The impact of artificial intelligence and advanced algorithm on Instagram

The impact of artificial intelligence and advanced algorithm on Instagram

Social media has become more than a simple photo and life-event sharing platform. Big brands and MNCs are utilizing the power of social media to advertise and convert leads into actual sales. Take, for example, the photo-sharing platform giant Instagram – with over a billion active users on the platform, it has come to the forefront as the social media option to obtain the most significant outreach and often on a global scale. 

There is a straightforward reason for the popularity of Instagram. It has an incredible engagement rate owing to its robust technology platform and advanced algorithms. But it also provides entrepreneurs with several business-friendly features that allow a concern to gain mileage as far as marketing is concerned. Higher engagement rates, in simple terms, mean more followers, and in business terms, a loyal follower base is what you have always been looking for. 

Why is Instagram popular?

A significant reason for the popularity of Instagram is the use of high-quality images. It is, after all, an image-sharing platform, and therefore there is a natural appeal to it compared to other forms of media across all demographics. Photos can convey messages succinctly when words can fail due to global language barriers. Interacting with Instagram posts is extremely simple as well. All you need to do is like a post to express your feelings about the content. You can comment on your feelings as well. 

Every content that becomes popular on Instagram starts with a few likes, and the more interaction it gathers, the higher is the popularity. Often such posts go "viral" which means it reaches a certain level of global visibility. If you are looking to cut the time-in-wait for a post to gather momentum, why not buy likes for Instagram photo from an authentic online seller?

The ability to monitor user activities

The Instagram algorithm provides the best user experience. The only way to do it right is to monitor user activities on the platform. It allows the algorithm to gather data about the user's online behavior. The ability of Instagram algorithms to understand user desires enables the platform to meet the expectations at the SERPs and the feed. When it comes to monitoring, gathering, and analyzing data, Instagram uses several technical platforms, AI, and machine learning tools. The impact of AI and similar platforms have been huge on Instagram, and in the following section, we have gone over it in detail. 

Developing insights

The benefit of AI is that it is an ever-evolving platform, and it will get progressively sophisticated with every run. It allows an expansion of the technology and its abilities to an extent never seen before. Instagram AIs can track user behavior every minute and gather insights in real-time. Keep in mind that user interactions on the platform, with contents, posts, and other users, are driven by spontaneity. It makes the ability to track user behavior all the more impressive. Over a while, intel collection results in gathering enough insight to predict the pattern of use.  It allows Instagram to cater to every user as per their specific requirements, searches, niches, and products. The task of sorting, filtering, and analyzing has been perfected to near-perfect accuracy and reliability using AI platforms. 

Analysis of image

Since Instagram is a visual platform, sorting through images is a tedious job. Photos are usually categorized as per the subject, and even then, they can get wrongly sorted simply because of their subliminal meanings and dual subject nature. That is where AI-driven machine learning comes to the forefront as the more reliable form of sorting option. With AI, there can be increased accuracy as well as the programmed ability to learn from errors. This image recognition technology allows Instagram to sort through millions of images per day while understanding the messages conveyed through it with clinical accuracy. It is the secret behind the specifically catered feed for every user on Instagram – you will always see what you wanted to see. 

Accuracy for targeted ads

Keep in mind that Instagram earns plenty from advertising. The platform has a very robust capability of targeting advertising with the use of AI. All the user insights gathered by the platform allow Instagram to provide user-specific links and targeted ads to the users. This ability to track user engagement and search preferences enables Instagram to sell advertisements to companies and brands within the correct niche. Through Instagram, brands and companies can provide messages, products and serve ads to the prospect-client with interest in the business.

Providing vital content

It is all about providing the most relevant and the "latest" content to the users. Whether you are a brand or are looking to enhance your personal profile the key is to upload great content.  Instagram AI is extremely capable of this and is on par with search engine giant Google. It can identify and judge the content on the worth and the relevancy to a user-end search. Instagram AIs use the caption, hashtags, and several identifiers from a post to categorize the post. So captions are an integral component of every Instagram post. 

To distinguish between the real and the fake

The process of buying likes is nothing new, and it is not wrong either. The only fact Instagram cares about is whether the "likes" and "followers" have real people behind them or not. Instagram is well-aware of the process of buying likes, and it only maintains surveillance to check whether the likes are genuine or fake. If you are looking to buy followers and likes, make sure it is authentic by using the service from It is vital to ensure the authenticity of the likes and followers because Instagram AI will flag the fake likes as these do not generate any engagement.

Instagram allows you to make the most of the platform with the use of AI technology. It provides the best in user experience as well as opportunities to growthrough targeted marketing. 

A Handy Guide to Incorporating Machine Learning into Enterprise Systems

A Handy Guide to Incorporating Machine Learning into Enterprise Systems

As of late, enterprises of all sorts and sizes are largely adopting machine learning at a faster pace. Many areas of enterprise management can be influenced by machine learning capabilities ranging from the customer experience to developing innovative products. We can see that there are no such areas in modern business administration that are untouched by ML.

Machine learning got introduced as a pathway to artificial intelligence, which also acts as the primary diver for machine learning implementation in enterprises. There are many disagreements over the actual nature of the relation between machine learning and artificial intelligence. These are intervened in many cases, and many people see machine learning as a subset of AI and vice versa. The objective of artificial intelligence is to replicate human tasks to enhance decision-making logically.

On the other hand, machine learning is effectively used to automate any task, not just conventionally by humans, but also the tasks that need more involvement than human cognitive abilities. However, AI and ML are closely connected, and they feed each other to expand their mutual capabilities. Let us further explore the four most common approaches to machine learning.

