At hiveonline we are developing a reputation system that will make it easier to clearly demonstrate the reputation of businesses and help build trusted relationships. Building a marketplace and creating a reputation score requires a lot of thinking about customer behaviour and the availability and use of data.
At hiveonline we are aiming to develop a reputation system that makes the process of having work done transparent for all people involved and thereby builds trust in businesses and creates ease of mind for the consumer. We want to show consumers evidence of previous work of a craftsman and make a tool not only for the end consumer but for the craftsman as well. The craftsmen and business owners we have talked to want, over everything, the consumer to be happy and satisfied with the work they have done.
Behaviour and data generate trust indicators
Having a good indicator of a business’ track record is key to employing them and paying for work to be done. When a craftsman is going to enter a customer’s house, their home, you really need to be able to trust that person. They also have specialist knowledge that the consumer does not have – that requires a higher level of trust too.
When building a reputation system, like hiveonline’s reputation score, you need to consider at least two things – what is the behaviour of the target segment and what data do you have? When dealing with craftsmen, end consumers and their interaction, the level of trust, and data accuracy, that is needed is much higher than if it was a low risk and low value product.
The foundation of our trust model is measuring the delivery of a task or project against what was committed. We encourage craftsmen and customers to build a simple transparent contract together before they start work, outlining key deliverables and any conditions. Then as the work is getting completed we measure the completion of the tasks and changes to the project. We then feed this into our reputation algorithm to work out how trustworthy both parties are on delivering what they agreed at the start.
In order to combine subjective and difficult to measure inputs into a fact-based reputation system you need to simplify those measurements and combine them with other obtainable and measurable data. In Denmark we have open public data – company number, tax certificates, number of vehicles. Some of these data gives an indication of the company – e.g. have they been around for a long time. If you combine that with data of certificates you can add more trust.
Bringing data together with standardised behaviour data points gives you an idea if a company is trustworthy, but what really adds to that trust will be data gathered in the future. The actual behaviour measured in the app when it is used by business every day to do their work and manage their projects.
Reputation is a large component of trust but not the only input
How can you base your trust on a reputation system? The reputation system is not a picture of the future. It is a picture of the past – giving you an indication of the future. But we can’t predict the future and therefore it can not stand alone. When you try to narrow down behaviour and data into indicators for a wide segment you need to be aware of the fact that you can create stereotypes and there may be exceptions to the rule.
This doesn’t mean that you shouldn’t try to create a system but that you should be aware that a reputation system is an indicator of trust not a guarantee, but in a world of fake reviews and lot of craftsmen you don’t know if you can trust, basing your judgement as much as possible on facts is a good way to go trying to help both craftsmen and end consumers.