What is *It's Not the Size of the Data* about?

*It's Not the Size of the Data* by Koen Pauwels explains how businesses can leverage marketing analytics dashboards to turn raw data into actionable insights. The book provides a step-by-step framework for designing dashboards that align marketing efforts with business performance, track key metrics, and foster data-driven decision-making across teams. It emphasizes connecting marketing strategies to measurable outcomes like sales and brand equity.

Who should read *It's Not the Size of the Data*?

Marketing professionals, data analysts, and business leaders seeking to transition from intuition-based strategies to data-driven approaches will benefit most. The book is ideal for teams aiming to build or optimize marketing dashboards, improve cross-departmental accountability, and align campaigns with long-term organizational goals.

Is *It's Not the Size of the Data* worth reading?

Yes, for its practical, structured methodology on dashboard creation and real-world examples from companies like Amazon and Unilever. Koen Pauwels combines academic rigor with actionable advice, making it a valuable resource for professionals looking to democratize data access, streamline marketing ROI, and foster a culture of accountability.

What is Koen Pauwels' background in marketing analytics?

Koen Pauwels is a Distinguished Professor of Marketing at Northeastern University and former Principal Research Scientist at Amazon Ads. With a PhD from UCLA and consulting experience for brands like Microsoft and Sony, he’s renowned for pioneering research on marketing effectiveness, mix modeling, and retail media. He’s frequently ranked among the top 2% of global scientists in his field.

What is a marketing analytics dashboard?

A marketing analytics dashboard is a real-time visualization tool that synthesizes data from multiple channels to track performance indicators like customer engagement, campaign ROI, and brand equity. Unlike traditional reports, dashboards highlight leading metrics (e.g., social media sentiment) rather than lagging ones (e.g., quarterly sales), enabling proactive strategy adjustments.

How does *It's Not the Size of the Data* suggest selecting KPIs?

The book advises teams to first generate a broad list of potential KPIs, then eliminate redundancies by prioritizing metrics that directly predict business outcomes. Examples include customer acquisition cost, social media conversion rates, and cross-country market penetration. The final dashboard should feature 10–15 key leading performance indicators (KLPIs).

What role does teamwork play in building a marketing dashboard?

Pauwels stresses assembling a cross-functional team including IT, data scientists, and marketing managers to ensure technical feasibility and organizational buy-in. Leadership must align the dashboard with the company’s vision, while IT supports data integration from sources like CRM systems and social platforms.

How does the book address data-driven decision-making?

By advocating for dashboards that translate complex data into intuitive visuals, the book bridges the gap between marketers and executives. For example, a retailer might use a dashboard to correlate email open rates with in-store foot traffic, enabling timely budget reallocations. Case studies show companies achieving 20–30% ROI improvements through such practices.

데이터의 크기가 아니라 활용법이 중요하다

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데이터의 크기가 아니라 활용법이 중요하다 개요

"데이터의 크기가 중요한 것이 아니다(It's Not the Size of the Data)"에서 마케팅 전문가 코엔 파웰스(Koen Pauwels)는 왜 더 큰 데이터 세트가 성공을 보장하지 않는지 밝힙니다. 아마존(Amazon)과 유니레버(Unilever)와 같은 거대 기업들이 신뢰하는 이 수상 경력에 빛나는 접근 방식은 다음과 같은 질문을 던집니다. 만약 당신의 마케팅 대시보드에서 투자 수익률(ROI)을 두 배로 높일 수 있는 단 하나의 지표를 놓치고 있다면 어떻게 하시겠습니까?

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1장

When Data Meets Decision-Making: Revolutionizing Marketing Through Analytics

Imagine standing at the intersection of art and science, where the creative pulse of marketing meets the analytical rigor of data. This is where Koen Pauwels, the most published and awarded researcher on marketing performance, has built his career. His book "It's Not the Size of the Data-It's How You Use It" arrives at a critical moment when marketers face unprecedented pressure to demonstrate ROI while navigating an explosion of data sources. The book has become required reading in top business schools worldwide and has been praised by executives at companies like Google, Microsoft, and Unilever for transforming their approach to marketing measurement. What makes this work particularly valuable is how it bridges the persistent gap between academic marketing research and practical business application-a divide that costs companies millions in misallocated marketing dollars every year.

