AI in Marketing - Gateway to Higher Customer Engagement and Revenue Generation

AI in marketing can have a profound impact on the entire marketing cycle. To understand the details about the topic, read ahead!

From billboards and banners to marketing using keywords, we’ve come a long way. Previously, the marketing was much more outbound in nature. Companies that had the money and resources were able to flourish as they had the budget to expand. On the other hand, small businesses were still limited to their local community catering to a handful of crowds.

With digital marketing and the rapid adoption of the internet, even SMEs had an opportunity to have international clients. However, the market swiftly started to change with customers having more options. 

The key to unlocking better customer offerings was to gather customer data. However, an article by DataAvail states that data is growing faster than Moore’s law. A report cited by them states that data is growing 64% every year. This is true in the case of marketing as well. To comprehend the mountain of data, AI in marketing came into existence.

We have created this article to tell you about artificial intelligence in marketing, and the different facets related to it.

AI in Marketing - Challenges Related to AI Integration in Marketing

Despite the interest of marketers in integrating AI into their operations, there are several impediments that block the way. Below, we have mentioned the most common challenges one can witness while implementing AI-driven marketing.

1. Inadequate Infrastructure

Having the will to implement something and the capacity to do it are two different things. Right now, AI is being used only by the top 28% of companies for marketing. With AI in marketing, the most fierce challenge that marketing companies face today is the lack of adequate infrastructure. In fact, Datasolution.org states in one of their articles that using AI tools for marketing can increase qualified leads by 451%. To give further perspective, here are some of the other challenges:

• Storage of large amounts of data on the premises
• Businesses require clean data for training models
• Requirement of high-speed internet
• Businesses require tonnes of hardware and software resources to enable AI in marketing
• Requirement of trained professionals

To bridge this gap, organizations are required to make heavy investments as well as a lot of resource aggregation. This is especially the case if some organizations are starting to build the infrastructure from the ground up.

Note: Here is a list of the top artificial intelligence development companies, check it out!

2. Lack of Training Data

Artificial intelligence in marketing isn’t possible without marketing data. However, there is a shortage of sufficient marketing data for training AI models. As per ThinkwithGoogle approximately 75% of marketers confessed that a lack of education & training related to data analytics is a huge barrier in aggregating marketing data. Aside from this, there are several other reasons that inhibit the aggregation of marketing data for AI-powered marketing such as:

• Multiple regulations stop private and government organizations to share data in order to protect user privacy. For example GDPR (General Data Privacy Regulation).
• The majority of marketing data is siloed within the different departments making it difficult to aggregate it for a single unified system
• Data provided or collected is often unstructured in nature making it difficult for the model to comprehend with it.
• Small organizations don’t have enough data to put in the AI engine and many others mentioned above

3. Lack of Skilled Professionals

As per Drift and Marketing AI Institute Survey, the major reason behind the adoption of AI in marketing is the lack of education associated with AI marketing. They gave 17 choices to the marketers out of which 63% selected lack of education. Adding to it, Paul Roetzer of Marketing AI Institute stated the same, comparing the data with a 2021 survey that 70% of respondents picked lack of education as the reason. 

Here are some barriers that stop the integration of artificial intelligence in marketing:

• Understanding of AI technology and the terminology of many marketers is at a beginner level.
• Marketers believe AI will take more jobs than it would create
• Marketers don’t have an integrated infrastructure that helps them learn about the technology
• Companies are still relying on conventional tools of marketing

4. Privacy of Customer Data

AI in marketing has to stumble upon user data to train its model. This is a huge problem as it raises privacy concerns for the user. It is considering not everyone is willing to share their personal data. However in order to train a model it is an absolute necessity.

5. Training Time and Quality of Data

More than the time that will be required for training a model for AI marketing. The time taken to aggregate relevant data is a lot more. This serves as a major hindrance to creating a versatile model that can cater to multiple tasks.

6. Changing Marketing Landscape

Marketing is ever-changing. What worked a couple of months ago may not work now. This keeps the marketing industry in a constant juggle. This forces marketers to change their strategies every now and then. However, with the change in technologies, the marketing data also changes. On the flip side, we need structured data to train AI models and effectively integrate AI marketing into the process.

AI in Marketing - Technologies Used!

