### How we successfully developed a personalised news application.

We were lucky enough to have been among the participants of the [Digital News Initiative](https://digitalnewsinitiative.com/). After 12 months of work, our project officially ended this July and now we believe it is time to share our insights so that everyone can grow and learn with us. In this report, we provide information about what exactly we did in the project and, more importantly, what we learnt about personalisation and how we will we proceed with the service.

### NZZ Companion

In a world where anonymous ‘one-size-fits-all’ news experiences are all around, we intended to create something different, something that would be as individual as our users. A product that would be able to take the reading habits and reading preferences of our users into account while ensuring that nothing important would be missed. With that in mind, we set off on a quest to develop a personalised news experience that helps users to find news relevant to them with less effort. The outcome was the NZZ Companion Mobile Application.

The NZZ Companion Mobile Application for iOS and Android consisted of two main visual parts: the curated NZZ.ch-Stream on one side and a user’s personalised stream called Companion on the other side. Additionally, a navigation element named ‘Bibliothek’ was introduced where more user-centred features such as personalised reading lists and bookmarks were found.

The content in the curated NZZ.ch-Stream was identical to our existing NZZ-News Mobile Application or mobile site (that is, it was similar to many news apps created by our competitors). Articles provided in this section were selected by our editors and the same content was shown to all users. The NZZ Companion-Stream, on the other hand, combined editorial curation with algorithmic technologies for a personalised news experience. This separation was chosen deliberately so users in the beta phase could better experience the difference between the two.

During the project, the personalised NZZ Companion-Stream differed heavily from the curated one due to the following features:

* It showed older articles that were published up to 48 hours earlier

* It used a variable mix between ‘editorial relevance’ and ‘personal interest’

* It displayed super-relevant news to all users, regardless of a user’s indicated preferences or interests (‘filter bubble’)

* The article’s visual interface was lighter and its user features more obvious

### What we learnt about personalisation

It was our goal to develop a personalised mobile application that would **help users to find relevant news with less effort**. This is in contrast to other personalisation efforts taken by other services, which are more likely to show more of the same content to a user to increase the Click-Through-Rate.

To be able to develop a valuable service for our readers we decided to roll out a beta mobile application early in the project. Doing so allowed us not only to co-create the data products and the application in accordance with the needs of our users but also to gather answers to the following questions, which would, in turn, provide valuable and statistically proven feedback to our initial hypotheses (listed below):

1. Do beta testers value personalisation at all and does this perception change over time?

2. Do beta testers actually use a personalised service and are the articles recommended relevant to them?

3. What benefits do beta testers see in the personalised NZZ Companion-Stream?

In the following, we would like to assess the answers to these questions and apply them to our three hypotheses.

**Personalisation creates added value**

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2Fq4ZM2ameUxZiXXPA8CMQeyRrboH2%2F5fUhxLHzlnZCg7tCZF3Q%2F56746b4e-739f-4bc8-9df9-bc6d103cc488.jpg?alt=media&token=cbbc3145-5418-47d4-8d53-eafd4828efc6","id":"56746b4e-739f-4bc8-9df9-bc6d103cc488","width":2000,"height":2352,"filename":"image (1).jpeg","type":"image/jpeg","caption":"","border":false}]}
```

The first hypothesis laid out the ground for any future actions in personalisation because it was all about the value creation of such a service. Our data shows that around 84% of beta testers believe that the personalised NZZ Companion-Stream created added value to them. More importantly, this perception changed and improved by 20 percentage points compared to the beginning of the beta test. We believe that this increase is due to improvements in the algorithms and the addition of new user-centred data products (e.g. personalised weekend reading list) and features (e.g. article rating). As advocates of user-centred design, we also believe that the more users are engaged in a product development process, the more useful they attach to the product, which leads to an increased perceived value.

**People need time to get used to personalised content**

The usage of the personalised NZZ Companion-Stream increased by 16 percentage points within the beta testing period. While at the beginning of the beta test around 45% of users read articles in the Companion-Stream, this number rose to 61% in the final month.

It is difficult to attribute one single factor to this increase in usage. We suspect the following factors played a major role:

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2Fq4ZM2ameUxZiXXPA8CMQeyRrboH2%2F5fUhxLHzlnZCg7tCZF3Q%2Fe658e76c-9fcc-45d2-bc47-95e489e77db6.png?alt=media&token=b0a37a0d-4d76-4c10-b17b-e9842cdc1f2f","id":"e658e76c-9fcc-45d2-bc47-95e489e77db6","width":2000,"height":1320,"filename":"image (2).png","type":"image/png","caption":"","border":false}]}
```

