Here Are The 5 German Startups from 2 Use Cases of AI in Marketing You Need to Know

5 German Startups from 2 Use cases of AI in Marketing

According to the German Economic Institute, there are to date 164 AI startups in Germany, most of which are based in Berlin, which is expected, considering it’s known as the Silicon Valley of Europe. I had the opportunity to learn about some of them in person at Asia-Pacific Week 2019 Berlin. AI startups cover a variety of industries, but of course, I am most interested in AI application in the marketing industry and the different uses and opportunities it presents. Even within the marketing industry, AI applications can cover a wide variety of purposes. For example, who recalls the Big Data buzz a few years ago? Well, having access to large sets of data is useless without the ability to accurately draw insights from it… That’s where machine learning, a subset application of AI, comes in. Without going into too many technical details, AI-based machine learning algorithms process Big Data, performing Data Labeling/Segmentation, Data Analytics, and Scenario Simulation, to create a big picture with insights and patterns that are sorted out, categorized, and packaged into a digestible form.

Apart from the wealth of knowledge and contacts that I got from attending APW2019, I got my hands on The Hundert Startups of Germany 2018, which, as the title implies, introduces a 100 of the most promising startups in Germany as of 2018. So without further ado, and in no particular order, here are 5 German startups from 2 use cases of AI in the marketing industry that I believe are worth checking out and learning about:

Customer Service

Perhaps one of the most mainstream and familiar use case of AI in Marketing are Chatbots. Chatbots aren’t new; they’ve existed since perhaps E.L.I.Z.A in 1966, or if you were like me, you’d recall from your teen years, messing around with A.L.I.C.E from 1995. But of course, the most modern depiction of intelligent chatbots would be Siri, followed by Google Now, Alexa and the army of FB Messenger Bots. The popularity of chatbos in modern business was catapaulted with the use of AI and machine learning, which made them not only an exciting way to engage with customers but an effective method to streamline some customer service processes, and ultimately increase sales. Capitalizing on the rising success of bots of customer service are these German startups:

  1. Solvemate

    Solvemate is a quick to setup and easy to use SaaS platform that uses machine learning to automate 24/7 customer service. What makes Solvemate special? Their virtual agents use only multiple-choice questions to dynamically generate decision trees. With this unique approach, Solvemate clients can reach an average self-service rate of 83% in less than three months, and offer the right solutions in just 12 seconds and in multiple languages.

  2. Twyla

    Twyla positions itself as the world's first professional conversation design software for chatbots. It doesn’t simply give businesses access to an AI-equipped chatbot, but the ability to train it by designing conversational patterns with their own terminology and vocabulary. This gives marketers the chance to personalize a brand’s chatbot to be an accurate extension of the brand’s voice and personality.

  3. Mesaic

    Mesaic is a platform for high mobile engagement through messaging, that leverages the power of automation and AI to transform customer interactions into personalized experiences and continuous relationships across all touchpoints. Beyond chatbots, it specializes in omnichannel and e-commerce solutions that integrates all customer service needs such as browsing products, concluding transactions with payment, and rating.

    Market Research

    This may be a lesser mainstream use case of AI in marketing, but certainly a very important one. Unsurprisingly, advanced data analysis is the #1 AI-tech expected to make an impact on the industry, with 63% of market researchers saying AI will take over data analysis within 10 years, according to a report by Qualtrics. Although 75% of market researchers believe that data produced by AI will be more accurate than it is today, only 40% expect it to explain survey findings as well as humans within 10 years. This sentiment was shared by Dr. Feiyu Xu, Vice President of Lenovo Group and Head of AI lab of Lenovo Research, in her presentation in APW2019. That’s exactly what makes this a good niche market to invest in now, and why these German startups deserve a shout-out:

  4. i2x

    This startup, while also revolving around customer service, focuses real-time conversation analytics and coaching. It aims to improve the communication skills of sales and customer support agents, rather than replace them with chatbots. It empowers them by recording customer calls for playbacks, and analyzing them with a clever combination of machine learning algorithms, big data and communication know-how to improve crucial KPIs (conversion rate and C-Sat score). It also gives feedback to the agents right after each call to level up their communication skills with features such as blacklisting keywords from annoying speech habits, and advising on talk-to-listen ratio, speech rate and volume.

  5. Tawny

Tawny is a pioneer in the field of multimodal AI-powered emotion analytics as it specializes in Emotion AI to “make the world’s products, services and experiences more empathetic”. It enables the analysis of human data from different sensors (e.g. physiological, video, text) to detect emotions and affective states using recognition algorithms powered by affective computing. Among other applications such as the development of tailor-made algorithms for the Automotive industry and detection of athletes’ states to predict future performance, emotion detection allows the assessment of user behavior that can aid User Experience designers and market researchers.

Expected revenue in the emotion detection and recognition (EDR) market to grow from USD 6.72 Billion in 2016 to USD 36.07 Billion by 2021 (Emotion Detection and Recognition Market by Technology (Bio-Sensor, NLP, Machine Learning), Software Tool (Facial Expression, Voice Recognition), Service, Application Area, End User, And Region - Global Forecast to 2021", published by MarketsandMarkets). Image Credit: HYVE/TAWNY.

