Business Intelligence solutions analyse increasing amounts of data coming from the web. Web Analytics solutions are equipped with interfaces which are worthy of Business Intelligence.
Will these two types of solutions come together one day? Should they?
“Business intelligence (BI) refers to computer-based techniques used in identifying, extracting, and analyzing business data, such as sales revenue by products and/or departments, or by associated costs and incomes. BI technologies provide historical, current and predictive views of business operations. Common functions of business intelligence technologies are reporting, online analytical processing, analytics, data mining, process mining, business performance management, benchmarking, text-mining and predictive analytics. Business intelligence aims to support better business decision-making. Thus a BI system can be called a decision support system (DSS). Though the term business intelligence is sometimes used as a synonym for competitive intelligence, because they both support decision making, BI uses technologies, processes, and applications to analyze mostly internal, structured data and business processes while competitive intelligence gathers, analyzes and disseminates information with a topical focus on company competitors. Business intelligence understood broadly can include the subset of competitive intelligence.”
Is this really different, however, from the solutions which are currently available and which have evolved from the field of Web Analytics? Yes and no.
If we take this definition and apply it to a company department which focuses on the company’s online activity, and then add to it the data generated by the company’s information systems (CRM, databases, marketing items etc.), it is clear that Web Analytics is Business Intelligence.
The difference between the two exists not in the wording that is used but in the thoughts of the specialists in each domain. Business Intelligence is created by large technological solutions such as the cube, distributed by the leading names in software. The main difference is in the complexity of Business Intelligence type projects, which are generally led by chief information officers and in a specifically targeted market: a market of experts.
Web Analytics has led to the creation of a new type of “key in hand” solution which is much more “work” oriented than Business Intelligence. By default Business Intelligence is somewhat generalist, lacking in consistency and does not have any standards. Only clients are able to determine their own needs and the way in which information is to be collected, as well as the different sources, the quality of data, rules to be applied etc, right through to the KPIs which are then to be shown on a dashboard, which also needs to be designed. Business Intelligence projects are often large, long and expensive projects, which rely on the use of complex solutions.
This is not the case for Web Analytics, however. A large part of the data which is collected is externalised and standardised, including variables which can be compared with one another, standards set by the WAA* (or OJD in France, the ABCe in the UK etc.), processing systems which are specific to each solution (managed by editors and easy to understand by the client), as well as an intuitive web interface made possible by this type of support and which can be used by all services within a company and not just for an elite few.
Business Intelligence is a method which can be used; Web Analytics on the other hand is a solution.
There may, however, be a significant gap in the field of Web Analytics: the quality of the database engine and data reproduction should make it possible to carry out advanced analyses and all types of cross analyses, whilst at the same time remaining accessible to the final user. This is the point where several Web Analytics solutions remain reporting solutions, and have difficulty in becoming Business Intelligence solutions. AT Internet is different from its competitors with its complete Analyzer package associated with the DataExplorer module, an advanced query decision engine.
This is where Online Intelligence differs as the agility from Web Analytics is combined with the processing power associated with the field of Business Intelligence.
Faced with the increasing complexity of online projects, is Web Analytics going to finally transform into Business Intelligence? It would be somewhat presumptuous to pretend to have the response, however, it would be a shame to turn a practical, quick, and simple yet powerful solution into a Business Intelligence tool, as is often the case. The Business Intelligence solutions which are currently in place are not adapted to the world of the Internet, the web or mobile. This is a world which is continually advancing, where it is necessary to constantly adapt to new features, and a world which requires reactivity.
AT Internet’s promise is, more than ever, to increase its capabilities and the powerful analyses of its solutions, whilst at the same time holding onto the notion of simplicity, clarity and agility which are required from the tagging process right through to analysing data. This is an important challenge because what is at stake is the creation of a new business intelligence tool which is more accessible than ever before.
* Web Analytics Association