* *People are creatures of habit*: Users needed time to get accustomed to the companion stream and then develop a positive attitude and trust towards the algorithm over time

* *Improvements in the algorithms*: The balance between editorially and personally relevant articles got better over time — we believe we managed to significantly develop the algorithm over the months of operation

* *Release of new features* *and* *new data products:* Providing users with an easy-to-use bookmarking feature or the introduction of desired data products such as a personalised weekend reading list could have led to more usage

* *Increased stability*: Fewer crashes and bugs

However, what we know for sure is that the perceived relevance of articles in the personalised NZZ Companion-Stream increased over time. In the surveys conducted, we found that beta testers found the personalised articles to be significantly more relevant in the final month as compared to the launch of the product in March.

The value proposition of NZZ Companion is to find relevant news with less effort. We are happy to confirm that we could increase the perceived relevance of personalised articles over time.

**There is no single reason why beta testers use the personalised stream**

One of the top benefits of the app, as perceived by our beta testers, is the way it provides quick access to interesting content since the companion stream decreases search times. Further, the beta testers appreciated having access to older content that they may have missed in the curated stream. Lastly, beta testers turned to the personalised stream if they wanted to discover articles that they would not have read otherwise.

In line with our goal, we were able to successfully offer quick access to interesting content as this is among the top benefits of using a personalised stream. Additionally, we believe that we succeeded at building personalisation that still allows its users to discover new and surprising content so they do not get trapped in a filter bubble.

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2Fq4ZM2ameUxZiXXPA8CMQeyRrboH2%2F5fUhxLHzlnZCg7tCZF3Q%2Fbfa9913a-06f1-443a-b5aa-fc3b8cbd9632.jpg?alt=media&token=8c244a9e-7aec-4774-b316-9f2fa7291f84","id":"bfa9913a-06f1-443a-b5aa-fc3b8cbd9632","width":2000,"height":1204,"filename":"image.jpeg","type":"image/jpeg","caption":"","border":false}]}
```

> Facts and Figures:
>
> *Five people worked part-time on NZZ Companion for over one year*
>
> A f*ully data-driven and user-centric approach*
>
> *Iterative development cycles and lean team management*
>
> *Five months of beta testing*
>
> *More than 400 beta testers were used for both iOS and Android*
>
> *Algorithmic releases roughly every three days*
>
> *Features: read/unread status of articles, article rating, bookmarks, sharing function*
>
> *Data products: personalised reading list, weekend and evening reading list*

NZZ Companion case study

### Scaling Audio Service: How we launched a high-quality Text-To-Speech service at “Neue Zürcher Zeitung”.

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2Fq4ZM2ameUxZiXXPA8CMQeyRrboH2%2FKsjyGakXnkjUhoK6IUIV%2F80a15d97-3065-40a5-83dd-ca048d5f7754.mp4?alt=media&token=90fdc639-f3b8-4df3-af42-5ebdd08906ca","id":"80a15d97-3065-40a5-83dd-ca048d5f7754","width":1920,"height":1080,"filename":"NZZ Audio.mp4","type":"video/mp4","caption":"","border":false}]}
```

At *Neue Zürcher Zeitung*, a Swiss publisher of high-quality journalism for a German-speaking audience, we successfully launched a Text-To-Speech (TTS) audio player feature as a beta version in our web and mobile channels. It is a service to our on-the-go and audiophile users that makes consuming news in an alternative way simple and convenient.

### How we defined the need for a Text-To-Speech service

With voice technologies like Amazon Alexa and Google Home emerging and becoming ubiquitous in our lives, media companies have been focusing a lot of their output towards delivering news with audio in the last few years.