Expected revenue in the emotion detection and recognition (EDR) market to grow from USD 6.72 Billion in 2016 to USD 36.07 Billion by 2021 (Emotion Detection and Recognition Market by Technology (Bio-Sensor, NLP, Machine Learning), Software Tool (Facial Expression, Voice Recognition), Service, Application Area, End User, And Region - Global Forecast to 2021", published by MarketsandMarkets). Image Credit: HYVE/TAWNY.

Beyond the marketing industry, AI has a major impact on the business models of German startups, especially considering 31.6% of them are in the information and communication technology. While 83% of startups sales are made in Germany, 95.4% of these startups plan to target the European market in the future, with other markets being a much lower priority., according to the Deutscher Startup Monitor 2018. So while AI German Startups may not be up to compete on a global scale, they can still serve as interesting case studies for the application of AI in marketing.

What startups from your country do you find most inspiring? Tag them in the comments!

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How to Be in 2 Continents at Once: Asia-Pacific Week Berlin Recap

APW.jpg

Last week, I had the pleasure of being in two continents at once: Europe and Asia. No, I am not talking about Istanbul… I am talking about Asia Pacific Week in Berlin! When I learnt about the open conference and made my decision to attend, I was expecting perhaps a small-scale networking event that would be a nice side-reason to visit Berlin… But it turned out to be the main event, literally. Companies from all around Asia and Europe, from start-ups to major corporations, came together for a few days of exchanging knowledge, expertise, and business opportunities.

Starting with the first day, a wealth of knowledge and experience was shared by inspiring personalities such as Joe Kaeser, President and CEO of Siemens AG, a global powerhouse in electronics and electrical engineering, Allan Chou, CEO and Founder of RAIDical China which focuses on finding and growing the next Unicorns in Robotics, AI, IoT and Big Data in China, and Lars Voedisch, Managing Director of PRecious communications.

In an interesting panel discussion on future-proofing, the panelists shared the expertise and insights on how businesses and startups can use change as a drive for innovation to stay relevant in the future. Luckily, to help the attendees start on their future-proofing journey, APW hosted a number of experts from several fields to take us through the latest happenings in technologies that are increasingly having a major impact on business: Blockchain, AI, IoT, Advanced Materials, and Cryptocurrencies.

Ruo-Mei Chua (SUTW impact), Allan Chou (RAIDICal China), Gerrit Dumstorff (Hella Fast Forward), Lars Voedisch (PRecious Communications) share insights from their experience on how to become and stay future-proof.

Ruo-Mei Chua (SUTW impact), Allan Chou (RAIDICal China), Gerrit Dumstorff (Hella Fast Forward), Lars Voedisch (PRecious Communications) share insights from their experience on how to become and stay future-proof.

Of all these technologies, I am most excited about AI, as a marketer and as a sci-fi fan! Although there is often chatter in the digital marketing sphere about technological advancements and how they’re going to revolutionize the marketing industry, there are often misunderstandings and a lot of confusion about how exactly to leverage these technologies. Remember the Big Data fuss a few years ago? Well, having access to large sets of data is useless without the ability to accurately draw insights from it… That’s where machine learning, a subset application of AI, comes in. Without going into too many technical details, AI-based machine learning algorithms process Big Data, performing Data Labeling/Segmentation, Data Analytics, and Scenario Simulation, to create a big picture with insights and patterns that are sorted out, categorized, and packaged into a digestible form. Sounds easy, right? Well maybe for a human, but machines have yet to learn how to “explain” things to us in human-form, as they still lack the ability to combine implicit and explicit knowledge, or as Dr. Feiyu Xu, Vice President of Lenovo Group and Head of AI lab of Lenovo Research, said: “common sense”. While there are AI methods that model implicit or explicit knowledge, the next big challenge is to bring these two together in “Explainable AI (XAI)”… An AI that can be trusted and easily understood by humans, not because it can explain itself, but because it is transparent enough with any explanations that are needed being part of its design process.

Dr. Feiyu Xu taking us on a deep dive into AI and the challenges it faces…

While omnious sci-fi movies and series (Black Mirror anyone?) come to the minds of most people when they think of such technolgoies, they can pose more opportunities than threats if we learn how to take advantage of them with a strategic plan, rather than just the fear that they’d drive businesses or employees obsolete (or the human race to extinction…). This fear, however, can still be useful data for innovation, according to Raymond Miranda from Laborastory, a story and innovation expert, and global speaker.  I had the pleasure of attending Raymond’s StoryMapping Unplugged workshop on the 2nd day, and found the process of using stories to guide startups through innovation, quite… innovative!

Raymond Miranda taking us through StoryMapping and how each step applies to starting a business.

Raymond Miranda taking us through StoryMapping and how each step applies to starting a business.

