Intégrez l'analyse de la concurrence avec l'IA

Contexte

L'utilisation d’internet pour comparer les offres d’assurance en ligne (simplifiée de surcroît par la normalisation de l’utilisation des comparateurs), associée à la possibilité de résilier désormais les contrats à tout moment, accroît la pression concurrentielle sur les assureurs. La connaissance et la prise en compte des prix des concurrents deviennent désormais nécessaires pour maintenir, consolider et accroître les parts de marchés et la rentabilité des contrats offerts.

La pression concurrentielle et la dépendance des bénéfices vis-à-vis du volume des souscriptions font de l'optimisation des tarifs en assurance non-vie un enjeu majeur. L’élasticité au prix des assurés ainsi que la segmentation des risques adoptée par la concurrence rend indispensable de connaître finement son positionnement tarifaire et de l’intégrer rétroactivement au modèle de tarification.

Nous avons accompagné notre client sur ses travaux de refonte du modèle tarifaire en assurance automobile, pour les aider à comprendre les politiques tarifaires menées par ses concurrents afin de les intégrer à ses propres calculs.

Use cases

We collaborated with a major brand to conduct an in-depth study on Sell-out Promo management aimed at optimizing and forecasting sales. Our intervention spanned several key areas, each meticulously designed to drive actionable insights and enhance operational efficiency. We began with a comprehensive audit of current processes, data, and tools to gain a holistic understanding of the existing landscape. Next, we embarked on the crucial task of mapping sell-out data from various sources, analyzing key aspects including timing, granularity, network coverage, and data quality. With this groundwork in place, we proceeded to define a robust Promo sell-out data model, encompassing scope, attributes, referential, sources, and more. Finally, we crafted a strategic framework encompassing processes and governance structures to effectively leverage promo sell-out data for demand planning and forecasting purposes. Through our collaborative efforts, we empowered our client to unlock the full potential of their promotional activities, driving informed decision-making and maximizing sales performance.

This project for a luxury brand, involved retrieving and analyzing sales and pricing data from data lakes on GCP and AWS. We identified the study's scope, defined a methodology for modeling elasticities, and developed a recommendation tool for product-level strategies with a confidence indicator. We also provided operational support to Pricing and Merchandising teams for informed decision-making on price changes. This collaboration empowered our client with data-driven insights for strategic growth and competitiveness.

We defined and implemented a complete revenue management strategy for a client in the tourism industry, tied to ticket revenues. Our project began with meticulously defining the revenue management strategy, followed by measuring the subsequent increase in revenue. We then evaluated the impact on the commercial and distribution policies, ensuring alignment with overarching business objectives. Additionally, we provided comprehensive support for change management, including the development of internal and external communication plans. Through our collaborative efforts, our client experienced tangible improvements in revenue generation, strategic alignment, and effective communication practices.