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2Fq4ZM2ameUxZiXXPA8CMQeyRrboH2%2FKsjyGakXnkjUhoK6IUIV%2Fb3780f43-05cd-4148-a4ce-7b5dab0dc6aa.png?alt=media&token=c442d6f7-f44d-47c1-81a6-4cd79e3d752f","id":"b3780f43-05cd-4148-a4ce-7b5dab0dc6aa","width":2000,"height":1336,"filename":"Minimized text-to-speech Player.png","type":"image/png","caption":"Minimized text-to-speech Player","border":false}]}
```

Our users have also been voicing their wish for more audio content. Classical podcast formats are not enough anymore — users want to have the choice between reading and listening to an article. We started wondering about the number of articles to be transformed into audio. Should we have professional, native speakers cover a certain amount of articles a day, as seen, for example in ‘The Economist’’? Or is it a greater need for our users to be able to access *all* of our articles as audio?

In user interviews, we identified that our users wanted to be able to choose whichever article they wanted to listen to freely. Thus, we decided that we wanted to offer all articles published as audio. With the large load of text — NZZ publishes up to 200 articles on its digital entities per day — recording with a native and professional speaker was not an option. The phase of finding an automated and scaling conversion of text to audio began.

### How we defined the business case

NZZ’s strategy is to stay profitable in the long term through digital subscriptions. With this goal in mind, NZZ’s digital product was relaunched in November 2017. We introduced a two-stage funnel as a driver for conversion. In a first step, a user has to register to be able to access features such as our bookmark function or personalization service. In a second step, after users have consumed a certain amount of content, users are requested to sign up for a paid subscription.

By filing our new audio functionality into the first step of the funnel, users have to register to be able to make use of the new service. Situating our new audio service behind the mandatory registration allowed us to not only seamlessly implement it in our business model but also makes it another trigger to drive conversion.

### Mature design patterns in the audio domain

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2Fq4ZM2ameUxZiXXPA8CMQeyRrboH2%2FKsjyGakXnkjUhoK6IUIV%2F0863f5bc-bb98-41bb-a54f-5600e48b0e3f.png?alt=media&token=4ee8b452-acad-483c-b640-6be90b5af309","id":"0863f5bc-bb98-41bb-a54f-5600e48b0e3f","width":2000,"height":3680,"filename":"image.png","type":"image/png","caption":"","border":false}]}
```

With state-of-the-art audio players such as those of Spotify, Apple Music, Acast or Sonos already being heavily represented in our everyday life as apps and services, we decided that we didn’t have to re-invent the design of an audio player and that it would be mostly confusing to our users to do so. We therefore drew from already existing players in many of our design decisions. When it came to new functionalities, such as the changing of the speed, we iteratively designed, co-created with our users and tested different versions until we arrived at the design we have today. We will however continue to do so over the next months as the use case is still new to the industry.

### How we built the service with its unique structure

When it came to the actual conversion from text to speech, we looked into several [TTS](https://en.wikipedia.org/wiki/Speech_synthesis) services, including [IBM’s ](https://www.ibm.com/watson/services/text-to-speech/)*[Watson](https://www.ibm.com/watson/services/text-to-speech/)*, *[Amazon Polly](https://aws.amazon.com/polly/)*, and *[Google Wavenet](https://cloud.google.com/text-to-speech/)* (just to name a few). For starters, we began working with Amazon Polly.

Knowing that any TTS service on the market would develop rapidly over the coming months, we had to build an architecture that would be flexible enough to react favourably to change (e.g. replacing the TTS engine). Our need to be flexible is what led us to opting for our unique structure: The text runs through our self-built middleware — we call this Orator — where words like “z. B” are replaced into “zum Beispiel” (German for “for example”) or abbreviations are changed from “boa.” into “Boas Ruh” (one of NZZ’s editors). The text is then transformed into [SSML](https://en.wikipedia.org/wiki/Speech_Synthesis_Markup_Language) and afterwards sent through the TTS engine where an MP3 is generated.

SSML, Speech Synthesis Markup Language, provides us with a standardized method for controlling different aspects of speech synthesis output. For example, with SSML, one can alter prosody attributes, such as rate, pitch, and volume, insert pauses of any length, change the speaking voice while reading, and control many other aspects of how the text is read by the synthetic voice. The great thing about SSML is that basically the same input can be fed to any TTS engine: Whether it’s Amazon Polly or Google Wavenet, they all follow the same commands — with some small exceptions. And because the output of our middleware lexica feeds into the SSML, any of the components of our structure can be replaced.

