CX transformation accelerated by Direct to Fan (D2F) × Entertainment-Driven Consumption: Fan Types and Consumption Behavior Observed from Sports Fans (Part 2)

While D2F has become a key element of business strategy for redesigning relationships with customers, several barriers arising from existing business structures and organizational frameworks continue to exist in practice (Figure 3). Based on ABeam Consulting's experience supporting clients, the primary reasons companies struggle to advance D2F can be summarized in the following five areas.

• Dependence on Existing Channels
  Companies often depend heavily on relationships with existing retailers and wholesalers, creating a risk that transitioning to D2F may damage these partnerships. In cases where wholesalers handle everything from product and service planning to sales, companies may lack an understanding of fan characteristics within their own organizations.
• Challenges in Corporate and Brand Recognition
  Even companies and brands that already enjoy market recognition often lack the expertise and strategies needed to promote products and services directly to fans. In D2F, proper targeting through social networking services and online advertising is essential, yet many companies lack internal expertise in these areas and rely on external providers.
• Challenges in Technology and Data Utilization
  Implementing D2F requires the technical capabilities to build and operate company websites and e-commerce platforms, as well as the skills to utilize customer data effectively. However, many organizations lack sufficient IT talent and therefore either do not conduct data analysis and one-to-one marketing or outsource these activities.
• Challenges in Logistics and Customer Support
  In D2F, establishing logistics networks to deliver products and services directly to fans and providing post-purchase support are critical. Because operating these functions smoothly requires significant resources and cost, companies frequently outsource them as well.
• Rigid Organizational Culture and Decision-Making Processes
  Particularly in large B2C companies, decision-making related to transforming existing business models often takes considerable time, making it difficult to respond independently to rapidly changing initiatives such as D2F. Organizations that lack a culture of embracing innovation may struggle to sustain momentum in D2F projects and may ultimately revert to traditional sales models.

To overcome these barriers, companies must break away from assumptions based on traditional sales models and increase business viability by conducting hypothesis validation before formal business planning, introducing specialized expertise, advancing internal consensus building, and deepening understanding of fan characteristics simultaneously. Designing and optimizing relationships with customers while accumulating knowledge internally is the key to achieving success.

D2F is not merely a marketing initiative; it is a transformation that spans business, organization, and technology. Accordingly, a phased approach based on business maturity is effective for driving transformation. ABeam Consulting recommends the following seven-step, three-phase approach:

1. Understand the company's vision and challenges
2. Develop business hypotheses
3. Conduct PoC (proof of concept) to identify fan types and behavior types using AI, interviews, surveys, and data analysis
4. Develop a business concept
5. Consider initiatives based on the business concept and current fan types and behavior types
6. Establish organizational and talent management frameworks for execution
7. Implement DX (digital transformation) and AI transformation for execution, including e-commerce, core systems, customer platforms, and marketing tools

The following sections explain each step in greater detail.

Visualize the company's vision and management challenges to identify the gap between the current situation and the future state the company seeks to achieve, such as creating new businesses or expanding profitability in existing businesses.

Business hypothesis development involves exploring and validating customer and business value using frameworks such as SWOT (strengths, weaknesses, opportunities, and threats) and PEST (political, economic, social, and technological) analyses, the Value Proposition Canvas (VPC), and the Business Model Canvas (BMC). For new businesses, this includes forming hypotheses regarding business concepts. For existing businesses, it includes identifying issues in current services, defining customer experience transformation themes, and developing PoC validation items for improvement.

It is effective to gradually refine business ideas through workshops and discussions that envision the future of industries and companies.

Based on business hypotheses, conduct PoC validation before full-scale launch to identify the fan types and behavior types most likely to become primary customers for the company's products and services. For existing businesses, customer interviews, surveys, and sales data analyses can be conducted through owned customer channels to strengthen loyalty among existing customers.

In addition, success rates can be further increased by combining customer data analysis powered by AI with digital twin-based PoC and simulations using AI personas (virtual customer profiles created digitally). This approach allows rapid validation of customer behavior hypotheses and initiative simulations. Hypothesis testing that previously required significant time can be repeated quickly to improve business accuracy.

For new businesses without customer channels, or for existing businesses experimenting with new sales methods, companies can also utilize ABeam Consulting's methodologies for new business planning and D2F Quick Marketing using model cases and operational procedures. Particularly during the pre-launch phase, it is possible to collect sales data not only through e-commerce platform sales functions but also through additional capabilities such as live commerce, NFTs (non-fungible tokens), and BOPIS (buy online, pick up in store). This enables validation of suitable sales models, target customer segments, marketing policies, business concepts, and strategic assumptions before making full-scale business investments.

Establish and refine the business concept defined through business hypotheses and PoC results to clarify business direction and objectives. This phase also includes making necessary adjustments before full-scale launch and preparing business plans for internal approval.

Promote consideration of appropriate initiatives based on the business concept and current fan types and behavior types through a PMO (project management office) or BPO (business process outsourcing) model. By implementing initiatives tailored to the most prevalent fan types and behavior types and executing efficient marketing activities, companies can maximize revenue. When necessary, multiple PoCs can be conducted through D2F Quick Marketing based on new business planning methodologies and model cases. By repeatedly validating outcomes and accelerating the PDCA (plan-do-check-act) cycle, companies can improve their understanding of fan characteristics and make initiative planning based on analytical insights easier and more accurate.

To execute initiatives successfully, companies should evaluate whether appropriate personnel have been assigned internally and externally and, where necessary, consider new organizational structures and select outsourcing partners. It is equally important to advance internal consensus building in parallel to ensure effective organizational and talent management.

To execute D2F initiatives effectively, pursuing DX and AI transformation as needed is essential. Companies should assess whether they possess sufficient customer channels, customer platforms, MA (marketing automation) and BI (business intelligence) capabilities, and smooth integration with core systems before determining the appropriate system architecture. Furthermore, by building AI foundations based on integrated customer data and advancing personalization, demand forecasting, and recommendation capabilities, companies can improve both customer experiences and decision-making accuracy. Subsequently, organizations can select the necessary systems and drive implementation from customer experience and data utilization design through system deployment, achieving digital and AI transformation aimed at enhancing fan experiences.

The seven steps described above can be divided into three major phases. We recommend implementing Steps 1 through 3 in Phase 1, Steps 4 and 5 in Phase 2, and Steps 6 and 7 in Phase 3, while continuously validating outcomes and making adjustments throughout each phase to ensure steady transformation progress (Figure 4).