Case Studies

 
 
carleton university
 

Carleton University is a Canadian post-secondary institution in Canada’s capital city. As an academic institution, they have a strong understanding of the assets data analytics can provide,  and see the significance of implementing modern technologies to monitor student, faculty and educational data to meet the degree level expectations set by the Ministry of Education.

the challenge

Every college and university must comply with the degree level exceptions of their Provincial government’s Ministry of Education. Regardless of the province, course outlines must meet degrees level expectations set by the Ministry. Unfortunately, Carleton’s existing data organization and management system did not work efficiently. The auditing system was not capable of auditing 7,000-course outlines from the Faculty of Arts efficiently without extra human power.

the solution

We used our semantic analytics technology to extract descriptive statistics from texts in the course outlines provided by Carleton, at a scale and speed difficult for humans to perform. This solution offered the institution the tools required to conduct a meta-analysis of course outlines. Our technology can extract and analyze information from text documents and turn it into valuable assets. For companies, this can produce audits conducted efficiently and accurately at a fraction of the human power required. By incorporating AI technology, the students, faculty and administrative staff at Carleton will all see a meaningful impact. Businesses using our tools function more productively, perform better and meet set requirements.

The results

Through incorporating our technology into their existing infrastructure, we enhanced the organization and management frameworks, resulting in, a wide variety of statistics and outputs being generated. We improved the workflow within the Faculty of Arts.  Administrative staff are now able to audit course outlines in compliance with Degree Level Expectations efficiently, faculty members will receive real-time reports on course delivery and performance, and students will gain valuable feedback into their current educational path and future successes. This technology can be expanded across multiple faculties and universities.

 
CT.png
 

Canadian Tire is a retail company providing automotive, hardware, sports, leisure and home products  to Canadians at over 1500 retail locations across Canada. They recognize the importance of staying competitive in the retail landscape and using modern technology to monitor store visitations and customer behaviour patterns.

The Challenge

To maintain a competitive edge in the marketplace, businesses must understand their customers and how they interact with their organization. Companies in the retail sector are particularly concerned with their customer’s behaviours and patterns of shopping, due to the impact it has on sales. However, when you do not have the proper technology to monitor and track customers in a store effectively, you cannot make accurate operational decisions.

The solution

We incorporated a network of cameras to count, track, and monitor customers in stores; including data on how many people entered the store, what they do while shopping, where they go in the store, and how many people are at check out at any given time. This solution offered the company key insights into customer tracking and forecasting. Our technologies can extract and transform critical insights from video feeds into valuable data. For companies, this translates into better operational decisions made to accommodate customer trends. By taking advantage of AI, staffing decisions can improve, and stores can perform at a more competitive level.   

The results

Through installing our technology into stores, we were able to track customer behaviour throughout the shopping experience. Cameras were placed at store entrances and exits, resulting in knowledge generated about the number of people in the store at any given time. The staff are now able to use customer tracking as a loss prevention method and make better staffing determinations. This technology can be rolled out throughout an entire store to predict other customer behaviours within the shopping experience.

 
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Innovapost cultivates synergy and business opportunities for the Canada Post Group of Companies by providing client-specific IT, IS, and Business Solution Services to drive efficiencies across the group. They understand the need to optimize IT services and within the mail, courier and logistics industries.

The Challenge

There are astounding amounts of unstructured data that goes unanalyzed. Every company regardless of the industry, with the right tools, has the ability to analyze and leverage data on a rolling basis. There is an untapped potential for businesses to make sense of and leverage data gathered from call centre interactions, efficiently and promptly. With multiple call centres, Innovapost had no visibility into one of their primary customer interactions. The valuable insights lost from this obstacle result in missed opportunities.  

The Solution

Our semantic search tools were used to analyze semantic meaning from the audio data, with high-quality performance and accuracy. This solution offered an end-to-end processing pipeline for quality scoring of call centre calls that provided opportunities to increase operational efficiency and employee performance. Our technology can identify and analyze the contextual meaning and intent of audio data from real-life call centre interactions. For companies, these new abilities translate into increase agent performance on-call time and decrease operational costs. Using our tools can improve call centre operations, save six-digit costs, and augment other business objectives such as focused employee training.

The results

We successfully installed our hardware and trained a call quality scoring model with a high degree of performance. Innovapost is now able to see accurate call quality scoring in a fast-paced environment, increase operational savings, train and improve agent performance and augment other business objectives based on insight on ‘good’ quality scores.