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AI Marketing: 10 Ways to Incorporate Advanced Tech in Your 2021 Day-to-Day

Learn why and how to use artificial intelligence to your advantage

Since early 2000, academics study the relationship between web-content, response to online stimuli, and user buying behavior. It was then that content personalization was first introduced.

Academics at the time recommended industry adoption of software, purposed to monitor online behavior and providing real-time responses, as a source of competitive advantage.

This is what we now call Artificial Intelligence marketing.

AI marketing first started as a system for e-commerce organizations, which wanted to individualize the online shopping experience, mimicking the personal approach of in-store personnel online. Initially, the effect of the highly-targeted personalization and search analytics-enabled long-tail marketing and assist the growth of the niche e-commerce industry.

Today, AI-powered marketing is everywhere.

The research defines it as companies’ effort to cast a wider data collection net to later use for targeted advertisements and personalized product and content recommendations.

So, here are 10 ways you can use AI marketing concepts in your digital marketing strategy in 2021.


1. Collect data for Customer Profiling

Imagine collecting data from more than 3.3 billion devices, analytics, and AI tools to create a 360-view of consumer behavior online, including motivations, beliefs, and purchasing patterns. How about being able to use this data to successfully predict future behavior? Well, that is the promise of companies like Drawbridge, recently acquired by Linkedin and re-branded as LinkedIn Marketing Solutions.

This is now referred to as social listening software and is used by both B2B and B2C companies. Even though it in some locations a breach of privacy and data protection regulations, the data trading industry, as highlighted by the Social Dilemma, is hidden, huge, and incredibly profitable. That is even though social network sites explicitly state the use of information, publicly obtained from them is for social, not commercial or business purposes.

The role of AI is to essentially process this big data and categorize the data to assist in building an accurate perception of the consumer, with the intent and hope that the online behavior and identity is close to the offline one.

Companies are being provided with highly targeted, data-driven insight, but this alone is not enough. It requires a bit of creativity applied in interpretation, as well as insight – into how we behave online, and also how our behavior in the past can influence future decisions.

2. Web Ads Personalization

The need to monetize the web-ad performance has hit unsurpassed highs with online advertising at its peak. Besides, as content engagement is linked with brand loyalty, the importance of content marketing is growing as it has shown to be a factor in decision-making in both a B2C and B2B context.

By allowing machine learning algorithms to filter behavioral data, this can not only be used in cases of e-commerce (such as Amazon, Netflix, Spotify, or YouTube) but also to strategically position ads that are relevant to individuals browsing the web (or the so-called ‘adaptive personalization‘).

Optimizing web-ad performance is vital to the cost-optimization in marketing strategy and beneficial for all stakeholders, building better brands, and more enjoyable experiences for web-users.

3. Sales Forecasting

AI-powered sales forecasting software gathers data about past sales. This is elsewhere referred to as predictive analytics. It analyzes various the presence of data entries and how they relate to sales outcomes.

Insights from the data are then applied to the current pipeline, and the software evaluates probabilities of a sale taking place or even advice to sales representatives.

The best AI-powered sales-forecasting software has implemented reinforcement learning, which allows them to go back and reconcile scoring accuracy rates, thus learning from past performance.

4. Trend Capture

Scientists have long correctly speculated that sales alone are a short-term goal, which is effectively achieved using analytical software. This is not often a strategic objective, though.

Web and social media analytics are becoming increasingly more important for measuring consumer response to online marketing stimuli, content optimization, and behavior modeling. By doing so, companies can capture trends as they evolve and capitalize on viral marketing.

5. Opinion mining and Sentiment Analysis

Opinion mining and sentiment analysis aim to extract underlying emotions hidden in the natural language through classification, specifically categorization of an opinion as positive, negative, or neutral.

Opinion mining is superior to data mining, as it also equips companies, who use advanced analytical software to gain behavioral insight from social platforms, as opposed to raw data points.

Ability to identify the digital consumer’s precise personality is the key to the future of marketing, as is the ability to understand, engage and empathize with current societal challenges and actively involve the consumer in the co-creation of the brand’s mission, vision and attributes.

The industry has long recognized that what is missing is the intelligence in recognizing the history of searches, attitudes, motivations, and changes of online personas, which will inform intelligent predictive analysis to better equip marketing decisions. Winer even went as far as claiming that traditional marketing alone fails to understand consumers at such depths.

AI software implementations in marketing campaigns assist consumers to take back the power in altering a digital identity once it has been constructed and allows companies to optimize their understanding of consumer psychology and inter-relationships.

6. Social media chatbots

According to Wikipedia,

Chatbots are computer programs or artificial intelligence, which conduct conversations via auditory or textual methods. They are designed to convincingly simulate how a human would behave as a conversational partner.

Increasingly, chatbots are used in e-commerce customer service applications, call centers, and social media, where they are used to complete simple and repetitive tasks, which are categorized as either time-consuming, tedious, or impractical for a human to perform.

They also offer also the potential of scripting conversations. If the bot is equipped with the functionality to learn from past conversations, it can read them once they have been carried out, extracting key trends, patterns, perform sentiment analysis, and uncover behavioral insights.

People Underestimate These 4 Benefits of Social Media Chatbots

Chatbots show that there is potential to achieve tremendous gains in efficiency, achieved through cutting down on the labor resources an organization must employ to complete a project or the time an individual must devote to routine tasks.

7. Automate the CRM process

CRM software is designed to help sales and customer service professionals track and manage their engagement efforts with customers.

There are four ways to use CRM Automation:

  • data entry automation
  • personalized email sequences
  • automated customer interaction logging
  • customer service automation (e.g. chatbots)

This can save time, help reps engage better with more leads, and potentially land sales faster.

8. Implement SEO Reporting Automation.

As an SEO consultant, this is by far the area I am most excited to see grow in future years. Platforms such as Big Query make big data visualizations effortless, while SEO software like DeepCrawl and SEMrush allows for integrations with both Big Query, Google Sheets, and Google Data Studio, making technical SEO reporting suitable for automation.

This bridges the communication gap between technical SEO analysts and the business and its investors. Not to mention it saves an enormous amount of time for all parties involved.

There are already communities making remarkable leaps in the area of SEO automation, and the big players in the tech SEO scene recognize this as a key trend for 2021.

9. Enable dynamic pricing

As with everything else, personalization in pricing is a trend happening all around us.

A bot can be enabled to monitor the webspace, using a variety of touchpoints, such as cookies data, browsing history, activity data, etc. The aim of this application is to provide you with the best, personalized offer at a specific point in time, which will persuade you into making a sale. Think Uber’s pricing model, but for everything you see online.

10. Implement product recommendation systems

With the rise of internet connectivity and the explosion of the e-commerce industry, came the need for companies to assist consumers to choose a product.

Recommender systems in e-commerce were implemented in the late 90s to assist user-product searches through incorporating past knowledge, related to the user (or other users’) preference and liking.

This helps eliminate the burden users could potentially face as a result of information or choice overload, which typically obstructs decision-making, especially if the presented options are unfiltered.

Behavior and attention monitoring assist the segmentation process of the digital marketplace and as a result – enables consumer profiling.


AI Marketing is more and more prevalent in our society, which shifts the way companies see us as consumers, as well as disrupts the industry dynamics.

As the technology advances, it is seen as a way to improve the relationship marketing process for both parties – by providing a better, more personalized, and connected user experience for customers, and a more data-driven, hands-off approach to process management for companies.


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