Data management consulting

Use cases for retail and e-commerce instead of abstract data science

Overview of data management consulting

Data management consulting is a growing sector within information technology (IT) and management consulting. The demand for consultants specializing in data management in e-commerce and retail has increased significantly over the years. This activity requires extensive knowledge in the areas of IT solution architectures, software development and IT infrastructure as well as business models in e-commerce and retail.

Data is the new gold. Data has already become one of the most important success factors in many industries. In many cases, the higher the quantity and quality of a company's customer master data, the more targeted it can develop its products and personalize its marketing. In more and more industries, the more data you have, the more competitive advantage you have.

Data-driven e-commerce & retail

Data-driven companies are becoming increasingly important in the e-commerce industry. They use data analytics to make decisions about products, prices, promotions, etc. These companies often rely on big data to predict consumer behavior and trends.

E-commerce websites that use data-driven marketing strategies are part of the customer journey. When a customer interacts with your company, it should look like it fits into the context of previous interactions. In the acquisition phase, for example, this can be achieved using lookalike lists for ad targeting, while product recommendations must use data from onsite personalization. The individual, personalized service experience can positively round off the customer journey. All of these steps are based on collected and used data. Touchpoints such as e-commerce are also able to generate new types of data. They provide data on customer loyalty and customer behavior as well as transaction data, which in turn can be used to improve the customer experience. For a company that does not yet have a digital infrastructure, it is quite a challenge to orchestrate all of this centrally.

Is your company ready for the data-driven future? - The path to becoming a data-driven company

Data management should be an integral part of every project. It helps to ensure that all data is available at the right time and that it is accurate and complete. Data management also helps companies avoid costly mistakes. For example, if a company does not manage its data properly, it can end up spending money on unnecessary services or products.

Data management consulting: our workshops on all aspects of data management. Get to know the basics of data management, providers and solutions for your company. Find out what is currently available and what is coming next. Our Data Prototype Workshop will help you identify potential use cases and create initial applications that meet your needs. We then work together to develop an application that matches your individual roadmap.

We offer consulting services in the field of digital customer management. We help our clients to develop successful customer strategies with the help of data analysis. Our team consists of experienced consultants who offer consulting services in the areas of marketing, sales, IT, finance, HR and law. These experts will advise you on the best strategy for your company and ensure that you implement it successfully.

Building blocks of data management

What data is already available?

A distinction can be made between the types of data:

Article and product data
Media data, in particular images, operating instructions, PDF files, etc.
Customer master data
Customer behavior data before purchase (e.g. on website, store, shopping cart / checkout etc.)
Transaction data through the purchase and customer behavior afterwards

What additional data can we generate to enrich this data?

Is your data infrastructure bursting at the seams? Do you want to create exciting use cases but lack the technical basis? We can help you find and build the right architecture for your planned use cases.

Analytical tasks: A data lake is an ideal solution for storing all types of data, including structured data, semi-structured data and unstructured data. A data lake is a repository for your data and allows you to analyze it at any time and put it to use. If you want to use the data later, you can simply extract it again. They are particularly useful when the need for the data is unclear, but we still see a potential value for it. Data lakes are often used for analytical purposes, e.g. to find patterns in the data, identify trends and make predictions.

How can this wealth of data be used efficiently to increase sales or improve customer relationships?

Data governance as a prerequisite for efficient data management

Data governance is about ensuring that your data is managed correctly so that no valuable information is lost. We need to ensure that all data is stored safely and securely (GDPR-compliant data management). This includes approval and review workflows as well as tools to get an overview of data quality and completeness. Data governance also helps you to manage your data efficiently, effectively and securely. A good data governance plan helps ensure that all stakeholders understand what information exists, why it is important and how it should be managed. You need to create policies and procedures to govern access to your data, including who has access to what data, when and under what circumstances. We can also advise you on implementing a data quality management system.

Data-related processes in e-commerce / retail

Data must be collected and organized before it can be analyzed. Once the data is collected, it may need to be cleansed or integrated. Integration means bringing together different types of information about your business. For example, you can combine customer data with sales figures to create an overall picture of business operations.