2장

The Marketing Measurement Crisis: More Data, Less Insight

Marketing departments today face a paradox that would have seemed unimaginable just decades ago: they're drowning in data yet starving for actionable insights. Despite the proliferation of big data and sophisticated analytics tools, many organizations struggle to connect marketing actions to financial outcomes. The problem isn't data scarcity-it's knowing which metrics matter and how they drive performance. Marketing analytics dashboards offer a solution by distilling essential information into a single display, much like a car's dashboard shows only critical metrics without requiring knowledge of what's under the hood. These dashboards bring together key market-based metrics into an interconnected system that allows users throughout the organization to monitor performance drivers and test scenarios in real time. What distinguishes a true marketing analytics dashboard from a simple scorecard is its underlying model connecting metrics-users can change inputs and watch projected outcomes change instantly. When properly implemented, these dashboards integrate data from diverse sources, connect marketing inputs to financial outcomes, and allow executives across departments to share a consistent view of the firm's market situation. The need for such dashboards has grown increasingly urgent as marketing departments face mounting pressure from CEOs and CFOs to demonstrate their contribution to growth while controlling costs. Surveys consistently show that marketing accountability ranks among the top concerns for senior executives, yet many organizations lack the tools to establish this connection clearly. Companies across industries have realized substantial benefits from implementing marketing analytics dashboards. Avaya used dashboards to enforce consistency in metrics across global operations, standardizing previously inconsistent definitions of "qualified leads." Google employs metrics as early warning indicators, taking corrective action when performance dips. Ameritrade integrated dashboards into their planning cycle tied to compensation, while Vanguard uses dashboards to communicate not just performance but what the organization values to its corporate board. The most powerful benefit may be how dashboards transform difficult conversations during budgeting cycles or when setting stretch targets. By enabling what-if analyses and scenario testing, they replace vague demands to work "harder and smarter" with specific, data-driven trade-offs that lead to better decisions and improved performance.

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데이터의 크기가 아니라 활용법이 중요하다의 각 단어가 오디오에 맞춰 실시간으로 강조되어 편하게 따라 읽을 수 있습니다.

3장

Breaking the ICE: Marketing Metrics Across Global Markets

When expanding marketing efforts globally, companies face the classic dilemma between standardization and localization. While Theodore Levitt famously argued for standardized global marketing, and many qualitative researchers advocate complete localization, the truth lies somewhere in between. Countries differ in systematic ways captured by institutional, cultural, and economic (ICE) dimensions that significantly impact how marketing works. Research shows that communication awareness is more responsive to advertising in emerging markets than in mature ones, while brand attitudes (consideration and liking) are less responsive to marketing in emerging markets. Additionally, sales conversion of brand liking is lower in emerging markets. These differences stem from emerging markets' lack of regulatory protection, collectivist cultures, and lower incomes. In emerging markets' "buyer beware" environment, consumers pay closer attention to marketing communications-74% of Latin American consumers trust TV advertising versus only 49% in the EU. However, in collectivistic cultures like China, India, and Latin America, consumers rely more on group opinions when forming brand attitudes, making them less responsive to direct marketing messages. L'Oreal learned this lesson when their individualistic slogan "because I am worth it" failed in emerging markets, prompting their 2011 shift to "because we are worth it." Income levels also significantly affect how consumers evaluate brands. High-income consumers can afford to make emotional purchases based on brands they love, while low-income consumers focus on tangible attributes like price and functionality. Research comparing Malaysia with France found that "brand love" concepts driven by passion, mystery, and sensuality work well in mature markets but fall flat in emerging ones where purchase decisions are based primarily on functional attributes and trust. These insights have profound implications for marketing strategy and measurement. A personal care brand comparing advertising effectiveness in the UK (mature) and Brazil (emerging) markets discovered that in the UK, advertising provided an immediate sales boost that quickly returned to baseline, working through the fickle metric of brand liking. In Brazil, advertising took longer to affect sales but created lasting impact by stimulating word-of-mouth that increased brand consideration permanently. To succeed across markets, brands must measure metrics consistently while prioritizing different metrics based on which ones respond more to marketing and convert better to sales in each specific market context. In emerging markets, prioritize reach over frequency to ensure awareness; be patient to allow word-of-mouth processes to develop after initial messaging; and focus on being trusted and respected rather than loved.

