How AI is creating the new data monetization opportunity
Free Subscriber Version | Issue #35
In this report, I'll cover:
How AI creates the new data monetization economy?
How generative AI is changing the way builders develop software?
How to monetize the future of data-driven economy?
Section 1: Key Market Trends
(1) Monetizing derivative data:
Derivative data products are becoming increasingly popular as companies seek to monetize the vast amounts of data available on the internet. Companies can extract, analyze, and package data from multiple sources to create valuable insights for their customers.
SimilarWeb provides data on website rankings, traffic sources, competitor analysis, and online behavior for businesses looking to improve their online presence.
Crunchbase, Dealroom, and Pitchbook provide information on companies and startups, including contact information, team members, funding, merger and acquisition, and industry trends.
Ahrefs and SEMrush provides insights for keyword research, keyword trends and ad cost analysis.
BuzzSumo provides insights into 5 billion trending articles, social sharing, and backlinks.
(2) Automate SQL database creation with AI:
With the rise of AI, you can now convert text into SQL databases without extensive coding knowledge. Users can input keywords that describe the query and generate optimized SQL database schemas.
AI Query helps you generate complex SQL in seconds.
Airops automatically generates SQL queries and provides various features such as query optimization, suggestion, automated documentation writing, and query updating.
AI Helper Bot matches your input with a database schema automatically. The platform supports languages such as English, Spanish, German, and more.
Text2SQL.AI translates plain English prompts to SQL with AI.
AI2sql writes queries using natural language (NLP) powered by OpenAI’s Codex.
(3) Automate machine learning models with AI:
AutoML solutions use AI to automate data preprocessing, which involves cleaning, transforming, and preparing raw data for use in machine learning models.
DataRobot is one of the leading providers in the market that offers a full lifecycle AI platform.
H2O.ai generates AI models in minutes.
RapidMiner enhances data capabilities by offering end-to-end automation and augmentation for data exploration, modeling and production.
Neuton.AI is a no-code automated machine learning platform that automatically preprocesses data, extracts features and creates tiny models.
more…!!
(🔒 MEMBERS-ONLY) +5 more key trends, backed by real company examples:
🔑 (4/8) Who is building the "Google" or "Amazon" for data? (5 examples)
🔑 (5/8) Monetize data using no-code AI (5 examples)
🔑 (6/8) The power of generative AI (5 examples)
🔑 (7/8) Monetize data through NoCode value-add processing (5 examples)
🔑 (8/8) Monetize data with a new business model (4 examples)
Section 2: Market Players & Market Needs
(🔒 MEMBERS-ONLY) Access the full database:
🏢 Total 92 market players.
📍 Total 9 niche segments.
🗃 Data points: value proposition, website, stage, total funding raised, year founded, company size, location and LinkedIn
Section 3: Problems & Market Needs
(1) Creating an alternative to Excel:
Excel often lacks the features required for businesses to easily organize, format, and present raw data in an accessible manner.
New startups are attempting to unbundle Excel by creating alternative spreadsheet software that offers more advanced capabilities such as transforming, visualizing and organizing databases in an intuitive, easy-to-use UI.
Coda combines the features of a spreadsheet, database, and document editor. Coda distinguishes itself by allowing users to create interactive documents and templates.
Stackby brings spreadsheets, API and no-code automation in one place.
Quip is a spreadsheet software built specifically for sales and marketing teams.
Smartsheet replaces Excel project management templates with team collaboration and workflow management features.
Grist is a lightweight spreadsheet alternative that combines CRM, data visualization, and business management.
(🔒 MEMBERS-ONLY) +4 more insights to validate customer needs:
🔑 (2/5) Monetize collaborative data (5 examples)
🔑 (3/5) Monetize by solving data privacy risks (4 examples)
🔑 (4/5) Monetize niche no-code tools (6 examples)
🔑 (5/5) Monetize by solving inaccuracy of data (5 examples)
Section 4: Startup Opportunities & Predictions
(1) Monetize video game data:
The gaming creator economy continues to grow as an alternative career path for younger generations [Refer: Unbundling of LinkedIn report]. Companies can leverage the data monetization economy by creating database products that provide insights into player behavior, game performance, and market trends.
GameAnalytics helps game developers manage their game development portfolio and optimizes game portfolios using data-driven insights.
Sensor Tower analyzes top grossing mobile games in the App Store to provide insights into game performance and market demand.
Esports Charts provides analytics for industry growth, tournaments, events, teams and popular games.
Shadow analyzes video gameplay to identify opponents' winning strategies and techniques.
(2) Turn user-generated data into data products:
Businesses can turn user-generated data into valuable assets and create monetizable products, such as API. Founders can repurpose data generated from their existing products, and generate revenue by charging subscription fees or transaction fees for each API access.
Twitter has developed APIs that allow developers to access user-generated information such as Tweets, user profiles, media and so on.
Fitbit collects data from its fitness tracker and converts it into free API products that offer valuable insights such as heart rates, sleep analytics, and activity statistics.
Airbnb API allows selected partners to obtain data such as property details, amenities filters, and customer reviews.
Booking.com has an API that costs $19/month (Pro) for 10,000/month call requests.
Skyscanner is monetizing travel data by providing access to prices for flights, hotels, and car rentals.
(3) Collective-generated database products:
Leverage DAO (decentralized autonomous organization) on the blockchain to build large datasets and reward contributors. For example, collective members can work on data projects, curate database entries, organize information while getting paid in cryptocurrency.
GenomesDAO pays you to contribute DNA data for medical research.
Matchpool rewards matchmakers who contribute to matching users based on submitted traits, characters, and interests.
DB DAO rewards members who contribute databases. Curators monetize their work through the use of decentralized databases by decentralized apps.
(🔒 MEMBERS-ONLY) +5 more startup opportunities:
🔑 (4/8) Repackage and sell Internet's data sources (5 examples)
🔑 (5/8) Drive more E-Commerce sales using first-party database (5 examples)
🔑 (6/8) Monetize data for consumer apps (4 examples)
🔑 (7/8) Niche data sources you can easily monetize (4 examples)
🔑 (8/8) How to monetize adjacent data products (4 examples)
Section 5: Product Strategy & Recommendation
(1) How to market a data product:
Developer tools: Most API products employ this strategy to attract developer users. You can build freemium APIs, SDKs, and documentation to encourage developers to integrate your data and build applications with your data product. Make an app showcase page to highlight developers who have used your APIs.
Chrome extension: Allow users to easily access your data product while browsing the web. The Similarweb Extension, for example, enables you to quickly check a website's traffic, engagement and competitor’s sites.
Product-led growth: Develop a free trial or freemium version of your data product and nurture the customer journey with onboarding videos, 1:1 setup calls and email marketing. Clearbit provides a free tool that allows you to see who is visiting your website and generate a free Weekly Visitor Report that highlights prospects with high purchase intent.
(🔒 MEMBERS-ONLY) +4 more actionable ideas and recommendations:
🔑 (2/5) 3 tactics to get more users using network effect (+ 3 examples)
🔑 (3/5) 3 tactics to create a no-code data marketplace (+ 4 no-code tools)
🔑 (4/5) 3 tactics to automate creation of database product (+ 7 nocode tools)
🔑 (5/5) 3 tactics to differentiate a data product (+ platforms)
Love the AI insights, thanks for sharing!