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What is the Classifier about?

An easy to use, no coding, online tool that helps you harmonize and classify your data. Since this is a plug-in tool, it is designed to respect your existing data solution, boosting its performance.

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How often do you wonder?

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How can I get meaningful results from databases which all have different product characteristics (attributes)?

Is there an alternative to writing complex code to classify your product characteristics (attributes), and end up with unreadable logic?

How could I easily verify if I’m getting the desired result from the business logic I’m implementing?

How do I get more business experts involved even if they don’t have technical expertise?

How can I optimize time and resources spent on maintenance?

Our Solution

NextGen Classifier is an online platform where you can:

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Define which product characteristics (attributes) you will need as an output and how you want to map databases accordingly.

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Set up rules using natural language, no coding needed.

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Verify the impact of these rules just with one click.

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Apply existing rules on new data, reducing the time spent on these repetitive tasks.

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Easily update your data when receiving new databases.

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Enrich your data with product characteristics (attributes) missing in the data provided.

We are only a phone call away (or whatever communication method you prefer) for any doubts on the settings or use of our solution. We can suggest recommendations or best practices to be as efficient as possible in your product classification.

How users benefit from NextGen Classifier

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It’s a simple solution for the complex process of data harmonization.

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You will get the input directly from the business experts.

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Anyone can use it, no technical skills required.

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Allows you to save time on repetitive tasks which can be better spent analysing.

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Easy to maintain.

Once upon a time...

For a long time, a global leading producer of confectionary had been successfully creating their sales reports based on retail measurements data. They had everything in place, from loading to consolidating and visualizing the data. This resulted in high level reports at country and manufacturer level. However, as their category became more and more competitive, it became increasingly important to identify trends on a more detailed level such as flavour, size, and specific segments like “healthy” and “indulgence”.

The data they received contained the products sold in each local market. This added up to tens of thousands of items, each with different product characteristics (attributes). These were then consolidated for a limited number of attributes like “global manufacturer” and “global brand”. Harmonizing more product attributes was too time consuming since most of it had to be done manually or with complex lookup tables.

This is where NextGen Dashboards was asked to provide the company with a solution. The process of the harmonization of the products needed to become simpler, faster, more accurate and more flexible to answer changing business needs. With the help of the online tool “Classifier”, algorithms (rules) were created without writing any code. For example, to classify a product into the segment of “indulgence” or “healthy”, the Classifier made it easy to create a rule that would look for combinations of specific keywords in the product name and sub-brand.

Each time new data was now uploaded, the rules would automatically apply to all products. This proved to be a huge time saver and provided management with a reliable set of harmonized attributes to slice and dice the data by.

Moreover, where previously the classification of the product data was done in the background by a team of IT specialists, the Classifier now allowed non-technical users to simply login and read the logic behind the rules being applied. If needed, they could even create new rules or modify existing ones. And with the integration of AI into the Classifier, that has become even easier to do. In short, the Classifier now allows the customer to focus on analysing the data rather than reworking the data.

… and they analysed happily ever after!

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