Machine learning for digital marketing

Il machine learning algorithm offers to experts marketing digital tools that make life easier. And not only. In fact, the processing, research and calculation capabilities of the tools we are going to see offer us numerous cards to play to improve our work. But be careful not to see tools and platforms that use machine learning as substitutes. In digital marketing, in addition to data, interpretations are also needed, which are often not based on purely numerical calculations. A possible working key consists precisely in observing with a human eye the activity you want to promote, the target, the environment, and thus making connections and associations that an AI is not able to make. In this sense, therefore, we can conceive these tools as integrations and, in general, theartificial intelligence as an assistant and not a substitute.

Each section of this article will give you an overview of what tools and platforms are out there. You will see the best 3 for each type. Find out how they apply to work on various aspects of digital marketing campaigns, from SEO to the customization of website, up to predictive analysis.

Let's get to the heart of it then.

Machine learning-based data analytics platforms

Machine learning-based data analytics platforms help you interpret large amounts of data and make informed decisions. These platforms help identify trends, user behaviors and market opportunities. Let's see the 3 most common ones:

1. google analytics 360: uses machine learning to deliver advanced predictive metrics such as probability of purchase and probability of abandonment. These predictive models analyze user behavior to predict future actions, allowing marketers to create specific audiences and optimize advertising campaigns.
2. Adobe Analytics: integrates machine learning technologies to provide real-time analysis of user behavior. It also offers advanced predictive modeling capabilities.
3. IBM Watson Analytics: leverages machine learning to deliver advanced predictive analytics and data visualization capabilities.

Customer service chatbot software

Artificial intelligence-based chatbots serve, in theory, to improve customer service offering immediate and personalized responses to user requests. If used properly, chatbots actually increase operational efficiency, but care must be taken. In fact, they are not always capable of satisfying particular requests. Plus, users don't always write questions that the chatbot interprets properly. So, if you want to integrate chatbots, don't think that they can totally replace customer service. The 3 software we show you are worth trying:

1. Drift: Use AI to understand context, respond dynamically and learn from past interactions. This can allow the bot, except in special cases, to manage complex and personalized conversations, increasing user engagement by 40% compared to button-based chatbots. Integrates features such as GPT suggested answers and automatic language translation to provide a 24/7 service.
2. Intercom: powered by advanced language models like GPT-4, End (name of the Intercom bot) is able to independently resolve up to 50% of customer queries, improving operational efficiency and reducing the support team's workload. The bot can handle natural conversations, understand context, and provide accurate responses based on business support content.
3. ManyChat: specialized in chatbot for social media. Use AI to automate conversations, qualify leads and improve customer service. Allows you to create custom conversation flows and automatically answer common questions.

AI-powered SEO tools

With these tools and platforms you will be able to optimize content and positioning strategies on search engines. These tools analyze keyword trends, user behaviors and offer suggestions to improve your SEO ranking.

1. Ahrefs: Use AI for keyword analysis, keyword clustering, and optimized content generation. Their AI Content Grader evaluates content based on the best-ranked pages for a given keyword and makes suggestions for improvement. Additionally, Ahrefs includes tools for discovery of new keywords and for backlink management, all powered by AI​.
2. SEMrush: offers several AI-based SEO tools. The Copilot, for example, identifies technical issues, discovers keyword opportunities, monitors competitors, and suggests improvements to the overall SEO strategy. Again, the Keyword Strategy Builder automates the creation of SEO content strategies, helping to organize keywords into pillars and sub-pages for an effective site structure.
3. Moz Pro: leverages artificial intelligence to provide accurate data and insights into keyword e SEO on-page. Their tool uses theAI to analyze SERPs and offer suggestions on how to improve the website's visibility and ranking. Moz Pro also includes features backlink analysis, location tracking and site audits.

Content creation tools that integrate machine learning

AI-powered content creation tools optimize the production of text, images and videos. These tools generate content that can be adapted to our needs and are also designed to address a specific audience.

1. Jasper AI: helps you generate articles, social media posts, emails and more. Jasper integrates AI with Surfer SEO to optimize content for search engines. It offers over 50 writing templates, including AIDA and PAS frameworks, and can create content consistent with your brand voice. Furthermore, Jasper is able to generate images and creative content for advertising campaigns.
2. copy.ai: texts for blogs, ads, product descriptions and social media posts. Use advanced language models to produce engaging and persuasive texts. Copy.ai is known for its ability to generate content quickly, making it ideal for everyday marketing needs. It offers a series of templates that help solve specific writing needs.
3. Writesonic: with similar functions to the other two tools just seen, it is particularly appreciated for its ease of use.

When we talk about tools that generate written content, we always recommend careful supervision, a thorough check and possibly the advice of a professional copywriter. If used improperly, in fact, these tools instead of making your work easier make it more difficult, risking ruining rankings on the SERP and your reputation.

Machine learning to personalize websites

AI for website personalization allows you to offer tailored user experiences, increasing engagement and conversions. These tools analyze user behavior and adapt site content in real time.