4장

Designing Dashboards That Drive Decisions

Even excellent analytics can fail if poorly presented. Effective dashboard design requires balancing simplicity with insight, following seven essential characteristics: simplicity, clarity, compactness, readability, insight, interactivity, and action-orientation. Three additional valuable but costly features include flexibility (allowing users to modify the structure), mobility (accessibility across platforms), and real-time data connectivity. The Inofec Right Chair dashboard exemplifies good structure by meeting all seven essential criteria: it's simple (showing only total money allocated to four marketing channels), clear (using just two colors-blue for action, beige for results), compact (displaying only the first fourteen planning days), readable (with clear labels), insightful (showing size and timing of profits), interactive (allowing budget multiplication with a single button), and action-oriented (enabling visual comparison of profit impacts across scenarios). Dashboard structure shapes how users understand business problems and make decisions. Good structure promotes logical organization that fosters quick comprehension while avoiding layouts that confuse users or lead to incorrect conclusions. Dashboards can be organized by time sequence, place (regions, products, or functions), cause-and-effect relationships, or organizational hierarchy. Effective data display requires strategic positioning of critical information in the upper part of the dashboard where users naturally scan first. Proper use of white space is crucial-cramming too much information reduces clarity and diverts attention from critical data. The "seven deadly dashboard sins" include: lacking focus on goals, displaying data without insight, limiting data sources, making updates too intensive, lacking data context, using poor visuals, and separating metrics from business objectives. Procter & Gamble excels in data visualization through their heat maps showing product market share across countries. Box sizes indicate the importance of growing specific market shares to overall company performance. Their dashboards highlight both poor and exceptional performance, helping marketers take smarter risks by assessing experimental projects and forecasting profit potential for bold initiatives. As P&G's CIO Filippo Passerini explains, it's about "getting beyond the what to the why and the how"-directing management attention where most needed. The minimalist approach works best-start with a customized, simple structure that respects busy professionals' time while providing a meaningful synthesis of the big picture and individual performance. Avoid unnecessary visual effects like 3D that hinder readability, use appropriate color coding (like dark green for monetary values), and present data consistently across dashboards with meaningful titles.

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5장

Implementing Dashboards: From Design to Action

Implementing a marketing analytics dashboard is challenging but critical for organizational success. The launch is particularly difficult, requiring careful planning and stakeholder alignment. Beyond the technical steps of communication, team identification, scope definition, data measurement system, requirements gathering, KPI selection, and prototype design, three final steps are crucial: testing the prototype with representatives of each user type, analyzing test results and making necessary changes, and launching the dashboard across the organization. Despite their effectiveness as performance measurement tools, dashboard projects face significant implementation challenges. Common obstacles include employee fears that integrated performance management will expose them to criticism and budget cuts, country executives believing their specific situations are unique, and disagreement about the relative value of different marketing channels. These challenges can be addressed by demonstrating how the dashboard helps employees excel and earn rewards, involving stakeholders from the start, and using correlation analysis to show how different channels contribute to performance. Dashboard projects often fail because managers miss critical success factors. Dashboards must be useful, containing relevant information that fosters analysis and action. They must align with organizational strategy, contain carefully selected metrics, and present information clearly. Good planning is essential, as is effective execution with committed people who understand that dashboards are ongoing works-in-progress requiring regular updates as strategies and KPIs change. Dashboard renewal is vital after the initial implementation period. User feedback naturally guides this process, highlighting metrics that don't generate sufficient insight or action and identifying missing metrics. The primary criterion for keeping a metric is whether it produces both insight (understanding relationships between actions and performance) and action (implementing changes based on those insights). Moving from dashboard insights to action represents a critical leap of faith that many organizations struggle with. Despite investing in data and analytics, risk aversion and uncertainty about personal benefits often prevent managers from implementing changes. Senior leadership must insist on data-driven decision making and demonstrate acting on insights. Four key steps help organizations move from insight to action: Adapt dashboard output to user needs and decision-making styles, Decide on rules for marketing budget setting and allocation, Design experiments to compare proposed actions versus status quo, and Address implementation challenges.

