3 books on AI for Marketing [PDF]
November 10, 2025 | 30 |
These books provide essential knowledge about AI applications in the marketing, like data analytics, customer segmentation and personalized marketing strategies.
1. AI in Marketing: How Algorithms Are Shaping Advertising Strategies
2025 by Ahmed Musa
A good book on using AI in marketing, but judging by the platforms offered, it is not 2025-fresh. I was interested in the chapter on predictive analytics, which systematized my knowledge of classical machine learning algorithms (which existed before neural networks, but are still effectively used). Linear regression - determining the predicted value of a parameter (for example, the sales amount) based on previous values via linear interpolation. Logistic regression - predicting a binary parameter (yes / no) by counting parameter*weight sum (like a single neuron). Decision tree - determines the category of an object (for example, a client) by descending it along a (pre-trained) tree with conditions. Random forest - a set of pre-trained trees for classification with a final voting. Support Vector Machines - divides objects into 2 categories by finding the nearest neighbors. K-Means Clustering - divides objects into a given number of K clusters by cyclically redefining cluster centers and redistributing objects. Hierarchical Clustering - does not require pre-setting the number of clusters and creates a tree-like structure of clusters, first creating a tree, then combining nearby objects into clusters.
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2. AI-Powered Marketing: The Future of Digital Advertising
2023 by Jim Stephens
This book is mainly about digital marketing, more specifically SEO marketing. The author was right to claim that AI would be a game changer in this field, but he painted a happy future where Google uses AI to rank websites better (rather than replace them with its AI answers). In particular, the book describes RankBrain algorithm, which helps Google deal with unusual queries that it has not seen before and works better than just associating search words with content in articles. RankBrain turns words in search queries into vectors and then tries to match the query with senses it knows. Thus, it understands what the user actually means and what they are looking for and returns results based on that. RankBrain also understands the relationships between words and how they work together. Previously, conjunctions like “the” or “and” were ignored by Google. Now Google understands how they change meaning and affect user intent. Like all machine learning algorithms, RankBrain tries to improve and adapt to user queries over time. It can see which links are clicked most often and understand when it’s working well and when it’s not. This way, it can quickly improve search results for specific keywords, which helps to weed out low-quality or spam content.
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3. AI-Powered Digital Marketing: Unleashing the power of AI for marketing success
2023 by Kabindra Kundu
This book, like Captain Obvious, talks about the basic tasks and technologies of digital marketing with some AI injections. In short, these injections are the following. AI helps to generate content, but it must be checked for accuracy, coherence and relevance and ALWAYS adjusted in accordance to your brand and style. You can use AI to analyze content for keywords, readability. Also, one chapter is dedicated to the creation of graphic content using Canva's AI tools. Perhaps the greatest value of AI is for personalization and customization of content in accordance with individual user preferences. AI algorithms can identify and fix technical problems, improve site performance and increase user experience. The book has an interesting example of evaluating the effectiveness of advertising campaign using ML-model written in Python and implemented in Jupyter Notebook. This example uses a simple linear regression to optimize advertising costs basing on historical data. Finally, determining the return on investment (ROI) of marketing campaigns can be also accomplished using an AI-powered attribution model - this solution is also given in the book.
Download PDF
How to download PDF:
1. Install Gooreader
2. Enter Book ID to the search box and press Enter
3. Click "Download Book" icon and select PDF*
* - note that for yellow books only preview pages are downloaded
1. AI in Marketing: How Algorithms Are Shaping Advertising Strategies
2025 by Ahmed Musa
A good book on using AI in marketing, but judging by the platforms offered, it is not 2025-fresh. I was interested in the chapter on predictive analytics, which systematized my knowledge of classical machine learning algorithms (which existed before neural networks, but are still effectively used). Linear regression - determining the predicted value of a parameter (for example, the sales amount) based on previous values via linear interpolation. Logistic regression - predicting a binary parameter (yes / no) by counting parameter*weight sum (like a single neuron). Decision tree - determines the category of an object (for example, a client) by descending it along a (pre-trained) tree with conditions. Random forest - a set of pre-trained trees for classification with a final voting. Support Vector Machines - divides objects into 2 categories by finding the nearest neighbors. K-Means Clustering - divides objects into a given number of K clusters by cyclically redefining cluster centers and redistributing objects. Hierarchical Clustering - does not require pre-setting the number of clusters and creates a tree-like structure of clusters, first creating a tree, then combining nearby objects into clusters.
Download PDF
2. AI-Powered Marketing: The Future of Digital Advertising
2023 by Jim Stephens
This book is mainly about digital marketing, more specifically SEO marketing. The author was right to claim that AI would be a game changer in this field, but he painted a happy future where Google uses AI to rank websites better (rather than replace them with its AI answers). In particular, the book describes RankBrain algorithm, which helps Google deal with unusual queries that it has not seen before and works better than just associating search words with content in articles. RankBrain turns words in search queries into vectors and then tries to match the query with senses it knows. Thus, it understands what the user actually means and what they are looking for and returns results based on that. RankBrain also understands the relationships between words and how they work together. Previously, conjunctions like “the” or “and” were ignored by Google. Now Google understands how they change meaning and affect user intent. Like all machine learning algorithms, RankBrain tries to improve and adapt to user queries over time. It can see which links are clicked most often and understand when it’s working well and when it’s not. This way, it can quickly improve search results for specific keywords, which helps to weed out low-quality or spam content.
Download PDF
3. AI-Powered Digital Marketing: Unleashing the power of AI for marketing success
2023 by Kabindra Kundu
This book, like Captain Obvious, talks about the basic tasks and technologies of digital marketing with some AI injections. In short, these injections are the following. AI helps to generate content, but it must be checked for accuracy, coherence and relevance and ALWAYS adjusted in accordance to your brand and style. You can use AI to analyze content for keywords, readability. Also, one chapter is dedicated to the creation of graphic content using Canva's AI tools. Perhaps the greatest value of AI is for personalization and customization of content in accordance with individual user preferences. AI algorithms can identify and fix technical problems, improve site performance and increase user experience. The book has an interesting example of evaluating the effectiveness of advertising campaign using ML-model written in Python and implemented in Jupyter Notebook. This example uses a simple linear regression to optimize advertising costs basing on historical data. Finally, determining the return on investment (ROI) of marketing campaigns can be also accomplished using an AI-powered attribution model - this solution is also given in the book.
Download PDF
How to download PDF:
1. Install Gooreader
2. Enter Book ID to the search box and press Enter
3. Click "Download Book" icon and select PDF*
* - note that for yellow books only preview pages are downloaded