  1. Supervised ML

Supervised machine learning is the most popular form of ML, which includes feeding a custom-made algorithm to the huge volume of training data to make predictions based on the data correlations as it learns from labeled data.

  1. Unsupervised ML

Unsupervised machine learning is used in advanced applications where artificial intelligence is used. This approach involves feeding unlabeled training data to the algorithms and instructing them to pick up the possible associations on their own. Unsupervised learning is so common in clustering applications, which can uncover the groups in the given data. It can also uncover the association between data sets and predict the rules to describe the same.

  1. Semi-supervised ML

In semi-supervised learning, the algorithms can be used to train smaller sets of labeled data, and as like in unsupervised learning, it can apply these learnings into unlabeled data. Such an approach is often used while there is a lack of data quality.

  1. Reinforcement ML

This is the use of algorithms that receive a custom set of guidelines and instructions, which can be further used to make a decision about properly handling a given task or process through a trial and errors approach. Decision made through it is either punished or rewarded, which will further train the AI system to optimize the solution for the task at hand.

Considering these four types of learning approaches, modern-day enterprises have derived a handsome array of real-time applications and techniques from ML. From sales forecasting to the latest AI autonomous tools now run-on ML models, there are many such areas. To tune your databases for machine learning capabilities, you can consult with experts.

Benefits and use cases of enterprise ML

As discussed in the first para itself, machine learning adoption in enterprise management is accelerating, and it is also reaching its core. Businesses are now putting ML applications at the center of their business strategies. Machine learning technology now enables businesses to run the tasks at a gigantic scale, which previously was unimaginable. It will help make enterprises more efficient and help them grab new business opportunities evolving out of the rapid market shifts. Let us further explore some real-time use cases of machine learning in enterprise applications.

Real-time use cases of machine learning

  • Recommendation engines

The consumer-facing online businesses and e-com service providers now largely leverage the recommendation engines, which can offer data-driven insights to present the right product in front of the right customer at the right time. A sample use case is the e-commerce giant Amazon, which pioneered machine learning technology for recommendations engines. Since Amazon succeeded in it, this had become a standard approach for all e-com sites. Recommendation engines consider the users' online behavior and browsing history of presenting products and services they may like in front of specific users.

  • Fraud detection

As of late, most of the financial transactions and loan processing, etc., are happening online, and the chances of fraud are at an all-time high. This demands an increasing need for fraud detection and correction. Banks, loan providers, credit card companies are using machine learning capabilities for financial fraud detection. This technology can learn the characteristics of legitimate transactions and sense any deviations to report suspected fraud.

  • Consumer analysis

Businesses collect huge data stores about their customer info. These big data stores consist of data from browsing history to the potential customers' in-store behavior and social media activities. Machine learning algorithms can troll these huge volumes of data and derive customer insights from it. Machine learning can also help develop personalized marketing strategies and target audiences to improve the overall user experience.

  • Financial trading

Wall Street first adopted machine learning applications in financial trading. Machine learning can examine huge volumes of historical data and find any patterns in terms of stock performance to make predictions about the movement of stocks in the future. Any edge is valuable in the high-stakes world, and ML can make a difference here.

  • Virtual assistants

We are so familiar with virtual assistants now. We know who Apple's Siri and Google Assistants are. Many of us do not know that machine learning powers these assistants and chat boats we interact with. Machine learning applies to it in various ways, including the concept of deep learning, where machine learning intervenes with neural networks to develop natural language processing or NLP.

  • Autonomous vehicles

Self-driving cars are one of the most sought-aftertopics on the internet now. Machine learning enters into the realm of artificial intelligence in self-driving cars, which goes on par with the application of human intelligence. Autonomous cars use neural networks to study and interpret the objects around them and detect them realistically using cameras and sensors. Going a step ahead, it can also autonomously decide what appropriate action to take next.

These are only a few popular use cases of machine learning, while countless more applications are out there. We can expect machine learning and AI to play a crucial role in all types of business operations in the future.

Real Time Examples of Artificial Intelligence Incorporated with Business Intelligence

Real Time Examples of Artificial Intelligence Incorporated with Business Intelligence

Modern day enterprises seem to enter into a new data-driven era. One was science fiction is now made possible with the help of advanced technologies like machine learning, artificial intelligence, and internet of things, etc. Companies largely use machine learning algorithms now to identify the trends and derive actionable insights in a wide range of industries with vast reams of data to make quicker decisions and position them to be highly competitive in real-time.

This is not a very simple process for organizations to incorporate machine learning and artificial intelligence into their business intelligence applications. However, there are many who are consistently experimenting with the same. AI helps organize the data collections and test the algorithms with data to check for accuracy over a few months and see where the business gets stuck.

However, as AI is gaining momentum, many prominent application providers have gone far beyond creating the traditional software to develop more holistic platforms, which can automate the business intelligence and analytics processes better. Some of the major vendors, including SAP, General Electric, Siemens, etc., now offer custom software suites. Also, there is an emerging number of providers in the startup market playing with AI in business intelligence. In this article, we will try to provide some real-time examples of the leading AI platforms.

SAP –Artificial Intelligence for Turning Databases

SAP is offering HANA, which is a platform for organizations to manage the DB info collected. In short, it helps to replicate and ingest structured data like customer info, sales transactions, relational DBs, app data, and other data sources. HANA can be installed on the cloud or as an on-premises installation. This platform can also take the information gathered from various access points across the businesses, including desktop computers and mobile platforms. Data can be done from sensors, financial transactions, and various production and industrial equipment. Suppose your sales staff uses the company's smartphones or tablets to record or purchase the orders. In that case, the data from such transactions can also be analyzed using HANA to understand the trends and irregularities.

