Image cover of an hotel icon with radius loops connecting everything together.


Goal of the project was to make it easier for property owners to find the right portfolio of technology solutions to grow their business. By putting customers first and using our proprietary data to generate a curated list of recommended providers, properties can make an informed decision. The idea behind this project was to make it easier for different property types (hotels, homes, chains, etc…) to find the right provider (channel manager, property management systems or revenue management systems) type to grow their business with. We want to  recommend providers with a demonstrated history of strong business performance and early API adoption – all while respecting property needs and explicit choices.


According to our annual partnership survey, around 50% of the participating properties were interested in a connectivity provider and expected advice from to assist them to pick the right one for them. This made me realise that there was a huge property need in the market.

Thus, I planned an in-depth property owner interview to follow up on these needs. The most important learning was to understand properties’ expectations from Properties saw our platform to be the top expert in the accommodation industry and that meant we had tons of data and knowledge of all the providers collaborating with us. Many of our property owners didn’t have a main source of reference in understanding the difference between one provider and the other. Therefore, properties were heavily relying on friends’ recommendation, word of mouth, Google searches or just trying out as many trials as possible from different providers. That was extremely time consuming, but the biggest challenge for property owners was that they still couldn’t make a confident decision on their search towards the right provider.


Currently in the property renting industry, there is nowhere available an intuitive platform/tool for property owners to learn about all the providers across different countries. Therefore, at, we have the opportunity to be the first one that provides property owners this platform/tool.

One great learning from property interviews is that the property type is a main factor when it comes to picking the right provider. Property owners are looking for providers that have advanced experience in their property type. For example, a home rental property will pick a provider specialised in holiday home rental services.

Another factor is the presence of local customer service. Properties prefer providers that offer support in their locations and languages. On top of that, reviews from previous or current properties are essential. In the reviews, property owners would like to have screenshots of the management tools and its features. These details are crucial for their decision making.


New and experienced properties needed help understanding the potential use of all types of providers and our Booking website just like any other platform across the internet, wasn’t providing a single source of truth to reference for properties on all the available possibilities.

Contextual advice

Once all property owners understood what to look for in a provider, we needed to provide a logical list of results of providers best suited for each property type, where the provider would offer services that would be specialized in the property business growth, location, scale, flexibility with services and needs.


Next step was to conclude the journey by providing a complete profile description of who the provider is, what they offer and how to connect with them.

This enabled the product managers to set timelines when to test each topic in our sprints plannings. We needed to first move backwards and build the foundation to improve the profile pages (discoverability), then move towards the provider selection (contextual advice) page where we list all potential candidates and then complete the project by creating a complete library of resources (onboarding) to help properties make better decision in who to connect with.


My extensive knowledge of all the available data we were collecting on the providers, helped break down the profile experiments. I created variations of the profile page, by updating the content with current data that was being shared with properties and testing its improvement with increasing connection requests by properties. Once that was completed and showed no increase in customer support requests and observing no spike on the  connection requests between properties and providers, I moved on to start connecting new missing details from the providers.

To resolve the process of property owners going through social media channels or word-of-mouth processes, I started creating a process in building a review system on providers by properties. This helped properties get relevant insights from their own peers in the same industry. All these improvements showed increased connection requests by building a richer profile description of the providers.

While the discoverability topic was being completed, I  took the opportunity with the help of our data scientist to map out the metrics to use when listing provider ranking. We validated the improvements of the matchmaking recommendation ranking through multiple phases and I followed up with a brainstorming session with key stakeholders across teams to agree on which categories to use. This led to creating a Google Sheet table that was pulling our data and rules, so they can be first shared internally with the product managers to test and refine the bugs or results.

Once this action was performed a few times, we ran an experiment with our old provider selection list and compared randomized results with our new algorithm ranking. This showed positive results, when comparing the length of connection of properties with providers between both pools. The properties that connected through the ranking results stayed connected longer while the properties who connected through the randomized results would switch or cancel their connection after a month or two. So these findings help me confirm that the algorithm was working better and concluded the contextual advice topic.

On the onboarding topic, I re-wrote all of our existing documentations and with the help of internal resources and discussions with key stakeholders, I was able to visualise what properties should look for when choosing a provider. When the onboarding phase was validated through property interviews on ease of understanding, 9 out of 10 properties were able to explain what was each type of provider and which features a provider could offer when selecting them for their business. Afterwards, we ran an experiment with a wider audience of properties and tracked the increase in connection requests to providers and switches from providers with limited features to others that provided a wider variety of functionalities.


My lead on this project fulfilled the need for easy accessible, relevant and trustworthy information for the properties. Creating a single source of truth for properties, helped reduce the amount of effort and time they spent to do proper research and enabled them to compare providers before selecting the right one. Because in the past the information sources were scattered and not always trustworthy, with matchmaking I was able to optimize the properties time spent in finding a provider, increasing their trust on knowledge and expertise.

My initiative helped fill the gap of knowledge regarding tools and capabilities for properties. However, besides helping property owners to select the right provider, I enabled to play a stronger role for less experienced properties, helping them to understand which features they need to look out for, for their specific business.

An important aspect of this project is the incremental business value this can bring to With the choice of the right provider, properties can increase significantly their revenue which creates a win-win situation for both properties and


Because of my experience in understanding what were the missed opportunities and pain points of properties, along with the business goals to increase connections between properties and providers, I was able to provide an improved management tool to increase connections for new and experienced properties to use and get all stakeholders to agree on its need and positive impact to our properties. Our connection requests increased by ~3.5% since its release and our follow up research proved that connected properties have been more satisfied with the recommendations of which provider would best suit their property type.