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Artificial intelligence is transforming the digital marketing landscape drastically. Whenever a Google search is made, a Facebook newsfeed is checked or a product recommendation pops up from Amazon, AI is lurking in the background. Let’s dive in and look into some areas of digital marketing in which AI is getting intertwined. we can say that AI technology is our future, our work becomes easy with the help of robotics and less time consumed to do the work effectively. Here are some points of AI in the marketing field:-

  • Facebook uses facial recognition to recommend who to tag in photos.
  • Google uses deep learning to rank search results.
  • Netflix uses machine learning to personalize recommendations.
  • Amazon uses natural language processing for Alexa.
  • The Washington Post uses natural language generation to write data-driven articles.

Our life is changed due to this technology and grow our market with the help of AI. It is a more effective way to do the work and create a marketing strategy that helps to take fast decisions.


Industries across the globe have been leveraging AI in the best possible way to advertise their products and services.
Let’s try to understand what AI can do with Google’s example:- Google has been using AI for a long time to extract detailed information from users, which can be used by marketers to analyze and then plan a marketing campaign accordingly. Google collects users’ data via Google Analytics, Android, Google Chrome, and YouTube. The procedure adopted by Google in the use of AI with Google Ads can be defined in terms of a pyramid, being divided into three levels from bottom to the top: bidding, targeting, and messaging.


It is important to know how much bidding should be made for a keyword, or how much amount is needed to be paid for an ad. It is advised to use Smart Bidding Strategies, which use AI, for bidding. Unlike the way bids were made earlier, where the price of a bid was increased or decreased manually based on the reports obtained; Google’s AI has enhanced the way it is done. It looks deeper into the user data obtained by channels such as Android, Chrome, YouTube, and Google Analytics for analyses. After the analyses, it records attributes such as the location of a user, apps that the user uses on the smartphone, and searches done on the browser and YouTube to drive decisions for the bid. Marketers are just needed to set the marketing objective and artificial intelligence takes care of the rest.artificial intelligence (AI)


The older targeting approach was based on broad demographics such as age group and gender; it did not consider the intent of the end consumers. artificial intelligence has brought into the picture the value of the intent of the target customers. The user data that Google collects are used by artificial intelligence to predict a consumer’s next step. This allows improved targeting for the marketers, as they get to know user interests like if a person is a cricket fan or basketball fan if the person is soon going to be a parent, etc. Using such predictions made by the AI, marketers can fix the price in a sale or a lead. Once all of this gets sorted out, Google shows an ad to the the right person at the right time.


Not just for the analytical aspects of online marketing, it also comes into practice for understanding meanings and context. Messaging forms the top layer of the pyramid. Google artificial intelligence can understand messages, their
contexts, and related subtle details. Google provides for messaging in the form of responsive search ads or responsive display ads. It requires 15 headlines and four descriptions, following which the technology can make combinations. These responsive ads require parameters that are AI-specific. Google can derive the best ad keeping the user in mind.


Social media platforms have become the priority of every business to have an effective presence. Various artificial intelligence-enabled tools such as the analytics tools Unmetric, Nudge, etc., have automated almost all the tasks of social media marketers using AI. Some of the ways in which social media marketing is used are as media marketing

Customer Service

Customers interact with businesses on a one-to-one basis on social media. However, it is not always possible for businesses to answer a large number of customer queries, and this is where AI comes to the rescue. It prioritizes customer queries and helps businesses understand whether these queries are coming from genuine people or not. Such tools help businesses provide enhanced services, engaging them for a longer time and increasing the chances of conversion. For instance, if we type ‘pizza’ in Domino’s Facebook Messenger’s installed chatbot, it opens up the procedure for ordering a pizza. The use of machine learning has enabled the company to provide completely automated services throughout the day.

Social Listening

Social listening monitors the brand’s social media channels for direct mentions of the brand’s name or customer feedback or any discussions regarding specific keywords and topics and then analyses the obtained data to gain insights and act accordingly. Social listening finds the root cause behind the conversations happening on social media platforms and helps marketers to plan a marketing strategy accordingly. Tools such as Mention, Hootsuite, etc. not only monitor the social media channels but also carry out analysis, using which marketers stay ahead of their competition. These tools are powered by AI.

