Corporate Communication 4.0: Precire supports companies with Artificial Intelligence
Digitization is no longer a new topic in most companies today. But especially in the areas of corporate communications and human resources, the current possibilities are only being exploited by a few digital pioneers. With an innovative language analysis tool based on artificial intelligence, the young Aachen-based company Precire supports companies in Germany and Europe in making their exchange with customers, employees and applicants smarter. We met psychologist and CIO Christian Greb and asked him about what is behind..
Christian, Speech Analysis with Artificial Intelligence – what does it mean and how does your tool help customers?
Precire is a software that uses spoken and written language to make predictions about people’s characteristics and emotions, as well as the way companies communicate internally and externally. Companies use Precire above all to learn more about themselves and to consciously shape how they are perceived by people. We help our clients, for example, to optimise texts in such a way that they perfectly match the corporate identity of the company or to coach managers so they can appear more convincingly.
In addition, Precire can also be used in the application and onboarding process. For example, our software conducts interviews with job seekers to indicate whether an applicant is suitable for a job. If necessary, we can later use the data collected for the design of individual induction and training measures.
Which aspects of language are crucial in your analysis?
Precire analyses up to 500.000 elements of language, including speaking speed, tonality, word weighting, emotion words, time-associated words, but also certain modes of action and voice pitch. The weighting of words in the context of other words is particularly examined.
If, for example, I have a word like “bad”, it initially seems like a negative emotional word. But if the whole sentence is “That’s really not bad.” the statement is positive. It is therefore important to look at the information contained in the language structure. In order to make reliable statements here, we combine procedures from modern algorithms with our psychological questioning.
Which customers use your tool? How large is the share of start-ups compared to established companies?
Precire is used by medium-sized companies, major corporations, but also start-ups at home and abroad. About 80 percent of our customers tend to be established companies. The fact that the share of start-ups is relatively low is certainly due to the fact that these young companies are often simply occupied with other topics before they even get the idea of optimizing their processes and communication with AI tools.
You are still a quite young company. How do you convince large corporations of their need for Precire?
We do have the decisive advantage that our product quickly arouses enthusiasm in personal contact. In the second step, however, we have to prove that the whole technology is not a hocus-pocus and that we can guarantee aspects such as data protection. Ultimately, it’s all about offering the customer added value.
Once you’ve managed to convince a company of your worth, it becomes easier. The companies communicate with each other more or less strongly. With little luck you will be recommended by word of mouth.
Can you tell us an example of your cooperation with corporations?
Yes, among other things we are supporting the Talanx insurance group in becoming an agile organization. Our language analysis tool is very well suited here to shed light on communication among managers and to derive concrete information that enables more communicative strategies and changes the way we work together. For other clients, for example, we optimize mailings. We look at how often letters are opened at all, how many customers respond and then improve the linguistic design significantly so it has a positive effect on the KPIs of the company.
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What should start-ups and established companies learn from each other?
I think on the one hand established companies can learn from start-ups to make their processes more flexible and to become more decisive and courageous. On the other hand, it is precisely the companies that have demonstrated very strongly how to establish a business model that earns money and gets many people into work. Many startups could take some of this as a lesson.
A few years ago, you were a start-up too. Looking back, what would you have liked to know back then?
At the beginning, we did not react quickly enough to the demands of the market, but were too focused on the development of our technology. That cost us a lot of time. In addition, we underestimated how important it is to consciously shape employee interaction. Who cooperates with whom? What is the mood like? What does the entire internal network of relationships look like? As a founder, it is definitely worth investing time in order to always keep an eye on the whole.
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