On that second day, my attention shifted from technologies to gender, culture and bias… A topic that is dear to me as a female entrepreneur from the Middle East, having also heard from and read about many other women in business, and the struggles they have to go through. I was glad to see Lu Ying, co-founder of Future Urban Living, bringing up the important point of male empowerment in the home world in her keynote “Bridging the gap between gender, industry and culture”. It is in my opinion that if we want to reduce bias towards women in business, we need to stop treating the desire for flexibility, work-life balance and family life as “feminine” traits, and reduce the stigma around men having the same desire. I want to feel that the way I want to do my job is a “human desire”, rather than a female thing. And women shouldn’t feel like their careers are less important or serious to them if they want to take time off to build a family, and feel pressured to compete with men in that regards. If we make it safe and normal for both genders to have a work-life balance, both would benefit and so would the employers.

Lu Ying sharing with us her insights on gender equality in business for better economic value.

Lu Ying sharing with us her insights on gender equality in business for better economic value.

In that regard, as a behavioral economics (BE) buff, I am quite enthusiastic about the possibilities that BE principles, such as nudging, present in fostering inclusion, and improving gender equality. I brought some points up from those articles with Miroslav Dimitrov, from SAP.iO No Boundaries, the first comprehensive inclusive entrepreneurship initiative for underrepresented entrepreneurs in the business software industry, during his keynote where he pointed out the low rate of female entrepreneurs with startups and even much lower rate of those who acquire funding and investments. I wondered if they’d be using techniques such as blind auditioning to reduce gender bias during start-up pitches for funding, he believes though that the right selection of open-minded judges who care more about the pitch than the pitcher’s gender is key.

One of the biggest takeaways from APW, aside from plenty of business opportunities, is the bridging of the very distinct cultures of Asia and Europe through sharing and understanding. That isn’t surprising considering Europe is mostly a low-context culture, that communicate information in direct, explicit, and precise ways, whereas Asia is a high-context culture, that communicate in ways that are implicit and rely heavily on nonverbal language. Attendees especially shared their experiences with cultural differences in business during the keynote and workshop “Yays and Nays of intercultural communication” by Tien Ma, Director, and Lucas Jahn, Senior Account Manager, at REDHILL international communications firm, who will soon be sharing with us a report of the workshop outcomes, which I in turn will share with you later.

John Lucas and Tien Ma from Redhill International Communications agency share low context and high context cultures where most central and northern European and western countries being low context, and Asian, Arab, south European, African and Latin American countries being high context.

John Lucas and Tien Ma from Redhill International Communications agency share low context and high context cultures where most central and northern European and western countries being low context, and Asian, Arab, south European, African and Latin American countries being high context.

Of course, it is not news that culture plays an important role in business, as cultural differences can pose quite a challenge, especially when doing business across borders. It is a discussion I indulged in with Alexander Jansen, a serial entrepreneur, mentor and professional consultant for startups, who provides leadership training & coaching, especially in agile and innovation environments across Europe and Asia. From our discussion, it was evident that there are difficulties in conducting business between two cultures that operate on a different pace, such as the German pace being quite steady and time-consuming to ensure quality, whereas the Asian pace in countries such as China and Singapore can be fast and ad-hoc to favor innovation.

Naturally, Europe and Asia have many distinct countries and cultures within, that can’t be just bundled under one label. During the third day of APW, Embassy Day, it was clear where interests lied when it came to Asia… Countries like Singapore and China garnered much formal business attention, but I personally was there rooting for one of the countries on my travel wishlist: Nepal. Home to friendly and modest people, it is perhaps most known as a trekking destination for the Himalayas, or for the devastating news of earthquakes in 2015 that left a high death toll and the country in ruins. Still, it is certainly not a formal or serious vibe that we got from the keynote of Mr. Ramesh Khanal, Ambassador of Nepal to Germany, that day, but a message of hope, music, dance and a warm invitation to experience Nepal’s natural beauty and sense of adventure. I’ll be taking up his invitation for sure some day, as I do believe in Nepal’s potential of being the next adventure and budget travel destination in Asia!

Me all huddled in with the Nepalese Ambassador, Mr. Ramesh Khanal, and the beautiful colorful Nepalese dancers.

Me all huddled in with the Nepalese Ambassador, Mr. Ramesh Khanal, and the beautiful colorful Nepalese dancers.

There was a lot more happening in APW, and a few more days to cover, but this was a very brief summary of what I was able to gather. Still, if you’d like to know more or need help connecting to any of these speakers/businesspeople, I am more than happy to help. Possibly being the only representative of the Middle East at APW, I felt like I was caught in the middle between East and West with barely anyone knowing much about the MEA region, but I tried to do my best to present the unique Middle Eastern culture and the business value and potential it holds. Hopefully next year, promising and innovative startups from the Middle East can also have a presence at APW! Until then, subscribe to my blog or connect with me on Linkedin, Instagram or Twitter to stay updated.

So, which technology do you think would have the biggest effect on your career/business:

  1. AI

  2. Cryptocurrencies

  3. Blockchain

  4. IoT

  5. Advanced Materials

  6. None

  7. All

  8. Other? Specify in the comments!