Galeria's E-Commerce success with AI-driven personalization

Galeria engaged KPS as a technical consulting and implementation partner, focusing on Google Cloud toolings, such as AI, modern data warehouse, and dynamic pricing.

The Challenge:
Galeria aimed to enhance its digital shopping experience by delivering
personalized product recommendations. The challenge was
processing vast amounts of user events, historical data, and product
information to generate precise, algorithm-driven signals for search,
sorting, and direct recommendations, significantly improving user
engagement.

Galeria drives revenue growth with dynamic pricing transformation

The Challenge
Recent advancements in pricing technology lend themselves perfectly
to Galeria’s vast and dynamic product assortment. A more automated
and therefore active pricing strategy would greatly improve alignment
to the market and profitability in general.

Galeria transforms data & reporting with BigQuery and PowerBI

The Challenge
Galeria needed to automate data pipelines and streamline processes
across diverse databases, but manual report creation was inefficient
and inconsistent. This complexity hindered data accuracy, making it
difficult for the company to make timely, data-driven decisions.

AI product recommendations for Globus with Vertex AI & SAP CAR

Globus engaged KPS to help prototype and build an AI based product recommendation engine with product master data joined with purchase data coming from SAP Customer Activity Repository (CAR) export (through SAP Business Warehouse).

The Challenge
Globus faced a significant challenge with product recommendations that lacked personalisation, particularly for unknown or unregistered customers. The existing recommendation system was not tailored to individual customer preferences, resulting in generic product suggestions that did not enhance the customer shopping experience or drive optimal sales performance.

Globus streamlines IT support with AI-powered enterprise search

Globus engaged KPS to leverage expertise in data-driven solutions and search technologies. KPS led the implementation of a Google Cloud-based solution, transforming raw data into a structured format suitable for AI-driven search functionalities.

The Challenge
Globus faced a recurring challenge in IT support, with many similar support inquiries. Users struggled to find relevant documentation to resolve issues independently, leading to an increased volume of first-level support tickets. The goal was to reduce this workload by implementing an intelligent search tool that provides precise answers based on integrated data.

Toolport uses AI to enhance Product Recommendation with Vertex AI

Toolport engaged KPS as a technical consulting and implementation partner, focusing on Google Cloud toolings, such as AI, modern data warehouse, and dynamic pricing.

The Challenge
Toolport needed to improve cross-selling opportunities and product discovery by leveraging AI for personalized recommendations. The goal was to prototype an AI-based recommendation system using historical product and customer data, demonstrating its effectiveness through A/B testing.

This might also interest you: What stages have companies reached in using Generative AI?

The Lünendonk study in collaboration with KPS provides comprehensive insights.

According to the study*, 47% of surveyed CIOs already see Generative AI as highly relevant in 2024. Looking ahead to 2027, this number rises to 60%, with many anticipating a significant business impact, particularly in areas such as IT operations, document processing, and knowledge management. The study also thoroughly examines the risks associated with implementing Generative AI, emphasizing the importance of clear guidelines and responsible practices to prevent data breaches and security issues.

*The survey included 150 IT and business leaders from German-speaking companies and authorities. The surveyed industries include manufacturing, retail, energy sector, healthcare, automotive industry, banking, insurance, and the public sector. The examined companies consist of 12% medium-sized businesses (50-250 million euros in revenue), 50% upper mid-sized businesses (250 million to 1 billion euros in revenue), and 38% large enterprises (over 1 billion euros in revenue).