
โWe are surrounded by data but starved for insights.โ โ Jay Baer
โ 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?
๐ Why It Matters
You can gain a competitive edge by fueling your decisions with the right data.
๐ Problem
You need to make better decisions.
๐ก Solution
DaaS helps you focus on your core competency. While outsourcing data collection and processing.
๐ Players
DaaS Companies
- Ahrefs โข Search queries, volume, links, keywords and more
- Abstract API โข Data on phones, emails and more
- Hunter โข Database of verified business and work emails
- Built With โข Analytics, advertising, hosting, CMS and other tools that websites use
- Apollo โข AI-powered database of B2B leads
- Quandl โข Data on private jets, jobs, forex transactions and more
- WordStream โข Ads and keyword grader
Data Tools
- Tally โข Build beautiful surveys
- QuickAPI โข Sell and share data APIs
- Databox โข Build data dashboards
- ScrapingBee โข Scrape the web with rotated proxies
- Obviously AIโs Data Validator โข Check if your data is ready for machine learning
๐ฎ Predictions
- Weโll 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.
- NielsenIQโs 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.
โ๏ธ 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 โjob to be done.โ
- 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 homeโs market value.
- Accessibility scores by Walk Score measure walkability, commute and travel routes.
๐๏ธ Risks
- Artificial Intelligence โข Customers will go straight to insights. Making DaaS companies obsolete.
- Depreciation โข Data becomes less accurate, reliable and useful over time.
- Platform Risk โข Youโre subject to the DaaS providerโs datasets, outages and fees.
๐ 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.
๐ฅ Hot Takes
- Weโll see recognized data quality metrics. Talend Trust Scoreยฎ 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 shoppersโ behavior.
๐ Haters
โAI will make DaaS companies less relevant.โ
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 wonโt reach it unless a breach occurs.
โAI companies use data to train their models. Without permission.โ
When was the last time you read a privacy policy? Non-AI companies use privacy policies to โsimulateโ your consent. Coresignal offers 660,000,000 employee records parsed from LinkedIn, Crunchbase and more. You never know when another โpartnerโ adds you to their dataset.
โSome DaaS companies resell data from companies like Crunchbase. Which kills margins.โ
Protect margins by adding value. Offer unique insights, branded metrics, productized services and more.
โGovernments can make it hard to operate in the DaaS space.โ
Stay away from regulated industries. It is easier to share B2B leads than patient data.
โProfiting from personal data is unethical.โ
Sell anonymized data that doesnโt link to people.
โCompanies like Clearview AI make it easier to spy on people. This can lead to less privacy, more surveillance and abuse of power.โ
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.
๐ Links
- Whoโs Offering Data as a Service? โข The tweet behind this report.
- What is Data as a Service โข Pros, cons and case studies of DaaS integration.
- The Empty Promise of Data Moats โข How to build durable data moats.
๐ Related Reports
- โโโโโChatGPT โข Automate work and save time coding, writing, researching and more
- Curation as a Service โข Find signal in the noise
- Crowdsourcing โข Leverage the time, energy and experience of others to reach your goal
- No-Code โข Build products faster, cheaper and better without writing code
- Agencies โข Help your customers solve problems without hiring and managing large teams
๐ Thanks
Thanks to Kevin Galang, Mishal Siddiqui, Mehmet Gonullu, Alex Doda, Benhur Desta, Reme Ekoh, Soma Mandal, Nirav Multani, Fausto Sรก Teles, Marc Fletcher, Emeric Victor, Stewart Townsend, Alex Espinoza, Thomas Sorheim and Stephanie Hekker. We had a great time jamming on this report.
โ๏ธ Emin researched and wrote this report. Dru researched and edited this report.
๐ What else?
Trends PRO #0116 โ Data as a Service has more insights.
What youโll 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 youโll learn:
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- (๐ Pro) How to monetize data?
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- (๐ Pro) How to boost data accuracy?
- (๐ Pro) What are data cleansing challenges?
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- (๐ Pro) How to build and sell a Data as a Service startup in 6 months?
- (๐ Pro) How to use data to make investment decisions?
- And much moreโฆ
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