A classic user of HANA is Walmart, which uses it to process huge volumes of their transaction records in a matter of seconds. Walmart now operates about 11,000 stores, and so you can imagine the volume of transactions they undertake. Considering this example, machine learning can be used to call attention to many variances. For example, suppose an application is installed on the factory manager's computer or smartphone to monitor an equipment's function. In that case, any data related to a production slowdown can be gathered in real-time to administer the best course of action when needed. For AI-related database solutions, explore what can offer.

DOMO – Artificial Intelligence for Business Dashboards

Not only have the big players liked SAP who develop ML platforms for businesses. However, Domo is a smaller one, which is growing at a faster pace now with its business management suite and raised nearly $500 million in funds. They are offering a business dashboard that gathers information to help organizations quickly and insightfully make decisions. This cloud-based system can scale up or down based on the organization's size, and it can also be used collaboratively by teams of 50 or larger. There are about 400 native software connectors that let DOMO integrate with various third-party apps, and it can also be used to offer some insight to give a proper context to BI.

This lets the companies use DOMO as a customized way to pull data from various platforms like Square, Salesforce, Shopify, Facebook, and various other applications, which they used to gain insight into their sales, customers, or product inventory. For example, Domo users who are merchants can also extract data from the Shopify POS e-com software, which can be used to manage their online stores. This information can further be used to generate some quick review reports and identify the market trends in real-time like product performance etc.

Apptus – Artificial Intelligence for Sales Enablement

There are many ways through which machine learning can help enhance business applications. Apptus is one such solution which offers recommendations to business on taking acts to boost the sales operations. Apptus specializes in establishing a connection between the intent of the customers to buy an entity and the business’ realization of the revenue.

Apptus’solution of eSales is custom-designed to automate the merchandising based on the predictive understanding of the consumers. This software helps to combine machine learning with big data to determine which all products may appeal to the customers as they search for recommendations online.

In standard use of Apptus, while the customer visits an online store using the eSales platform of Apptus and looks for a product, the integrated machine learning solutions will exact the product and display all related phrases. It can also automatically display the products associated with the related phrases along with the search terms.

Now, many companies use Apptus like, a bookseller business from Sweden, who use this platform to minimize their overhead by tapping into the automated technology. 

Avanade – Business Insights with AI

Came up as a joint venture of Microsoft and Accenture, Avanade leverages the capabilities of Cortana Intelligence Suite to do predictive analysis. Businesses like Pacific Specialty tap the benefits of Avanade with an intention to give a better perspective and insights to the staff. The goal of Avanade is to use the policy and customer data to help the sales team drive in more results. By understanding the exact behavior of the policyholder and the market trends through analytics, Avanade can advise the scope of development of new products accurately.

Along with these, you can see many more examples of AI in business intelligence like BI and AI applications for heavy industries like General Electric, Predix for logistics management, Aircraft Landing Gear Prognostics offered by GE and Infosys, Siemens – AI to Monitor machine fleets, etc. By considering your area of focus in business intelligence, you may find AI to deliver value.

Current and Future Trends of Artificial Intelligence

Current and Future Trends of Artificial Intelligence

In the year 2020, the world witnessed two major achievements in the pursuit of artificial intelligence. OpenAI launched the GPT-3, and DeepMind from Google introduced AlphaFold2. Both of these companies are racing to create, advance, and research the role of AI in the community today. Several others are making big advancements in AI; however, GPT-3 and AlphaFold 2 were two of the most notable achievements in 2020.

Conversation between humans and computers 

Thanks to the advent of GPT-3, the interaction between humans and computers has progressed. Today, we can talk to computers about specialized topics. In the case of AlphaFold2, last year was engulfed by the coronavirus pandemic, and hundreds of leading names in the pharmaceutical industry were on a single goal to get a vaccine. AlphaFold2 is precisely what scientists need to get closer to their goals of understanding diseases faster, especially on molecular levels, to save more lives in the future. 

GPT-3 and language processing with artificial intelligence 

With the help of GPT-3, scientists could render training to an AI model for interacting with humans and reading and writing different texts. This was surely an astounding development byOpenAI, and the GPT-3 known as the Generative Pre-Trained Transformer was a revolution indeed. For several years, human beings have been fascinated with the thought of interacting with humanoid robots in their languages, and it is artificial intelligence that is a critical milestone that has been achieved today. The GPT-3 can process texts in various languages and is touted to be better than GPT-2. This is because it has about 175 billion parameters (these are the values that neural networks attempt to maximize during training) if you compare it to GPT-2’s now very small 1.5 billion. 

AlphaFold 2 Breaks a 50-Year-Old Challenge 

Scientists belonging to Google’s DeepMind were able to make AlphaFold 2 that has been touted to be one of the biggest breakthroughs in biology and medical science. This model can derive and detect 3D protein structures of the human body's amino acids that can boost the rate at which humans can comprehend diseases and improve the rates of pharmaceutical manufacturing. Never before, especially in the last century, has this been more crucial for medicine. 

Artificial intelligence is ideal for helping the global medical industry, especially when it comes to modeling proteins on molecular levels, compares medical images, or find patterns or anomalies faster than humans. It also helps in countless other opportunities to progress in the field of clinical processes and drug discoveries. For example, scientists spend days, months, and even years making attempts to comprehend the DNA of new diseases. However, they can save time now with some assistance from artificial intelligence. It is here that breakthroughs like AlphaFold 2 should continue for humans to understand a lot of things still unknown to them in the future. 

