and measuring customer experience levels.
Traditional WiFi/Bluetooth solutions offer low accuracy due to a wide range of factors.
Aggression Recognition
Aggression Recognition
Aggression Recognition automatically detects and identifies aggressive behaviour or signs of aggression in individuals. This technology utilises various methods, such as video analysis, facial expression recognition, and behavioural cues, to analyse and interpret aggressive behaviour.
Aggression Recognition
Aggression Recognition
Aggression Recognition automatically detects and identifies aggressive behaviour or signs of aggression in individuals. This technology utilises various methods, such as video analysis, facial expression recognition, and behavioural cues, to analyse and interpret aggressive behaviour.
Aggression Recognition
Aggression Recognition
Aggression Recognition automatically detects and identifies aggressive behaviour or signs of aggression in individuals. This technology utilises various methods, such as video analysis, facial expression recognition, and behavioural cues, to analyse and interpret aggressive behaviour.
Aggression Recognition
Aggression Recognition
Aggression Recognition automatically detects and identifies aggressive behaviour or signs of aggression in individuals. This technology utilises various methods, such as video analysis, facial expression recognition, and behavioural cues, to analyse and interpret aggressive behaviour.
Demographics Recognition
Demographics Recognition
Demographics Recognition refers to the process of automatically identifying and categorising individuals based on various demographic attributes, such as age, gender, ethnicity, and facial features. It is crucial to handle demographic information with caution and avoid perpetuating biases or stereotypes. Bias mitigation techniques and diverse training datasets can help minimise the risk of inaccurate or unfair categorisation based on demographic attributes. No personal information is identifiable.
Demographics Recognition
Demographics Recognition
Demographics Recognition refers to the process of automatically identifying and categorising individuals based on various demographic attributes, such as age, gender, ethnicity, and facial features. It is crucial to handle demographic information with caution and avoid perpetuating biases or stereotypes. Bias mitigation techniques and diverse training datasets can help minimise the risk of inaccurate or unfair categorisation based on demographic attributes. No personal information is identifiable.
Demographics Recognition
Demographics Recognition
Demographics Recognition refers to the process of automatically identifying and categorising individuals based on various demographic attributes, such as age, gender, ethnicity, and facial features. It is crucial to handle demographic information with caution and avoid perpetuating biases or stereotypes. Bias mitigation techniques and diverse training datasets can help minimise the risk of inaccurate or unfair categorisation based on demographic attributes. No personal information is identifiable.
Demographics Recognition
Demographics Recognition
Demographics Recognition refers to the process of automatically identifying and categorising individuals based on various demographic attributes, such as age, gender, ethnicity, and facial features. It is crucial to handle demographic information with caution and avoid perpetuating biases or stereotypes. Bias mitigation techniques and diverse training datasets can help minimise the risk of inaccurate or unfair categorisation based on demographic attributes. No personal information is identifiable.
Dwell Time Recognition
Dwell Time Recognition
Dwell Time Recognition automatically measures and analyses the length of time individuals spend in a particular location or area. This technology is often used in retail, hospitality, and public spaces to understand customer behaviour, optimise space utilisation, and improve operational efficiency.
Dwell Time Recognition
Dwell Time Recognition
Dwell Time Recognition automatically measures and analyses the length of time individuals spend in a particular location or area. This technology is often used in retail, hospitality, and public spaces to understand customer behaviour, optimise space utilisation, and improve operational efficiency.
Dwell Time Recognition
Dwell Time Recognition
Dwell Time Recognition automatically measures and analyses the length of time individuals spend in a particular location or area. This technology is often used in retail, hospitality, and public spaces to understand customer behaviour, optimise space utilisation, and improve operational efficiency.
Dwell Time Recognition
Dwell Time Recognition
Dwell Time Recognition automatically measures and analyses the length of time individuals spend in a particular location or area. This technology is often used in retail, hospitality, and public spaces to understand customer behaviour, optimise space utilisation, and improve operational efficiency.
