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Maryna Postrelko
Written by
Maryna Tarasenko
Head of Marketing at Gepard
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Product Data Mapping In eCommerce: Purpose And Techniques

9 min read
November 17, 2022

With the unprecedented increase in the volume of information in eCommerce, a process called data mapping certainly helps to handle, at times, extremely intense data flows. Data coming from different sources requires systematization, transformation, and automation, without which it remains an impossible task to manage. The process ensures that you accurately record, correctly use, and seamlessly integrate all incoming data into systems.

Gepard specialists would like to share some firsthand knowledge and experience concerning data mapping and its ultimate benefits.

What Is Data Mapping?

The term refers to extracting information fields from any database or source system and mapping them to related target fields in other business applications. In a nutshell, it is a procedure for establishing an identity between data display models in different sources and target systems.

What Is The Purpose Of Data Mapping?

The process involves linking the data fields of the source and target systems. Product Data Mapping (PDM) helps consolidate information, so it is the first step in any data extraction, transformation, and loading (ETL) process.

With it, you can:

1. Create, transform, integrate, and move data warehouses;

2. Link data from multiple sources;

3. Check data quality with data mapping software that automatically highlights inconsistencies, inaccuracies, and other problems in databases;

4. Spot trends and share real-time reports.

The procedure links products to their respective categories, making it easier for customers to find the product. Improved catalog structuring allows you to better categorize vendors based on their products/services and allows businesses to display and transform data to make their business more efficient.

Product Data Mapping Techniques

You get a pretty sufficient choice of the most efficient model. Information mapping techniques can be commonly subdivided into automated, semi-automated, and manual approaches.

1. Automated Data Mapping

In this case, the whole process is carried out by a software tool. As a rule, this is a ready-made paid solution, but it is optimal if there is no encoder in the team or the object is temporarily unavailable. Often, such software uses promising technologies of machine learning and automation, which gives the user a number of advantages, including:

  • Easy data extraction;
  • Launching complex processing flows from a convenient UX;
  • Data flow visualization with attractive effects;
  • Receiving notifications when there are problems and getting help in fixing them.

A well-chosen data management tool saves a lot of time in solving immediate business problems as it scales.

2. Semi-Automated Mapping

This method, or, as it is also called Schema Mapping, requires knowledge in the field of coding and a little manual work. This is a hybrid process in which the data mapping tool creates links between sources and targets, and then the IT specialist checks and manually corrects them if necessary. The main benefits here are:

  • Balance of performance and accessibility;
  • Only some basic coding input is necessary;
  • Saves time without full-on automation;
  • Useful data visualizations for data analysts.

This model is ideal for teams on a tight budget for basic integration and small data management.

3. Manual Mapping

This model requires professional implementation. You will need a data engineer or developer capable of coding rules for passing or inserting data from one field to another and a mapper that will encode and transform your data sources. The manual approach also has its strengths, like:

  • The ability to fine-tune your data tasks;
  • Fuller control of the whole data mapping process;
  • More individual customization of elements where needed.

This is the optimal solution for a one-time process (for example, data storage) when the database is not too large.

In a simplified form, the procedure includes three steps: identifying the source, and the target, and linking the two structures using matching patterns. In practice, depending on the overall data mapping approach (manual or otherwise), you may also need to define compatible formats and transform data accordingly, specify rules for its transformation, and test out schema logic.

Data Mapping Techniques

1. Identifying Product Content Fields To Map

You need to start by determining what data will need to be restructured or moved. There is no universal recipe, so it all depends on your priorities:

Integration

For each source, you need to determine how much data to merge and how often the integrations will be performed. If you have large and frequent integrations coming up, you should choose a solution from among automated data mapping tools. You can use manual work only for small one-time projects with limited amounts of data.

Migration

Take a close look at the source information and determine the tasks that need to be solved at the target location. How large the amount of data is will determine how you approach migration. If the mapping flow is too wide, choose automated software.

Transformation

Specify which data processing format should be used for the intended purpose. In most cases, automated tools are required, but small projects can be done manually.

2. Defining A Format For The Target Data

Determine the format and structure for displaying information in each of your sources and target databases. They must match so that when they reach the goal, there is no confusion (for example, in the list of the sales department).

3. Specifying Product Content Transformation Rules

This will depend on the chosen method of how to do data mapping. With an automated approach, the system will do all the work for you without the need for coding. For semi-automatic, create the connections using the program, and then have an experienced person manually check that they work correctly.

4. Testing Schema Logic And Completing Mapping Process

If you use the automatic matching method, then the check is performed by built-in means. In other cases, move a small sample of prepared data and manually check for errors. By testing your logic, you can complete any process with high quality.

Mapping Data Use Cases

Here are some of the most popular data mapping examples:

Product Content Integration

Successful content integration depends on how identical the structures of the source and target stores are. Product data mapping tools help eliminate differences to more effectively consolidate information from different sources without the additional involvement of programmers.

Migrating Product Content

Moving data between repositories is easy to do using data mapping automation. It is harder to do it manually. Invalid or not quite correct comparisons will reduce the accuracy and will not ensure the completeness of the information.

Possible real-world use case. Timely product information migration can help businesses stay flexible and sturdy in the face of growing demands and shifting trends. For instance, when scaling from legacy systems to more up-to-date hardware in order to meet the seasonal demand or simply widen user outreach.

Data Mapping Use Cases

Transforming Product Content

When corporate data is located in different places and in different formats, the automated process of extracting and transforming data into valuable information has no alternative. The data is placed in the staging area for conversion to the desired format and then moved to the target database without your participation.