Two key AI Trends to watch out for in 2021 

Experts from the esteemed name in database administration and management,, state the following are two of the key AI trends that you should look out for in 2021-

  1. AI will be voice and language-driven - 2020 witnessed economies coming to a complete halt as schools and businesses closed down due to the coronavirus Pandemic. Businesses had to suddenly cope with this change and embrace a remote working structure in just a few days and weeks to deal with the rampant spread of the virus. This has given birth to the need for both voice and language-driven artificial intelligence to curb the volume of technology primarily touch-based in nature. 
  1. Cloud adoption and AI - Both AI and the cloud go hand in hand in the world of technology today. For instance, take the case of digital assistants like Google Home, Apple Siri, and Amazon Alexa. They have penetrated every arena of our lives today. You will find them in industries, communities, and homes. Tasks like ordering food online, asking a question, scheduling an appointment, communicating with another person over text, listening to music, etc., can be done with the help of these digital assistants that deploy both AI and cloud resources. 

For companies today, cloud computing has provided and continues to provide scaling operations efficiently and effectively. Computing resources can be duplicated with just a click of a button for scaling up and down as required. Faster memories and extra memory can be added faster along with large volumes of data like gigabytes, petabytes, and more. All of the above can be deployed in a single database by providing provision for additional memory. New software can be tested and deployed through the company effectively, along with lots more. 

Cloud services like Amazon Web Services, Google Cloud, IBM Cloud, and Microsoft Azure all provide ready-to-use and pre-trained machine learning, models for artificial models, deep learning, algorithms, and business services for using in their process for data analytics. This also gives small businesses the scope to access potent models that have received training on billions of data rows at just a fraction of the cost. In this way, one can start with cloud-based services till one gets an on-premise AI workstation, cluster, or server that is more affordable and under their complete control. 

You will find that 2021 will see the advent of several AI start-ups that use cloud-based services to develop their businesses. With artificial intelligence, they can focus on their finances better and invest in essential business factors. 

Last but not least, 2020 was when the world witnessed the worst Pandemic after the Spanish Flu. Radiologists and other medical professionals have been using AI for scanning MRIs and X-rays to detect diseases and other healthcare problems. With the advent of 2021, the healthcare industry will lean more on artificial intelligence as its rates for accuracy will continue to surge above what humans can rise. 

Efficient use of AI can help in many ways including heath and development sector. Users need to implement things in a way to ensure that everyone can enjoy the maximum benefits. 

How AI Is Revolutionizing the Gen Z Ecommerce Experience

How AI Is Revolutionizing the Gen Z Ecommerce Experience

The outbreak of the COVID-19 pandemic had changed the ways in how people perceive e-commerce. It has become their first choice in acquiring goods and services. While these customers continue to go through online shops, they stick to the platforms which offer them a user-friendly experience. We can see that only such e-commerce portals retain customers and earn a profit in the longer run. When considering the role of artificial intelligence, we can see that it significantly impacts delivering a seamless online shopping experience to users.

E-Commerce and retail brands are utilizing artificial intelligence to offer better customer engagement. Overall, the AI-driven approach will ensure an intuitive shopping experience for the users at large, and it is not just limited to tech-savvy people. The focus now is more towards intuitive and simpler processes to offer a successful checkout. As a result, global e-commerce sales are projected to touch about 4.8 billion dollars by the end of 2021. Gartner also predicts that artificial intelligence technologies may manage about 80% of these customer interactions without the interference of any human agent.

How intelligent e-commerce works out?

The use of artificial intelligence in the e-commerce industry is now helping to predict the shopping behavior of different people based on when and what they do online. For example, suppose an online shopper tends to purchase a particular brand of rice repeatedly online. In that case, the retailer may send a personalized offer to the shopper for that particular product. Machine learning recommendations will help in cross-selling by suggesting a product that goes well with the rice dishes.

For example, the digital native e-commerce companies like Amazon, Alibaba, Walmart, etc., now leverage the benefits of AI to predict the market trends, optimize their logistics and warehousing set competitive pricing, and personalize their promotions. In addition, some of the artificial intelligence-enabled digital assistants like the Google Duplex tool are now evolving in their capabilities as creating a grocery list for people based on their preferences and even placing online shopping orders by themselves. Other solutions like the Amazon Dash button will further make the everyday purchases of the consumers easier using automated reordering services.

Artificial intelligence to augment e-com customer experience

There is another new wave in e-commerce, which is changing the way how brand-customer engagement is happening as modern brands continue to refine their digital strategies. E-commerce is now the fastest growing and evolving channel, so it does not need some derived insights and the need to provide actionable recommendations in real-time. Let us explore how AI is disrupting different aspects of customer experience by unifying real-time data and incorporating critical business contacts. For incorporating AI benefits to enterprise ecom database management, you may consult expert providers like

Makeover in customer service

Ai has a big impact on customer service automation by making it hassle-free and swift. The businesses can pre-empt the customer expectations by understanding their history and offering appropriate solutions. This will enhance the overall customer service experience. Conversational AI is used largely in customer engagement now. These are engineered to simulate human-like interactions and give much personalized and immediate responses round-the-clock. This had also reduced the turnover time and errors in handling the customer queries. Conversational AI and virtual assistants can now also answer out-of-the-box questions. Spring is one of the online retailers, which started using the Facebook Messenger bot store to offer a personal shopping assistant. It helps to simplify their shoppers' journey by assisting them in finding what they are looking for. The ingenuity of the assistant is that it does its work by engaging them in casual conversations. WhatsApp Chatbot integration is also gaining momentum among retailers.

Predictive personalization

It is also helping the businesses emulate user experiences to integrate with the customer's lives. Smart predictions and customization will make the users feel like each product or be very are custom-tailored for their exact needs. E-commerce companies and retailers can easily understand the shoppers’ inventory and patterns to forecast and deliver goods automatically. This instant shopping experience can convert any page into a quick check-out center and thereby expedite the purchasing process of motivated customers. It is also possible that AI makes shopping a seamless one-click experience with an instant checkout button. It can also adapt this checkout reference and turn new customers into loyal customers irrespective of their preferences and devices.