Just few weeks before the beta launch of our audio player functionality, DeepMind’s Wavenet released its TTS service fo the German Language. Thanks to the flexibly chosen architecture, we completed the change at short notice. The result was a service that was better by quantum leaps. We expect this rate of continuous improvement to accelerate further and that the human nativeness of the voice will massively increase over the coming months.

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2Fq4ZM2ameUxZiXXPA8CMQeyRrboH2%2FKsjyGakXnkjUhoK6IUIV%2Fd3eb0dbf-8a32-4a00-ad72-fe255422b3d5.png?alt=media&token=60d07eba-d62f-4394-a4ff-eb2b9b7c2af9","id":"d3eb0dbf-8a32-4a00-ad72-fe255422b3d5","width":980,"height":1323,"filename":"Service ready to be distributed on any kinds of outputs such as Smart Speakers or in Cars.png","type":"image/png","caption":"Service ready to be distributed on any kinds of outputs such as Smart Speakers or in Cars","border":false}]}
```

---

## Five things we learned while building our new text-to-speech service

### 1. Google Wavenet is super clever. But when it comes to Swiss-German, that’s just not enough

Google Wavenet, the text-to-speech engine we used to generate audio files, is a talented little thing when it comes to languages. So far, it speaks nine languages with a quality that sounds much more natural than other systems. It uses a neural network that has been trained with a lot of speech samples. This allows it to create audio waveforms from scratch that follow the tone sequence and structure of the samples. This works wonderfully for languages the engine already knows and is attuned to. When it comes to Swiss German words, however: not so wonderful.

With *Neue Zürcher Zeitung*being a Swiss newspaper and some words or names being derived from Swiss German (some strange dialect stuff) or French, our audio service tends to stumble over them. We can’t blame it — we’re the ones that told it to interpret everything in high German, after all.

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2Fq4ZM2ameUxZiXXPA8CMQeyRrboH2%2FKsjyGakXnkjUhoK6IUIV%2F779904d2-17f0-4d5f-bfae-b94223d1edcd.png?alt=media&token=6a994013-6d25-444b-96a2-dfd304f8e574","id":"779904d2-17f0-4d5f-bfae-b94223d1edcd","width":2000,"height":4032,"filename":"image (1).png","type":"image/png","caption":"","border":false}]}
```

We have taken these cases (which, incidentally, also affect words from other foreign languages), into account in our solution and equipped a middleware with a lexicon through which all words flow before they are converted into audio. For example, if a “Cervelat” (a Swiss sausage) is referenced in an article, it is converted to “Servellah” in our middleware, which we lovingly call “the Orator”.

Meanwhile, our lexicon counts almost 12'000 entries: our editors’ author abbreviations, the correct pronunciation of a Vietnamese restaurant in Zurich (Co Tschin Tschin), the title of a Black Mirror episode (Ark Äyntschl), you name it.

Of course, we can probably never cover all the exceptions by ourselves — this is why we will introduce a feedback feature for our users in the future.

### 2. Make your architecture mix-and-match-friendly or don’t make an architecture at all

With that constant wind of change blowing in your face, there are a few things you can do to stay warm: Carry a backpack full of spare clothes. Mix and match. Layer, if needed. The same thing applies to text-to-speech services: In a changing industry with changing tools, needs and products, we needed to build a service that could easily be adapted to changing circumstances. So we opted for our unique structure.

