Using sentiment analysis to provide the elderly with personalised care.


Data Hub service

Using sentiment analysis to provide the elderly with personalised care.

Data Hub service

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Sentiment analysis using Razor Sprint

The Challenge

With an ageing population across the UK, the demand on charities who support the elderly is increasing. As a result, they need to scale their operations, whilst maintaining quality of service. The quickest and most reliable way of doing this is by tapping into their data reserves.

Our Razor team worked with a charity whose volunteers undertake the vital task of contacting elderly people to better understand their circumstances and anticipated needs.

The volunteer’s task is to speak to the caller and decide the type of support they require. The challenge they face is that every decision made is subjective; it is the volunteer’s perception of the situation which decides what support is provided.

Because the decision is based on individual perception, the results vary from volunteer to volunteer. This leads to inconsistencies or, in the worst case, people not getting the right support.

To combat this, they wanted to ensure they have a meaningful way of capturing and monitoring people’s situations. This would enable them to provide the right care to those who really need it. With the number of volunteers and service users increasing, they needed to tackle these discrepancies to accurately identify those who are most in need of their support.

The Solution

Our Razor team was engaged to deliver a technology prototype that could help to make the decision- making process simpler and more standardised.

The solution allows the call information to be extracted from Microsoft Dynamics CRM, in a highly secure manner, to establish a guided process for volunteers to follow when speaking with those seeking help.

At each step, the volunteer can ask their caller a series of pertinent questions, which helps the charity to collect exact responses. Using Microsoft’s Azure Cognitive Services, including sentiment analysis, this data can be processed to intelligently capture and determine emotion. These results can then be combined with the volunteer’s perception to establish a consistent baseline analysis of whether the person seeking help needs additional assistance.

The Result

By gathering and analysing caller data, this charity can provide informed, personalised care to those in need with no additional effort overhead. This solution empowers their volunteers to continue supporting vulnerable people as the demand for their service continues to grow.

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