6장

From Interpretation to Action: Optimizing Marketing Investments

When moving from interpretation to action, key questions include whether to optimize budget allocation only or both budget size and allocation. The golden rule of allocation optimization is the ratio of elasticities-marketing resources should be allocated proportionally to their effectiveness. For example, if doubling online advertising increases sales by 20% (elasticity 0.2) while doubling offline advertising increases sales by 10% (elasticity 0.1), you should spend two-thirds of your budget on online advertising. Rather than immediately implementing optimal allocations, gradual adjustment toward the proposed solution allows observation of real-world results. For Inofec, the office furniture seller, modeling revealed that Google AdWords (13% of budget) returned 55.72 per euro spent while flyers (80% of budget) returned only 0.57. Instead of immediately shifting 98% of budget to AdWords as the elasticity ratio suggested, they conducted a field experiment doubling AdWords spending and halving flyer spending in selected regions. Results were dramatic-regions with doubled AdWords and halved flyers saw profit increases 14.2 times larger than control regions. When determining optimal marketing budget size, managers must consider whether marketing effects are linear (same sales increase for each dollar spent) or multiplicative (diminishing returns). For linear effects, the Dorfman-Steiner rule applies: advertising-to-sales ratio should equal advertising elasticity divided by price elasticity. For multiplicative effects, the Wright rule states optimal ad spending equals gross contribution multiplied by advertising elasticity. When exact optimization isn't feasible, directional budget changes can still improve performance. Heat maps and slider bars help decision makers visualize projected performance across budget ranges. Companies like Zara, Bayer, and BauMax have successfully implemented phased roll-outs as low-risk implementation strategies, starting with limited test stores to benchmark performance against reference outlets before expanding to more products and locations. Implementation of allocation and budget rules reveals additional challenges requiring adjustment. Analysis of INFORMS Practice Prize winners across four continents and diverse industries reveals five common implementation challenges: executives' time constraints, interdepartmental coordination difficulties, data integration complexity, demonstrating ROI, and establishing trust. Successful implementation requires building trust in dashboard metrics, managing expectations about benefits and start-up problems, and convincing decision makers that the dashboard enhances their job performance.

들리는 모든 단어를 눈으로 확인하세요

데이터의 크기가 아니라 활용법이 중요하다의 각 단어가 오디오에 맞춰 실시간으로 강조되어 편하게 따라 읽을 수 있습니다.