Possible real-world use case. Employing proper mapping techniques in order to turn existing data into a form compatible with a new or alternative system is yet another major use case. It can help you stay open to new mediums and data management solutions.

Electronic Data Interchange Exchange

The procedure for converting files to various compatible formats uses built-in functions without writing code. This helps to implement the most simple B2B data exchange.

Possible real-world use case. Automation of file conversion through EDI accelerates the way you do business by granting seamless opportunities for B2B data exchange. This can help you stay operational no matter what type of system your B2B client uses.

What To Look At When Choosing A PIM Software With Data Mapping Capabilities?

The choice of the software tool is critical to the success of any data-related project. The key to making the right choice is research. Online reviews can be a great help. The following are some of the must-have functions you will need when working with data:

Connectivity To Varied Data Sources

Capability is key for data mapping and modeling tools. To properly link data to the right product, choose a centralized Product Information Management (PIM) system with asset management functionality. This is especially important if product descriptions are oversaturated with media.

Drag-And-Drop Function

The ability to easily drag and drop files effectively overcomes the challenge of converting, managing, and sharing large digital data assets. This is one of the most important features of PIM.

Intuitive UX

A graphical interface in a richly integrated ecosystem enables critical product information to be quickly visualized and centrally managed. A quality solution supports many custom options and product hierarchies, including packages, attributes, categories, and collections.

Ability For Different Types Of Mapping

The ability to automate your workflow by time and events is invaluable. You will reduce the amount of manual work, increase productivity and free up the most valuable asset – time. The best choice would be PIM, which provides several data mapping techniques.

PIM Data Mapping

Product Mapping Functions Offered By Gepard PIM System

Now that you know what to search for in a PIM solution with a mapping module, let’s review the product data mapping process of the Gepard PIM software.

At Gepard, we understand taxonomy as a large set of strictly structured and interrelated data that describes real-life products. Such data sets mainly include product categories and related product features (or attributes, specifications) with values and units of measure. Some taxonomies may also include product brands.

A successful data mapping is key for further data enrichment. For this purpose, Gepard PIM system offers a mapping module that allows mapping the product taxonomy data from the source to the target endpoint. Here are the main features of the data mapping module of Gepard PIM.

1. Creation and management of data mapping rules.

To map the data of the two taxonomies, we configure mapping rules that determine the matching relationship between the source data item and the target data item. Mapping rules are applied by the Mapper Engine module, which executes the enrichment of product data. This allows for further product description enrichment and delivery to the data endpoints.

2. Mapping user interface

Gepard’s mapping module UI is made to be understandable even for non-technical users with no need for coding and ensures a flawless mapping process. Seamlessly create mapping rules, save them in the database, edit, add new rules or delete the existing ones. For more comfortable work, you’ll get edit history as well as an option to revert to an earlier version of mapping.

3. Management of mapping templates

The mapping module, offered by Gepard, has an option of Back Office service, which is especially useful for users who do not have any experience with taxonomy mapping. With this option, experienced taxonomists can create and manage mapping templates for the user, and send the ready-made templates back to the Front Office for the next filling-in.

4. Support of simple and complex mappings

Gepard’s mapping module offers both simple and complex data mapping. The first one allows so-called “value-to-value” mapping. For example, a provider’s category “clothing” is mapped to the category “wear” on the client’s side, which allows for correctly enriching and syndicating the client’s product descriptions.

On the other hand, complex mappings are when more than one condition can be used to map the items between the provider’s and the client’s sides. For example, the client’s feature “Size” is mapped to the provider’s three features “waist”, “sleeve length”, and “shoulder width” which are labeled in the product description.

5. Support of different data formats

Gepard configures mapping of source and target product taxonomy data to enable the enrichment of final product descriptions and delivery of these product descriptions as output files in a particular format (CSV, JSON, XLSX, etc.) to a particular endpoint (email, API, FTP, etc.).

Read more about choosing a PIM system:

Gepard PIM vs In-house PIM
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Alina Virstiuk
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Gepard vs. In-House: Which PIM Solution Is Better?

What is better, buying or building a PIM solution? Why not both? Find out how you can get unique functionality faster than custom development.

PIM product information management

Product Data Mapping FAQ

What Tools Are Used For Data Mapping?

Semi-automatic or fully automated tools can be used. The former helps create a link between the source and target fields, and then the developer manually verifies the link. The latter does all the work for you and can be used by ordinary personnel.

Can I Map Product Data Myself?

You surely can, but this is a laborious process that is difficult to perform correctly and accurately. At the least, you will need a tech-savvy employee with extensive experience, a database management system, and an appropriate file conversion method.

Can I Pass The Stage Of Data Mapping?

You cannot because then you will not be able to take advantage of it. The consistency of the process is critical to ensuring the accuracy and quality of data as it moves from source to destination.

Data Mapping – Sealing Up The Deal

Product data mapping is the unconditional foundation of an efficient data management strategy, and employing PIM is one of the best eCommerce strategies as a whole. Want to make the most of them? Feel free to contact us.

Gepard PIM system makes a perfect tool for data mapping for any kind and size of product content. Request a custom demo to learn how Gepard can help grow your specific eCommerce business.

How To Solve Product Data Mapping Challenges?

Maryna Postrelko
Written by Maryna Tarasenko
Head of Marketing at Gepard
A passionate professional with solid expertise in Content Marketing, External Communications, Email Marketing, and Social Media. Head of Marketing at Gepard, the product information management & syndication platform, helping to centralize diverse product data and deliver complying content to sales channels.

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