Case Study: How Flormar builds loyalty with predictive AI and increases average ticket.

Customer loyalty has become the differentiating factor in customer relationships. Flormar, an international cosmetics brand, understood this many years ago and decided to bet on customer segmentation and predictive artificial intelligence to personalize its loyalty strategy.

The results speak for themselves: 47% higher average ticket and 69% repeat purchase rate.

This success case demonstrates how the combination of strategic vision, advanced technology and customer-centric approach completely transforms the customer relationship.

This is the content of the success case:

1. A brief introduction to Flormar
2. The challenge: Creating an intelligent loyalty club for physical stores
3. The solution: Customer-centric predictive artificial intelligence
4. Implementation: From strategy to execution
5. Results: The numbers behind the project
6. Lessons learned and success factors

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A brief introduction to Flormar

Flormar is a Turkish cosmetics brand that has expanded globally, being recognized for its quality, innovation and accessibility. With presence in more than 100 countries and an offering that ranges from makeup to personal care, Flormar has positioned itself as a reference in the international beauty sector.

The brand is characterized by:

• Constant innovation: Continuous development of new products and trends in cosmetics.
• Accessible quality: High-quality products at competitive prices to democratize beauty.
• Global presence: International distribution network with strong presence in physical stores.
• Customer focus: Strategy centered on understanding and satisfying the specific needs of each market.

However, like many brands in the sector, Flormar faces the challenge of creating deeper connections with its customers in an increasingly competitive and digitalized market. The need to evolve towards a more intelligent and personalized loyalty model has become critical to maintain its position.

The challenge: Creating an intelligent loyalty club for physical stores

Flormar had a clear opportunity: to create a loyalty program that was not simply a traditional points system, but an intelligent platform capable of understanding, predicting and satisfying the individual needs of each customer in its physical stores.

The strategic objectives were ambitious:

The complexity of the challenge lay in the fact that the cosmetics sector presents very specific purchasing behaviors: variable replenishment cycles depending on the type of product, seasonal preferences, influence of trends and a strong emotional component in purchasing decisions.

A solution was needed that understood these particularities and turned them into competitive advantages.

• Increase purchase frequency: Get customers to visit stores more regularly.
• Increase average ticket: Ensure that each visit generates greater purchase value.
• Improve retention: Reduce abandonment rate and increase repeat purchases.
• Personalize the experience: Offer relevant recommendations and communications for each customer.
• Integrate online and offline: Create a coherent omnichannel experience.

The solution: Customer-centric predictive artificial intelligence

Flormar chose Pleasepoint as its technology partner to develop a revolutionary loyalty club based on predictive artificial intelligence. The solution was structured around three fundamental pillars that would completely transform the relationship with its customers.

Pleasepoint's predictive marketing platform allows Flormar to successfully solve the various challenges posed and maintain the existing technology stack. The solution delivered by Pleasepoint includes:

• Personalization and automation in CRM communications for each customer according to lifecycle and customer profile.
• Real-time personalization for each user in eCommerce or email marketing.

Pillar 1: 360° customer view with advanced predictive metrics

The first step was to implement a predictive analysis system that went beyond basic transactional data. Pleasepoint developed advanced Customer Intelligence capabilities for Flormar:

• Predictive Customer Lifetime Value (CLV): Real-time calculation of each customer's potential value throughout their relationship with the brand, considering purchase patterns, seasonality and cosmetics sector trends.
• Dynamic purchase propensity: Algorithms that predict the probability of each customer making a purchase in different time windows, identifying optimal moments for impact.
• One-to-one recommendations: Personalized recommendation system that combines purchase history, declared preferences, seasonal trends and behavior of similar customers.
• Intelligent segmentation: Automatic customer grouping based on behaviors, not just demographics, enabling hyper-segmented strategies.

Pillar 2: Intelligent automation of the customer journey

The second phase focused on creating an ecosystem of automated communications that would accompany each customer on their specific journey:

• Hyper-personalized newsletters: Communications adapted to individual purchasing preferences, including recommended products, relevant trends and personalized offers based on history and predictive behavior.
• Segmented on-top campaigns: Specific activations according to each customer's loyalty status, from onboarding for new members to reactivation of dormant customers.
• Trigger-based automations: Automatic sequences activated by specific behaviors such as first purchases, anniversaries or replenishment cycles.
• Predictive communications: Messages sent at optimal moments calculated by AI to maximize the probability of opening, engagement and conversion.

Pillar 3: Integrated omnichannel experience

The third pillar consisted of creating a perfectly integrated experience between physical stores and digital channels:

• Unified profile: Each customer has a unique profile that is updated in real-time with each interaction.
• Recommendations in communications: Customers receive personalized recommendations based on AI.
• Complete journey tracking: Tracking the customer experience from first contact to long-term loyalty.
• Continuous optimization: The system constantly learns from each interaction to improve predictions and recommendations.

Implementation: From strategy to execution

The project implementation was carried out in progressive phases, allowing results to be validated and the system optimized before each expansion:

Phase 1: Infrastructure and data integration

Integration of all Flormar touchpoints with the Pleasepoint platform, including point-of-sale systems, eCommerce, customer databases and existing marketing tools.

Phase 2: Development of predictive models

Training of specific algorithms for the cosmetics sector, considering seasonality, product life cycles and unique behavior patterns of the beauty market.

Phase 3: Communication automation

Implementation of automated email marketing flows, dynamic segmentation and content personalization based on AI predictions.

Phase 4: Continuous optimization

Constant monitoring of KPIs, A/B testing of strategies and model refinement based on real results.

Results: The numbers behind the project

The implementation results highlight the transformative power of artificial intelligence strategically applied to customer loyalty:

Lessons learned and success factors

The success of the Flormar project provides valuable insights on how to implement loyalty strategies based on predictive AI to improve engagement, repeat purchases and prevent churn.

These are the critical success factors of the project:

• Comprehensive customer view: Transactional data is not enough; it's necessary to understand behaviors, preferences and predictive patterns.
• Real vs. superficial personalization: The difference lies in using AI to predict needs, not just showing the customer's name.
• Intelligent automation: Automated flows must be adaptive, not rigid.
• Continuous measurement: Success requires constant monitoring and optimization based on real data.
• Omnichannel integration: The experience must be coherent across all touchpoints.

Beyond the metrics, the project has transformed the way Flormar understands and relates to its customers:

• Data-driven culture: Decisions are based on predictive insights, not intuitions.
• Operational efficiency: Automation frees up resources for strategic activities.
• Customer knowledge: Deep understanding of behaviors and preferences in the beauty market.
• Competitive advantage: Clear differentiation from competitors with traditional loyalty programs.

The key to success lies in understanding that predictive artificial intelligence is not just a technological tool, but an enabler of genuinely personalized experiences that generate real value for both the brand and the customer. Flormar has managed to create a virtuous circle where customer satisfaction translates directly into business results.

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