Use of analytics for discovering high-impact customers

Optimal customer experience can be achieved only if the business remembers their customers and treat them with original consideration through the shopping journey. AI-enabled analytics has the power to sift through larger data sets containing minute and complex details to uncover business opportunities. As a result of this, one can spend time examining these insights instead of doing away with the crucial data available. Analytics led by artificial intelligence looks at each piece of meaningful data and predicts the likelihood of the future behavior of the customers with high accuracy. It can also simultaneously find the drivers and inhibitors in terms of the customer experience. Thus, it will mine a huge amount of data to derive actionable insights with AI. Say, for example, retail banking now uses predictive analytics for visualizing the high impact journey of the customers, which leads to a decrease in savings account deposit reduction, etc.

Forecasting the customer demand

Artificial intelligence will also help to forecast and automate the decision-making of the dealers in real-time. By learning and identifying from the patterns of user data sets across various sources, social media Trends, weather forecasting, customer viewing history, and even facial expression analysis, AI will help the companies to readjust their strategies and gain a better grip on the evolving market environment. In addition, improving forecasting accuracy, machine learning, and computer vision will help in better anticipating consumer expectations and optimizing and automating supplier negotiations.

Artificial Intelligence can also efficiently manage inventory, automate the customer experience, enhance consumer engagement and ensure a smooth sail of the businesses even during adverse times.

Author’s Bio:

Walter Moore is a blogger and digital marketing expert. He is quite experienced in the field of web marketing as well as website designing. He has been working as a database administrator in the IT industry RemoteDBA. His research has helped thousands of users and brands with marketing campaigns too.


How AI Can Improve Online Marketing Campaigns

How AI Can Improve Online Marketing Campaigns

At first, you may find it difficult to see the connection between artificial intelligence and marketing strategy. However, when you examine the topic closer, you realize that there is no market or industry on this planet that has not in some way been impacted by artificial intelligence. Digital marketing is just one of many industries that AI is currently revolutionizing.

What Can AI Do for Digital Marketers?

Using big data analytics in marketing is not new. It is a strategy that marketers have used for years to improve the way they interact with their audience. Big data coupled with machine learning is the backbone of AI. It is only logical to conclude that AI can help enterprises improve their marketing campaigns and reach wider audiences.

Big data has phenomenal amounts of structured and unstructured information. Traditional data processing software can't control or analyze all of this data.

Machine learning is part of building programs that can fetch and utilize data of its own accord. These machines are trained to learn and improve themselves continually.

Big data and machine learning work together. Automation makes it possible to extract, segment, and aggregate massive amounts of data, allowing insights about customers to become more accessible and apparent. The data is gathered and sorted and then handed over to the machine learning side of the equation.

With machine learning, organizations can identify patterns, trends, and insights. They can look at that data, extrapolate solutions, and predict outcomes. All of this is at the heart of what marketers need to tailor their marketing to meet the needs of their customers.

Search relevance is an example of how artificial intelligence and machine learning are improving quality for customers. A person may be searching for a product. They put a query into the search bar that explains a product or service the best way they can. The high-quality search uses AI to identify a searcher's intent and prioritize what it offers based on what the searcher wants to see. In this way, AI is making the searching experience better for the customer.

Using AI to Get the Marketing Advantage

Predictive analysis allows a marketer to look at page views, bounce rates, click-through rates, and time spent on the page to make informed decisions about the specific ways and areas their marketing strategy needs to be improved. It can also identify ways that the current strategy is working.

Predictive analysis can extract data and create informed predictions about how customers will engage with a website or an application in the future. This can be used to drive more people to a site, keep them on the site longer, and increase the chance they will convert and buy a product.

Machine learning algorithms improve audience targeting and segmentation. These algorithms can be used to identify important and reoccurring patterns. These include things like demographic information as it connects to specific content or individual users.

For example, a machine learning algorithm may identify that people between the ages of 18 and 25 are interested in social media posts. In contrast, those between the ages of 40 and 60 are drawn to blog posts. With this information, marketers can change their strategy to target certain demographics with different types of content or create unique outreach programs to meet the needs of different demographics.

The Power of Chatbots

One of the most powerful ways AI can help in marketing is by powering chatbots. AI-powered chatbots can assist customers at any hour. Successful marketing depends on customers having multiple channels to contact your organization. This includes during work hours and off-hours.

Clients from Australia who need to reach out to a company in the United States should not have to wait until the company opens to communicate with them or their chatbots. AI-powered chatbots allow companies to answer queries in real-time. As chatbots gather information from users, they can improve their interaction with customers and give customers what they need when they need it.


AI is helping marketers bridge the gap between the product and service they offer and their audience. It can take massive amounts of information and compile it into something insightful and useful. This improves customer experience, which improves revenue for a business.

Essentials For Your Digital Strategy: Infuse AI In Customer Experience

Essentials For Your Digital Strategy: Infuse AI In Customer Experience

Without a doubt, AI has drawn a mixed reaction from enterprises and consumers alike. Yet, it’s also true that it is steadily reshaping the structure of the world as we see it. While all industries are impacted by the AI revolution, at present, its biggest footprint lies in the customer service sector.

Read on to find out how AI identifies customer goals and requirements to build a solid digital strategy for any business and how you can implement it in yours.

How AI Drives Customer Experience

Artificial intelligence has come a long way from being a trend to a necessity and now a norm. Since the first lockdown in 2020, we have noticed a shift in consumer behavior. The doubt and ambivalence towards AI solutions have now been overridden by the advantages it offers, viz. quick resolution and efficient task management. And don’t take my word for it — a rather recent Salesforce report claims that 87% of consumers now expect companies to expedite their digital capabilities given restrictions imposed in the wake of COVID-19.