To introduce artificial intelligence in marketing, we need to make use of multiple AI technologies that are present out there. Therefore, let's start to learn about them one by one.

1. Machine Learning

Machine learning can be an effective tool for AI marketing. It enables the capability of AI systems to make decisions. It does it by processing a variety of data from the industry, current trends, the present market, and the profiles of the customer. 

Machine learning is an AI technology that enables a computer to make decisions in real-time situations. The machine learning models used in the marketing process variety of marketing data such as demographic data, intent data, technographic data, quantitative data, qualitative data, etc. This data can be both from the industry operating in or in-house. Once a machine learning model is developed, it is capable of providing insights from the data provided leveraging the potential of AI marketing.

Below are the benefits of using machine learning in marketing:

• Personalization: Machine learning enables you to process customer data and their past behavior. This makes the companies capable of providing offers, services, and launching new products that have a higher penetration rate. 
• Better Segmentation: The combination of machine learning and natural language processing helps you segment customers effectively into categories based on their preferences.
• Reduced Cost: A lot of time is spent on research to create products that have a higher ROI. However, by using the insights from AI, this gap can be bridged, thereby, letting organizations reduce costs.

2. Natural Language Processing

One of the biggest barriers that a computer system faces while processing data is understanding the intent and categorization based on it. With natural language processing (NLP), this barrier is resolved. 

NLP models are large dictionaries of human language clubbed with other AI technologies to create an AI engine. Once a user puts in a query, these AI engines are capable of processing it. In marketing, NLP is used for the categorization of marketing data, chatbots, market research, social media analysis, etc.

Here are the benefits of using natural language processing for AI marketing:

• It can be used for processing large datasets of unstructured data
• NLP can help in segmenting the content by reviewing the data fed to it
• NLP can be used to provide better customer experience by using a conversational tone with the chatbot
• It is capable of producing insights that are actionable in nature

3. Semantic Search

Semantic search is a technique that is used to search for relevant content from a pile of data. Using the combination of machine learning, natural language processing, and semantic search to understand the context and the intent behind a query provided by the user.

A great example of semantic search would be searching for any item to buy on Amazon. For instance, if you intend to buy headphones under $25, the Amazon semantic search system automatically applies a filter for showing headphones up to $25. 

To provide further clarity, here are some benefits of using semantic search for AI marketing:

• It provides easy searchability of the content on the website
• It helps in improving the ranking on the SERP by providing relevant metadata
• It helps in increasing the organic traffic on the website
• It caters to the customer by understanding the context of the query
• It helps in building brand awareness

4. Named Entity Recognition

Named entity recognition (NER) is a subset of NLP. It helps in the classification of the data classifying them as entities. These entities are typically used for classifying products with multiple synonyms. For instance, earphones, headphones, earpieces, etc. can be classified under a single entity. This enables a computer system to effectively provide results whenever these queries pop up.

Here are some of the benefits of using NER for AI marketing:

• It helps in understanding the intent of the customer
• It helps in personalizing marketing messages for the customer referring to their name and interest
• It helps in categorizing synonyms of a similar product
• It can improve SEO on the website by properly tagging website content
• It can be used to figure out trends

5. Neural Networks

Neural networks work on the concept of the human brain. A neural network is a combination of multiple nodes interconnected together to provide enhanced decision-making for computer systems. Neural networks are complex in nature and require tonnes of ever-evolving training data to effectively work. In fact, there are existing applications that take benefit of it such as Siri, Google Assistant, Cortana, etc.

With the emergence of big data, the capacity of local systems to process volumes of unstructured data is limited. Using neural networks, it is possible to segregate this data into categories and gather insights from it. It also helps the AI engine develop over time. Therefore, one can witness the performance and accuracy of the AI engine improving over time.

Here are some benefits of neural networks for AI and marketing:

• Neural network has the capacity to gather information from large datasets of customer behavior and preferences
• It has the capacity to identify complex patterns in data
• It can be used to provide personalized marketing messages for a segment of customers for increasing engagement
• It can be used to predict the future based on past behavior

6. Sentiment Analysis

Sentiment analysis is a technique used for identifying the opinions and expressions behind a piece of text. Different style tones that are captured using sentiment analysis are negative, positive, and neutral. 