7장

Nurturing a Culture of Accountability

Marketing analytics dashboards require and reinforce an organizational culture committed to smarter marketing. Three critical cultural factors provide fertile ground for dashboard adoption: the overwhelming need to manage by exception due to information overload in today's digital age, the strategic desire to focus on targeted performance metrics that directly impact business outcomes, and organizational crises or competitive pressures that create openness to change and heightened accountability. To motivate dashboard adoption, organizations must clearly articulate each employee's specific role in the project and their direct impact on company performance. This includes showing sales teams how their activities correlate with revenue metrics, helping marketing specialists understand their contribution to lead generation, and demonstrating to executives how integrated data drives strategic decisions. Personal benefits should be emphasized, such as the ability to track and improve individual performance, identify skill gaps, and showcase achievements. Organizations should encourage initial trial use through pilot programs, actively incorporate employee feedback during implementation phases, seamlessly integrate dashboards into daily operations through regular team meetings and reviews, and develop performance-related incentives that resonate with different roles. Dashboard effectiveness relies on three fundamental principles managers must internalize: dashboards communicate interconnected metrics that drive action (rather than presenting isolated data points), they must answer specific questions about individual roles and broader business goals, and organizations need clear policies about data accessibility across departments. Marketing analytics dashboards serve multiple crucial functions - they clarify marketing's strategic role, enable fact-based decision making through real-time data, establish clear lines of responsibility for outcomes, and elevate marketing accountability with C-suite executives through quantifiable results. Maintaining accountability culture post-launch requires systematic approach: integrate dashboard software directly into user workstations with comprehensive training programs, establish it as the mandatory corporate standard for business review and performance evaluation, and create meaningful connections to employee incentives and career advancement. Since initial implementation enthusiasm typically wanes over time, the ongoing benefits must consistently outweigh perceived costs and be regularly communicated through success stories and case studies, while performance incentives need to evolve to motivate sustained engagement. The true data revolution manifests through fundamental organizational culture change, not merely technological implementation. Seven proven strategies for instilling lasting accountability include: beginning measurement immediately rather than waiting for perfect conditions (user satisfaction typically increases over time), implementing metrics for all marketing activities including traditional channels, making substantial investments in robust data collection infrastructure, ensuring coordination between traditional and digital campaign measurements, establishing clear and measurable objectives for all initiatives, involving external vendors and agencies in dashboard goals and metrics, and creating direct links between dashboard performance indicators and compensation structures at all levels. Success requires patience and persistence - organizations that maintain focus on these principles while adapting to feedback and changing conditions are most likely to create sustainable cultures of accountability that drive long-term business value through data-driven decision making.

8장

Identifying Key Leading Performance Indicators

The dashboard creation process must transition from gathering potential metrics to selecting those most critical to performance. Research shows organizations perform best with neither too few (under five) nor too many (over twenty) metrics. Selecting the right metrics presents a significant challenge, particularly for customer-focused measurements. To identify metrics that truly lead performance, two steps are recommended: first turning metrics into leading performance indicators (LPIs), then into key leading performance indicators (KLPIs). Sir Clive Granger's causality principle provides the foundation: if a metric leads performance, it should help predict future performance. Testing involves comparing two predictions: one based only on past performance, and another incorporating both past performance and the metric. If the second prediction is significantly better, the metric "Granger-causes" or leads performance. After identifying leading performance indicators, the next step is ranking them by importance to further narrow the focus to 5-10 key metrics for dashboards. Vector autoregressive (VAR) models quantify dynamic effects that standard marketing mix models miss. VAR models capture how marketing actions affect metrics over time, how metrics convert into sales, and both direct and indirect sales effects. Two key tools derived from VARs help managers understand metric importance: impulse response functions (IRFs) that reveal how much and when a metric change affects performance, and forecast error variance decomposition (FEVD) that shows how much current performance is explained by past changes to each variable. By integrating consumer survey data with actual brand sales, VAR modeling can identify which metrics truly drive brand sales. For a male shaving product, VAR analysis revealed communication awareness led sales with ten times the impact of other KPIs. "Allows shaving against the grain" and "good enough shave" emerged as strong product KLPIs, while user imagery showing "ordinary" (not beauty models) yet "attractive to opposite sex" men drove sales effectively. These findings contradicted what consumers directly reported as important-they rated "gives a close shave" highest but this failed to drive actual sales. When comparing VAR with other methods for reducing metrics, VAR demonstrated superior predictive power. The analysis for a snack brand revealed that while the national brand's price had the largest immediate impact on sales, surprisingly, the store brand's price had a larger long-term effect-a crucial insight for brand managers concerned about store brand growth. These VAR-based findings proved highly actionable, with nine of ten metrics under managerial control, helping managers develop better marketing plans.

