Core Insights - The article emphasizes the importance of preparing a digital budget for 2026, which serves as a strategic reflection of a company's future direction and requires sufficient funding to support technological advancements [1][20]. Group 1: Strategic Alignment and Annual Goals - The digital budget should be closely tied to the company's strategy and business pain points, ensuring that leadership recognizes the necessity of the initiatives [2]. - A review of the current year's digital achievements and challenges should be included, showcasing key results from digital investments, such as a 5% increase in sales conversion rates due to CRM implementation [2]. - The new year's business strategy should be clearly articulated, demonstrating how digital initiatives will support strategic goals, such as implementing RPA to enhance efficiency and free up 30% of finance personnel's time [3]. Group 2: Annual Construction Planning and Project List - The planning section should reflect the CIO's professional capabilities, categorizing digital projects by type, such as efficiency improvement and technical foundation projects [5][6]. - Each key project should be detailed, including its name, business pain points addressed, core construction content, expected value, and timeline [7]. - A visual roadmap, such as a Gantt chart, should be used to illustrate the start and end dates of all projects, showcasing the CIO's planning and resource allocation skills [8]. Group 3: Investment Estimation and Budget Details - A clear and transparent cost model is essential, detailing both one-time and ongoing costs associated with digital initiatives, such as software licensing and maintenance fees [9][10][11]. - The annual budget summary should itemize costs by project category, including both one-time and recurring expenses, to provide a comprehensive financial overview [13]. - Justifications for each expenditure should be clearly outlined, referencing market benchmarks and supplier quotes to enhance credibility [15]. Group 4: Expected Returns and Risk Analysis - The budget should include a thorough investment return analysis, quantifying hard savings and soft benefits, and calculating key performance indicators [17]. - Risks associated with the projects should be identified, along with proposed mitigation strategies to address potential challenges [17]. - The budget preparation process should involve extensive communication with business departments to ensure alignment and support for the proposed initiatives [19]. Conclusion - A successful digital budget is the result of thorough communication with business units, clarifying resource allocation and business value relationships, while adopting an investor mindset to maximize returns and control risks [20].

Core Transformation: AI Reshaping Brand Customer Acquisition Logic - Traditional marketing relied on the AIDA model and a "traffic thinking" approach, focusing on broad coverage and high exposure, but AI enables a shift to "value-driven, precise reach, and deep interaction" [2] - The transition involves four dimensions: from "traffic thinking" to "user value thinking," from "mass communication" to "hyper-personalized communication," from "post-analysis" to "predictive analysis," and from "labor-intensive" to "technology-driven" [2][3][4][5] Five Core Trends Driven by AI in Brand Customer Acquisition - Trend One: Intelligent orchestration of the customer journey through data integration and automation tools, creating a seamless user experience [6][8] - Trend Two: Generative AI enhances content marketing efficiency by enabling scalable production and dynamic optimization of marketing materials [9][10] - Trend Three: Conversational AI upgrades interactive customer acquisition by transforming passive inquiries into proactive need identification [11] - Trend Four: Predictive analytics allows brands to transition from blind outreach to precise targeting by identifying high-value users and conversion opportunities [12] - Trend Five: AI-driven search engine customer acquisition requires brands to adapt SEO strategies to leverage AI tools for capturing search traffic [13] Practical Framework: Building an AI-Driven Intelligent Customer Acquisition System - Step One: Establish a solid data foundation by integrating diverse data sources into a Customer Data Platform (CDP) to ensure high-quality data [14] - Step Two: Select and integrate technology that matches business needs, ensuring compatibility among tools to prevent data silos [15] - Step Three: Focus on strategy and creativity by defining the division of labor between AI execution and human strategic input [16] - Step Four: Create a testing and iteration loop to continuously optimize strategies based on user data and feedback [17][18][19] - Step Five: Evolve measurement metrics to focus on long-term value indicators, such as customer lifetime value (LTV) and marketing contribution revenue [20][21] Current Challenges and Future Outlook - Brands face challenges in data privacy compliance, algorithm bias, and the need for skill transformation within teams to effectively utilize AI tools [22][24] - Future developments may see AI evolve from a tool to an autonomous decision-making entity, capable of setting acquisition goals and executing strategies in real-time [25]

Core Viewpoint - The marketing industry is facing collective challenges such as high content costs, fragmented MarTech systems, and a disconnect between marketing and sales, prompting the need for effective AI solutions to drive growth [2][4]. Group 1: Industry Challenges - Content costs are high and the frequency of updates is rapid, yet it remains difficult to engage consumers effectively [2]. - Various MarTech systems are disjointed, leading to redundant investments and low usage rates [2]. - There is a persistent gap between marketing and sales, making it hard to measure the impact of marketing expenditures on growth [2][4]. Group 2: AI's Role in Marketing - Despite the proliferation of AI technologies in marketing, such as generative AI and marketing automation platforms, few have successfully addressed the industry's core challenges and gained client recognition [2][4]. - The complexity and precision required in marketing have increased, necessitating AI to enhance insights and execution capabilities [4]. Group 3: Evaluation and Participation - The "Big Whale List" aims to identify companies that effectively use AI to solve marketing problems and drive business growth [2][4]. - Companies eligible for participation must provide AI-driven marketing technology services across at least one of six key areas and have two or more verifiable paid client cases [5]. - The evaluation will consider technical capabilities, implementation success, and commercial value [6]. Group 4: Recognition and Opportunities - The top 10 "AI + Marketing Strongest Companies" will be announced by the end of September 2025, providing exposure and networking opportunities for the selected firms [7][8]. - Participants will benefit from promotional activities, speaking opportunities, and inclusion in a case library [8].