Data as a Service: Insights as a Service, Competing with AI, Cold Sales Agencies

“We are surrounded by data but starved for insights.” — Jay Baer

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❓ 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

🔮 Predictions

  • AI will help us save time collecting, cleaning and interpreting data. It doesn’t need to sleep, eat or rest.
    • NewtonX uses AI for audience research.
    • Crayon uses AI to separate signal from noise.
    • Gazelle uses AI to forecast fast-growing companies.

☁️ Opportunities

🏔️ 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

😠 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

  1. Who’s Offering Data as a Service? • The tweet behind this report.
  2. What is Data as a Service • Pros, cons and case studies of DaaS integration.
  3. 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:

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  • (📈 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…

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