This is How Priceonomics Gets 1 Million Visitors to its Blog Per Month

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Rohin Dhar, CEO of Priceonomics, teaches how to create content based on your data and finding distribution channels to make it spread.

What is Priceonomics
We make data-driven
content that spreads
Free content promotes $ information

What are you goals?
• Press hits
• Traffic
• SEO
• Become an “industry expert”
• Customer leads
Make, Distribute & Measure

Interesting
Information
Information that
helps your
company
Why is every company blog
terrible?

Information is currency
Helps a
reporter
Helps you
out
Doesn’t help you
out
Creates work
for the
reporter
Traditional
PR
Information
Marketing
PR crisis
Investigative
report

Information
Data
Industry
Stories

Data: 40 hours
100% worth it in terms of press mentions, traffic, leads

Industry: What do you know that is
valuable to others?

Everything fits a story

Chasing “The Bump”
• Nothing happens at all till a critical mass of
people see it
• The Bump happens
• Everything good that can possibly happen
from that content, will happen after that

Spreading Information: Journalists
• 50 journalists who’d be interested in your content
• Craft your pitch to them in a short email
• Then start writing your article
• Then send them all an short, individualized
message
• It just takes one

Spreading Information: Supernodes
• Reddit, HN, Digg, Metafilter, Product Hunt,
NextDraft, MediaREDEF
• Your own audience (email lists, twitter, fb)
Key point: anticipate where your content
will be popular before you start writing it.

Social Networks
• Nothing happens on Social Networks until you
already have The Bump
• Social networks = Facebook for traffic, Twitter for
Journalists
• Before you write: Why will someone share this?
What will they say about it?
Your content is on equal footing

Process
• Start with good ideas
• Hiring: pay people to write for you first
• Anything that can be misinterpreted, will be
misinterpret. Edit carefully. Any mistakes will
be found.
• Measurement matters

Implementation Plan
• Make one good thing, don’t write everyday
• Success is addictive – Measure everything
and celebrate the wins
• Have a plan for distribution
• Make good things and have people in place
that can succeed

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With more memory available, system performance of three Dell devices increased, which can translate to a better user experience Conclusion When your system has plenty of RAM to meet your needs, you can efficiently access the applications and data you need to finish projects and to-do lists without sacrificing time and focus. Our test results show that with more memory available, three Dell PCs delivered better performance and took less time to complete the Procyon Office Productivity benchmark. These advantages translate to users being able to complete workflows more quickly and multitask more easily. Whether you need the mobility of the Latitude 5440, the creative capabilities of the Precision 3470, or the high performance of the OptiPlex Tower Plus 7010, configuring your system with more RAM can help keep processes running smoothly, enabling you to do more without compromising performance.

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Tata AIG General Insurance Company - Insurer Innovation Award 2024

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Scaling API-first – The story of a global engineering organization Ian Reasor, Senior Computer Scientist - Adobe Radu Cotescu, Senior Computer Scientist - Adobe Apidays New York 2024: The API Economy in the AI Era (April 30 & May 1, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/

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Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe

Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe

Effective data discovery is crucial for maintaining compliance and mitigating risks in today's rapidly evolving privacy landscape. However, traditional manual approaches often struggle to keep pace with the growing volume and complexity of data. Join us for an insightful webinar where industry leaders from TrustArc and Privya will share their expertise on leveraging AI-powered solutions to revolutionize data discovery. You'll learn how to: - Effortlessly maintain a comprehensive, up-to-date data inventory - Harness code scanning insights to gain complete visibility into data flows leveraging the advantages of code scanning over DB scanning - Simplify compliance by leveraging Privya's integration with TrustArc - Implement proven strategies to mitigate third-party risks Our panel of experts will discuss real-world case studies and share practical strategies for overcoming common data discovery challenges. They'll also explore the latest trends and innovations in AI-driven data management, and how these technologies can help organizations stay ahead of the curve in an ever-changing privacy landscape.