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2Fq4ZM2ameUxZiXXPA8CMQeyRrboH2%2FKsjyGakXnkjUhoK6IUIV%2F396e8cf3-e693-4dd3-8000-f15f30a90b2a.png?alt=media&token=4630f452-ca41-4169-8966-8219c24ae38e","id":"396e8cf3-e693-4dd3-8000-f15f30a90b2a","width":2000,"height":743,"filename":"Text-To-Speech Architecture.png","type":"image/png","caption":"Text-To-Speech Architecture","border":false}]}
```

This way, we were able to move our service from Amazon Polly to Google Wavenet at short notice. The result is a service that has improved by quantum leaps. As Google Wavenet learns on its own, we expect the service to improve quickly. Another major advantage: We can roll out the audio feature in our other products such as the finance vertical “The Market” or our Sunday publication “NZZ am Sonntag” — all we need to do is attach their CMS endpoints.

### 3. Some people love audio, others just don’t

There are people that love audio. They listen to their morning news through a podcast or on the radio. They don’t *read* books. And they can’t wait to finally get to listen to their newspaper.

And then, there are people who actually still really like to read their news. They really don’t need to be bothered with this audio business. They just. don’t. need. it.

We asked both user types to evaluate different text-to-speech engines and tested a section of text read by an actual human for comparison. The results weren’t really surprising regarding the preferred voice: Both groups rated the natural human voice the highest.

But the actual exciting insight for us was, when we listened to the reasoning behind their answers: People who already used a lot of audio were not really bothered by worse quality — they just wanted to be able to listen.

On the other hand, people who didn’t really use audio much up to this point said they probably wouldn’t use the service even if the voice were more natural.

Thus, our conclusion: Either you like and use audio, or you don’t like and use audio. The quality of the speaker doesn’t seem to have a relevant influence on the usage.

### 4. How to make a written piece pleasing to listen to

You can imagine the elements coming out of our CMS like the pieces of one of those pre-fabricated houses which can be put together in lots of different ways.

An article that is published in its text form on our website is one house layout, and the one in MP3 format is a different house layout: They had the same elements to pick from but were laid out in a different way.

For the audio version of the article, we put all the elements back into the article construction kit and freshly looked into how our users would like an article read to them. Does it make sense to have the article read out according to exactly the same structure as a screen reader, for example? Or would it be better to define a new order or to omit certain elements? We opted for second and defined audio templates, which make our solution unique.

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2Fq4ZM2ameUxZiXXPA8CMQeyRrboH2%2FKsjyGakXnkjUhoK6IUIV%2Fc97d8b81-ae56-4ae8-9084-94149a9715a5.png?alt=media&token=80b137b3-f3b3-4e64-9894-13ee7807866a","id":"c97d8b81-ae56-4ae8-9084-94149a9715a5","width":2000,"height":1558,"filename":"To implement our templates, we took example articles and transcribed them into SSML.png","type":"image/png","caption":"To implement our templates, we took example articles and transcribed them into SSML.","border":false}]}
```

To implement our templates, we took example articles and transcribed them into [SSML.In](http://SSML.In) the templates, we determined which elements on the page should be pronounced in which order, which ones should be omitted and which should be pronounced in a different volume. So, read the headline first, (and just a tad louder,) go on with the lead, pause for a bit, then read the author byline. If there’s a new chapter title, read that one just a tad louder again. What we received was an article structure created especially for the audio experience.

### 5. Many different player experiences might make your life a little difficult

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2Fq4ZM2ameUxZiXXPA8CMQeyRrboH2%2FKsjyGakXnkjUhoK6IUIV%2Fa13e389f-9f50-48e7-bae9-2954f9f5769d.gif?alt=media&token=7003e2ae-c8cc-4623-89e4-805018ff4404","id":"a13e389f-9f50-48e7-bae9-2954f9f5769d","width":226,"height":400,"filename":"One of many versions_ The player in the app.gif","type":"image/gif","caption":"One of many versions: The player in the app","border":false}]}
```

When we set out to implement audio, we knew that we wanted to introduce it across *all* of our products: On desktop, in the app, and on tablets.

We realized relatively early on that we had to design and develop many, many different player variants: On the web version of *Neue Zürcher Zeitung*, for example, background playing was not possible with the current technology stack, so we left out the previous and next buttons. In turn, the app needed a minimized player with an integrated image to provide orientation. And then, of course, there were landscape versions that had more space to accommodate different sets of icons.

Sometimes we find ourselves dizzily wondering which version we are currently looking at and which the fine-tuned little differences between all of them are, but then we remember: We’re creating the most pleasant experience for our users across our different products, and that’s something we’re pretty darn proud of.

