PagesJaunes
204 rond point du Pont de Sèvres, Boulogne Billancourt,
Paris, 92100,
France
Paris, 92100,
France
33 1 46 23 30 00
Professional Services
PagesJaunes Technographics
PagesJaunes Software Purchases and Digital Transformation Initiatives
Discover the latest software purchases and digital transformation initiatives being undertaken by PagesJaunes and its business and technology executives. Each quarter our research team identifies on-prem and cloud applications that are being used by the 700 PagesJaunes employees from the public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources.
During our research, we have identified that PagesJaunes has purchased the following applications: Dataiku Data Science Studio (DSS) for ML and Data Science Platforms in 2017, Algolia Search for Application, Web and Enterprise Search in 2014, Capgemini Odigo for Call Center, Customer Experience in 2014 and the related IT decision-makers and key stakeholders.
Our database provides customer insight and contextual information on which enterprise applications and software systems PagesJaunes is running and its propensity to invest more and deepen its relationship with Dataiku , Algolia , Capgemini or identify new suppliers as part of their overall Digital and IT transformation projects to stay competitive, fend off threats from disruptive forces, or comply with internal mandates to improve overall enterprise efficiency.
We have been analyzing PagesJaunes revenues, which have grown to $135.0 million in 2024, plus its IT budget and roadmap, cloud software purchases, aggregating massive amounts of data points that form the basis of our forecast assumptions for PagesJaunes intention to invest in emerging technologies such as AI, Machine Learning, IoT, Blockchain, Autonomous Database or in cloud-based ERP, HCM, CRM, EPM, Procurement or Treasury applications.
PagesJaunes Data, Technology Stack, and Enterprise Applications
AI Development
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
| Dataiku | Legacy | Dataiku Data Science Studio (DSS) | ML and Data Science Platforms | AI Development | n/a | 2017 | 2017 |
In 2017, PagesJaunes implemented Dataiku Data Science Studio (DSS) to build an application that scores customer satisfaction and automates detection of problematic search queries. The deployment leveraged ML and Data Science Platforms capabilities to address search relevance and user experience on PagesJaunes.fr, with an explicit focus on supporting Category Managers responsible for directory quality.
The core implementation ingested search engine artifacts including query lists, navigation logs, clicks, and page visit rankings, and centralized those heterogeneous sources inside Dataiku Data Science Studio. Within DSS PagesJaunes developed data pipelines, feature enrichment workflows, and an algorithmic scoring model that computes a satisfaction score per query and predicts which queries will deliver unsatisfactory results. The application encapsulated rule engines and model outputs so that predicted failures could be surfaced as operational tasks for content remediation.
Operational integrations included direct consumption of clickstream and search logs and adoption of Hadoop as the scalable processing layer to support large volumes of usage data. The solution was scoped to Category Management and search/content teams, enabling those business functions to inspect, validate, and act on model-driven signals. More than ten PagesJaunes collaborators were trained on Hadoop, machine learning, and statistics using DSS as part of the rollout.
Process and governance were restructured to close the loop between model insights and manual curation, enabling automatic detection of the most critical signals and application of the most relevant interpretation rules for queries. The PagesJaunes team built the application in approximately three months and instituted ongoing monitoring workflows to manage unsuccessful searches and to prioritize remediation work for Category Managers.
The explicit outcomes reported included a 30% boost in Category Manager productivity and continuous optimization of customer satisfaction, driven by the Dataiku Data Science Studio application that enables PagesJaunes to explore and correlate multiple data sources, deduce rules and models, and feed those artifacts back into production.
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Content Management
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
| Algolia | Legacy | Algolia Search | Application, Web and Enterprise Search | Content Management | n/a | 2014 | 2014 |
In 2014, PagesJaunes implemented Algolia Search on its website. PagesJaunes deployed Algolia Search to power site search across business listings, aligning with the Application, Web and Enterprise Search category and focusing on customer-facing discovery and local search queries.
The deployment implemented core search capabilities including real-time indexing, relevance tuning, typo tolerance, faceted navigation, synonyms, autocomplete and query suggestion to support rapid retrieval and refined result sets. Algolia Search was configured to expose search APIs consumed by the front-end search components to enable instant results and search as you type experiences.