Competitor Analysis

In the present competitive time, it is important to monitor the activities of competitors and plan the marketing strategy accordingly. It reveals their weaknesses and strengths. This monitoring and analysis is a time-consuming, tiring process. AI-backed tools are there to pacify the efforts to a certain extent. Tools such as Buzzsumo, SEMRush, Linkody, etc., give a detailed analysis of the content strategy followed by a certain brand, its backlinks, and much more, giving you an opportunity to stay a step ahead of the competitors.

RECOMMENDATION ENGINES IN Artificial intelligence

While growing up, we all went shopping for clothes with a person who would keep suggesting what would look good on us. So finally deciding on cloth was a time-consuming task. With the coming of e-commerce platforms on the Internet, the experience of shopping underwent a change – it now takes lesser time. E-commerce allows people to buy anything in a matter of a few scrolls and clicks. A lot of advice on the kind of purchase a customer can make is sent in the mailbox and news feed of the potential customer. Once the customer purchases an item from an e-commerce platform, the customer would be receiving suggestions about similar products in the future. In such cases, the concept of a Recommendation engine comes into practice. It is a marketing tool that is mostly used by e-commerce or business platforms but presently finds usage in several other domains such as navigation systems, traffic control systems, and entertainment as well. Some of the popular examples of recommendation systems include Facebook’s ‘People You May Know, ‘Other Movies You May Enjoy on Netflix, ‘Jobs You May Be Interested In’ on the LinkedIn feed, and ‘Recommended Videos’ on YouTube.

In order to provide customers with suggestions, two types of filtering are performed by AI that power recommendation engines:

1. Content-based Filtering – It is based on items that customers want to purchase on e-commerce platforms and the keywords customers used to search for that items. It also considers the customers’ preferences.
2. Collaborative Filtering – This kind of filtering emphasizes the activities and behaviors of the customers. Following this, predictions are made on what a customer would prefer to purchase based on choices made by similar customers.
There are many applications of AI in the digital marketing landscape; chatbot is one example.

CHATBOTS In Artificial intelligence

Customers may choose to get in touch with companies on their social platforms, websites, or telephone calls. But being available 24 × 7 for customer service can be an issue for companies, knowing that it would require a person to attend to queries with every passing minute. In such cases, chatbots find good use. A chatbot is a kind of conversational interface that allows interaction with the software in a natural language that is understandable by humans; unlike a programming language like JavaScript or a GUI (graphical user interface) for example. They automate conversations with visitors on websites and social media, bringing consistency to user experience. When a customer service team is unable to respond to a customer, chatbots fill in the space to entertain the customer on their behalf. Depicts an interaction that a user is having with a chatbot. The user first asks a question to the computer software in natural language (here, English) and the software on the other end takes the interaction forward by understanding the user’s context and expressions.

what is chatbot in artificial intelligence


In online advertising, chatbots can work as an important marketing tool. They can enhance the engagement on an online ad, bringing a good return on investment. For instance, ads that are displayed on Facebook provide marketers with the option to take users to Facebook Messenger, where they can interact with the bot and complete their inquiries. When this bot interaction occurs, marketers get the contact details of the users and can contact them later to occasion more conversions.


The basic use of chatbots came about for answering queries posed by customers, like providing information about a product or a company. But there are uses of chatbots for purposes other than answering queries. Here are some ways in which chatbots are used apart from just answering queries and doubts.

For Selling Products – H&M, a prominent fashion brand, uses a chatbot for having quizzes about what kind
of fashion customers relate with. Once the chatbot gathers enough information from the customers, it comes
up with suggestions that align with customers’ responses.

Obtaining Insights from Customers – Chatbots can analyze a customer’s online behavior and purchasing pattern. Once it garners enough customer data, it’s easy to understand what kind of products they like. It can also grasp what kind of queries customers come up with during their online journeys. Such insights help to improve the marketing process.
Galvin, an AI-powered chatbot developed by Insites Consulting, is injected into the Twitter platform that works to keep users updated with consumer research, which it extracts from a database that contains consumer insights of an organization.

Personalization – Brand loyalty increases when customers recognize that brands tailor content and offerings according to their needs. Chatbots give a human touch to customers when they are online. Rue21, an AI-powered chatbot36 designed by, works on the basis of knowing the fashion preferences of customers and responding to them with recommendations and suggestions about dresses.

