Marketing Artificial Intelligence Quotes

“AI-powered technology enables advertisers to reach more of the right people in the right moments for much less than it would have cost decades ago to buy a billboard or create a television commercial. But in practice, while the tools to target and distribute ads are decidedly futuristic, advertisers have been unable to keep up. Creating, targeting, and optimizing modern ads effectively is simply too complex a task for human advertisers to do well.”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“10. Present the final report and implementation plan”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“Develop recommendations”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“Phase 2: Planning 7. Analyze options and build a solutions matrix How can we define the path forward?”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“6. Validate issues and drivers Does discovery research validate the initial issues and drivers? Has anything been learned that alters the issue tree and key drivers? If yes, go back to steps two and three and make the necessary changes.”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“What are the internal capabilities related to data and AI? •​What were the KPIs and goals for the last twelve months? •​What are the current processes for solving the problem? •​How is performance being monitored and reported? •​How can we benchmark goals moving forward? •​What are industry benchmarks and best practices? •​What opportunities exist to create a competitive advantage? •​What technologies are being used? •​Review current tools and processes to address the business challenge •​Document the existing technology stack, including costs, capabilities, and utilization”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“Phase 1: Discovery 1. Define the problem statement What is the challenge that will be solved? The problem statement is defined at this step and becomes the foundation of the project. Here is a sample problem statement: The company has more than one hundred thousand email addresses and has sent more than one million emails in the last twelve months, but open rates remain low at 8 percent, and sales attributed to email have remained flat since 2018. Based on current averages, a 2 percentage-point lift in email open rates could produce a $50,000 increase in sales over the next twelve months. It’s important to note that a strong and valid problem statement should include the value of solving the problem. This helps ensure that the project is worth the investment of resources and keeps everyone focused on the goal. 2. Build and prioritize the issues list What are the primary issues causing the problem? The issues are categorized into three to five primary groups and built into an issues tree. Sample issues could be: •​Low open rates •​Low click rates •​Low sales conversion rates 3. Identify and prioritize the key drivers. What factors are driving the issues and problem? Sample key drivers could include: •​List fatigue •​Email creatives •​Highly manual, human-driven processes •​Underutilized or missing marketing technology solutions •​Lack of list segmentation •​Lack of reporting and performance management •​Lack of personalization 4. Develop an initial hypothesis What is the preliminary road map to solving the problem? Here is a sample initial hypothesis: AI-powered technologies can be integrated to intelligently automate priority use cases that will drive email efficiency and performance. 5. Conduct discovery research What information can we gain about the problem, and potential solutions, from primary and secondary research? •​How are talent, technology, and strategy gaps impacting performance? •​What can be learned from interviews with stakeholders and secondary research related to the problem? Ask questions such as the following: •​What is the current understanding of AI within the organization? •​Does the executive team understand and support the goal of AI pilot projects?”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“Keep in mind that a little bit of AI can go a long way to reduce costs and drive revenue when you have the right data and the right use case.”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“The top ten individual use cases by score across all 5Ps were as follows: 1.​Recommend highly targeted content to users in real time (3.96) 2.​Adapt audience targeting based on behavior and look-alike analysis (3.92) 3.​Measure ROI by channel, campaign, and overall (3.91) 4.​Discover insights into top-performing content and campaigns (3.86) 5.​Create data-driven content (3.82) 6.​Predict winning creatives (e.g., digital ads, landing pages, calls to action) before launch without A/B testing (3.81) 7.​Forecast campaign results based on predictive analysis (3.80) 8.​Deliver individualized content experiences across channels (3.80) 9.​Choose keywords and topic clusters for content optimization (3.78) 10.​Optimize website content for search engines (3.77)”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“Forecasting: Predicting business outcomes •​Pattern Recognition: Identifying patterns in data •​Personalization: Personalizing experiences •​Recommendation: Making recommendations to achieve desired outcomes”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“Prediction is the ability of machines to predict future outcomes based on historical data. With machine learning, predictions continually evolve and improve based on new data. The better the data that goes in (the inputs), the better the predictions that come out (the outputs).”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“it only takes about 500 images or 10 seconds of video to create a realistic deepfake.”31 That means all those social media photos and YouTube videos your company shares could be used against your brand.”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“When you talk to Alexa, the machine uses NLP to understand and process what you are saying to it. Amazon also uses voice profiles so you can train Alexa to know who is speaking (i.e., speaker recognition). And when the machine talks back to you, it’s using NLG.”