Conforama: PIM data quality
Problem
Ensuring the quality of the information on the product page is key to SEO strategies and to the customer experience in e-commerce.
Solution
Consulting and project management in the integration with the ERP and Marketplace. Monitoring through reports the content quality objectives with the SEO manager. Use of AI tools for content creation and translation into other languages.
Results
The quality of the product content contributed to generating more traffic to e-commerce, the customer experience and had a positive impact on sales figures. Process automation meant fewer resources from the content team.
Context
Conforama is a retail chain specialized in home furniture that operates through 50 stores located in the Iberian Peninsula. It also has an e-commerce platform with the best product and content to achieve the goal of being market leaders.
Data quality is key at Martech
No one doubts that to have a benchmark ecommerce you must have the best tools on the market. A proven CMS (Salesforce, Adobe…), a PIM that helps in product management (Akeneo, Pimcore, Sales Layer…), a DAM for digital assets (Bynder, Cloudinary…) and others… But who cares about the quality of the information, which, at the end of the day, is what you are going to use to reach the platform and help you make the purchase. Remember the maxim “garbage in, garbage out”.
Data project, from strategy to execution
Although the quality of the data requires constant maintenance, the project was developed in less than a year.
Challenge: Improve the information of our products sold in the ecommerce in the shortest possible time.
Objectives: SEO: no empty fields, minimum length in key fields, images (number and weight). Consistency: Take advantage of all the correct information existing in other systems. Minimize Resources: Automate and free the content and sales team from the tasks that consumed the most effort.
Data Audit: Descriptive by field of (PIM Akeneo: number of cases, mean, maximum, minimum, outliers…), contrast against data masters, data normalization. Decisions on data discarding, possible values…
Integration with other data sources: Integration of Akeneo PIM with data sources (ERP MS Dynamics, Marketplace Mirakl), to take advantage of the fields already reported and maintain data consistency between the different systems.
Information creation: Use of AI Rytr and Deepl tools for content translation. Image adaptation.
Data visualization: Monitoring the evolution of the PIM content through KPIs defined by a dashboard developed in PowerBI.
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