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TRU for Retail Stores

Use existing Infrastructure to boost customer engagement and sales.

The TRU Recognition Platform can provide significant business value to retail 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.

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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Click on the dots to learn more about each recognition technology.

Recognition for Retail Stores

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. 

Safety

Safety

The TRU Recognition Platform can be used to detect potential safety hazards in retail 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. 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 retail 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.

Customer insights

Customer insights

The TRU Recognition Platform can be used to analyse customer behaviour and preferences, allowing retail stores to deliver targeted marketing and advertising messages.

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.

What’s a Rich Text element?

The rich text element allows you to create and format headings, paragraphs, blockquotes, images, and video all in one place instead of having to add and format them individually. Just double-click and easily create content.

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Static and dynamic content editing

A rich text element can be used with static or dynamic content. For static content, just drop it into any page and begin editing. For dynamic content, add a rich text field to any collection and then connect a rich text element to that field in the settings panel. Voila!

How to customize formatting for each rich text

Headings, paragraphs, blockquotes, figures, images, and figure captions can all be styled after a class is added to the rich text element using the "When inside of" nested selector system.

Choose TRU Recognition for your AI capabilities

The TRU Recognition Platform can provide significant business value to Retail Stores by improving safety, enhancing customer experience, enhancing security, providing customer insights, and increasing revenue. By leveraging the power of Recognition Technologies/Vision AI, retail stores can become more competitive and profitable along with mitigating risks.

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.

Convenience Stores

Use existing Infrastructure to boost customer engagement and sales.

Quick Service Restaurants

Enhancing customer experience and streamlining operations even in the quick service industry

Healthcare

Accurate, real-time analytics and insights to improve the experience and safety of patients, staff and visitors.

Shipping Ports

Streamlining shipping port operations with real-time insights.

Airports

Real-time analytics to improve the experience and safety of passengers, staff and visitors.

Smart Cities

Improving the infrastructure and analytics of all cities from around the world.

Supermarkets

From aisles to algorithms, the future of supermarkets.

Mining

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