Now, the question is no longer whether AI can get widespread adoption but rather how it improves customer experiences as it goes mainstream. Let’s take a look at some of the ways in which your employees can directly benefit from AI (this indirectly improves the customer experience).

ML Improves Search

We’ve already seen this on search engines like Google — when we ask a question, and we’re presented with alternative answers and suggestions of other similar questions in the same domain. “People also ask” is actually machine learning at play, and considering this, the intelligence behind search can further be used to improve the efficiency of intranet applications. For whatever questions you may have, the search tool will connect your workforce applications and dig for a set of solutions. For instance, if you ask, “How much paid time off I have left?” the search application will realize you’re asking about your balance PTO and connect you to the relevant request process.

Listening Tools Assist Customer Service Agents

Listening tools are advanced AI solutions that help customer service agents by listening to customer conversations. The software can then recommend solutions to the customer or provide information regarding user policies on chatbots and other channels. So, instead of the agent doing all the digging, an embedded AI solution can be useful in querying multiple databases simultaneously, allowing the agent to focus on the customer and reduce the call time.

Identifying Trends From Data

This is yet another mainstream use of AI in improving the digital customer experience at the very root. AI can comb through a mountain of data to identify trends and insights. The data can range from the user interactions on your website to the products being viewed and the searches being made. With the power of AI at your disposal, you can create an entire timeline of interactions users have from start to finish and perform sentiment analysis at scale.

Making Artificial Intelligence The Cornerstone of Your Digital Strategy

AI is one of those technologies that can power your entire digital strategy, including content management, end-point experiences, and everything in between. Its ability to measure customer requirements, read behaviors and detect patterns makes AI the engine running your entire CX game plan. The best part is that getting started with it is far easier than you think.

Data Science, analytics, and customer experience have together given rise to something which is called Big Data Market Research. The idea is simple — instead of experimenting with bigger projects with rather expensive and risky cycle times, you can work with shorter sprint cycles. Ensure your data scientists and subject matter experts from your CRO, SEO, and digital and social media teams collaborate to achieve the desired results.

According to a Salesforce study, 65% of businesses and 52% of consumers are most likely to switch brands if the vendor doesn’t personalize communications or fails to understand their requirements. Again, a long wait time for customer support can also force the customers to look for other options.

Various businesses have invested heavily in developing a CRM data center that records every interaction the consumers have with their brand. Doing this helps them understand the expectations customers have with their brand at every touchpoint throughout the customer lifecycle.

AI-Powered Digital Marketing In Business

As artificial intelligence continues to advance, so will its credibility in turning the way we imagine digital marketing. Here are a few practical approaches in digital marketing where AI is indispensable. 

Email Marketing

AI helps to personalize email marketing campaigns at scale by making adjustments based on user behavior. So, your emails can be triggered based on certain user actions ensuring that the content is always relevant and thereby maximizing results. The very same tech can help you analyze and optimize your campaigns instantly, which might take you weeks manually.

AI Chatbots

With the consistent development of natural language processing, voice conversion technology, and AI semantic recognition, customer service has a new face. For starters, AI chatbots have made one-on-one customer service optional by offering 24/7 instant support to all users in any time zone.


Chatbots can be linked with your enterprise knowledge base to answer all the commonly asked questions in real-time. In addition to that, customers can converse in a language of their choice. If the issue is more complex, the service can escalate the issue to the proper service department and if they are unavailable, ask the user to wait until they return during the working hours.

Content Marketing and Digital Advertising

Back in 2018, the digital ad spends worldwide was estimated at nearly $273.29 billion. By analyzing user data like demographics, interests, age, gender, etc., AI has revolutionized digital advertising. Viewers now receive largely relevant adverts, thereby improving the performance of the campaign. This goes beyond ads too. Through the same collected data, marketers get a better understanding of the best kind of content for their audience. This includes not only the domain and the genre but also the kind of content (textual, image, and video).

Parting Thoughts

AI is far out of the age of discovery and research when scientists experimented with deep learning to find patterns and make predictions. This is the age of implementation where entrepreneurs and engineers use the technology to transform how businesses function, especially in customer service and CX.

While largely responsible for influencing customer decisions, it is one of the greatest means at our disposal to deliver quick and irrefutable customer service. Including AI in your digital strategy is one of the single best decisions you will make to meet customer expectations and accelerate the growth of your brand.

Author’s Bio: Srushti Shah is an ambitious, passionate, and out-of-the-box thinking woman having vast Digital Marketing exposure. She is working as a Digital Marketer and Content writer at Acquire. Her key focus is to serve her clients with the latest innovation in her field, leading to fast and effective results. Working beyond expectations and delivering the best possible results is her professional motto. Other than work, she loves traveling, exploring new things, and spending quality time with family. Reach out to Srushti Shah on Twitter or LinkedIn

Artificial intelligence breathes new life into content marketing

Artificial intelligence is about to change the way we get our content marketing fix. Why? Because AI helps businesses develop better content without all the hard work. AI has some useful skills in creating engaging content, making it easier for marketers to do their jobs. The power of artificial intelligence can see the habits of the readers of your site and tell you which piece of content perform best is what AI harnesses the most.

What are the challenges marketers face when developing content that draws readers in?

1. Understanding your audience

2. Meeting the needs and interests of your audience

Discovering what content is interesting to your target audience is critical for a successful and engaging content marketing strategy. Once you know exactly what your audience wants, you can create content that meets their needs and interests. And the more targeted your content it is, the more likely readers will be to engage with it.

