“We are surrounded by data but starved for insights.” — Jay Baer
❓ What You’ll Learn
- How do data marketplaces make it easier to buy and sell data?
- Who will opt in for active and passive data sharing?
- How will AI streamline data management?
- How to build a cold sales agency?
- How can you escape competition by using branded metrics?
- How will AI change the Data as a Service industry?
- How much should you charge for your data?
- How to turn data into a byproduct?
- How to boost margins?
- How can you build a durable data moat?
💎 Why It Matters
You can gain a competitive edge by fueling your decisions with the right data.
🔍 Problem
You need to make better decisions.
💡 Solution
DaaS helps you focus on your core competency. While outsourcing data collection and processing.
🏁 Players
DaaS Companies
- Ahrefs • Search queries, volume, links, keywords and more
- Abstract API • Data on phones, emails and more
- Hunter • Database of verified business and work emails
- Built With • Analytics, advertising, hosting, CMS and other tools that websites use
- Apollo • AI-powered database of B2B leads
- Quandl • Data on private jets, jobs, forex transactions and more
- WordStream • Ads and keyword grader
Data Tools
- Tally • Build beautiful surveys
- QuickAPI • Sell and share data APIs
- Databox • Build data dashboards
- ScrapingBee • Scrape the web with rotated proxies
- Obviously AI’s Data Validator • Check if your data is ready for machine learning
🔮 Predictions
- We’ll see more data marketplaces. Data can be a hard sell. Marketplaces will foster transactions with curation, ratings and more.
- Narrative offers datasets from 40+ data providers.
- Datarade offers datasets from 500+ data providers.
- Snowflake Marketplace offers free and premium datasets.
- AWS Data Exchange offers 3,500+ data files, tables and APIs.
- Google Cloud Marketplace offers 200+ business and consumer datasets.
- Consumers will opt in for active and passive data sharing.
- Nielsen uses panels to track consumer behavior.
- Tesla tracks the use of autopilot, multimedia and more.
- Prodege members upload receipts from in-store purchases.
- UK Biobank collects medical data from thousands of volunteers.
- Mozilla Rally is a browser extension that tracks how tech giants collect data.
- NielsenIQ’s Scanning Panel members scan and share products they have at home.
- DataSkop users shared their YouTube data in 2021 and can share their TikTok data in 2023.
- AI will help us save time collecting, cleaning and interpreting data. It doesn’t need to sleep, eat or rest.
☁️ Opportunities
- Build an AI-powered data analytics tool. Let users use AI to clean, analyze and visualize data.
- Sisense uses AI to query and analyze datasets.
- 6sense uses AI to find, analyze and enrich buyer data.
- LenddoEFL uses AI to analyze digital and behavioral data for credit scoring.
- CSW Insights uses AI to get insights into stock trades by congress members.
- Build a cold sales agency to help customers get more sales.
- Alex West grew CyberLeads to $500,000 ARR by finding recently funded companies.
- Jakob Greenfeld and Ryan Doyle grew Damn Good Leads to $100,000 ARR in 3 months by finding B2B leads.
- Dancho Dimkov grew BizzBee Solutions to $18,000 MRR in 2 years by focusing on small and medium-sized businesses.
- Offer Insights as a Service. Data is a means to an end. Insights get you closer to the “job to be done.”
- PitchBook offers actionable advice based on data insights.
- Delphi Digital offers deep market analysis, office hours and more.
- Fortune Business Insights offer market research with actionable insights.
- Build branded metrics to escape competition. Others referencing your metric will lead to free marketing for your company.
- Domain Authority by Moz is a search engine ranking score.
- Zestimate by Zillow is an estimate of a home’s market value.
- Accessibility scores by Walk Score measure walkability, commute and travel routes.
🏔️ Risks
- Artificial Intelligence • Customers will go straight to insights. Making DaaS companies obsolete.
- Depreciation • Data becomes less accurate, reliable and useful over time.
- Platform Risk • You’re subject to the DaaS provider’s datasets, outages and fees.
🔑 Key Lessons
- DaaS is cheaper than in-house data management. You don’t need to spend time, money and energy to build and maintain your own infrastructure.
- Price your DaaS based on the value you create. It is easier to charge $1,000 if you help your customers make $100,000.
- Data loses value over time.
🔥 Hot Takes
- We’ll see recognized data quality metrics. Talend Trust Score® shows how reliable your data is.
- AI poses an existential risk to DaaS companies. Who wants to dig into data if AI gives insights on a platter?
- Data is a byproduct. Sell your sawdust. Walmart built Walmart Luminate to sell data on shoppers’ behavior.
😠 Haters
“AI will make DaaS companies less relevant.”
