Experimenting with AI to Enhance Our Product: Firsthand E…

By admin
At trivago, our talents get to work with many of the latest technologies, including

Artificial Intelligence
ORG

(AI). In fact, we are actively using AI not only to enhance our day-to-day work, but also to innovate on our product. We chatted with

two
CARDINAL

Product Managers at trivago,

Sören Weber
PERSON

and

Henrique Portes
PERSON

, who shared how their teams are experimenting with

Generative AI
PRODUCT

in their projects. We discussed the challenges they faced, their key learnings, and asked them to share advice for other product managers looking to integrate AI into their product.

Could you tell us a bit about the project you and your team are working on?


Henrique
PERSON

:


Artificial Intelligence
ORG

suddenly shifted from a futuristic promise to our

daily
DATE

routines. At trivago, we saw the opportunity to experiment by allying AI with our existing user needs, which seems natural for a tech company like us. The question was: how are we going to do it?

From the beginning, the process was exciting: from understanding which skills and knowledge would be required, to building the team and inviting the people who could contribute (some were amazed, some were a bit suspicious). And finally, putting everyone on the same page to shape a solution, implement, test, analyze, and learn.


Sören
PERSON

:

After the big breakthroughs in generative AI, we started exploring ways to integrate it into our product.

We generated ideas in design sprints and ideation sessions with the core product team and stakeholders from across the company.

Given the diverse applications of generative

AI
ORG

, we came up with a wide range of ideas spanning search functionality, content creation, user personalization, and conversational interfaces.

To demonstrate the value of using generative AI in our product, we decided to focus on a single use case

first
ORDINAL

. Specifically, we want to use AI to summarize hotel information and reviews to provide concise summaries to our users. This will serve as our team’s pilot project before we expand the application of AI to other areas.

What do you find most exciting about working with & integrating AI at trivago?


Henrique
PERSON

:

We are handling such a transformative technology, reaping many benefits, like any early stage development. Our goal is to turn it into something that is useful, maybe even unique, for our users. We are living the transition, seeing it from the inside, being part of it in a way, and that’s very exciting!

I believe that even

many years from now
DATE

, when

AI
ORG

is perceived as a commodity, our current experience will still be a good souvenir and hopefully a small building block of a much better and bigger story.


Sören
PERSON

:


First
ORDINAL

of all,

AI
ORG

is a fascinating field in itself, and I believe it will have a transformative impact. Being at the forefront of adopting this technology is an exciting prospect.

But we don’t want to just tinker with it, we want to create tangible business and user value. What excites me is the potential to apply this new technology to our hotel search use case and help

our millions
CARDINAL

of users find the ideal hotel for their specific needs.

trivago offers our team the right environment, resources, and freedom to explore this new technology that is new for all of us. I believe this strategy will pay off and position us as

one
CARDINAL

of the fast movers in the travel industry who effectively capitalize on AI.

What were the main challenges you faced while working with AI?


Henrique
PERSON

:

In our particular case, we had a brilliant PM who started out the whole project, she was the heart and soul of it. However, she stepped out of the project when the

MVP
ORG

was released, due to a wonderful reason: she became a mom. We all needed to adapt without her, collecting some skills from each individual to rebuild motivation and get back on track.

Regarding the product, it’s probably dealing with this magical black box called

AI
ORG

. We have control over the inputs, but from that point on,

AI
ORG

brought us a lot of surprises – ranging from slightly misleading answers to complete nonsense. We have no control over what’s going on ‘inside’. Evolving from this point towards a reliable output machine for our users requires a lot of ‘prompt engineering’ – a skill that none of us had familiarity with prior to it.


Sören
PERSON

:


One
CARDINAL

of the main challenges of working with

AI
ORG

is that the field is evolving rapidly, making it difficult to keep up with the latest developments and understand the implications.

Additionally, using generative AI in our product is new to us. So, we need to quickly learn how to use it, and its advantages and disadvantages are for use case.