Path Map Recognition
Path Map Recognition
Path Map Recognition automatically detects and recognises paths or routes taken. It has the potential to improve marketing strategies and campaign effectiveness measurement in store.
Path Map Recognition
Path Map Recognition
Path Map Recognition automatically detects and recognises paths or routes taken. It has the potential to improve marketing strategies and campaign effectiveness measurement in store.
Path Map Recognition
Path Map Recognition
Path Map Recognition automatically detects and recognises paths or routes taken. It has the potential to improve marketing strategies and campaign effectiveness measurement in store.
Path Map Recognition
Path Map Recognition
Path Map Recognition automatically detects and recognises paths or routes taken. It has the potential to improve marketing strategies and campaign effectiveness measurement in store.
Product Interaction Recognition
Product Interaction Recognition
Product Interaction Recognition automatically detects and recognises how users interact with products or physical objects. It has the potential to improve user experience, quality control, pricing, and theft detection.
Product Interaction Recognition
Product Interaction Recognition
Product Interaction Recognition automatically detects and recognises how users interact with products or physical objects. It has the potential to improve user experience, quality control, pricing, and theft detection.
Product Interaction Recognition
Product Interaction Recognition
Product Interaction Recognition automatically detects and recognises how users interact with products or physical objects. It has the potential to improve user experience, quality control, pricing, and theft detection.
Product Interaction Recognition
Product Interaction Recognition
Product Interaction Recognition automatically detects and recognises how users interact with products or physical objects. It has the potential to improve user experience, quality control, pricing, and theft detection.
Queue Length Recognition
Queue Length Recognition
Queue Length Recognition automatically detects and measures the length of queues or lines in various settings. It has the potential to improve customer service, resource allocation, wait time management, crowd control, and performance evaluation.
Queue Length Recognition
Queue Length Recognition
Queue Length Recognition automatically detects and measures the length of queues or lines in various settings. It has the potential to improve customer service, resource allocation, wait time management, crowd control, and performance evaluation.
Queue Length Recognition
Queue Length Recognition
Queue Length Recognition automatically detects and measures the length of queues or lines in various settings. It has the potential to improve customer service, resource allocation, wait time management, crowd control, and performance evaluation.
Queue Length Recognition
Queue Length Recognition
Queue Length Recognition automatically detects and measures the length of queues or lines in various settings. It has the potential to improve customer service, resource allocation, wait time management, crowd control, and performance evaluation.
Slip & Fall Recognition
Slip & Fall Recognition
Slip and Fall Recognition automatically detects and identifies instances where a person slips, trips, or falls. It has the potential to improve safety measures, prevent accidents, and provide timely assistance in case of a slip or fall incident.
Slip & Fall Recognition
Slip & Fall Recognition
Slip and Fall Recognition automatically detects and identifies instances where a person slips, trips, or falls. It has the potential to improve safety measures, prevent accidents, and provide timely assistance in case of a slip or fall incident.
Slip & Fall Recognition
Slip & Fall Recognition
Slip and Fall Recognition automatically detects and identifies instances where a person slips, trips, or falls. It has the potential to improve safety measures, prevent accidents, and provide timely assistance in case of a slip or fall incident.
Slip & Fall Recognition
Slip & Fall Recognition
Slip and Fall Recognition automatically detects and identifies instances where a person slips, trips, or falls. It has the potential to improve safety measures, prevent accidents, and provide timely assistance in case of a slip or fall incident.
TRU CX+
TRU CX+
TRU CX+ utilises various inputs, such as Queue Length and Dwell Time Recognition. TRU Recognition provides CX+ which can enable the experience of a customer to be measured empirically without the use of traditional surveys etc. This results in the experience of all customers being measured, with friction points being highlighted in real-time.
TRU CX+
TRU CX+
TRU CX+ utilises various inputs, such as Queue Length and Dwell Time Recognition. TRU Recognition provides CX+ which can enable the experience of a customer to be measured empirically without the use of traditional surveys etc. This results in the experience of all customers being measured, with friction points being highlighted in real-time.