Operational coverage centered on the public website search surface and the catalog of local business listings, with implementation work occurring in web development and content operations channels. Integration patterns followed standard search architectures, using Algolia Search indexing pipelines to pull content from backend content sources and API calls to serve results to client-side components.
Governance focused on iterative relevance management and search analytics to tune ranking rules and synonym sets, with teams leveraging query logs and analytics to refine sorting and facets. The architecture emphasized a cloud-hosted search service model, with Algolia Search providing the application layer for search functionality on PagesJaunes' site.
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CRM
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
| Capgemini | Legacy | Capgemini Odigo | Call Center, Customer Experience | CRM | n/a | 2014 | 2015 |
In 2014, Capgemini implemented Capgemini Odigo for PagesJaunes to localize customer interactions and virtualize its contact center footprint. The deployment targeted PagesJaunes' customer service organization, bringing more than 300 contact center employees across 30 locations into a unified virtual contact center architecture while preserving local telephone presence rather than consolidating to a single national number.
The implementation leveraged Capgemini Odigo capabilities aligned with Call Center,Customer Experience requirements, including telephony virtualization, distributed agent desktops and skills based routing to deliver localized handling at scale. Configuration emphasized local number presentation and localized routing rules so calls ring to the appropriate local agent pool, and the platform was provisioned to support consistent interaction handling across the distributed sites.
Operational scope covered PagesJaunes' contact center operations across the 30 sites, affecting customer service workflows and agent desktop routing. Governance and rollout focused on central orchestration of the virtual contact center while retaining local caller identity, enabling PagesJaunes to maintain a local touch in customer engagement using Capgemini Odigo as its Call Center,Customer Experience solution.
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Customer Data Platform | CRM |
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2015 | 2015 |
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Customer Experience | CRM |
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2020 | 2020 |
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Customer Loyalty | CRM |
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2015 | 2016 |
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Digital Advertising Platform | CRM |
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2013 | 2013 |
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Digital Advertising Platform | CRM |
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2022 | 2022 |
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Digital Advertising Platform | CRM |
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2022 | 2022 |
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Marketing Analytics | CRM |
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2013 | 2013 |
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TRM
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
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Treasury Management | TRM |
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2010 | 2010 |
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IaaS
Vendor |
Previous System |
Application |
Category |
Market |
VAR/SI |
When |
Live |
Insight |
|---|---|---|---|---|---|---|---|---|
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Application Hosting and Computing Services | IaaS |
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2014 | 2014 |
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Application Hosting and Computing Services | IaaS |
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2021 | 2021 |
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Content Delivery Network | IaaS |
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2018 | 2018 |
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Content Delivery Network | IaaS |
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2021 | 2021 |
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IT Decision Makers and Key Stakeholders at PagesJaunes
| First Name | Last Name | Title | Function | Department | Phone | |
|---|---|---|---|---|---|---|
| No data found | ||||||
Apps Being Evaluated by PagesJaunes Executives
| Date | Company | Status | Vendor | Product | Category | Market |
|---|---|---|---|---|---|---|
| No data found | ||||||
FAQ - APPS RUN THE WORLD PagesJaunes Technographics
PagesJaunes is a Professional Services organization based in France,
with around 700 employees and annual revenues of $135.0 million.
PagesJaunes operates a diverse technology stack with applications such as
Dataiku Data Science Studio (DSS), Algolia Search and Capgemini Odigo,
covering areas like ML and Data Science Platforms, Application, Web and Enterprise Search and Call Center, Customer Experience.
PagesJaunes has invested in cloud applications and AI-driven platforms to optimize efficiency and growth,
collaborating with vendors such as Dataiku, Algolia and Capgemini.
PagesJaunes recently adopted applications including
PubMatic in 2022, Index Exchange in 2022 and Google Cloud Platform (GCP) in 2021,
highlighting its ongoing modernization strategy.
APPS RUN THE WORLD maintains an up-to-date database of PagesJaunes’s key decision makers and IT executives,
available to Premium subscribers.
Our research team continuously updates PagesJaunes’s profile with verified software purchases,
vendor relationships, and digital initiatives identified from public and proprietary sources.
Subscribe to APPS RUN THE WORLD to access the complete PagesJaunes technographics profile,
including detailed breakdowns by category, vendor, and IT decision makers.