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“Natural Language Processing (NLP): Processing human language so the machine understands what is being written or said •​Natural Language Generation (NLG): Generating written or spoken language •​Sentiment Analysis: Understanding the meaning of words, specifically whether the words are positive, negative, or neutral •​Speaker Identification: Recognizing who is speaking”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“Amazon Comprehend is a natural language processing (NLP) solution that uses machine learning to find and extract insights and relationships from documents. •​Amazon Forecast combines your historical data with other variables, such as weather, to forecast outcomes. •​Amazon Kendra is an intelligent search service powered by machine learning. •​Amazon Lex is a solution for building conversational interfaces that can understand user intent and enable humanlike interactions. •​Amazon Lookout for Metrics detects and diagnoses anomalies in business and marketing data, such as unexpected drops in sales or unusual spikes in customer churn rates. •​Amazon Personalize powers personalized recommendations using the same machine-learning technology as Amazon.com. •​Amazon Polly converts text into natural-sounding speech, enabling you to create applications that talk. •​Amazon Rekognition makes it possible to identify objects, people, text, scenes, and activities in images and videos. •​Amazon Textract automatically reads and processes scanned documents to extract text, handwriting, tables, and data. •​Amazon Transcribe converts speech to text. •​Amazon Translate uses deep-learning models to deliver accurate, natural-sounding translation.”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“•​Artificial Intelligence: The science of making machines smart. •​Marketing AI: The science of making marketing smart. •​Algorithm: Set of rules that tell a machine what to do. •​Traditional Automation: Automation powered by sets of instructions (aka algorithms) coded by humans that tell machines what to do. •​Intelligent Automation: Automation powered by AI that has the potential to define its own algorithms, determine new paths, and unlock unlimited potential. •​Machine Learning: The primary subset of AI in which the machine uses data to continually learn and make more increasingly accurate predictions. •​Deep Learning: An advanced type of machine learning that mimics the functioning of the human brain, giving machines humanlike abilities to see, hear, write, speak, understand, and move.”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“AI dominance may not be obvious in a product or service. It’s everything that is done to optimize the things you don’t see, from pricing, mfg, customer service, etc. These lead to better cash flows. It’s a new paradigm in organizing companies but it’s INCREDIBLY HARD to do right.5 The “AI Squad”. The companies that have harnessed AI the best are the companies dominating. To paraphrase a great movie line, “They keep getting smarter while everyone else stays the same.”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“To a machine, something is either a 0 or 1. Something either is, or it is not. The machine is not actually intelligent. It is artificially representing intelligence by performing mathematical calculations at superhuman levels.”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“For example, when you teach a toddler what a dog is, that child learns and can recognize dogs with ease for the rest of his or her life. For a machine to learn what a dog is, you have to train it using millions of images of dogs. After enough training, it can identify dogs with reasonable accuracy, but it still doesn’t actually know what a dog is. The machine uses what are called neural nets to analyze an image through different layers (such as a layer for size, a layer for color, a layer for shape, a layer for fur) and predict that what it is “seeing” is what it was trained to identify as a dog.”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“Deep learning is a subset of machine learning. A simplified explanation is that deep learning takes different approaches to emulating how the human brain learns and works in order to give machines the ability to see, hear, speak, write, move, and understand.”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“Humans are unable to conceive of the optimal set of instructions to guide a machine to personalize thousands of unique experiences. This is where AI excels. It takes data-driven, repetitive tasks, and makes them look easy. But AI doesn’t stop at setting up the initial rules to maximize performance. It uses machine learning to constantly evolve. In other words, it learns, it gets smarter, and it creates its own algorithms.”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“Machine learning is literally a system that learns. It takes in structured (e.g., names, dates, addresses, numbers) or unstructured (e.g., text, images, videos, voice) data, discovers insights, and finds patterns that marketers would often miss (or never think to consider), and then makes predictions, recommendations, and, in some cases, decisions.”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“Basically, AI is the umbrella term for the algorithms, technologies, and techniques that make machines smart and give marketers superhuman capabilities.”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“the science of making machines smart.”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“AI is forecasted to have trillions of dollars of impact on businesses and the economy, yet the majority of marketers struggle to understand what it is and how to apply it to their marketing.”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“Automate This: How Algorithms Took Over Our Markets, Our Jobs, and Our World by Christopher Steiner.”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“There are more than ten million marketers worldwide according to a simple LinkedIn Sales Navigator job function search.”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“AI enables marketers to: •​Accelerate revenue growth •​Create personalized consumer experiences at scale •​Drive costs down •​Generate greater return on investment (ROI) •​Get more actionable insights from marketing data •​Predict consumer needs and behaviors with greater accuracy •​Reduce time spent on repetitive, data-driven tasks •​Shorten the sales cycle •​Unlock greater value from marketing technologies”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“AI is not going to replace you. Rather, it will replace specific tasks and augment what you are capable of doing.”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business

“Next-gen marketers know that in order to deliver the personalization and experiences modern consumers expect, marketing must become smarter. It must become marketer + machine.”
― Paul Roetzer, Marketing Artificial Intelligence: Ai, Marketing, and the Future of Business