Sales and Marketing
“Data is the new oil” is a saying that is readily quoted today. Although this sentence still describes the current development well, it ides not get down to the real core of the matter; more suitable would be “artificial intelligence empowers a new economy”. The autonomous automation of ever larger Felds of tasks in the business world will trigger fundamental economic and social changes. Based on a future world in which unlimited information is available on unlimited computers, ultimate decisions will be generated in real time and processes will be controlled objectively. These decisions are not liable to any subjectivity, information or delays.
Analogy of the Dating Platform
Tell us your customers with the highest sales and we will predict who your next successful customers will be. In principle, lead prediction can be easily compared with a dating platform. In comparison with a simple assumption about which products go well with a company, lead prediction learns new information from every new customer to, in turn, predict better customers. The predictions become more reliable and precise from the interaction and the feedback resulting from it.
Under many different aspects, a comprehensive picture of every potential lead is generated. Te task at hand is the complete recording of the current state and an estimation of the development of the company. Tis covers the classical master data, an exact classification of the activity and an estimation of the development of the company in its sector.
Firm graphics contain traditional company data that is taken from the company registry (name, location, commercial sector) and extended by further indicators such as turnover and number of employees. The commercial sectors are a classification of the activities of companies that were published by the Federal Statistical Office in 2008.
Tanks to the dynamic identification of the subjects from the website, in comparison with the commercial sectors, lead prediction achieves a very accurate thematic classification and localization of the company. I addition, these tags have high topicality and new trends quickly become visible. In comparison with the commercial sectors, instead of commercial sector software development, a company is given the tags app development, big data or machine learning.
Digitalis of Companies
The digitalis of a company shows how far the company has completed the process of digitalization. Various aspects of digitalis are included in this score: the technology of the website, the visibility of the company on the web, the ad spending and SEO optimization and the degree of innovation of the business model. On the basis of this score, companies can be easily segmented depending on the degree of their digitalization. Both young startups and established companies in the e-commerce sector are distinguished by a higher-than-average digital index, whereby more traditional business sectors reveal a rather less distinct degree of digitalis.
Prediction per Deep Learning
Deep learning is a subject that is causing quite a stir at the moment. In principle, it is a branch of machine learning that uses algorithms to recognize objects, for example, and understand human speech. The technology is in principle a revival of algorithms that were popular from the beginnings of AI: Neuronal networks. Neuronal networks are a simulation of the processes in the brain whereby neurons and the specifcfre patterns are imitated. The real innovation is the layering of various neuronal networks which, in combination with the essentially greater performance of current computers, led to a quantum leap in diverse sectors of machine learning.
Random Forest Classifier
The algorithm gradient boosted regression trees, also called random forests, belong to the ensemble learning methods Tis classifier uses an ensemble of weak regression trees that have a low hit quota when considered in isolation. The quality of the prediction can be improved significantly when various trees are trained with different parameters or samples. The results of the individual trees are aggregated to a total result which then enables a more balanced and high-quality prediction. see more here skymovieshd
Alerting openly scans the Internet and crawls cyclically websites and social media channels for content snippets containing information about a company. These snippets are the potential alerts that are faltered and aggregated according to significance down the line. In the first step, the probability of a company being mentioned in the given text is determined. Sequence learners, which make a decision based on the lexical similarity and the context of the word as to whether the mention refers to a company or not, are used for this purpose.