Short Story
Problem
- Customer satisfaction, crowd management and alarm generation is an important factor for industries.
- Industries are paying high attention to get the customer feedback but it is difficult to get the right feedback from all. only a few of the customers provide the feedback even in case they are highly dissatisfied. Customer service representative prefer to ask the feedbacks from happy customers.
- Crowd Management where customer footfall ratio for a day/time, customer type age/gender detection is still unresolved. Industries are looking for a solution to plan their resources and products.
- Activities based Alarm should be raised in case of any emergency, theft or panic situation.
Solution
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- Our Computer Vision, Sensors and edge based solution ensures the Customer satisfaction, crowd management and alarm generation.
- Product 1 – Customer facial expressions are noted while customer is making the purchase/transection using the facial expression recognition program in cameras implemented at customer service desk.
- Product 2 – Cameras with Human physical activity detection programs will be installed to detect the foot fall count, Customer type (Age, Gender), customer In and Out count. This data is feeded into a centralized/local system to provide the insights.
- Product 3 – Cameras with highly trained ML model will be installed to detect the theft situation, medical emergency situation or any panic situation and raise instant alarms with multiple authorities (govt./pvt) in the form of notification/sms/emails/.
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More Information:
Problem
- Customer satisfaction, crowd management and alarm generation is an important factor for industries.
- Industries are paying high attention to get the customer feedback but it is difficult to get the right feedback from all. only a few of the customers provide the feedback even in case they are highly dissatisfied. Customer service representative prefer to ask the feedbacks from happy customers.
- Crowd Management where customer footfall ratio for a day/time, customer type age/gender detection is still unresolved. Industries are looking for a solution to plan their resources and products.
- Activities based Alarm should be raised in case of any emergency, theft or panic situation.
-
- Our Computer Vision, Sensors and edge based solution ensures the Customer satisfaction, crowd management and alarm generation.
- Product 1 - Customer facial expressions are noted while customer is making the purchase/transection using the facial expression recognition program in cameras implemented at customer service desk.
- Product 2 - Cameras with Human physical activity detection programs will be installed to detect the foot fall count, Customer type (Age, Gender), customer In and Out count. This data is feeded into a centralized/local system to provide the insights.
- Product 3 - Cameras with highly trained ML model will be installed to detect the theft situation, medical emergency situation or any panic situation and raise instant alarms with multiple authorities (govt./pvt) in the form of notification/sms/emails/.
Story
Use Case- for a banking Industry
- Case 1 (Product 1) – A customer goes to a famous government bank in India while his visit he found lot of crowd inside and unmanaged banking services. This converts him into highly dissatisfied customer. On the event of his turn when customer service representative logged in CRM for his account his facial expressions are recorded in the camera implemented on customer service desk and a result of his expressions (which is highly dissatisfied) is sent to CRM and logged.
- Case 2 (Product 2) – bank wants to what are the peak times and what is the average number of customer inside the branch in that period. To plan the resources.
- Case 3 (Product 3) – Robbers attacks the bank, fire arms and panic situation is are detected in the camera. Alarm is raised with banking authorities and local police.
Bank management wants to know –
- What is the footfall count of the branch?
- When is the peak time and what number of customers are inside at the peak time? (to plan their resources and headcounts)
- Are the customer who visited the branch happy with the services, what is the level of happiness/sadness for each customer?
- Is there any panic/emergency/theft situation detected and required authorities were informed?
SWOT Analysis
Strength
- Latest solutions on New Technology
- Reuse for multiple industries
- Limited Products
- Highly trained and lab certified products
Weakness
- Expensive
- Scalability
- Less Operating Margin (no money to burn)
Opportunity
- Products for multiple use cases
- Worldwide growth possibility
Threats
- Entry of new competitor
- Burn Out Capacity is Zero
Market Analysis
- TAM – The global computer vision market size was valued at USD 20.31 billion in 2023 and is projected to grow from USD 25.41 billion in 2024 to USD 175.72 billion by 2032, exhibiting a CAGR of 27.3% during the forecast period.
- SOM – Targeted for Banking, Retail, tourism, Agriculture, Airline and government sectors (railway station, bus station, markets, highways)
- SAM – Start with solution for banking industry.
Competitor Analysis
- We were unable to find any Indian company which works for customer satisfaction using facial emotion recognition.
- For Human activity based implementation some Indian companies like AIVID, mavencluster, kritikalsolutions which works to provide such customized solutions.
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