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Data Processing: efficient data management in marketing
Over the years, modern companies have integrated tools and services into their workflow to improve performance within the company and get more out of the product or service. Today, in the next step of optimization, many are faced with the problem of how to make tools previously integrated into the process and data silos that have arisen jointly usable.
We explain to you why data processing is worthwhile and how you can best implement it!
What are data silos?
Data silos, also often referred to as isolated solutions , are collections of information (data) that are in the possession of one department and which other departments in the same company cannot easily access or can only access to a limited extent. The individual departments, such as finance, administration, HR or marketing, usually store the information, i.e. the data they need for their work, in separate locations. This is encouraged by the separate work processes and a closed company structure. At first glance, these data collections do not appear to be a problem, but they become one when company processes change and departments have to work more closely together. Data silos then make collaboration and data exchange between departments more difficult. One problem here is often the data quality due to inconsistencies between the stored data of the individual departments (e.g. different addresses for the same person). It is also difficult for managers to obtain a holistic overview of company data if the data is organized in silos.
Improved data management with firmly integrated data processing methods helps companies to gain a better overview and thus take the next step towards optimization.
Goals of Data Processing
The daily volume of data within tools and processes in the company is unbelievably large and almost impossible for an individual person or department to keep track of. The amount of data will continue to grow in the future. Data processing is part of every company and the use of optimized data offers many advantages. For example, potential risks and opportunities to increase financial success can be detected, analyzed and processed using data processing alone.
Integrated tools and software also benefit from optimized data processing and adapted data management. The potential can be fully exploited by seamlessly linking underlying databases, processes and interfaces. The result is an improvement in the customer experience, for example.
What is Data Processing?
"Data processing is the collection of data and its processing into the desired and usable form. This is nothing more than data processing that is carried out either manually or automatically in a predefined sequence of operations. In the past, processing was carried out manually. However, this was very time-consuming and error-prone. Today, digital processes enable automatic and time-saving processing and a correct result.
Why is data processing worthwhile?
Creation of a foundation for data analytics
Faster cross-platform processes
Performance boost through synergies
Overview for management of departments and dependencies
Automation of data warehousing
Well-functioning marketing is based on a good understanding of the customer base or target group and the product data.
These include the following factors:
- Site-specific offers and product information
- Demographic information such as age or location information
- Preferences and purchasing power of customers from online stores
- Information obtained from voucher promotions or loyalty programs
A high processing speed of this information in order to respond quickly and in a personalized manner to interactions with customers quickly and in a personalized is of crucial importance if the information is to be used to its full extent. This is a clear advantage over manual cross-departmental analysis processes, which require more time.
However, fast processing alone does not lead to success. To be effective, retailers need a unified customer data platform that responds to the activities of an individual customer across all channels.
Apart from that, data processing methods help in the following areas:
- Conversion tracking: determining how and in what form ads or marketing techniques lead to sales
- Real-time segmentation : active segmentation of customers during their customer journey
- Budgeting: maintaining an overview of advertising expenditure and automatic adherence to set budgets
An improved data process almost always involves revising or renewing the existing system architecture. system architecture architecture. Each specific use case requires an individually tailored solution and a system that meets the requirements of the respective company.
What is the best way to implement data processing?
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Analysis of the actual state
Definition of the goals
Stakeholder requirements analysis of the result
Prototype implementation
Adaptation and expansion through iterative development cycles
Our conclusion
Companies are confronted with an ever-increasing amount of data. Big data can quickly become confusing, but it offers many opportunities.
Would you like to use your data with the help of analysis tools to gain useful insights that will help your company move forward? Whether you want to analyze customer data to make your marketing more customer-centric or collect data from different sources to create predictive models - no matter how you want to use the data, it requires knowledge, time and a high level of diligence. Unfortunately, it is often not enough to simply enter data into a business intelligence system and then expect high-quality results.
To successfully implement data processing methods, you shouldn't just follow the trends. Instead, focus on where the added value for your company is greatest and where it is most needed.
Whether it's intelligent portal solutions, PIM and MAM solutions or the integration of analyses, automation or marketing evaluations, we are happy to advise you from the first step through to support during implementation and operation. Benefit from our experience at
!
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