Pragmatic Analytic Services
DECODING SOCIAL GENOMES WITH PAS
Mind or gut – how do consumers choose? A question that has troubled experts since time immemorial. For the digital advertisers at komm.passion, it’s not even a question. Why? Because the agency’s analysts deliver precisely the information that customers need for their marketing decisions. The goal: transparent data that makes excellent decisions possible. Their latest tool in this area is PAS 2.0: With this social medial analysis tool we designed and built ourselves, it is possible to read all social media platforms to obtain precise data for the optimization of digital advertising – worldwide.
Never has it been so easy to captivate target groups, find influencers or create personas – today 3.5 billion people are busy revealing where they are, what they eat, and what they buy, love or hate. And this is only the beginning. A flood of expressive information is swelling, with no end in sight. By 2025, it is estimated that total data volume worldwide will swell five times its current size to 175 zettabytes – stored on DVDs, the stack would reach higher than 23 times the distance from Earth to the moon.
Even if, according to the IT-market observers at IDC, “only” 20% of this data is created by consumers and the rest is from companies, one thing is certain: Marketing campaigns will be virtually impossible to plan, implement or control without AI. Because monitoring and analyzing millions upon millions of new images, texts and videos is simply impossible to do manually. The digital advertising experts at komm.passion have long recognized this fact, which is why we created PAS 2.0. This analytical tool is highly efficient at combing user data on social networks with the help of AI technologies. PAS has been used by major business consultancies and even international brands for several years now. We have implemented target-group projects in China, France and Eastern Europe.
“We are able to precisely map target group behavior practically in real time on all social media platforms in every market in the world. That is extraordinary.”
komm.passion-CEO Prof. Dr. Alexander Güttler
Understanding how target groups tick is the foundation for market success. The marketing mantra will never change. What does change constantly, however, are the spaces where consumers shop and communicate. For the web: Users are still moving unselfconsciously, even curiously – i.e., in a very human way – on platforms and markets. But the age of naiveté may soon come to an end. Social media channels are massively struggling with data scandals, hate speech and fake news. In early 2019 alone, Facebook stated that it blocked 2.2 billion fake accounts – an alarming statistic. In Europe, the world’s most well-known bandwagon network started losing users for the first time in 2018. Does this herald the slow death of the social media giant?
Meanwhile, Instagram is booming. The photo app – also part of Zuckerberg’s empire – is currently clicked by over a billion people per month. And 80% of them follow at least one company! Whether it’s social networks, video sharing, the blogosphere or influencer platforms: Marketers who don’t explore the abundance of data on social media channels and use it as the foundation for their content strategies have completely missed the potential of digital marketing and dialogue offerings. This is precisely komm.passion‘s ambition with PAS 2.0.
Banks, boutiques, bookstores: More and more shops and businesses are closing in Germany. Customers are becoming a rare sight. According to the market researchers at Shoppertrak, in 2018 the number of visitors in city centers lay below those of the previous year during ten out of twelve months. This means looking for the right location for a new store is risky business. Not with PAS 2.0! With the use of social media analysis and heat-map data visualization combined with the operating figures for existing locations, it is possible to make a reliable prediction for successful new branches. With PAS 2.0, it is actually possible to link any combination of online and offline data in order to provide valid forecasts for questions like where consumers will shop or what their buying behavior will look like.
“There’s no viable alternative to AI technologies when it comes to investigating B2B and B2C relationships,” says Dr. Klaus Holthausen as he explains: “In the future, data-driven target group research isn’t something that will just be switched on and off. It will continuously measure, monitor and observe, because AI is designed to be constantly listening and learning.”
Dr. Klaus Holthausen is Lead Developer of PAS 2.0. Holding a PhD in Physics, he has spent decades working in the field of semantic networks and crawlers. These refer to knowledge models and programs that scrape information from web spaces like Facebook, Twitter, Xing or LinkedIn. Both AI technologies are critically important to digital market research, because they make it possible to filter patterns and solutions out of enormous data sets.
“Based on a very small amount of customer information and publicly available data, an intelligent algorithm can deduce what product a consumer needs, where they would prefer to buy it, what potential objections they might have or how secure their income is. And these recommendations can be the foundation for building, evaluating and managing campaigns.”
Dr. Klaus Holthausen
That means: The louder things are in the digital channels, the more exceptional results self-learning algorithms can provide. To put it another way: The larger the data volumes, the better the AI can decode the DNA of fans, critics and potential customers. This is already the case in areas like lifestyle, sports, politics, food, leisure and fashion. Here, particularly large numbers of people are active in social media. One piece of evidence for this: A whopping 147 million people follow reality TV star Kim Kardashian on Instagram alone.
PAS 2.0’s data quality goes far beyond simple counting metrics: On the one hand this is because it is able to identify specific objects – a person, a vehicle, a current condition. And on the other, PAS 2.0 can assign user statements about brands or products to specific moods and emotions. This so-called “sentiment analysis” yields deep insights into how people are talking about a topic or product.
The quality of today’s analytical data is determined by marketing executives’ desire for ever more precisely differentiated target groups. Social milieus are constantly being fragmented into smaller and smaller segments. Managing content and offers accurately requires having as detailed knowledge as possible about needs, desires and preferences. “Intelligent target group models are the foundation for high-quality social media analysis. The rest is math. We spend 90% of our time on creating these models,” explains Klaus Holthausen.
For PAS 2.0, this means: User data is clustered in familiar milieus like Sinus and Sigma, but also in alternative models such as archetypes. These include 12 personality structures – from the hero to the fool to the sage – developed by Swiss psychiatrist and psychoanalyst C.G. Jung and frequently used in brand storytelling today.
PAS 2.0 is AI-driven, internet-based research – but research that has a precise impact on the real lives of people in Berlin or Paris, Madrid, Sao Paolo or Shanghai. With PAS 2.0, you can optimize the creative nucleus of a campaign just as effectively as traditional or digital marketing initiatives – because PAS makes it clear what the real DNA of your target group is. Not because these users have been subjected to expensive surveys complete with the usual margin of error from socially acceptable answers, but because crawlers can see what they actually click – quickly and at low cost.
“Platforms like QQ, Ozone, Douyin or Weibo are bustling with millions of fake profiles. Any digital market research that included the fake profiles in its reporting would be unreliable. PAS 2.0 has enabled us to completely eliminate false profiles – and we achieved this in all Chinese provinces including the country’s five largest cities. This has enabled us to collect data that is by no means inferior to offline market research, but is actually better. To my knowledge we’re the first ones to conduct this kind of high-quality social media analysis in China.”