Data as a Service: Moats, Privacy, Crowdsourcing

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🔍 Problem

You need to make better decisions

💡 Solution

Data as a Service (DaaS) bridges the gap between perception and reality.

🏁 Players

DaaS Companies

DaaS Marketplaces

🔮 Predictions

  • Powerful services will move downmarket. Acxiom now competes with self-serve models like Clearbit. Clearview faces consumer-side alternatives like PimEyes
  • High-fidelity shadow profiles will emerge. Lead enrichment services build profiles of prospective customers. Facial recognition takes this a step further.
  • Real-time shadow profiles will emerge. Social media firehoses increase the recency of what’s available.

☁️ Opportunities

🔑 Key Lessons

  • Data helps you bridge gaps between perception and reality. The lower your spread, the better your decisions. 
  • Data is a means to an end. Insights are closer to the “job to be done.”
  • The more data is shared, the less valuable it becomes:
    • Shared lead lists have low close rates
    • Shared flight deals are sold out
    • Shared credit card transactions are priced into stocks
    • Shared travel destinations are busy and expensive 
    • Shared marketplace listings are expensive or unavailable

😠 Haters

“‘Data are’ not ‘Data is'”
That sounds weird to say. And write.

“All data doesn’t become less valuable the more it’s shared.”
In cooperative environments, like public health, sure. In competitive environments, the model holds.

“DaaS companies don’t have a moat.”
First-party data sources have an obvious moat. Third-party DaaS competes on distribution, design and sometimes infrastructure

“The problem is bigger than bridging gaps between perception and reality.
Some DaaS companies give you data that you can pull yourself, faster.

“DaaS isn’t always about making better decisions.”
Cleaning The Glass customers may pay for the joy of knowing. This is an exception.

“This is scary. What about data privacy?”
When’s the last time you read terms and conditions? We’re trading privacy for convenience.

“Some companies will want data not insights.”
Sure. Commoditized answers don’t lead to competitive edges. 

“Data privacy and ownership will prevail.”
When it becomes convenient. Plausible and DuckDuckGo have users. So does the DVORAK keyboard. Whether these cross the chasm isn’t a matter of right or wrong. But human nature.

🔗 Links

  1. Meet Clearview AI • Clearview scrapes billions of images to find “anyone.”
  2. Crowdsourcing • Tactics to crowdsource and collect first-party data. 
  3. Reducing Bias in AI-Based Financial Services • A look at whether machine learning will perpetuate existing bias.

Thanks to Stewart Townsend (Channel as a Service), Natwar Maheshwari (Mailchimp), Kristen Carney (Cubit Planning), Alec Ellin (Laylo), Sam Schrup (Textiful), Ed Freyfogle (OpenCage), Paul Martin (Integrity Music), Jeremy Abraham (Spiffy), Neeraj Hirani (OnMobile Global Limited), Uwe Dreissigacker (InvoiceBerry), Michelle Penny (Grounded Vertigo), Wit Sumathavanit (Builders’ Sun), Fernando Nikolic (Xeneta), Stuart Sim (FinLister), Harish Garg (Explore Hacker News) and Jasper Sky (Hypetrace). We had a great time jamming on this report. 


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What you’ll get:

  • 54 DaaS Companies (440% More)
  • 12 DaaS Marketplaces (140% More)
  • 19 No-Code DaaS Tools (📈 Trends Pro Exclusive)
  • 6 Predictions (100% More)
  • 10 Opportunities (233% More)
  • 5 Key Lessons (66% More)
  • 10 Links (233% More)

With Trends Pro you’ll learn:

  • (📈 Pro) Who’s using no-code tools to build DaaS products?
  • (📈 Pro) How to use DaaS as a growth tool?
  • (📈 Pro) Which DaaS tools help you find and value alternative assets?
  • (📈 Pro) How to build a micro-monopoly with commoditized data?
  • (📈 Pro) Who’s using exhaust data to acquire customers?
  • (📈 Pro) What’s the Red Queen Effect? And how does it drive alternative data?
  • (📈 Pro) What do DaaS customers really want?
  • (📈 Pro) What’s SaaS-enabled DaaS?
  • (📈 Pro) Which app turns your phone into a passive data source?
  • (📈 Pro) How to crowdsource first-party data?
  • and a lot more…