This technique for marketing is utilized for understanding customer feedback and analyzing the general sentiment of the customer of the brand on social media. Using it, the response for the services can be measured. It will also help determine if there are changes required with the existing service.

Here are some benefits of using sentiment analysis for AI and marketing:

• It can extrapolate meaning from unstructured data
• It can be used to understand the emotional tone to revamp the existing service
• It can be used to reduce the churn rate of customers
• Integrated with a chatbot, it can provide empathetic responses to the users
• It can be used to respond quickly to the poor customer experience

Benefits of Using AI in Marketing

Here are some stats as mentioned in an article by Hubspot that proves the effectiveness of artificial intelligence in marketing. These are:

• About 67% of marketers think that the biggest benefit of AI is generating content faster
• 49% of marketers believe that AI’s biggest use is that it can generate personalized content
• 48% believe that the capability to generate new ideas is the most important use

Despite what marketers believe, there are plenty of other benefits of using AI. Therefore, let’s check them out!

1. Increased ROI for Marketing Campaigns

Marketing is all about understanding the pulse of the customer. With AI and marketing bunched together, the capability to understand customer preferences, behaviors, and other aspects becomes much clearer. AI-powered marketing helps in providing customized offers, discounts, and products to consumers that provide much more value to customers. This thereby increases the ROI associated with the entire marketing campaign.

2. Better Customer Relationship

Managing customer relationships is empirical to establishing a great running business. With AI in place, there are several ways that AI in marketing is affected such as:

• Friendlier tone of conversation
• 24*7 operation without human resource
• It recommends products to the customer as per their requirements
• Provides close to accurate information for establishing customer behavior and pattern of purchase
• It provides solution to the customer on the chat window itself
• It escalates customer problems directly to the support team

Aside from these benefits of AI marketing, there are others as well such as:

• Real-time personalization of content and offers to enable filters & to assess behavior patterns of customers with similar preferences
• AI-powered marketing can break the ROIs into different metrics making it measurable for the marketing team
• Insights gathered by the AI engine can help in taking decisions and the creation of effective strategies

Artificial Intelligence in Marketing - Use Cases!

The majority of marketers want to adopt AI technology and the ones that are reliant on it because it can cater to a variety of use cases. At its core, AI is a way of developing systems that are self-learning and self-evolving in nature. This makes artificial intelligence in marketing a solution that can be applied to a variety of use cases, especially the ones that generate and utilize data.

Here are the different use cases which can be reinforced using AI marketing:

1. Audience Targeting

Audience targeting is the process of creating ads and copies for people who are more likely to purchase. Audience targeting works on a granular level and focuses on different segments of demographics. This is usually conducted using relevant ads, A/B testing, and sending targeted emails to different demographics.

AI-driven audience targeting uses machine learning and other AI techniques to segment, identify, and engage. The AI model makes segregation based on different groups on the basis of geography, behavior, demography, and psychographic.

Using AI for audience targeting has several advantages such as:

• It helps in sending relevant content to the target audience
• It aids in reducing cost by segregating the target audience as per their requirement ensuring minimal wastage of budget
• It helps in creating tailored messages
• It enables you to tap the niche market
• It offers higher customer satisfaction in terms of brand affinity and long-term relationships

2. Lead Generation

Leads are possible customers that can further turn into sales. The process of gathering leads is considered lead generation. In a sales funnel, there are several types of leads such as:

• Cold Leads: It is a lead that is a plausible customer from the perspective of your product but hasn’t shown any interest
• Warm Leads: These are the leads that are aware of your business and consume your content
• Hot Leads: These are the types of leads that have shown interest in your product in one way or another
• Information Qualified Lead (IQL): It is a lead that has started to find a solution for their problem or is in the research phase
• Marketing Qualified Lead (MQL): These are the leads that are a step ahead of IQL and have downloaded your content such as case studies, brochures, etc.
• Sales Ready/Accepted Lead (SRL): These are the leads that can be handed over to the sales team for possible business
• Sales Qualified Lead (SQL): It is a lead that has shown interest in your business and is willing to talk to the sales team

By using AI for marketing, the user can automate a variety of operations and quantify the quality of leads automatically. AI-powered marketing for lead generation can help in empowering chatbots to aggregate business, lead scoring, prioritization of leads, lead nurturing, predictive analytics, and segmentation of customers.

