How Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning Marketing Technology (MarTech) Tools are Scaling Personalization

We live in exciting and turbulent technological times driven by data. Businesses are increasingly relying on data to make better business decisions. As a result of increasing investments in Artificial Intelligence (AI), Machine Learning (ML), and deep learning, the days of frustrating, inaccurate statistics, trends, and data-sets are coming to an end.

AI, ML, and deep learning have unfortunately become buzzwords, and mean different things to different industries. From a marketers standpoint, it may be hard to take this highly technical knowledge and apply it specifically to your marketing environment.

social media animation GIF by Slanted Studios

Let’s break these topics down from a marketing standpoint:

Artificial Intelligence (AI) – is an overarching field of computer science that focuses on solving cognitive problems linked with human intelligence like problem solving, learning, and pattern recognition. In a broad sense, AI is any innovation allowing machines to solve human problems, similar to the way we would.

Machine Learning (ML) – is a subfield of AI, and its purpose is to enable computers to learn on their own. Machine Learning marketing tech tools are the bread and butter behind business growth, better user experiences, and optimization. Now, ‘martech’ companies are baking ML technology directly into their products, which makes ML more accessible and user friendly for business applications and growth.

Deep learning – is a subfield of ML involving the use of neural networks to improve computer speech recognition, language processing, and vision. Unlike Machine ‘Learning,’ deep learning does not require human supervision to produce its output.

From a marketing standpoint, deep learning will vastly change the landscape and mysterious realm of Search Engine Optimization (SEO). Rank optimization will increasingly be done by machines and search channels will become more diverse. For example, we are already seeing the implications and applications of voice search products and services like Amazon’s Alexa.


Marketers often worry about making the most of their budgets, clicks but no conversions, rank competition, and ineffective social media. Businesses want to do more with less, and they are letting the technology tools do the heavy lifting. Marketing teams are incorporating AI, ML, and deep learning tools into their technology stacks. A marketers technology stack is their secret weapon in efficiently analyzing big data and creating better personalized experiences.

Salesforce, the world’s leading Customer Relationship Management (CRM) platform, gave a 2017 survey to global industry marketing leaders. Over 60% of them expect AI to create better landing pages, website development, campaign analytics, and asset management. For example, a startup called Unbounce, increases website and marketing campaign conversions by quickly creating, launching, and successfully testing landing pages without developers.

Let us take a deep dive into the specific ways that AI-powered digital marketing applications have on future business.

AI is Scaling Personalized User Experiences

The days of one size fits all for user experiences are long gone. Successful companies are customer-centric and will do practically anything to bolster the customer experience. According to the Pareto Principle 80/20 Marketing Rule, which is one of the core principles in marketing, 80% of most sales are generated from 20% of your customers. We have already seen breakthroughs in personalized user experiences on Facebook, Instagram (owned by FB), Snapchat and more. They give consumers curated feeds, because they know user content preferences.  Knowing your target audience and catering to them is an important, yet complex recipe. AI acts as a personal sous chef to help marketers get the recipe right every time. Personalization can improve customer engagement, revenue, and conversion rates.


Chatbots are increasingly being used to immediately begin a personalized conversation with a prospective customer. Instead of having a large customer support center, people are given the comfort and impression of talking to a real person during this personalized user experience as soon as they land on the page. The chatbots can help with a range of given inputs (problems) and outputs (solutions). Chatbots are not perfect and are always improving, but they have already proven useful in saving time and money.

toddoto martech chatbot


Let’s be honest, we’ve all searched for something, or said something about a product or service, and then saw that ad magically appear on our phones or computers. Come to find out, it’s not magic, but successful AI personalized shopping recommendations. When you shop online, you leave behind data breadcrumbs that are full of rich data regarding individual preferences, spending habits, and preferred consumer channels. To put this in perspective, the McKinsey Institute estimates that 35% of Amazon’s customers and 75% of what Netflix consumers watch comes from personalized recommendations.

A/B Testing

A/B, Split, and Bucket Testing (which all mean the same thing) are a hot topic in the current marketing arena. You run two different versions (A & B) of whatever you want to test, whether it’s a minute detail or a complete landing page makeover, A/B testing takes the guessing game out of website optimization. By measuring the impact over time, you can better test user experience and engagement hypotheses.

However, be cautious about cloaking. Cloaking is the act of deceiving the Google bot ‘crawlers’ that scan the content by presenting different content to the crawlers than what is actually presented to users. Cloaking is unethical and can demote your SEO ranking.

In swoops AI-enhanced A/B testing, in which ML is able to learn, explore, and micro-measure the delivery of content and UX optimization. Leave the optimization over time to the machine, so you can focus on core innovations and growth. For example, Sentient ASCEND allows you to simultaneously test multi-page funnels and dozens of individual optimizations as you designate, implement, and track desired KPI’s such as leads, sales, and average order sizes.

Individual marketing technology tools are great, but can easily become cluttered when marketers switch from channel to channel and get lost in the data and analytics. As we continue to witness the fourth industrial revolution powered by data, AI, ML, and deep learning MarTech tools are going to be at the forefront of future customer engagement, conversions, and overall business growth. There will be AI tools for every marketing facet.

The Good and Bad

AI-powered marketing technology is powerful, but you can still lose time and money investing in these emerging products. It is imperative that marketers fully understand which AI MarTech tools they deploy and the results they hope to gain. You don’t want the blind leading the blind. It is also important to always stay on top of data privacy and the negative news that accompanies it. From Equifax to Facebook, even these massive conglomerates are having an awfully hard time keeping their privacy rules and regulations under control.

On May 25th, 2018 the General Data Protection Regulation (GDPR) passed by the European Union (EU) became effective. Once you decipher the alphabet soup, the GDPR requires certain procedures to be met, while giving more rights to data “subjects,” the people who provide the data.

EU citizens are given more power and insight into the data they provide, and it has sent shockwaves to small and large business all over the world; which is why our inboxes in the U.S. are being flooded with privacy protection changes. The EU will enforce the GDPR through a maximum fine of 4% of a company’s annual global revenue. We will continue to see changes in consumer data protection legislation, but the question remains as to whether it can keep up with the rapid, exponential development of technology.

One thing is for certain, AI powered marketing technology tools will continue to be used to scale personalization, optimization, growth, and data context. We will soon see extreme personalization, cross-channel engagement, and less guesswork. If you’re unsure of where to start and feeling a little overwhelmed, check out these 45 AI Marketing Tools to get started with.

Thanks for reading!





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