To be effective, a good data management consultancy must first conduct a thorough process analysis to identify inefficiencies, redundancies and missing controls, and then take appropriate action to eliminate them by removing redundancies, automating processes and adding new controls.

Suitable data management platform

As the different data may be in different systems, we recommend setting up a single system that can create a complete 360-degree customer profile. This type of software is commonly known as a Customer Data Platform (CPD). It creates a comprehensive customer view. The segmentation of customer profiles and the provision of the corresponding segments and data are the core functions of Customer Data Platforms (CDP). Depending on the software provider, special strengths are added. For example, in the analysis and playback of third-party systems or in the free configuration of so-called event systems, which play back data from the CDP in real time on the basis of website interactions.

Data delivery - the right data in the right systems at the right time

Data has value when it is processed and passed on. The discipline can be divided into different aspects:

Data exchange with customers - This concerns the exchange of article master data as well as order initiation and processing. The decisive factor here is the interval at which the data is exchanged and the format in which the data is transmitted.
Data exchange with marketplaces and sales platforms: This involves the exchange and processing of item and customer master data and transaction data. Data governance also plays a special role here, as this is business-critical data.
Data exchange with suppliers: This involves the exchange of data with suppliers of raw materials and components. Here too, the type of data and the purpose of the data exchange are decisive.
Data exchange within the company: This relates to internal processes such as accounting, human resources, procurement, etc. The decisive factors here are the type of data, the purpose of the data and the frequency of data exchange.

Data management consulting - process model for professional data management

With the help of our experts, you will get an overview of the current status of your data management and what needs to be done to improve it. We advise you on the best procedures and tools for efficient data management. Our consultants will also make recommendations on how to implement them. As a result, you will receive an overview of the maturity level of data management in your company. This allows you to plan future developments and expansions of your digital activities. Data management plays a key role in many of our solutions, such as the selection of software systems, business process optimization, e.g. lean management consulting.

Introduction / Concepts

Every data management project begins with a conceptual phase in which a question or problem is defined. This usually begins with a brainstorming session and ideally leads to the most precise possible description of the problem, which we use to decide what type of data is needed to answer the question.

Overview of data management and data collection

Once the problem has been clearly defined, suitable data sources can be specifically identified, evaluated and selected. On the one hand, the relevance of the content, the assumed or even verified quality of the data and other factors such as availability and costs play a relevant role.

After selecting the right data sources, the next step is to collect the data. There are various ways to achieve this. Depending on the format of the data, data mining tools can be used. Collecting primary data (e.g. user surveys, research) is costly, but if you pay attention to the data collection process, you can achieve better results. We know suitable concepts and the right freelancer or consultant for data management in this operational form.

Check data quality and data cleansing

Data quality should be monitored from the start of data collection. Several indicators should always be considered simultaneously, reflecting as many determinants of data quality (e.g. completeness, consistency) as possible. Unfortunately, the generation process or parts of it are often not under your own control. At the latest before the actual analysis begins, the data quality must first be evaluated so that remedial action can be taken if necessary. Before the data can be used to create models, it must be prepared correctly. Many data scientists believe that this task makes up a large part of their work. Data, especially when combined from multiple sources, must be standardized (e.g. uniformly formatted data). The establishment of a so-called "data pipeline" enables at least extensive automation of some of the steps mentioned above, which can lead to considerable time and labor savings in the course of the project.

We know the right data scientists for these challenging areas of data management.

Modeling and analysis incl. conclusions

Good modeling is not just about making good predictions. It is about doing this with a high degree of accuracy. For example, when it comes to deriving insights from the results of a model, the results must be interpreted appropriately with regard to the original question in the context of the project and beyond.

As a result, you receive a clear overview of the maturity level and the recommended measures for your data management. Cost estimates and potential savings. This means you are well equipped to develop and expand your digital activities.

An overview of Beyond E-Commerce's consulting fields: