Please tell us about your journey into marketing data technology and how you started at 1PlusX.

I started working in the digital advertising space in 2000 when I joined Bertelsmann Media company. While there, I oversaw the design and implementation of digital products and services. In 2009, at Google, I led the product management team of Google Search and Consumer Products in Europe, and later on the product and engineering teams of YouTube EMEA.

We focused on developing advertising and marketing technology for audience building, at a time when the industry was just starting to talk about what is now the current mantra: match the right message to the right user, though the right channel. I’ve always been fascinated by how artificial intelligence can help bring all that together.

When I left Google, I realized many European companies had access to vast sources of data, but weren’t using this to its full potential. The next step came naturally – we started 1plusX to help these companies extract useful insights and achieve better marketing results through artificial intelligence.

Tell us about the data science engine driving 1PlusX’s offering to the Marketing and Data Science teams.

When we started 1plusX, we noticed one main trend: everyone focused on the user, but not many looked at the item the user interacted with.

Back then, Amazon’s algorithm was already sending product suggestions to online shoppers based on their search and purchase history. I was surprised more companies weren’t doing the same. Knowing this, we built what we call user-to-item embedding space; through machine learning, we continually adjust users and items, gathering important audience insights as a result.

We did this at a time when everyone copied or bought data from third parties, but we were determined to find a more efficient, sustainable way to do things. By enriching already available data through machine learning, we enabled marketing teams to achieve faster, higher-quality audience segments at a fraction of the cost. With the tightening of GDPR and privacy legislation, this became even more crucial.

How much have Customer Intelligence technologies evolved in the last 6-12 months?

In my opinion, they haven’t evolved enough.

Many of these technologies still follow the basic principle of gathering as much data as possible, when really they should prioritize data quality. This has been a common approach to data processes in the U.S. for a long time. Following the introduction of the CCPA – alongside Apple’s IDFA and the demise of third-party cookies – innovating data solutions is now a necessity. It’ll be interesting to see what this innovation will bring to the market in the coming year.

DMPs have made phenomenal progress in the last 5 years. What are the most profound developments in the Martech landscape?

Only a few companies are truly innovating at the moment; many, I would say, have stagnated.

We are observing how larg companies are getting rid of old-generation DMPs, because these providers didn’t move in the same direction as the rest of the industry, or at least not as fast. When we talk to businesses all over the world, the frustration towards old DMP technology is evident. They now have to compete with solutions that can build audiences in real-time.

AI is significantly changing the data and marketing space. With less hard-fact data available, predictive capabilities will become even more crucial for success as they will enable companies to both work with anonymous users and strengthen their understanding of known customers.

Tell us more about 1PlusX and how it helps media companies and publishers.

When we started the company, we discovered that media companies had large data sets but simultaneously the wide majority of their users were anonymous.

For example, of all their logged-in users, only between 3%-10% declared their gender and age. Even today, a large part of brands’ advertising efforts go towards targeting based on age and gender. It’s crucial for publishers to have this insight, especially when they’re competing with Google and Facebook. For media companies and publishers, we can provide age and gender data for 100% of their audience, regardless of whether they’re anonymous or logged-in users. That gives an enormous boost to our clients in terms of targetable inventory. Through the 1plusX predictive engine, publishers can forecast who is going to click on ads, as well as who is more inclined to subscribe to premium services. In doing so, we enable today’s publishers to maintain a multilayered revenue stream.

Could you tell us about the tools / technologies you currently use for Marketing, Sales and Revenue generation?

Beside our sales CRM system, we have developed our own technology to find out what kind of marketing tools companies use.

When we enter new markets and talk to prospective clients, this allows us to discover their pain points and initiate a conversation on how 1plusX can meet their specific needs. The rest of our sales and marketing strategy involves search engine marketing, social media, events – now mostly in virtual format – and public relations. Events are especially important for understanding the current market trends and taking part in key conversations around privacy, adaptability, and digitalisation.

During COVID-19, how did you stay on top of your Marketing and Product Engineering goals?

When COVID hit we did what everybody did – take stock and adopt a cautious wait-and-see approach.

We soon realized, however, that our clients needed even greater support to become efficient in the more challenging environment. The world had suddenly gone digital-only, meaning companies that generated revenue from passing footfall had to change their business model overnight. Digital publishers and ecommerce sites experienced unprecedented spikes in traffic, which need to be maintained to convert ‘lookers’ into returning visitors beyond the apex of the pandemic. Media companies especially, were under great pressure due to paused advertising spend. While most businesses went introspective, for us, it was important to keep an open dialogue with our clients.

Tell us about the COVID-19 specific personalized marketing activities that your customers (anonymous is fine) testified to you as feedback.

Consumer behavior changed dramatically during the first half of 2020, but the sentiment analysis we conducted for our clients was vital when helping them navigate this. They were able to better understand how their audience reacted to events in real time, which was key to driving resonance and engagement.

Our solutions enabled clients to respond rapidly to audience changes and be adaptable in these unprecedented times. 

Tag a person from the Marketing technology / Data Science industry whose answer you would like to see here:

I’d like to tag two!

Amy Chang, who I worked with at Google, she is the brainchild of Google Analytics.

And, Rick Van Yperen, whose brilliant work on data-driven marketing at Unilever would make him a very interesting interviewee.

Thank you, Jürgen! That was fun and hope to see you back on MarTech Series soon.