3. Deep Understanding of Customers

Here are several ways a marketer can gather a deeper understanding of its customer. These are:

• Mapping the journey of their customer
• Analyzing social media and gathering important information from it
• Get both quantitative and qualitative feedback from the customers
• Automate data to churn out insights from it
• Approach a third-party solution to come for aid
• Focus more on behavior analytics

AI has the capacity of processing large volumes of data. With AI-driven marketing, marketers will be able to segment customers better, create their psych profile or buyer persona, understand their requirements, understand their inclination towards certain products, and a lot more.

4. Behavioral Analysis

Behavior analysis works on understanding the behavior of the customers. It focuses on questions like:

• What do they want?
• What do they interact with?
• What is their past behavior in terms of product requirements?
• What is the decision-making attribute such as the price of the product, features, brand value, etc?

Based on this analysis, marketers try to create a website, application, products, etc. that can improve the chances of sale. With AI, the capability to analyze this data becomes much easier. An AI solution can provide insights regarding purchasing behavior, preferences, spending habits, etc.

5. PPC Advertising

Using PPC advertising or pay-per-click advertising, marketers purchase ad placement of their product for a certain keyword. For instance, “best air conditioners under $700” can be a keyword for which PPC can be conducted. Once the user searches this query on the internet, the PPC advertisement would be shown to them. This increases the chance of creating a possible sale.

Using AI for PPC advertising, marketers can control various aspects of the advertising and increase the ROI while reducing the wastage budget immensely. This is possible because AI marketing for PPC allows:

• Effective selection of keywords for maximum penetration
• It helps in managing the bid of the keyword
• It helps in targeting opportunities that can become customers

6. Search Engine Optimization

Search engine optimization (SEO)is a technique used to optimize the website content and the website itself to increase its likelihood to rank higher on SERP (search engine result page) results. The idea behind SEO is to make the website get found, crawled, indexed, and shown as per a relevant search query.

AI helps in SEO in primarily two ways. The first is by providing SEO-optimized AI content on different topics that can be posted on the website. The second is by assessing the website. This helps the AI engine to figure out and showcase areas of improvement for overall better searchability.

Below are some of the AI tools for marketers that can be used such as:

• Jasper.AI
• Outranking
• Pro Rank Tracker
• RankAI
• Hubspot AI Tools

7. Social Media Listening

Social listening or social media listening is the practice of monitoring social media channels for overall brand engagement, feedback, and other responses from customers. This practice also helps in understanding competitor brands and finding relevant keywords for your brand.

There are several ways AI can be used for social listening:

• It helps in adding more context to the information shared on social media
• It can be used for researching the market
• It can be used to interact with the customers
• It can be used to understand the sentiment of the customers
• It can be used to measure the effectiveness of your social campaigns and how it is being perceived

8. Email Marketing

Email marketing is the process in which marketers send emails to their subscribers telling them about new products, offers, and discounts. It is a relatively older technique still prevalent in niche and commercial markets. Almost every company that offers products and services uses email marketing to a certain extent. This technique helps spread awareness about the latest offering of a company and has the capacity to aggregate potential customers. 

Here are some use of AI for email marketing:

• It can be used to optimize the mailer list
• It can be used for creating engaging subject lines
• It can be used to send personalized emails
• It can be used for writing emails
• It can be used to create a personalized newsletter for different demographics

9. Chatbots

Chatbots are computer programs that are capable of engaging with incoming customers on the website or an application. Chatbots have been in use for a while now and they have garnered a positive reputation for engaging customers. Right now, the market has a variety of chatbots that don’t seem robotic like their predecessors. These chatbots are backed by AI and have a conversational tone.