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9장

Measuring What Matters in Digital and Social Media

The internet represents the new frontier in metrics, promising better accountability while simultaneously overwhelming managers with options. Despite claims of uniqueness, emerging channels should still be measured by how they "move the needle for the business"-not by vanity metrics like tweet counts or page views. What truly differentiates online marketing is that many forms require deliberate customer action rather than passive exposure, social media enables customer-to-customer conversations that companies can track and influence, and the medium allows for inexpensive real-time experimentation with ad executions. Online advertising often requires deliberate customer action rather than passive exposure, making customer-initiated contacts (CICs) potentially more valuable than firm-initiated contacts (FICs). Content-integrated CICs (like price comparison sites or organic search results) typically have the highest sales impact because customers are more attentive to relevant information they're actively seeking, and such placements are generally found more informative and less irritating than separated content. Despite their flaws, many managers still use last-click attribution methods, which particularly fail to distinguish between converting and non-converting clicks, and favor bottom-funnel channels like paid search at the expense of top-funnel exposure like banner ads. Research shows that switching from optimal allocation to last-click methods would decrease revenues by 28%, while following KLPI methods could increase revenue by 17% through reallocating budgets to content-integrated CICs. Social media management requires balancing between letting go and maintaining control-achieving "organized chaos." Companies should track four key metrics: quantity (volume), sentiment (positive/negative mentions), dispersion (variation in sentiment), and topic (conversation content). Understanding what people are talking about is crucial for interpreting social media data. For example, Apple's iPad received 54% negative mentions initially, but many related to data plans or service providers rather than the device itself. Despite claims that measuring social media ROI is infeasible, companies making substantial investments should project and measure monetary benefits. A U.S. fashion retailer analyzed how different social media mentions and marketing actions drive retail traffic. They categorized conversations into three buckets: "Love WOM" (brand love), "Purchase WOM" (store visits/purchases), and "Ad WOM" (mentions of advertisements). In the short-term, all WOM types increased traffic more than paid marketing, with Purchase WOM (26% traffic increase when doubled) outperforming Ad WOM (13%). Marketing actions had both direct and indirect effects-TV ads increased store traffic directly (68%) and indirectly through online traffic (10%) and Purchase WOM (23%).

10장

The Journey to Marketing Intelligence

Marketing analytics dashboards help marketers take smarter risks by assessing experimental projects and forecasting profit potential of bolder initiatives. Far from extinguishing creativity, they help art and science feed off each other, as CMOs at Target, Fidelity, MasterCard, and H&R Block note: "Science enriches the art in marketing, and art accelerates the science." Building an effective dashboard requires commitment supported by communication and a cultural shift toward accountability and transparency. Implementation is an everyday responsibility whose success depends on managerial support, alignment with company strategy, and employee engagement. Like any innovation, dashboards can't be effective unless users understand their functions, believe in their benefits, and want to use them. The core challenge for dashboard project managers is combining diverse talents toward a common goal. Effective managers need both strong interpersonal and technical skills to balance task performance (budget, quality, technical results) with relationship factors (conflict resolution, trust, communication). The most dangerous barriers-differing priorities, role conflicts, and power struggles-are often the hardest to detect and require exceptional leadership sensitivity. A well-built database is fundamental to dashboard success, though its development requires tedious work of cleansing, formatting, and loading data. When properly constructed, databases offer numerous benefits including determining customer value, identifying profitable customers, building better relationships, targeting acquisition efforts, customizing offers, and measuring marketing effectiveness-ultimately providing competitive advantage through targeted communication. The real data revolution comes through organizational culture change, not just technology. Seven suggestions for instilling accountability: start immediately (satisfaction increases over time), use metrics for all marketing actions, invest in data collection, coordinate traditional and digital campaigns, set measurable objectives, involve external vendors in dashboard goals, and link dashboard performance to compensation. Don't be discouraged by the gap between where you are and where you could be, or distracted by flashy software or management fads. What you need is courage and vision! Research shows five key success factors that increase company performance by 8-20%: top management support, a supportive analytics culture, IT support, appropriate data, and analytic skills. Improving any area will enhance your marketing insights and decisions while raising your standing with colleagues, bosses, and investors.

★★★★★

데이터의 크기가 아니라 활용법이 중요하다 완독을 축하합니다

100만 명 이상의 학습자가 사랑합니다

“23일째 매일 사용하고 있어요. 이제 제 일상의 한 부분이 되었습니다.”

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데이터의 크기가 아니라 활용법이 중요하다의 핵심 주제

marketing performance measurement
data-driven decision making
marketing analytics dashboards
global market localization
return on investment

데이터의 크기가 아니라 활용법이 중요하다의 명언

More data, less insight.
Countries differ in systematic ways.
Even excellent analytics can fail if poorly presented.

