Consulting

German companies still have a lot of room for improvement when it comes to digitization. Do you think so too? We analyze the status quo of your web apps - from security to seo to cross-selling - and find your untapped potential. We advise and support you in developing requirements engineering for system enhancements, optimizing deployment processes and making profitable use of big data.

Software analysis of PHP projects

You have a PHP software project and want to analyze or refactor it. We analyze your PHP software using various measurement methods. You will receive a detailed analysis report with objective key figures such as Code Coverage, Duplications, Coding Standards Breach, Bad Complexity and Technical Debts.

  • Soncarcube installation and configuration
  • Jenkins installation and configuration
  • Bamboo installation and configuration
  • Set up automatic build scripts
  • Connections to version control systems

Software Security of Web Apps

Any website can become a target for professional hackers. With the help of manual and automated analyses, we uncover possible points of attack, for example known security holes and other technical vulnerabilities. We perform common attack scenarios such as penetration tests or client piercing and provide a detailed report.

  • Test for SQL injections
  • Cross-Site-Scripting (XSS)
  • TLS exams
  • Server header analysis
  • Load tests/stress tests
  • OpenVAS analyses

SEO (On-Page Optimization)

Your website does not reach a good position (Search Engine Ranking Position, SERP) with the relevant keywords in relevant search engines. We analyze the site for technical weaknesses such as poor page semantics and compression. If necessary, we optimize for example sitemap and loading speeds.

  • Verification of W3C compliance, HTML and CSS
  • HTTP status messages
  • Sitemap and robots.txt
  • Metadata and meta descriptions
  • Rich-Snippets and Microdata
  • Page semantics
  • Keyword density and keyword cannibalism
  • Loading speeds, compressions and best practices

Cross Selling and Recommender Systems

If you already have an online store, a video portal or a content management system, you want to recommend suitable products or content to your customers. We use machine learning methods to develop a recommender system: from data collection and selection of a suitable method such as collaborative filtering to testing and implementation on your site.

  • Display of suitable accessories based on the currently visited PDP (product detail page)
  • Display of follow-up articles, for example within product series
  • Suggestions of products, content or videos using machine learning methods.
  • Implementation of recommender methods such as collaborative filtering or cluster analyses for customer typologies
  • Validation and optimization of recommendations based on selected key figures with AB tests