When we launched our digital platform in August 2015 we were facing the risk that Reach was slowly becoming irrelevant – even redundant – which is a risk that all charities face if they do not think through how they should be incorporating digital. It was the burning platform that inspired us to radical action.
Two years on and £80k later our new online service has, in a year, delivered a 32% increase in placements – the number of trustees and volunteers who have been successfully recruited by charities; and a 24% fall in transaction costs (cost per placement) in the first 6 months of 2017 a new integration with LinkedIn, where all our roles are automatically cross-posted to LinkedIn members, has generated an additional 500 volunteers, who have already made over 370 applications for roles.
We can continue to scale without increasing our cost base – which means that our transaction costs will continue to fall. We estimate that they will have fallen by 37% by 2019.
Our old offline service was quite clunky and labour intensive to deliver. We had to spend a lot of time doing inefficient things that didn’t add value like passing messages between charities and volunteers. Scaling was never going to be viable, so we started looking at how other brokers were taking advantage of the internet to match supply and demand.
We were inspired by the success of the likes of Kiva and internet dating sites, and realised going online offered us a chance to both scale, through self-service, and to provide a much more personalised and compelling service to our audience of charities and volunteers – more than 60% of whom are under 50.
The promised hike in efficiency and productivity got our trustees’ backing and commitment to spend the time and money needed to build a new platform, which was essential. Having trustees with experience of digital was crucial as they could provide robust support and challenge to the executive, and could take a seasoned view when things went a bit awry.
It took almost two years to build the new platform and website. This probably took longer than it should have done, due to supplier issues. The core product cost about £80k but doesn’t include the staff and volunteer and pro-bono time.
Along the way we have learned a lot including these three key things:
1. Have a really clear and detailed understanding of your users’ needs.
We spent several months undertaking research with charities and volunteers before we started designing the service. We had a holistic understanding of their needs, and of how volunteering fitted into their world. These included charities wanting to be able to manage their recruitment themselves, rather than through an intermediatary, so we built functions such as a dashboard and messaging tools.
Both volunteers and charities were interested in a more flexible range of volunteering opportunities – so our new service incorporates short term projects and ‘remote’ or ‘virtual’ roles which can be done from anywhere.
These user requirements based on hard evidence were our guiding star during the build. It meant that we didn’t compromise on core features or get distracted by shiny new ones.
2. Engage a brilliant product manager – they will ensure that you end up with what you need!
3. Respect the data.
My background is in anthropology, so I’ve always preferred qualitative research, but I am really beginning to understand how valuable quantitative data can be. Digital services and websites generate a wealth of real time data about what your users are doing, and you can experiment with improvements and see if they work, instantly! For example, we’ve almost halved the number of people who don’t complete our volunteer registration form by breaking it down into pages and playing around with the order.
We are currently analysing things such as the conversion rate at each point in our user journey from joining, to volunteers applying for a role or charities registering one, to when a match is made. We are looking at this through the lens of different criteria such as where the volunteer first saw the role, or demographic factors like age. There is lots of potential to examine questions of broader interest, like emerging skills gaps, as the data is refined.
This article was originally published here.