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Paul Roetzer

Paul Roetzer (@paulroetzer) is founder and CEO of PR 20/20, author of The Marketing Performance Blueprint and The Marketing Agency Blueprint, and creator of The Marketing Artificial Intelligence Institute and Marketing Score. Full bio.
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MAICON includes five interactive workshops and 37 general and breakout sessions—all developed to help marketers understand, pilot and successfully scale artificial intelligence.

Presenters will explore the next frontier in digital marketing transformation, covering topics such as: advertising, analytics, content marketing, email marketing, ethics, robotics, sales, strategy, voice and more. 

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I’ve attended and presented at hundreds of conferences in my nearly (gulp) 20 years in the industry, but, this is my first time on the event organizer side as we build the 
Marketing Artificial Intelligence Conference (MAICON).

And, like every event I’ve been to, we see the diversity and quality of the speakers as the fundamental building block of a great attendee experience.

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Editor's note: This post was originally published in 2015 and has been updated to be more current and comprehensive.

"High performers differentiate by doing, not planning. Do your homework, put strategies in place, and then start testing and revising."
— The Marketing Performance Blueprint

Consider this scenario . . .

A B2B SaaS company with $10M in funding and aggressive growth goals is struggling to meet lead generation targets. The CMO fears they’re going to fall short of Q4 goals.

The marketing team is blogging 2x per week, and producing a high-quality ebook with an accompanying webinar each month. But, not enough people are organically finding the content.

What do they do?

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Gartner and McKinsey Global Institute forecast trillions of dollars in annual impact from artificial intelligence, yet most marketers still struggle to understand what AI is and how to pilot it in their organizations.

A recent research project from MIT Sloan Management Review and The Boston Consulting Group (BCG) analyzed AI adoption based on a global survey of 3,076 business executives. The report—Artificial Intelligence in Business Gets Real: Pioneering Companies Aim for AI Scale—broke responding companies into four groups:

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This post originally appeared on the Marketing Artificial Intelligence Institute's blog. The Marketing AI Institute was created and is powered by PR 20/20. 

How do you get started with, and scale, artificial intelligence in your marketing? There’s a conference for that, and you’re invited.

Registration for the inaugural Marketing Artificial Intelligence Conference (MAICON) is now open. The event will be held in Cleveland, Ohio at the Huntington Convention Center, July 16 - 18, 2019.  

MAICON is designed to help marketing leaders truly understand AI, educate their teams, garner executive support, pilot priority AI uses cases, and develop a near-term strategy for successfully scaling AI.

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This post originally appeared on the Marketing Artificial Intelligence Institute's blog. The Marketing AI Institute was created and is powered by PR 20/20. 

Artificial intelligence has reached peak hype stage, but is it possible that its potential to transform marketing, and your career, is even greater than advertised?

Gartner forecasts global business value derived from AI is projected to reach $1.9 trillion in 2019, ramping up to $3.9 trillion in 2022 through three primary sources of customer experience, cost reduction and new revenue.

Meanwhile, McKinsey Global Institute projects up to a $6 trillion impact of AI and other analytics on marketing and sales, including the areas of pricing and promotion ($1.9T), customer service management ($1.0T), next product to buy/individualized offering ($1.0T), customer acquisition/lead generation ($0.7T), marketing budget allocation ($0.6T), churn reduction ($0.38T) and channel management ($0.32T).

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Editor's note: This post was originally published in 2014 and has been updated to be more current and comprehensive.

The proliferation of marketing channels, apps, mobile devices, social networks and content has given consumers more choices and greater control, while increasing complexity for marketers.

We want to help simplify and optimize the marketing planning process for your business.

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You use artificial intelligence dozens, if not hundreds, of times everyday. From choosing recommended shows on Netflix, to navigating trips in Google Maps, asking questions of Siri and Alexa, ordering products on Amazon, reading your Facebook Newsfeed, and unlocking the iPhone facial recognition.

In short, your life is already machine assisted, and your marketing will be too.

AI makes things more convenient, more simple, and more personalized. And, the real magic of AI is that consumers often have no idea it’s there. Things just work, better.

Marketers who take the initiative to find AI-powered solutions will be able to intelligently automate time-intensive, data-driven activities, and execute personalized campaigns of unprecedented complexity that drive meaningful business results.

But, how do you get started?

How do you figure out which use cases to prioritize? And, how do you navigate the hundreds of vendors touting AI and machine learning capabilities?

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This post was originally published in November 2016 and has been updated for comprehensiveness. If you’re making the shift to value-based pricing, join us for the live and on-demand series Point Pricing for Agencies.

I spent the first six years of my marketing agency career chasing hourly quotas instead of results. Our goal was to bill a minimum of five hours per day. 

Yes, we cared if the client was happy and successful, but the fundamental economic driving force behind the firm's existence, and my career potential, was the billable hour.

I discovered early on that the billable-hour model was a flawed, archaic, agency-centric system that wrongly tied agency performance to outputs, not outcomes. 

In 2004, four years into my career, I became highly motivated to build a more efficient and profitable solution that shifted the focus to client needs and goals. 

The idea was centered on making services tangible with clearly defined costs, features and benefits, almost like buying a product off a retail shelf or signing up for a software service.

My theory was that if clients understood exactly what they were getting, and agreed ahead of time what it was worth, then we could remove the mystery from the equation and focus on delivering value and results. 

The problem was that the billable-hour model was the only one I had ever known. How would I build an entirely new financial model and productize a service business?

>> If you’re getting started with value-based pricing, check out the 12 Questions to Guide Your Marketing Agency Pricing Model Transformation.<<

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This post originally appeared on the Marketing Artificial Intelligence Institute's blog. The Marketing AI Institute was created and is powered by PR 20/20. 

“Can we automate content creation using artificial intelligence? More specifically, can we use machines to write blog posts at scale?”

These are the questions we sought to answer in spring 2015 when I launched an internal initiative named Project Copyscale at my content marketing agency, PR 20/20.

I’d had a growing fascination with artificial intelligence since IBM Watson won on Jeopardy! in 2011. I didn’t understand the underlying technology at the time, but when I read Automate This by Christopher Steiner in late 2012 I became convinced that artificial intelligence would transform marketing as we know it. It was only a matter of time.

“Some algorithms’ roots trace to the field of artificial intelligence. They may not be intelligent and self-aware like Hal 9000 (Heuristically programmed ALgorithmic computer), the machine from the movie 2001: A Space Odyssey (1968), but algorithms can evolve. They observe, experiment, and learn—all independently of their human creators. Using advanced computer science techniques such as machine learning and neural networking, algorithms can even create new and improved algorithms based on observed results.” — Christopher Steiner, Automated This (Penguin Group, 2012)

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