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[2024]Digital Global Overview Report 2024 Meltwater.pdf

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The presentation explores the development and application of artificial intelligence (AI) from its inception to its current status in the modern world. The term "artificial intelligence" was first coined by John McCarthy in 1956 to describe efforts to develop computer programs capable of performing tasks that typically require human intelligence. This concept was first introduced at a conference held at Dartmouth College, where programs demonstrated capabilities such as playing chess, proving theorems, and interpreting texts. In the early stages, Alan Turing contributed to the field by defining intelligence as the ability of a being to respond to certain questions intelligently, proposing what is now known as the Turing Test to evaluate the presence of intelligent behavior in machines. As the decades progressed, AI evolved significantly. The 1980s focused on machine learning, teaching computers to learn from data, leading to the development of models that could improve their performance based on their experiences. The 1990s and 2000s saw further advances in algorithms and computational power, which allowed for more sophisticated data analysis techniques, including data mining. By the 2010s, the proliferation of big data and the refinement of deep learning techniques enabled AI to become mainstream. Notable milestones included the success of Google's AlphaGo and advancements in autonomous vehicles by companies like Tesla and Waymo. A major theme of the presentation is the application of generative AI, which has been used for tasks such as natural language text generation, translation, and question answering. Generative AI uses large datasets to train models that can then produce new, coherent pieces of text or other media. The presentation also discusses the ethical implications and the need for regulation in AI, highlighting issues such as privacy, bias, and the potential for misuse. These concerns have prompted calls for comprehensive regulations to ensure the safe and equitable use of AI technologies. Artificial intelligence has also played a significant role in healthcare, particularly highlighted during the COVID-19 pandemic, where it was used in drug discovery, vaccine development, and analyzing the spread of the virus. The capabilities of AI in healthcare are vast, ranging from medical diagnostics to personalized medicine, demonstrating the technology's potential to revolutionize fields beyond just technical or consumer applications. In conclusion, AI continues to be a rapidly evolving field with significant implications for various aspects of society. The development from theoretical concepts to real-world applications illustrates both the potential benefits and the challenges that come with integrating advanced technologies into everyday life. The ongoing discussion about AI ethics and regulation underscores the importance of managing these technologies responsibly to maximize their their benefits while minimizing potential harms.

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This is How Priceonomics Gets 1 Million Visitors to its Blog Per Month

1.

2. What is Priceonomics We make data-driven content that spreads Free content promotes $ information

3. What are you goals? • Press hits • Traffic • SEO • Become an “industry expert” • Customer leads Make, Distribute & Measure

4. Interesting Information Information that helps your company Why is every company blog terrible?

5. Information is currency Helps a reporter Helps you out Doesn’t help you out Creates work for the reporter Traditional PR Information Marketing PR crisis Investigative report

6. Information Data Industry Stories

7. Data: 40 hours 100% worth it in terms of press mentions, traffic, leads

8.

9. Industry: What do you know that is valuable to others?

10. Everything fits a story

11. Chasing “The Bump” • Nothing happens at all till a critical mass of people see it • The Bump happens • Everything good that can possibly happen from that content, will happen after that

12. Spreading Information: Journalists • 50 journalists who’d be interested in your content • Craft your pitch to them in a short email • Then start writing your article • Then send them all an short, individualized message • It just takes one

13. Spreading Information: Supernodes • Reddit, HN, Digg, Metafilter, Product Hunt, NextDraft, MediaREDEF • Your own audience (email lists, twitter, fb) Key point: anticipate where your content will be popular before you start writing it.

14. Social Networks • Nothing happens on Social Networks until you already have The Bump • Social networks = Facebook for traffic, Twitter for Journalists • Before you write: Why will someone share this? What will they say about it? Your content is on equal footing

15. Process • Start with good ideas • Hiring: pay people to write for you first • Anything that can be misinterpreted, will be misinterpret. Edit carefully. Any mistakes will be found. • Measurement matters

16.

17.

18. Implementation Plan • Make one good thing, don’t write everyday • Success is addictive – Measure everything and celebrate the wins • Have a plan for distribution • Make good things and have people in place that can succeed

Editor's Notes

How publishers normally make money: ads or subscriptions. Inventory of ads are approaching infinity. No one wants a subscription. We sell software services and information instead. We want to change how content is funded.