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Formations/CDO Track/Data products & monetization/Data monetization & economic value/Data monetization: three modes & the data flywheel
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Data monetization & economic value

1Data monetization: three modes & the data flywheel+802Data productization: pricing, distribution & business case+803Pricing models for data products+180

Data monetization: three modes & the data flywheel

Data is an asset. Like any asset, it can generate returns beyond its original purpose. The CDO who understands data monetization expands the value propositionvalue propositionA clear statement of the benefits your product delivers, the problems it solves and why customers should choose you over alternatives.Voir la définition complète → of the data function from "cost center that enables internal decisions" to "capability that generates external revenue and competitive advantagecompetitive advantageA lasting edge over competitors: a resource, capability or position they cannot easily replicate, letting a firm earn above-average returns over time.Voir la définition complète →."

The three modes of data monetization

Direct monetization:
Selling data directly to third parties. The most obvious form, but the most restricted by privacy regulations. Requires explicit consent frameworks and careful legal review. More common in B2B contexts (industry benchmarks, market data) than B2C.

Indirect monetization: Using data to improve products and services that generate revenue. This is where the largest value lies for most organizations. Amazon's recommendation engine, Netflix's personalization, Spotify's Discover Weekly, each monetizes data indirectly by making the core product better.

Data-enabled business models: New business lines built on data capabilities. A retailer building a retail media network (selling advertising inventory to brands using their customer purchase data). A bank building a data-as-a-service offering for fintech startups.

Most organizations should focus on indirect monetization first, it requires no new legal frameworks and the ROIROIReturn on Investment: the ratio of net profit to the cost of an investment. A 300% ROI means each dollar invested returns $3.Voir la définition complète → is often the highest.

Data Monetization Strategies for Business

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Vérification des acquis

1. Why does the lesson recommend that most organizations focus on indirect monetization first?

2. A retailer builds a retail media network, selling advertising inventory to brands using its customer purchase data. Which monetization mode does this represent?

3. According to the infonomics framework, why is cost-based valuation described as setting a 'floor'?

CHOIX MULTIPLES

4. Select ALL statements that correctly describe direct monetization of data.

Sélectionnez toutes les réponses correctes.

CHOIX MULTIPLES

5. Select ALL correct statements about the economic value-based valuation approach.

Sélectionnez toutes les réponses correctes.

Calculating the economic value of data

Before monetizing data, you need to understand its value. The infonomicsinfonomicsDiscipline fondée par Douglas Laney (Gartner) traitant l'information comme un actif économique mesurable, avec une valeur qui peut figurer au bilan de l'entreprise. framework (Douglas Laney) provides three approaches:

Cost-based valuation: What did it cost to create, collect, and maintain this data? This sets a floor, selling data below its creation cost destroys value.

Market-based valuation: What would similar data sell for in the market? Comparable transaction data, data broker pricing, and licensing benchmarks provide reference points.

Economic value-based valuation: What business decisions does this data enable, and what is the measurable economic impact of those decisions? This is the most rigorous and often the highest valuation, but requires connecting data to business outcomes.

The economic value approach is also the most useful for internal prioritization: which datasets are enabling the highest-value decisions? Those deserve the most investment in quality and accessibility.

The data marketplace model

Several industries have evolved toward data marketplaces, platforms where multiple data providers and consumers exchange data. Key examples:

Financial services: Bloomberg, Refinitiv, S&P Capital IQ aggregate financial market data and sell access. Alternative dataAlternative dataDonnées non-traditionnelles utilisées pour l'analyse d'investissement ou le renseignement concurrentiel : images satellites, transactions bancaires, géolocalisation, scraping web, mentions sociales. brokers (Quandl, YipitData) sell non-traditional datasets (satellite imagery, credit card transaction panels, app usage data).

Healthcare: Real World Data providers (IQVIA, Symphony Health) aggregate de-identified patient data and sell to pharmaceutical companies for drug development, safety monitoring, and market access research.

Retail media networks: Walmart Connect, Amazon DSP, Target Roundel, retailers selling advertising inventory powered by purchase data. Walmart's advertising revenue exceeded $3B in 2023.

The CDO's role in these models: ensure data is accurate, clean, de-identified where required, and delivered with appropriate contractual protections.

Data as a competitive moatmoatA lasting edge over competitors: a resource, capability or position they cannot easily replicate, letting a firm earn above-average returns over time.Voir la définition complète →

The most durable form of data monetization isn't selling data, it's using proprietary data to build capabilities competitors can't replicate. This is the data flywheeldata flywheelEffet de volant d'inertie appliqué aux données : plus vous collectez de données, meilleurs sont vos services, ce qui attire plus d'utilisateurs, générant encore plus de données. L'avantage compétitif auto-renforçant d'Amazon et Netflix.:

More users → more behavioral data → better models → better product → more users.

Amazon's flywheel has been running for 25 years. Their product recommendation accuracy, pricing algorithm, and logistics optimization are built on data advantages that would take a competitor a decade to replicate, if they could at all.

Building your flywheel: identify which data assets are unique to your position in the market, invest in the ML capabilities that exploit those assets, and design the product feedback loops that generate more data as the product improves.

Quiz Questions

1. Quelle forme de monétisation des données offre le ROIROIReturn on Investment: the ratio of net profit to the cost of an investment. A 300% ROI means each dollar invested returns $3.Voir la définition complète → le plus élevé pour la plupart des organisations et ne nécessite pas de nouveau cadre juridique ?

A) La vente directe de données à des tiers

B) La monétisation indirecte, utiliser les données pour améliorer les produits qui génèrent du revenu

C) La crcrThe percentage of visitors or prospects who complete a desired action (purchase, sign-up, contact form), calculated as conversions divided by total opportunities.Voir la définition complète →éation de marketplaces de données

D) Les data-as-a-service offerings pour des startups

Réponse: B

2. Dans l'approche "economic value-based valuation" de Douglas Laney, comment est calculée la valeur d'un dataset ?

A) Par le coût de collecte et maintenance des données

B) Par le prix de marché de données comparables

C) Par l'impact économique mesurable des décisions business que ces données permettent de prendre

D) Par le volume de données stocké

Réponse: C

3. Qu'est-ce que le "data flywheeldata flywheelEffet de volant d'inertie appliqué aux données : plus vous collectez de données, meilleurs sont vos services, ce qui attire plus d'utilisateurs, générant encore plus de données. L'avantage compétitif auto-renforçant d'Amazon et Netflix." illustré par Amazon ?

A) Un outil de stockage de données haute performance

B) Une boucle vertueuse : plus d'utilisateurs → plus de données → meilleurs modèles → meilleur produit → plus d'utilisateurs

C) Une stratégie de vente de données à des tiers

D) Un système de backup automatique des données

Réponse: B

À faire, tiré de cette leçon

Ces actions sont compilées dans le plan d'action du rôle.

  • Prioritize indirect monetization improving revenue-generating products over selling data externally
  • Value datasets by the economic impact of decisions they enable
  • Design product feedback loops that generate more data as products improve
Voir le plan d'action complet →

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Data productization: pricing, distribution & business case