데이터의 크기가 아니라 활용법이 중요하다의 등장인물

Koen PauwelsAuthor and researcher on marketing performance
Theodore LevittEconomist who argued for global standardization

저자 소개

*데이터의 크기가 아니라 어떻게 사용하는가가 중요하다(It’s Not the Size of the Data—It’s How You Use It)*의 저자인 벨기에계 미국인 코엔 헨드릭 파웰스(Koen Hendrik Pauwels)는 마케팅 분석 및 데이터 기반 의사결정 분야에서 세계적으로 인정받는 권위자입니다. 노스이스트 대학교(Northeastern University) 다모어-맥킴 경영대학(D’Amore-McKim School of Business)의 마케팅 석좌교수이자 연구 부학장인 파웰스는 전략적 마케팅을 위한 분석 활용 가이드에서 학문적 엄격함과 실무적인 비즈니스 통찰력을 결합합니다. 그의 전문성은 아마존(Amazon), 마이크로소프트(Microsoft), 유니레버(Unilever)를 포함한 포춘 500대 기업들을 대상으로 한 수십 년간의 컨설팅과 마케팅 효과성, 장기적 브랜드 자산, 리테일 미디어 최적화에 관한 선구적인 연구에서 비롯되었습니다.

파웰스는 편집장을 맡고 있는 International Journal of Research in Marketing과 뉴스레터인 Pauwels on Marketing 및 Amazon Days를 통해 자신의 사상적 리더십을 확장하고 있습니다. Modeling Markets 및 Break the Wall과 같은 그의 다른 저작들은 그를 데이터 리터러시 대중화의 선두 주자로 자리매김하게 했습니다.

*마케팅 위크(Marketing Week)*로부터 2023년 "지구상 최고의 마케팅 학자"로 선정되었으며 스탠퍼드 대학교가 발표한 세계 상위 2% 과학자에 이름을 올린 파웰스의 프레임워크는 전 세계 MBA 프로그램에서 교육되고 있으며, 가공되지 않은 데이터를 실행 가능한 성장 전략으로 전환하려는 경영진들에 의해 활용되고 있습니다.

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지금 바로 학습 여정을 시작하세요

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데이터의 크기가 아니라 활용법이 중요하다

개요데이터의 크기가 아니라 활용법이 중요하다 개요

한 권의 책, 다양한 듣기 방식.

When Data Meets Decision-Making: Revolutionizing Marketing Through Analytics

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Implementing Dashboards: From Design to Action

From Interpretation to Action: Optimizing Marketing Investments

들리는 모든 단어를 눈으로 확인하세요

Nurturing a Culture of Accountability

Identifying Key Leading Performance Indicators

데이터의 크기가 아니라 활용법이 중요하다에서 더 많은 것을 얻으세요

Measuring What Matters in Digital and Social Media

The Journey to Marketing Intelligence

데이터의 크기가 아니라 활용법이 중요하다 완독을 축하합니다

데이터의 크기가 아니라 활용법이 중요하다의 핵심 주제

데이터의 크기가 아니라 활용법이 중요하다의 명언

데이터의 크기가 아니라 활용법이 중요하다의 등장인물

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데이터의 크기가 아니라 활용법이 중요하다 요약 다운로드

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이 책에 대한 FAQ

What is It's Not the Size of the Data about?

Who should read It's Not the Size of the Data?

Is It's Not the Size of the Data worth reading?

What is Koen Pauwels' background in marketing analytics?

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1,000,000+ curious minds.

1,000,000+ curious minds.

한 권의 책, 다양한 듣기 방식.

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데이터의 크기가 아니라 활용법이 중요하다에서 더 많은 것을 얻으세요

Implementing Dashboards: From Design to Action

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들리는 모든 단어를 눈으로 확인하세요

Nurturing a Culture of Accountability

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데이터의 크기가 아니라 활용법이 중요하다에서 더 많은 것을 얻으세요

Measuring What Matters in Digital and Social Media

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데이터의 크기가 아니라 활용법이 중요하다 완독을 축하합니다

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