Today, I was asked in an interview. What is web analytics? Tell me all you know about Web Analytics. This may not be a perfect answer, but gives a direction to answer the same. Web analytics is the measurement, collection, analysis and reporting ofweb data for purposes of understanding and optimizing web usage.[1][dead link] Web analytics is not just a tool for measuring web traffic but can be used as a tool for business and market research, and to assess and improve the effectiveness of a web site. Web analytics applications can also help companies measure the results of traditional print or broadcast advertising campaigns. It helps one to estimate how traffic to a website changes after the launch of a new advertising campaign. Web analytics provides information about the number of visitors to a website and the number of page views. It helps gauge traffic and popularity trends which is useful for market research. There are two categories of web analytics; off-site and on...
If most digital marketing programs or campaigns have a weak area, it’s analytics. One recent study identified that the biggest talent and hiring gap in online marketing is in the analytics space. 37% of companies surveyed said that they desperately needed staff with serious data chops. If you’re in the field of online marketing or content marketing and want to ensure that you’re bringing the best data to bear on your projects, here’s a quick look at some strategic approaches that can help you improve your performance in 2014. This applies whether it’s upgrading your own skills, adding strategically to your freelance stable, or improving your content planning skills. The Case for Data HBR declared that data scientist is the sexiest job of the century . Research company Gartner suggests that there will be 4.4 million big data jobs available in the next two years, and that only a third of them will be successfully filled. It’s no surprise. Everything i...
Text analytics is still largely an immature science, and embraces several different approaches. Natural language processing (NLP) includes dozens of techniques for accomplishing tasks such as language translation, document categorization and tagging, extraction of meaningful terms and so on. Text mining on the other hand is primarily concerned with the extraction of meaningful metrics from unstructured text data so they can be fed into data mining algorithms for pattern discovery. Some suppliers have applied text analytics to very specific business problems, usually centering on customer data and sentiment analysis. This is an evolving field and the next few years should see significant progress. Other suppliers provide NLP based technologies so that documents can be categorized and meaning extracted from them. Text mining platforms are a more recent phenomenon and provide a mechanism to discover patterns which might be used in operational activities. Text is used to generate extra...