How can you improve your TSM scores? By using the power of data-driven decision making... we'll show you how to make the most of your qual feedback data.
The key to improving your tenant satisfaction measures (TSMs) depends on your ability to make data-driven decisions using your qualitative customer feedback.
The social housing sector has completed its first full year of Tenant Satisfaction Measures and organisations are now facing the challenge of how to improve their scores and, more importantly, improve the lives of their tenants.
With over half a million respondents contributing to the initial TSM submissions, the data presented brings about both opportunities and challenges for housing providers looking to make meaningful improvements. In this blog, we’ll be showing you:
The first year of TSM results reveals an average satisfaction score of 70% across the sector (Inside Housing). Perhaps the most crucial insight from this initial data is that residents who are satisfied with their repair service and property maintenance are significantly more likely to be satisfied with their landlord overall. This correlation outweighs other factors such as tenant age, location, or property age. But overall, no matter what the average scores are, HAs are looking for how they can improve.
With the TSMs now being presented in a comparison table, in the words of our CEO Pete Daykin, we have to remember that "Every social landlord has their own unique cocktail of conditions, issues, geographies, demographics, socioeconomic groups. And for that reason alone, it's impossible to accurately compare one person's score with another."
Naturally, seeing your scores in a table will mean that you want to make improvements for next year and to do this, you need to be utilising the feedback from TSM results in a meaningful way, which can be hard to do if you’re stuck doing traditional feedback analysis.
Many housing associations are struggling with a common set of challenges when it comes to analysing and acting on resident feedback:
What we commonly find is that most people who work in customer experience, insight or in service improvement know broadly speaking anecdotally what their big issues are... they just don't know exactly how many people are experiencing those issues.
Many housing associations that we speak to are using manual tagging aka manual feedback analysis. This was the case when Sovereign Housing came to us needing help with trying to understand the huge amounts of tenant feedback.
The initial goal was to generally improve tenant satisfaction and reduce contacts to their complaints team, but Sovereign has since integrated Wordnerds across multiple facets of the business.
By using Wordnerds, Sovereign now:
Watch our full interview with Sovereign 📷 How Sovereign saved 10 hours of manual tagging per week while staying ahead on tenant satisfaction
Leading housing associations are now turning to advanced analytics and AI to transform their approach to resident feedback. The most successful organizations are following a four-stage process:
Our customer The Guinness Partnership is a stellar example of a housing association making an impact with their data-driven decision making. Through detailed analysis of resident feedback, they identified an unexpected correlation between ivy and creeping plants blocking exterior ventilation and damp problems in properties.
Chris Haynes, Customer Insights Manager explained how they used Wordnerds to identify issues they would never think to look at like ivy and creeping plants potentially causing damp and mould. They had a couple of comments from customers when they felt that ivy and creeping plants were blocking ventilation on the exterior of their property, with the belief that that was causing damp problems.
Wordnerds allowed them to identify every comment which mentioned those sorts of plants, create a botanical topic to capture all the possible things that could go into that. They created that topic, whether damp was mentioned or not, and then cross-referenced that against our damp and mould data.
They found this really useful and it allowed them to turn a potential hypothesis into concrete evidence which was data-led in terms of proving it or disproving it.
Insights like this might have been missed through traditional analysis methods, but the knowledge allowed them to take targeted action and fix the issues related to damp and mould.
Check out the full Case Study 🔎 How the Guinness Partnership identified damp and mould risks and prioritised red-flag complaints
Why You Should Be Sharing Customer Feedback Across the Organisation
One of the most powerful trends emerging in the world of CX is the democratisation of data - this means that everyone in the business can see how customer data is impacting decision making and vice versa. VoC data should be shared cross-functionally across various departments - customer support, sales, marketing and leadership - in an easy to use dashboard that gives users access to insights so they can leverage them for decision making.
Having a tool that allows you to compile the data in a comprehensive, engaging and understandable way - as well as integrating with your existing business intelligence tools, survey tools - whatever you use for customer experience is crucial so that everyone can be singing from the same hymn sheet.
When looking to improve your TSM data, organizations should focus on answering three fundamental questions:
By reflecting on these key questions you can begin to form a plan of action on how you plan to improve your scores for the following years.
Inside Housing recently reported they received the highest TSM score nationally for complaint-handling and the reason why is because they follow the approach of listening, understanding and putting right what they did wrong. It’s about finding the things that are affecting your tenants and finding ways to resolve those things in good time.
As we move into 2025, the importance of data-driven decision making in improving TSM scores shouldn’t be ignored. The organizations seeing the most success are those that are utilising their data from multiple data sources, applying advanced analytics, and turning insights into action.
The key is not just to collect data, but to make it accessible and actionable across the organisation. As we know and repeatedly mention time and time again, the quant data and dashboards will tell you when there's a problem, but to tell you why there's a problem you need to overlay the resident feedback data.
By embracing these approaches, housing associations can move beyond simple measurement to meaningful improvement in both TSM scores and resident satisfaction.