One
CARDINAL

particular challenge we faced in our content use case was the issue of inaccurate information. We’re aware that the

AI
ORG

model’s output is not

100%
PERCENT

accurate and is non-deterministic, meaning that the results can vary with each query. This raises the question of how to assess the quality of the generated content and strike a balance between occasional inaccuracies and the overall value delivered.

Can you highlight any lessons learned from working with AI?


Henrique
PERSON

:

It’s not because ‘it’s AI’ that users will immediately fall in love with it and you’ll become their go-to place.

One
CARDINAL

thing is how appealing the technology is in theory, another one is how to apply it in a way that it seamlessly blends into the users’ journeys – to the point it’s not even being perceived as AI.

Even cutting edge technology requires the users to be at the center of the strategy. Otherwise, it‘ll be misused and forgotten.

Were there any surprising or unexpected outcomes?


Henrique
PERSON

:

Oh yes, quite a lot! Starting with some misleading items on a list, for example recommended restaurants in

Salvador
GPE

,

Brazil
GPE

included accidentally

one
CARDINAL

pastry shop which is actually in

Rio de Janeiro
GPE

,

1200 km
QUANTITY

away. Then we can mention neighbourhoods in

one
CARDINAL

city that end up leading users to another continent. Sometimes you ask something and you won’t get anything other than an apology; change a word and you’ll get a shiny answer.

Sören:

Like many people in the

AI
ORG

community, we were surprised by how well the new generative

AI
ORG

technology works. Despite its existing limitations, the technology now seems advanced enough to find widespread application and create tangible value. Some people compare the ChatGPT breakthrough with the iPhone moment of

AI
ORG

, where everything comes together in a product that everyone understands.

Working with the models has many surprises. For example, providing more and more data or complex training of your own models doesn’t necessarily lead to better results. Interestingly, simple techniques like prompt engineering have proven to be remarkably effective in enhancing the model’s output.

What advice would you give to other product managers and their teams looking to integrate AI into their products for the

first
ORDINAL

time?


Henrique
PERSON

:

AI is still far from being completely reliable, even with fine-tuning and a lot of iterations. And that’s fine depending on your use case.

Minor mistakes are sometimes acceptable. Like any other

MVP
ORG

, it’s important though to consider risks, from usability to legal aspects.

Don’t leave all the responsibility to the

AI
ORG

itself. It’s important to design a product and a process in which you can have visibility on the inputs/outputs and you’re able to iterate and improve the product in a humanly way.


Sören
PERSON

:

In my view, it is crucial to adhere to the principles of strong product management and to ensure that all initiatives are based on a deep understanding of the user, the industry, and the business. The use of AI should not be an end in itself.

That said,

AI
ORG

significantly extends the scope of potential solutions. Once a user problem is identified, AI opens up innovative ways to address it. I think it is very important to understand what AI can do because it has a lot of potential and is evolving quickly. Even if you haven’t identified an

AI
ORG

use case yet, I recommend playing around with it to understand what’s possible.

What’s more, AI can be used to enhance you as a product manager and you can use it to improve your product management work. It offers a variety of ways to improve your productivity such as generating product ideas, analyzing data, summarizing user research findings, analyzing competitors, streamlining communication, or formulating OKRs.

Thanks to

Sören
PERSON

and

Henrique
ORG

for sharing their insights!

At trivago, we are actively learning about and experimenting with AI. We have internal resources for sharing knowledge on the topic, and even AI-powered tools that help us to streamline workflows, improve communication, and boost our productivity.


Earlier this summer
DATE

, we hosted a hackathon, where most of the proposed solutions included some sort of AI application. The winning team proposed an innovative way to implement AI into our product, and we’re excited to explore their forward-thinking ideas. We will continue to share our experiences and learnings from experimenting with AI in future articles – stay tuned!

Disclaimer: Features mentioned in this article are currently undergoing live testing and may not be available to all users.