```cv
gallery
{"layout":"hscroll","images":[{"src":"https://firebasestorage.googleapis.com/v0/b/maitake-project.appspot.com/o/pages%2Fq4ZM2ameUxZiXXPA8CMQeyRrboH2%2FKsjyGakXnkjUhoK6IUIV%2F8705902f-6c7a-49eb-b1f2-66af27b337ee.png?alt=media&token=1385eb27-d71d-497e-bc76-a546bcdb8846","id":"8705902f-6c7a-49eb-b1f2-66af27b337ee","width":2000,"height":1054,"filename":"The audio player experience on the digital NZZ (Web, Desktop)The audio player experience on the digital NZZ (Web, Desktop).png","type":"image/png","caption":"The audio player experience on the digital NZZ (Web, Desktop)The audio player experience on the digital NZZ (Web, Desktop)","border":false}]}
```

NZZ Audio case study

Director Digital Unit

Edi.11 Gold

Best of Swiss Apps Award Bronze in User Experience

Best of Swiss Apps Award Silver in Design

UX Design Award Public Choice for Cookidoo®: Created Recipes

Red Dot Design Award for Cookidoo® Created Recipes - provided by Thermomix®

iF Design Award for Cookidoo® Created Recipes - provided by Thermomix®

Scrum Product Owner

Certified SAFe® 5 Agilist

NZZ Companion

Ricola Farmer mobile game experience

NZZ Audio

Vorwerk FiBRE Design Principles

A new personalised experience for the NZZ.ch ecosystem

Product design themarket.ch

Relaunch of the NZZ E-Paper App

Cookidoo Created Recipes

For 2023 I decided to further work on my feedback and reflection skills. This will also mean spending more time working with my teams at Vorwerk and supporting, mentoring and role-modelling how a healthy feedback culture should look like. I reworked the training material that served me well in the last few years and decided to open-source it.

Receiving and giving feedback. An actionable guide.

TeamKit provides a practical solution for teams everywhere to work towards improving team culture and experience. It is a self-facilitated team formation process which encourages teams to use the right tools or methods during team formation. TeamKit enhances effectiveness by focusing on “how“ teams come together and define their journey ahead. Importantly, TeamKit does not require any prior knowledge of team formation.

TeamKit

A simple but essential core set of rules to guide us towards better solutions.

Manifesto for service and product design

Fachevent #1 mTrends

Challenges & applications of mobile technologies

Vice President

President

Organisation Youth Festival

Guest lecturer

Communication Planner

Intern

Concept Developer / Information Architect

Customer Program Manager

* Managed the native app portfolio for NZZ, leading strategy, design, and execution.

* Directed the redesign of NZZ.ch, introducing a digital-only subscription model.

Product Manager Apps

Vice President Digital Unit

* Directed the digital experience strategy for the Cookidoo ecosystem.

* Doubled the Cookidoo user base from 1.5M to 3M subscribers.

* Expanded the design team from 2 to 6 FTEs.

* Built a global UX community of 25+ members.

* Developed and implemented a global design system, enhancing quality and reducing costs.

* Led the team to win several awards for Thermomix-created recipes (Red Dot Design Award, iF Design Award, UX Design Award Public Choice).

Head of Experience Design

Head of Administration

Product Marketing Manager

Account Manager

Operations Manager

* Founded and led NZZ’s digital product development.

* Managed the market.ch project from inception to completion, overseeing strategic development, pricing, branding, and design.

* Developed an intelligent news personalisation service for Google’s Digital News Initiative.

Head of Digital Product Design

* Led Vorwerk’s digital strategy, driving annual revenue growth into the nine-figure range, with substantial contributions from digital leads.

* Oversaw a budget exceeding EUR 15M, achieving cost efficiencies while maintaining high-quality standards.

* Facilitated six-figure sales of Thermomix units through optimised online channels.

* Supported M&A and market expansion, integrating business units using the global design system.

* Directed e-commerce strategy for Vorwerk’s transactional websites, overseeing sales of EUR 100M+.

* Resolved initial resistance and established effective collaboration across seven markets.

* Implemented a demand and prioritisation process, reducing time-to-market by 50%.

Global Head of E-Business ad interim

Niklaus

2023