How artificial intelligence helps develop engaging content

Artificial intelligence not just helps you understand your audience and their needs but also enables you to reach out to them so that they engage with your brand. It becomes a real-time marketing tool. AI is all about making customers feel special by providing them with instant engagement—if you know your customers, the inPowered Content Marketing Platform can help you deliver content they actually want to read. That's why it's important to consider your customer and what they expect from your brand when creating content.

AI can help market the right things to your target audience and deliver just-right content that immediately engages them.

What are some of the benefits of using artificial intelligence for content marketing?

1. Reach more customers

2. Deliver targeted content that engages customers

Artificial intelligence can make it easier for businesses to connect with their target audience, creating engaging content that specifically addresses their needs. The more specific and targeted a marketing strategy, the more likely it will reach a broad audience. This helps businesses reach and engage with their customers on a deeper level. Tapping into a wider audience means that businesses can build their brand through more than just word-of-mouth.

The most significant benefit of artificial intelligence is that it helps businesses create engaging content. Content that's engaging is content that connects with customers, shares their feelings, and relates to them on a personal level. When you create content that understands your audience's needs and meeting them, your brand will become a trusted source of interesting information.

How do you know your target audience?

Identifying your target customer is the key to delivering content that they actually want to engage with. You need to set up a profile for each of your customers or target audience. This will help you refine your content to speak to your target audience's needs and interests.

So, how do you know your target audience? You can conduct market research to find out if you're hitting the right tone. Check your website analytics to see what content is most popular with your readers. These will give you a basic idea of what your target audience wants to know about.

If you're not sure where to start, investigate your competition's content. Look at what they're talking about, and see if they talk about the same things as you. Focus on the types of content they're producing. This will help you figure out if your target audience is interested in content similar to what you want to create. Once you've identified your target audience, learn more about their needs and interests.

AI Is Changing Businesses

7 Ways AI Is Changing Businesses

Artificial Intelligence (AI) can get a negative reputation for being perceived as stealing jobs, but in actuality, it has the potential to aid current employees and open new job opportunities in multiple industries. Here are seven ways AI is changing business.

1. Improving Employee Hiring and Retention

AI applications can improve the hiring process by helping hiring managers sift through job applications more quickly and efficiently. Some of these programs search out specific keywords and phrases in resumes that match what the hiring manager is looking for. Other, more sophisticated programs are capable of matching applicant profiles in a company's talent system with jobs that are good potential fits for that profile. AI in talent management doesn't stop after an employee is hired, though. It can also be leveraged to improve employee retention. Various programs are able to monitor and analyze employee behavior and feedback to construct strategies meant to improve individual and team performance.

2. Enhancing Security

Cybersecurity is one of the most common applications for AI currently. These programs can be taught to recognize and monitor suspicious behavior and automatically flag that behavior for review in case of fraud or hacking attacks. The learning abilities of AI are particularly useful, as these programs can be capable of keeping up with the evolution of cyberattacks. AI security doesn't just apply to protecting device data either. You can use AI to monitor physical security systems, operate cameras or review audio-visual data for suspicious behavior. For example, there are AI products available such as a vehicle camera system that can alert drivers when they're distracted, coach drivers to improve performance in real-time and send video feeds to managers to monitor driving hazards someone might come across.

3. Improving Customer Relations

Currently, one of the most popular uses of AI in customer relations is the chatbot. However, AI in customer relations is continuously increasing in popularity. Chatbots continue to improve in speed, efficiency and dynamic customer interactions. New programs are being developed which will leverage AI programs to provide customers with accurate insights and product suggestions and to be able to answer specific questions and concerns rather than just routing the issue to a customer service associate.

4. Streamlining Workflows

AI is already being utilized to streamline workflows and take the pressure off employees to perform repetitive low-priority tasks constantly. With AI taking over such tasks as entering and analyzing data, scheduling meetings and appointments and providing simple customer service,  employees are able to spend more time focusing on high-priority and highly creative tasks such as program coding, marketing strategizing and product development. AI streamlining also applies to supply lines. Automating production, packing and distribution can significantly enhance the accuracy and efficiency of your supply lines.

5. Enhancing Informed Decision-making

Because AI programs are capable of quickly and accurately entering, sorting and analyzing data, they are also able to compile their analyses and interpret them. These results can be applied to personalize customer insights and improve marketing campaigns. These insights can also be turned inward. You can apply AI data analysis to your resources, production, budget and other financial information such as taxes. Then, you can use those analyses to adjust your workflows, cash flow and budgetary allocations.

6. Improving Smart Technologies

In the consumer market, smart technology is becoming increasingly popular. There are virtual assistants, smart televisions and security systems and the now commonplace smartphone. All of these technologies leverage various AI applications and programs. Assistive AI technologies can also be applied by businesses. Smart technologies can leverage the Internet of Things to help employees increase their workflows' efficiency. AI can help employees connect more easily when they work remotely, as well. There are applications available that help employees filter out audiovisual distractions during meetings, as well as to improve audiovisual quality.

7. Increasing Mobile Connections

Every year, the use of mobile devices to connect to businesses increases. This goes for both customers and employees. Customers are becoming more likely to check accounts via apps and mobile devices. While employees still tend to do most of their work on traditional computers, mobile access for phone calls and meetings is becoming more common and reliable. AI and machine learning programs can provide businesses with insight into trends in mobile device usage and with strategies to take advantage of those trends.

As AI technology improves and increases in prevalence, it will continue to instigate and accelerate change in the business world. Its uses continue to diversify and AI and machine learning programs can be found in nearly every industry.

5 Ways to Optimize Your Content Strategy Using AI

Content marketing continues to be highly beneficial to businesses that want to grow online. It raises brand awareness, builds authority and credibility, creates loyalty and trust so that your business is an expert in its industry. 