While AI can process data more efficiently. It can only process data that it has access to. To protect their moats, DaaS companies will lock data behind walls. AI won’t reach it unless a breach occurs.
“AI companies use data to train their models. Without permission.”
When was the last time you read a privacy policy? Non-AI companies use privacy policies to “simulate” your consent. Coresignal offers 660,000,000 employee records parsed from LinkedIn, Crunchbase and more. You never know when another “partner” adds you to their dataset.
“Some DaaS companies resell data from companies like Crunchbase. Which kills margins.”
Protect margins by adding value. Offer unique insights, branded metrics, productized services and more.
“Governments can make it hard to operate in the DaaS space.”
Stay away from regulated industries. It is easier to share B2B leads than patient data.
“Profiting from personal data is unethical.”
Sell anonymized data that doesn’t link to people.
“Companies like Clearview AI make it easier to spy on people. This can lead to less privacy, more surveillance and abuse of power.”
While such tools can be misused. They can make our communities safer by lowering crime, fraud and risk. DaaS is just a tool. We define its purpose.
🔗 Links
- Who’s Offering Data as a Service? • The tweet behind this report.
- What is Data as a Service • Pros, cons and case studies of DaaS integration.
- The Empty Promise of Data Moats • How to build durable data moats.
📁 Related Reports
- ChatGPT • Automate work and save time coding, writing, researching and more
- Curation as a Service • Find signal in the noise
- Crowdsourcing • Leverage the time, energy and experience of others to reach your goal
- No-Code • Build products faster, cheaper and better without writing code
- Agencies • Help your customers solve problems without hiring and managing large teams
🙏 Thanks
Thanks to Kevin Galang, Mishal Siddiqui, Mehmet Gonullu, Alex Doda, Benhur Desta, Reme Ekoh, Soma Mandal, Nirav Multani, Fausto Sá Teles, Marc Fletcher, Emeric Victor, Stewart Townsend, Alex Espinoza, Thomas Sorheim and Stephanie Hekker. We had a great time jamming on this report.
✏️ Emin researched and wrote this report. Dru researched and edited this report.
📈 What else?
Trends PRO #0116 — Data as a Service has more insights.
What you’ll get:
- 27 Data as a Service Companies (286% More)
- 27 Data as a Service Tools (440% More)
- 11 Predictions (267% More)
- 16 Opportunities (300% More)
- 6 Risks (100% More)
- 6 Key Lessons (100% More)
- 8 Hot Takes (167% More)
- 12 Links (300% More)
With Trends Pro you’ll learn:
- (📈 Pro) What are personal data stores?
- (📈 Pro) How will Data as a Service companies use crowdsourcing?
- (📈 Pro) How to help companies get data from their target audience?
- (📈 Pro) What is federated learning?
- (📈 Pro) How do “Data Trusts” fuel good and bad decisions?
- (📈 Pro) What is Data Trust as a Service?
- (📈 Pro) How can data clean rooms boost ad performance?
- (📈 Pro) What are data agencies?
- (📈 Pro) How to build a data-driven paid newsletter?
- (📈 Pro) How to find alternative data?
- (📈 Pro) How to break data silos?
- (📈 Pro) What is the strongest data moat?
- (📈 Pro) How does commoditization affect data?
- (📈 Pro) What tools can streamline Data as a Service operations?
- (📈 Pro) How to know if your data is a commodity or an asset?
- (📈 Pro) What is the downside of building APIs?
- (📈 Pro) How to design and build “Data Trusts”?
- (📈 Pro) How to monetize data?
- (📈 Pro) What are the 3 KPIs to measure the impact of data analytics?
- (📈 Pro) How to boost data accuracy?
- (📈 Pro) What are data cleansing challenges?
- (📈 Pro) Who grew a cold sales agency to $300,000 ARR?
- (📈 Pro) How to build and sell a Data as a Service startup in 6 months?
- (📈 Pro) How to use data to make investment decisions?
- And much more…
Get Weekly Reports
Join 65,000+ founders and investors
📈 Unlock Pro Reports, 1:1 Intros and Masterminds
Become a Trends Pro Member and join 1,200+ founders enjoying…
🧠 Founder Mastermind Groups • To share goals, progress and solve problems together, each group is made up of 6 members who meet for 1 hour each Monday.
📈 100+ Trends Pro Reports • To make sense of new markets, ideas and business models, check out our research reports.
💬 1:1 Founder Intros • Make new friends, share lessons and find ways to help each other. Keep life interesting by meeting new founders each week.
🧍 Daily Standups • Stay productive and accountable with daily, async standups. Unlock access to 1:1 chats, masterminds and more by building standup streaks.
💲 100k+ Startup Discounts • Get access to $100k+ in startup discounts on AWS, Twilio, Webflow, ClickUp and more.
