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Analysing employee online reviews to help a global healthcare company understand all areas around retention, recruitment and talent development.
Challenge
A global healthcare company, who has partnered with STRAT7 many times, wanted to know how their employee experience compared to that offered by their competitors. They were keen to develop a deep understanding of their strengths and weaknesses, what mattered most to employees and where they could improve.
Where better to gather this information than from past and present employees themselves?
Publicly available online employee reviews offered the perfect data source from which to conduct our analysis. Until recently, this kind of unstructured data was extremely difficult to collect and process. But now, thanks to developments in AI, we can tap into this rich data source and extract actionable insights.
Using proprietary strat7.ai web scrapers, we collected publicly available data from US-based employees, where current and former employees anonymously review companies.
Approach
Deep exploration of employee reviews
Using proprietary strat7.ai web scrapers, we collected publicly available data from US-based employees, where current and former employees anonymously review companies.
Review data was collected on a total of seven global healthcare companies: our client and six of their competitors.
A few thousand unique conversations were collected, both before and after the pandemic, which detailed the pros and cons of the employees’ experience, as well as metadata such as date, former/current employee status and tenure.
Then we used a hybrid approach, consisting of machine learning and domain expertise, to find the categories of conversation within the reviews.
We tracked standard topics such as pay, benefits, and the perception of management, as well as less obvious things like pension schemes and office location. Then we applied the topic modelling framework and star rating data to uncover clear areas of strength, weakness and deterioration of the company in focus.
Using textual analysis to isolate the key drivers, we uncovered the precise reasons why the company in focus performed well on non-pay benefits and less well in areas like recruitment and management.
We also found common words and phrases that employees used when discussing each topic. For example, within non-pay benefits, consumers repeatedly mentioned their 401k and paid leave.
Impact
Adding value with unstructured data
Our analysis gave our client a clear understanding of their strengths and weaknesses in all areas regarding employee experience. These insights have been combined with other forms of research to inform their talent strategy in the future and improve their offering.
The strat7.ai engine made the collection, analysis and visualisation of the data quick and easy, plus it offered a cost effective way of turning unstructured qualitative data into a competitive advantage.
Tap into the power of unstructured data
Leverage AI to get a rigorous comparison of your brand and product portfolio against competitors, through the voice of consumers and/or employees.
strat7.ai supports a wide range of business questions through the lens of unstructured data. Speak to us to find out what AI can do for you.