TRU CX+
TRU CX+
TRU CX+ utilises various inputs, such as Queue Length and Dwell Time Recognition. TRU Recognition provides CX+ which can enable the experience of a customer to be measured empirically without the use of traditional surveys etc. This results in the experience of all customers being measured, with friction points being highlighted in real-time.
TRU CX+
TRU CX+
TRU CX+ utilises various inputs, such as Queue Length and Dwell Time Recognition. TRU Recognition provides CX+ which can enable the experience of a customer to be measured empirically without the use of traditional surveys etc. This results in the experience of all customers being measured, with friction points being highlighted in real-time.
Licence Plate Recognition
Licence Plate Recognition
Licence Plate Recognition is a technology that uses cameras and image processing algorithms to automatically detect and recognise licence plates on vehicles. It has the potential to improve law enforcement, parking management, toll collection, and traffic monitoring.
Licence Plate Recognition
Licence Plate Recognition
Licence Plate Recognition is a technology that uses cameras and image processing algorithms to automatically detect and recognise licence plates on vehicles. It has the potential to improve law enforcement, parking management, toll collection, and traffic monitoring.
Licence Plate Recognition
Licence Plate Recognition
Licence Plate Recognition is a technology that uses cameras and image processing algorithms to automatically detect and recognise licence plates on vehicles. It has the potential to improve law enforcement, parking management, toll collection, and traffic monitoring.
Licence Plate Recognition
Licence Plate Recognition
Licence Plate Recognition is a technology that uses cameras and image processing algorithms to automatically detect and recognise licence plates on vehicles. It has the potential to improve law enforcement, parking management, toll collection, and traffic monitoring.
Fuel Drive Off Recognition
Fuel Drive Off Recognition
Fuel Drive-off Recognition automatically detects and identifies instances where a vehicle leaves a fuel station without paying for the fuel. It has the potential to improve loss prevention, enhance security, support law enforcement efforts, and improve customer service at fuel stations.
Fuel Drive Off Recognition
Fuel Drive Off Recognition
Fuel Drive-off Recognition automatically detects and identifies instances where a vehicle leaves a fuel station without paying for the fuel. It has the potential to improve loss prevention, enhance security, support law enforcement efforts, and improve customer service at fuel stations.
Fuel Drive Off Recognition
Fuel Drive Off Recognition
Fuel Drive-off Recognition automatically detects and identifies instances where a vehicle leaves a fuel station without paying for the fuel. It has the potential to improve loss prevention, enhance security, support law enforcement efforts, and improve customer service at fuel stations.
Fuel Drive Off Recognition
Fuel Drive Off Recognition
Fuel Drive-off Recognition automatically detects and identifies instances where a vehicle leaves a fuel station without paying for the fuel. It has the potential to improve loss prevention, enhance security, support law enforcement efforts, and improve customer service at fuel stations.
Heat Map Recognition
Heat Map Recognition
Heat Map Recognition automatically analyses and interprets heat maps, which are visual representations of data where values are depicted using colours, gradients, or intensity variations. It can provide valuable insights for user behaviour analysis, retail optimisation, crowd management, facility planning, and infrastructure development.
Heat Map Recognition
Heat Map Recognition
Heat Map Recognition automatically analyses and interprets heat maps, which are visual representations of data where values are depicted using colours, gradients, or intensity variations. It can provide valuable insights for user behaviour analysis, retail optimisation, crowd management, facility planning, and infrastructure development.
Heat Map Recognition
Heat Map Recognition
Heat Map Recognition automatically analyses and interprets heat maps, which are visual representations of data where values are depicted using colours, gradients, or intensity variations. It can provide valuable insights for user behaviour analysis, retail optimisation, crowd management, facility planning, and infrastructure development.
Heat Map Recognition
Heat Map Recognition
Heat Map Recognition automatically analyses and interprets heat maps, which are visual representations of data where values are depicted using colours, gradients, or intensity variations. It can provide valuable insights for user behaviour analysis, retail optimisation, crowd management, facility planning, and infrastructure development.