However, with approximately 409 million people viewing more than 20 billion pages each month, businesses are finding it harder than ever to cut through the noise and provide content that truly resonates with their audience. And yet, if you don’t manage to do this, your audience will turn to another brand for the information they are searching for.

This is where artificial intelligence AI comes in -- most (80%) ahead-of-the-curve business execs who use it say it’s helping them already. You may not have thought about this, but AI can help you improve every aspect of your content marketing efforts, from strategy to creation. It can help you ensure that your content engages and converts your audience for higher ROI. 

In this article, we’ll look at 5 ways to optimize your content strategy using AI. 

1. Perform A Competitor Analysis 

Why should you study what your competitors are doing? 

Analyzing competitor content, performance, and distribution highlights gaps in your own content marketing strategy whilst showing you what marketing strategies and tactics your competitors are implementing (and making huge gains). 

Once you’re armed with this information, you can then reverse engineer what your rivals are doing, and create content that your audience wants to read.

Moreover, you can take what you’ve learned from your competitors and make your content better than theirs, simply by spotting any weaknesses they have. 

Perform a competitor analysis by using an SEO tool that’s powered by AI, such as SEMrush’s Competitive Research Toolkit. It collects data on your rivals' traffic sources and other content marketing efforts and then pulls all of the information into a dashboard for you to research and then take action quickly and seamlessly so that you can outperform your competitors. 

Another tool you can use for competitor analysis is using Advanced Web Ranking's Market Share dedicated module. This shows you the percentage of your Estimated Visits, from the total that top 20 keywords in your project can generate.

The nicest part is that you get all these metrics calculated exactly for the keywords you're targeting for your content. More than that, you can narrow the analysis to keyword group-level.

This analysis will make it easier for you to spot new competitors you might not be aware of and keep an eye on them from that moment on. You can also discover keywords for which your competitors are ranking that you might wish to optimize your website for.

2. Perform Research Using Chatbots & Other Tools 

What topics interest your audience the most? What are their pain points and challenges? 

Unless you know the answers to these questions, you’ll be producing content that does not interest your readers. 

You can, of course, research your audience manually, and you can use tools like BuzzSumo to generate content ideas. But this takes time and effort, and it’s not always accurate. A much better idea is to use AI-powered tools that allow you to generate data-driven research and feedback. 

For example, you can use social listening tools that give you insights into what your target audience is talking about on social media. You can “listen in” on conversations they’re having about your brand and your current content, as well as what problems they’re currently experiencing. 

You can also use chatbots to learn more about your audience. Chatbots are essentially messaging software powered by AI. They interact with your site visitors when they land on your page, asking them questions, recommending products, and solving any problems they have. Over the course of a conversation, the chatbot gains data that you can use to understand more about your customers, and therefore provide content that addresses their core pain points. 

3. Create Topic Clusters Using AI

What are topic clusters and why do they matter? 

A topic cluster is a group of web pages that are linked around a connecting topic. 

For example, a topic cluster will always contain one pillar page, which is the main topic page. It’s usually the longest, most in-depth, evergreen, and discusses a key topic that your audience is interested in. For the sake of illustrating a point, let’s imagine this is digital marketing. 

Your topic cluster will then also contain several subtopic pages that expand on a particular topic within your main topic. In our example, these pages will be centered on social media marketing, content marketing, SEO, and more. Each of these pages links back to your pillar page, thus creating a topic cluster. 

Topic clusters are important because they demonstrate to Google that you’re an expert on a particular topic. You’ve covered all the bases and you’re delivering lots of value to the end-user. They’re also important for SEO reasons as they allow you to get more juice out of keywords.

To ensure you’re creating effective, high-quality topic clusters, you can use AI.


AI tools such as Hubspot’s content strategy tool show you possible topic clusters that will send more organic traffic to your pages. This will help you increase your reach with the right audience, whilst allowing you to improve your search authority.

4. Use AI To Optimize Content 

Optimizing content for discoverability and readability is essential when your audience has so much content available at their fingertips. If your content isn’t optimized, search engine users will view your competitors’ content instead. 

If you don’t have the time to go through each piece of content with a fine-tooth comb yourself, you can use AI tools such as Atomic Reach. Atomic Reach automatically rewrites difficult-to-read sentences to words your readers are familiar with. 

The tool edits the content based on recommendations from historical content and its engagement metrics. Other edits it can make will be around readability, length, language complexity, vocabulary, and emotional tone so that every single article to publish is designed to maximize a desired response from the reader. 

5. Let AI Generate or Design Content By Itself 

The idea of letting a machine create our content for us sounds a little bit daunting. However, in 2020 AI is now able to automatically create smaller pieces of content by using data and transforming it into an insightful narrative. 

Indeed, you’ve probably read AI-generated content without even realizing it. Companies such as Yahoo who has used Wordsmith to generate 70 million reports and match recaps.

It’s ideal if you’re in a hurry and need short content creating quickly, but don’t have the time to do it yourself. 

If, however, you’re not keen on the idea of letting AI generate content by itself, you can at least let it assist you with the content creation process. For example, a tool like Cortex is able to accurately predict how your target audience might connect with your content. It suggests ways of optimizing content via image placement, themes, colors, structure, and so on. This allows you to boost customer engagement rates, and thus conversions.

And, on the web design front, you can take advantage of UI kits to automate the creation of graphic elements and other components of the user interface. Essentially, these can help you automate wireframing and save countless hours of your time.   

Wrapping up 

AI is here to help companies transform their content marketing efforts into a high-converting, well-oiled machine. When companies start utilizing the content marketing tools that it powers, they will be able to better research their audience, build a solid content marketing strategy, and create content that improves brand awareness and ultimately boosts sales.