Project Title: AI-Enabled Customer Analytics and Customer Strategy for Fine and Rare Wine Retail

Sokolin, LLC

Details
Project Title AI-Enabled Customer Analytics and Customer Strategy for Fine and Rare Wine Retail
Project Topics Artificial Intelligence & Machine Learning Customer Service & Account Management Data Management Growth Strategy Information Technology (IT) Innovation Market Research Marketing Operational Performance and Metrics Research, Analysis, Evaluation Sales & Business Development
Skills & Expertise
Project Synopsis: Challenge/Opportunity
Sokolin is America's premier fine wine merchant, established in 1934, specializing in rare and collectible wines for a customer base that has historically consisted of affluent collectors, Wall Street professionals, and serious enthusiasts. While demand for high-end and rare wine remains strong, the company faces two interconnected strategic challenges that this project is designed to address.
The first is a generational transition: many long-time customers are aging out of the market, purchasing less frequently, or already hold extensive collections. Younger generations, Millennials and Gen Z, are engaging with alcohol and fine wine differently, creating genuine uncertainty about the long-term composition of the fine wine buyer base. Building a pipeline of next-generation collectors is a priority, but must be done in a way that preserves Sokolin's identity as a trusted advisor and relationship-driven merchant.
The second is customer retention. Sokolin's high-touch sales model means that customer relationships are often deeply tied to individual sales representatives. When those relationships are disrupted through rep departure, transition, or reduced engagement, customers can quietly attrite before the company has an opportunity to intervene. Understanding the behavioral and transactional signals that precede churn, and building systematic early-warning and re-engagement capabilities, is as strategically important as acquiring new customers.
Sokolin operates through a relationship-driven sales model in which dedicated representatives build personal, long-term relationships with collectors, guiding purchasing decisions over many years. Digital sales, while growing, represent a small portion of revenue, and most online interactions quickly transition into relationship-driven sales conversations. The company is not seeking to abandon this model. Rather, it wants to augment it with better data, smarter tools, and a more systematic understanding of who its customers are, which ones are at risk, and how to cultivate the next generation of them.
This project will address both dimensions through two interconnected workstreams: a customer segmentation and retention analysis, and a CRM architecture designed specifically for high-touch fine wine sales. The final output will position Sokolin to reduce customer attrition, grow its next generation of collectors, and give its sales team the tools to build stronger, more durable relationships.
Project Synopsis: Activities/Actions Required
  1. Conduct a structured review of Sokolin's existing customer and transaction data, identifying what is currently captured, what is missing, and what additional data sources could be integrated.
  2. Research and document how fine wine buyers differ by archetype, including collectors, investors, gift buyers, and drinkers, covering behavioral signals, purchase patterns, and lifecycle characteristics.
  3. Develop an AI-assisted customer segmentation model that maps Sokolin's existing customer base to defined archetypes, with supporting analysis of behavioral and transactional patterns.
  4. Analyze patterns in customer attrition and at-risk account behavior to identify the key signals that precede churn, and develop a framework for proactive retention intervention.
  5. Identify the characteristics and engagement patterns of Sokolin's highest-value customers, and develop a framework for applying those findings to prospecting and onboarding of new buyers.
  6. Research the next-generation fine wine buyer, including Millennial and Gen Z collectors, and develop a strategic framework for how Sokolin can build a pipeline of younger customers without disrupting its existing model.
  7. Design a CRM architecture tailored to relationship-driven fine wine sales, specifying the key customer attributes, engagement signals, lifecycle milestones, retention risk indicators, and sales rep workflows the system should support.
  8. Evaluate how AI-driven tools could surface actionable insights within the CRM, including purchase timing signals, relationship health indicators, churn risk flags, and cross-sell opportunities.
  9. Develop a strategic roadmap with prioritized recommendations across customer segmentation, retention, marketing targeting, and CRM implementation, including resource requirements and sequencing.
  10. Prepare and deliver a final presentation of findings and recommendations to Sokolin's leadership team.
  11. Produce a comprehensive project report documenting methodology, analysis, and all deliverables for organizational use and future reference.
Project Synopsis: Expected Results
  1. A defined customer segmentation model with distinct archetypes, behavioral attributes, and data-driven profiles applicable to Sokolin's existing customer base.
  2. A retention risk framework identifying the key signals that precede customer churn and a recommended workflow for proactive intervention by sales representatives.
  3. A strategic framework for identifying and engaging next-generation fine wine buyers, with specific recommendations on channels, messaging, and relationship-building approach.
  4. A CRM architecture document specifying required data fields, engagement tracking logic, retention risk indicators, sales rep workflows, and AI-assisted insight capabilities suited to high-touch wine sales.
  5. An assessment of current data gaps and a prioritized plan for closing them.
  6. A set of actionable recommendations, with clear prioritization and implementation sequencing, that Sokolin leadership can realistically act on following the program.
  7. A final presentation delivered to Sokolin's leadership team with findings, supporting analysis, and a clear strategic narrative.

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