Shoplifting Recognition
Shoplifting Recognition
Shoplifting Recognition automatically detects and identifies instances of shoplifting or theft in retail environments. This technology utilises various methods, such as video analysis, object tracking, and behaviour detection algorithms, to monitor and analyse activities within a store and identify suspicious behaviours associated with shoplifting. It has the potential to improve loss prevention, enhance overall security and provide valuable evidence for law enforcement purposes.
Shoplifting Recognition
Shoplifting Recognition
Shoplifting Recognition automatically detects and identifies instances of shoplifting or theft in retail environments. This technology utilises various methods, such as video analysis, object tracking, and behaviour detection algorithms, to monitor and analyse activities within a store and identify suspicious behaviours associated with shoplifting. It has the potential to improve loss prevention, enhance overall security and provide valuable evidence for law enforcement purposes.
Shoplifting Recognition
Shoplifting Recognition
Shoplifting Recognition automatically detects and identifies instances of shoplifting or theft in retail environments. This technology utilises various methods, such as video analysis, object tracking, and behaviour detection algorithms, to monitor and analyse activities within a store and identify suspicious behaviours associated with shoplifting. It has the potential to improve loss prevention, enhance overall security and provide valuable evidence for law enforcement purposes.
Shoplifting Recognition
Shoplifting Recognition
Shoplifting Recognition automatically detects and identifies instances of shoplifting or theft in retail environments. This technology utilises various methods, such as video analysis, object tracking, and behaviour detection algorithms, to monitor and analyse activities within a store and identify suspicious behaviours associated with shoplifting. It has the potential to improve loss prevention, enhance overall security and provide valuable evidence for law enforcement purposes.
Click on the dots to learn more about each recognition technology.
Enhanced Security Business Value
Enhanced Insights
Enhanced Safety
Adding value to your sector
The following examples demonstrate how the TRU Recognition Platform can be utilised to generate business value and deliver benefits to customers in convenience stores.
Customer insights
Customer insights
The TRU Recognition Platform can be used to analyse customer behaviour and preferences, allowing convenience stores to deliver targeted marketing and advertising messages.
Safety
Safety
The TRU Recognition Platform can be used to detect potential safety hazards in convenience stores. Using computer vision technology, cameras can identify objects or people that may pose a threat to safety, such as potential slip and fall hazards, or accidents involving vehicles or equipment. This can alert staff to take corrective action and prevent accidents, injuries, and damage to property.
Security
Security
The TRU Recognition Platform can be used to enhance security in convenience stores by monitoring for unauthorised access, suspicious behaviour, and potential threats. Using computer vision technology, cameras can detect unusual behaviour, such as shoplifting or theft. This can alert security personnel to investigate and prevent security breaches, theft, and other crimes.
Other benefits include:
- Empirically understand the customer experience level your business is delivering.
- Measure the experience of all customers rather than only those who complete surveys.
- Understand friction points in real-time.
- Increase basket size by enhancing customer experience.
- Easily evaluate new product launches
- Drive a strong customer experience culture at the Board level.
- Optimise staff allocations.
- Leverage existing infrastructure.
- Increase the level of store insights.
- Augment NPS and Customer Survey data.
Choose TRU Recognition for your AI capabilities
The TRU Recognition Platform provides high business value outcomes to Convenience Stores by improving safety, enhancing security, providing customer insights, and increasing revenue. By leveraging the power of Recognition Technologies/Vision AI, Convenience Stores can become more competitive, mitigate risks, and become more profitable.
Book a demo today!
See for yourself how TRU Recognition can transform your operation or contact us for further information.
Other Solutions
Tap into TRU Value, accurately, efficiently and responsibly.
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Airports
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Smart Cities
Improving the infrastructure and analytics of all cities from around the world.
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Mining
How AI is modernising the mining industry.
Acknowledgment of Country
We acknowledge the traditional owners of the land we know as Australia. We recognise the long and continuing relationship that our first nations people have with the land on which we meet, work and learn. We pay our respects to elders, past, present and emerging.