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.
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.
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:
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 companies, check it out!
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:
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:
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.
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.
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.
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.
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:
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:
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:
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:
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:
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:
Here are some stats as mentioned in an article by Hubspot that proves the effectiveness of artificial intelligence in marketing. These are:
Despite what marketers believe, there are plenty of other benefits of using AI. Therefore, let’s check them out!
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.
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:
Aside from these benefits of AI marketing, there are others as well such as:
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:
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:
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:
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.
Here are several ways a marketer can gather a deeper understanding of its customer. These are:
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.
Behavior analysis works on understanding the behavior of the customers. It focuses on questions like:
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.
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:
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:
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:
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:
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:
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:
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:
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:
There are several AI-based tools that can be used for conducting website audits:
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:
Here are some companies that have used AI marketing to engage more customers and create a word about a specific product & branding.
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:
Starbucks has another major player that has been using AI for improving its customer's experience. Starbucks has used AI in primarily two ways.
Adding to it, the company also used AI technology to create loyalty programs, discounts, and offers for the customers.
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.
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.
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.
AI content marketing is the creation, distribution, and analysis of content that is made possible using machine learning and other AI technologies.
AI affiliate marketing is a strategy for rewarding affiliate marketers to bring more customers to their products and services.
Some AI in marketing examples are:
There are several ways one can conduct marketing with AI such as personalization of content, data analytics, media buying, forecasting sales, etc.
Some examples of AI in marketing are:
Some names of AI marketing companies are:
An AI marketing strategy is one that makes use of AI technology to serve customers.
Aparna is a growth specialist with handsful knowledge in business development. She values marketing as key a driver for sales, keeping up with the latest in the Mobile App industry. Her getting things done attitude makes her a magnet for the trickiest of tasks. In free times, which are few and far between, you can catch up with her at a game of Fussball.
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