Here are some benefits of using chatbots for AI marketing:

• It can be used for generating leads
• Chatbots helps in saving cost by engaging users and staying operational 24*7
• It provides better marketing with their conversational tone and capability to change the style of conversation i.e. formal, casual, informal, friendly, etc.
• It can gather insights from the customer while simultaneously staying operational
• It can help with gathering customer personal data as well as feedback

10. Content Generation

Content is an integral aspect of marketing whether it be emails, marketing copies, blogs, articles, newsletters, etc. The entire marketing funnel starts with the creation of engaging content for the users. Content is created in marketing for several reasons such as:

• Informing the customers about the latest products
• Providing information regarding discounts and offers
• Extrapolating the features of a product
• Providing detailed information about a particular topic
• Driving traffic to the website
• Pushing the sales funnel from awareness stage to buyer stage

Right now, there are several AI tools that can help you create engaging content in different ways such as blogs, articles, titles, meta descriptions, research, etc.

Below are some of the most famous tools for generating AI content:

• ChatGPT
• Bard
• Bing AI
• Jasper
• Grammarly

11. Intelligent Website Audits

Website audit is often a part of SEO that helps in determining the aspects that can be changed, updated, or improved for better website performance. There are several types of website audits such as:

• Competitive website audit
• SEO Link audit
• Lead conversation optimization audit
• Social media audit
• SEO website audit

There are several AI-based tools that can be used for conducting website audits:

• UberSuggest
• Google Search Console
• SEMrush keyword research
• CanIRank
• RankMath

12. Augmented Reality

Augmented reality (AR) is a technique that is used to superimpose computer-generated graphics onto the real world. AR is a common technique that has a growing market and is used by marketers in many creative ways. With the usage of AI along with AR, the marketers can produce much more personalized content for customers.

Here are some existing examples of AR being used in marketing:

• Walmart using AR for the inventory
• Snap painting the city
• Pull & Bear Video game
• Studio App for IKEA
• Hair coloring at Amazon Salon

Companies Using AI for Marketing - Use of AI in Marketing

Here are some companies that have used AI marketing to engage more customers and create a word about a specific product & branding.

1. Amazon

Amazon has applied AI in multiple facets of its marketing, sales, and product offerings. Here are some of the ways Amazon has been using AI to increase its effectiveness:

• Providing personalized products based on the past behavior of the customer
• Dynamically pricing customers based on the demand for the product
• Creating check-out free stores for the customers
• Suggest outfits to the customers

2. Starbucks

Starbucks has another major player that has been using AI for improving its customer's experience. Starbucks has used AI in primarily two ways.

• To understand the taste and preferences of the customers (for improving their product i.e. variety of coffee beverages)
• To send personalized messages to improve customer experience

Adding to it, the company also used AI technology to create loyalty programs, discounts, and offers for the customers.

3. BMW

Unlike Tesla which is using AI for creating self-driving cars, BMW took a different AI approach. It used intelligent AI systems to adapt to the driver’s preferences while driving and tuning the internal systems as per the driver’s likeness. The company also used the technology to design cars and create intelligent personal assistants.

Future of Artificial Intelligence in Marketing

Saying that AI in marketing is the future would be an understatement. Today, as we log on to our favorite OTT platforms, shop online, book an Uber, or book a flight, we are using AI. From compelling offers and discounts to your favorite products are curated using AI technology. In fact, there are innovative technologies such as virtual reality and augmented reality that have been used in multiple innovative ways to promote services, movies, books, series, products, etc.

Yet, the future holds much more extensive use of AI marketing. In fact, McKinsey has stated that aside from sales, marketing would have the most amount of impact in terms of revenue. This is enough reason for creating many more technological breakthroughs in the domain of artificial intelligence in marketing.

Right now, there are multiple marketers that are not taking the data-focused approach. However, in the future, this practice will be omnipresent throughout the industry. We will be seeing the rise of the collaboration between human writers and AI content. The products and offerings will become much more personalized. We might have digital assistants with AI avatars with a conversational tone selling products and sustaining customer engagement. Mailers will be able to better filter the plausible customers and reach customers that need your products. 

Overall, the marketing will become more customized for the customers, marketers will be able to target segment customers 5X better, and the operational cost (in terms of wastage) will reduce. The future of artificial intelligence in marketing holds a much more target centric focus.

Wrapping Up!

AI in marketing has been a boon to the industry. Marketing is a stream that is always dynamic in nature. With customer preferences changing, the changing market, incoming trends, etc. marketers are always on the lookout for insights. Insights that can help them build their brand. With the effective usage of artificial intelligence in marketing, this is being realized. However, the future holds a lot more promises with the collaboration of AI and marketing in mind.