A quick overview of the most important and most frequently used terms in the field of analytics.
Behavioral analytics is a sub-area of data analytics. It specifically describes the recording, collecting, evaluating and understanding of user behavior with digital content (e.g. on websites, in online shops, apps, etc.). For example it can be used to find out how users interact with new features and at which point in the funnel they drop off.
Business intelligence describes the processes and, in some cases, the department in companies that are responsible for the systematic analysis of all generated data. In this way, insights can be gained to improve business decisions. Special BI software or analysis tools are often used to collect, evaluate and present the data.
A cookie stores information about website users on the respective device, e.g. to be able to recognize them again over a certain period of time, across several websites or devices. Cookies can be divided into first and third party cookies.
A consent is required to process personal or personally identifiable data. A consent management platform helps to obtain and save the consent preferences of a user.
A Customer Data Platform collects data from various company-wide sources and aggregates them to a comprehensive profile of an individual user. It then usually distributes data to third-party tools in order to e.g. enable the targeted (re-) activation of customers.
Any data can be graphically prepared on a dashboard in order to obtain an overview of company-specific KPIs.
A Data Delivery Platform enables the collection and flexible distribution of behavioral data to any third-party tool or data warehouse. A Data Delivery Platform reduces manual programming effort and guarantees a high data quality in all tools used.
A Data Lake is a very large data store. This is where raw event data flows in and where unprocessed data is stored. This form of data storage is in contrast to conventional databases in which data is already processed. In a data lake, on the other hand, data is only prepared, structured and formatted at the point where it is needed.
A Data pipeline describes the process where data flows from one system to another.
A data warehouse is a database in which data from several data sources is backed up in a structured manner. A data warehouse is often used for data analysis. In contrast to a data lake, the data flowing in here is already processed.
Digital analytics describes the systematic analysis of data generated through digital channels. Analyzes, reports, statistics, etc. are usually created with the help of software. Digital analytics can be further broken down into e.g. web, app & social media analytics.
The General Data Protection Regulation (GDPR for short) is an EU-wide regulation created for the protection of natural persons when processing personal data by private and public organizations. It has been in effect since May 25, 2018. Since then, many changes have also occurred for website owners regarding the use of digital analytics. There will be more specific regulations for website operators in the future with the ePrivacy regulation.
ePrivacy is a regulation within the EU, with the purpose that the privacy of citizens should be better protected in the web. So far it has not been determined when the regulation will come into force and which changes will come specifically for the digital economy.
An event describes an interaction of a user with a website or application, e.g. clicks, adding items to the shopping cart, seeing images/elements/products etc.
With event tracking, user interactions (events) are captured and analyzed. Events can for example be button clicks, downloads, search for products, watching videos, etc. With event tracking, the entire customer journey on a website or platform can be analyzed.
If a website is opened and it sets a cookie itself, it is called a first-party cookie.
Marketing Intelligence supports those responsible for marketing in companies in making data-based decisions and in measuring and optimizing the success of marketing activities. For Marketing Intelligence, all of the company's marketing data is brought together, reported and analyzed.
A markup language is a text-based and machine-readable descriptive language. The best known markup language is hypertext (HTML). elbwalker also uses its own markup language, so-called “elbish”, for measuring events without programming. You can find more information on this in our documentation.
The goals and KPIs that are to be achieved with the website, the online shop or the application should be documented and maintained in a measurement plan. In the measurement plan it is determined which metrics are measured when and how and which properties should be measured too. An example: An “add to cart” should be measured when the “Add to cart” button is clicked. The information “article number, product name, price, brand, size and number” should also be captured.
Structured data has a fixed structure with a clear division (e.g. rows and columns) and description. This includes for example, tables, CSV files or relational databases. Structured data can be processed quickly.
Cookies that are not set by the website itself, but by a different domain is called a Third-Party Cookie.
In contrast to structured data, unstructured data does not have a fixed structure. Most data that is collected by companies, is unstructured. Examples are: text, video, image or audio files, emails or social media data. Before unstructured data can be analyzed, it must be structured - i.e. processed.
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