1. Optimizely: this platform uses machine learning to create personalized experiences in real time, based on customer data and omnichannel behaviors. Allows you to define custom audiences and to dynamically update customer profiles.
2. Dynamic Yield: provides advanced personalization solutions for site content, product recommendations and promotional offers based on user behavior. The platform supports A/B and multivariate testing.
3. Coined: in addition to the customization tools seen above, Monetate offers analysis tools to measure the effectiveness of personalization campaigns and continuously improve marketing strategies.

PPC campaign optimization tools with machine learning

These tools are dedicated to data analysis of marketing campaigns and suggest improvements to maximize ROI. The machine learning here also automates bid management and budget distribution.

1. Google Ads Smart Bidding: in addition to providing the functions just described, this platform offers strategies such as Target CPA (Cost per Action) and Target ROAS (Return on Advertising Spend), which allow you to maximize conversions and their value continuously adapting offers based on performance data. The AI ​​here analyzes and processes billions of signals.
2. WordStream: PPC management platform that uses machine learning to optimize advertising campaigns. The software automatically suggests keywords, ads, audience segments and the best offers to achieve your objectives, improving budget management and campaign effectiveness.
3. Acquisition: automates above all the bids taking into consideration factors such as budget, CPA target and ROAS target. It also features reporting and performance analysis, allowing advertisers to continuously monitor and improve their campaigns.

Marketing automation solutions

These tools simplify and optimize broad-spectrum marketing processes. Speaking of less specific tools, you will therefore find functions that you have already seen in other tools, with the advantage that they are all in one.

1. HubSpot: with this tool you can create content via AI assistants, automate emails, lead scoring and the personalization of campaigns. Hubspot also analyzes the data to offer predictive insights and improve campaign performance. Additionally, tools like ChatSpot.ai make it easy to manage customer interactions via a platform chatbot.
2. Marketo: this one offers instead advanced marketing automation solutions that use machine learning to segment audiences, manage lead scoring and personalize communications. The platform allows you to create automated multi-channel campaigns which improve engagement and increase conversions by analyzing user behavior in real time.
3. Pardot: exploits artificial intelligence above all to improve lead generation and customer engagement. It also offers functionality of automation of B2B marketing, such as email marketing, predictive lead scoring and advanced segmentation. With this you create great funnels.

A/B Testing tools with artificial intelligence

A/B Testing tools with artificial intelligence allow you to test different variations of campaigns and content, analyzing the results to identify the most effective versions. These tools optimize performance quickly and efficiently.

1. VWO (Visual Website Optimizer): facilitates and optimizes A/B tests. Generates text suggestions and variations, allowing you to quickly test different versions of your content. It also offers advanced features like detailed visitor segmentation, heatmap and clickmap integration to analyze user behavior.
2. Optimizely: this platform also allows you to conduct A/B and multivariate tests, offering predictive analysis and automatic suggestions to improve conversions.
3. Google Optimize: with this you can test different variations of content and layout of the website quickly. The platform is integrated with Google Analytics, allowing you to leverage user data to create personalized tests and analyze the effectiveness of variations.

CRM platforms

They improve the management of relationships with customers, automating processes and offering valuable insights.

1. Salesforce Einstein: integrates artificial intelligence into all its CRM applications. Features include predictive analytics, automation of sales activities, personalization of marketing campaigns and customer service management.
2. HubSpot CRM: improves contact management and communication with customers. Includes features like automated email marketing, AI-based lead scoring and predictive analytics. You can also create custom content, automate workflows, and optimize marketing campaigns.
3. Zoho-CRM: offers advanced sales analytics, email automation and customer management. Integrate machine learning especially for lead scoring, sales forecasting and communications personalization.

Predictive analysis tool for digital marketing

These are focused on predicting future customer behaviors. Other tools you've already seen offer similar functions, so these are suitable for those who want more specific tools.

1. H2O.ai: platform of open-source machine learning which offers advanced AutoML (Automated Machine Learning) capabilities, facilitating the creation of predictive models. H2O.ai supports numerous machine learning algorithms such as deep learning, gradient boosting and neural networks, allowing you to analyze large volumes of data and improve the accuracy of forecasts.
2. RapidMiner: platform of data science which integrates artificial intelligence to offer powerful and easy-to-use predictive analytics tools. It supports the entire data science lifecycle, from data preparation to modeling and deployment.
3. IBM SPSS: a software suite for statistical analysis which includes advanced machine learning tools for predictive analytics. Used primarily in academic and business settings, SPSS allows you to build complex predictive models, perform detailed data analysis, and generate reports. Its features include regression, time series analysis and clustering.

Data visualization tools with machine learning

We close with machine learning-based data visualization tools. These allow you to easily interpret large amounts of information, transforming complex data into intuitive and useful visualizations.

1. Board: helps you with features they also offer explanations based on advanced statistical models, very useful for understanding the data well. So it's useful too to study. Plus it provides personalized and contextual insights. It also allows you to create visualizations and dashboards.​
2. PowerBI: this also provides predictive insights, automation, pattern discovery, creation of detailed reports and the ability to ask questions in natural language and get immediate visual answers.
3. QlikSense: with this you can explore data from different perspectives and still get automatic graphical suggestions, visualizations and analyzes based on the available data. It helps you discover hidden insights.