Enhancing Engagement – The definition of engagement changes when chatbots jump into the scenario. Take an example of Disney’s Zootopia, a Facebook Messenger bot that was created to raise a buzz about the movie and provide some fun for the users. The persona taken was that of Officer Judy Hopps, which was a character from the animated film, and users were seen to be spending as long as 10 minutes interacting with the chatbot.

Filtering Leads from Prospects – Identifying leads from a list of prospects could be tedious and tricky. Chatbots in such cases help customers in filtering out leads from prospects by asking questions regarding their preference for products. This data is then forwarded to the sales department of the organization to improve efficiency. Cluster, a bot generation platform, provides a framework to design chatbots as per its client’s requirements. The platform maintains conversations with prospects at the right time and helps in understanding the offers that are made by a business.Artificial intelligence Use of voicechat in daily life


In a survey conducted, 63.9% of the respondents accepted that instant messaging using chatbots should be provided by companies, and 49.4% agreed that to connect with a company they preferred using a messaging application to making a phone call.39 Let’s find out why. Following are some of the advantages of chatbots.

1. Always Active – Unlike humans, chatbots are available all the time to attend to inquiries, doubts, or queries from customers.
2. A New Alternative for Interacting with the Audience – In comparison to rolling out a form on a website for users and having two-way communication based on their requirements, chatbots allow better interaction opportunities for companies.
3. Improved Marketing Strategy – Chatbots collect vital details from the users. Be it their likes, needs, or apprehensions, if subtle details are known about customers as stated earlier, they can be leveraged to make suitable corrections in the marketing strategy of an organization without much expense on human resources and efforts.
4. Easier to Build than Apps – Mobile applications require a higher investment of time and money to be ready for use and come up with updates. Chatbots are based on a server and are easier to create in comparison to applications.


1. Installation Cost – Every chatbot needs to be programmed with respect to the domain of work they will be used in, such as health care, fashion, education, etc. The initial investment is quite high for installing chatbots. Not only this, but the changes required post-installation also increase the overhead costs.

2. Zero Decision-making Capabilities – Chatbots cannot make a decision on their own. One such instance was encountered with Twitter where a Microsoft-powered chatbot received several misogynistic and racist entries from Twitter users, which affected the chatbot such that it acquired a similar tone.

3. Zero Memory Retention – Chatbots cannot retain the conversations that have occurred before. If a user returns to a chatbot after some period of time, the conversation will resume not from where it was left last time, but from the start.


Defining the Goal
The first step is to come up with a concrete objective that you would want your chatbot to accomplish. This involves encapsulating use cases. Do we want a chatbot for customer service? Or for spreading the word about a new product, or is it about generating new valuable leads? This step involves working closely with the marketing team regarding social media handles and websites.

What is voice recognition

Plan Out a Content Strategy
Plan out what kind of interaction you want your chatbot to do with your customer. This can begin with frequently asked questions. Consult the customer service team, since they sit at the doorstep through which customers clear their doubts.

Coming up with a Personality and Voice
This is done to give chatbots a human touch and feel. Many companies assign a name to their chatbot.

The first message or the opening message should be framed in a way that would engage users to go further with the thread. This could begin by asking about what they are looking for, to coming up with optional responses that would determine further actions in the interaction. Adding visual content such as GIFs can work in favor as it increases the chances of the user feeling more connected.

Action Buttons
Once the conversation between the chatbot and the user is over, providing action buttons is the next step of the process. This takes the user to a goal. These buttons can vary from taking customers to a page of a website, or a product catalog to name a few.

Suggestive of the name, it involves knowing whether the users can find relevant information through chatbots or not. Chatbots mostly come with a preview feature, allowing for a mock drill.

Marketers can integrate chatbots with their websites. For instance, provides a framework for designing a chatbot, in which marketers can choose a field of information that they wish to take up from the prospects. The process helps in designing the bot, its name, its texture, and the welcoming note. The data obtained from the chatbot can be sent to an email address or can get stored in Google Spreadsheet. Most technological advancements such as voice search, chatbots, or Beacon technology used for marketing have the ability to gather user data, which has led to the creation of huge reserves of user data.


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