How Artificial Intelligence is Enhancing Customer Experiences
AI Customer Experiences

How Artificial Intelligence is Enhancing Customer Experiences

Artificial Intelligence (AI) can no longer be ignored in the digital age. Businesses need to understand how AI works. AI programs and services can transform virtually every aspect of a business.

Automated processes and artificial intelligence are deemed the most significant technological advances of the century. Modern companies are now using artificial intelligence and machine learning to transform interactions, relationships, revenue, and services. 

Approximately 51% of companies now use artificial intelligence to improve customer experiences and hyper-personalize them. A good customer experience can be achieved with the use of customer service applications.

What is Customer Experience?

Making a purchase, using a product, or receiving a pop-up message all start the customer life cycle. It can also include contacting customer support or using the product. In general, the better the customer experience with a brand, the more likely they are to continue using and recommending it. Net promoter score is essentially a measure of customer satisfaction. 

Customers who have positive experiences with a brand tend to buy from that brand again. As companies strive for positive customer experiences, they are increasingly relying on artificial intelligence.

As a result, marketing departments are no longer required to manually segment audiences, write campaigns, or respond to communications from customers personally. These activities can now be assisted by AI.

AI’s impact on customer experience

1. Customer understanding is facilitated by AI

Brands can gain a much more accurate understanding of their customers by combining automatic learning and AI to gather social, historical, and behavioral data.

AI software is continuously learning and improving as it analyses data and can anticipate customer behavior, unlike traditional data analytics programs. The result is more relevant content, more sales opportunities, and a better customer journey.

2. Increasing sales and customer satisfaction

The use of artificial intelligence is becoming increasingly prevalent as companies look to maximize sales and customer satisfaction. 

A customer may see ‘recommended’ products while shopping online, for instance. To increase conversion and sales, brands can utilize clustering algorithms to provide better recommendations.

The same goals are being sought by these AI systems: to maximize purchases, sales, and customer satisfaction. The store, however, should not recommend products the customer does not like, since the customer is likely to return or not buy them.

3. Making real-time decisions and predicting behavior

A real-time decision is one made with near-zero latency by using the most current data available, such as data from current interactions between a customer and a business. 

The decision-making process can be used to market to customers more effectively using real-time data. Customers who use ad blockers can be identified in real-time and offered alternative UI components that keep them engaged.

One aspect of personalized recommendations is presenting customers with more relevant content. AI and real-time decision-making can optimize the experience of brands by recognizing and understanding customer intent as they produce data, in real-time.

4. The age of the AI chatbot is here

Customer service (via chatbots) is the leading application of artificial intelligence deployed today, according to an MIT Technology Review of 1,004 business leaders. As many as 73% of respondents believe companies will use AI for sales and marketing by 2022, followed closely by other departments at 59%.

Final Thoughts

The use of AI in customer service provides easy, efficient solutions. By harnessing big data and customer information, AI can help deliver a great customer experience. 

Customers will be effectively served if a customer service center is AI-based. Competitiveness can be improved with AI solutions. To gain the trust of your customers and increase loyalty, contact us at Byonic.AI. 

Unleash AI to Improve Your B2B Email Marketing
Article is about How to Improve B2B Email Marketing with AI

Unleash AI to Improve Your B2B Email Marketing

There are countless strategies that marketers implemented in their campaigns in order to see more conversions. With that said, the most popular and useful method continues to be the email with 91% of marketers saying that email marketing is essential in their efforts. This means that the focus of any campaign should be to improve email marketing.
  1. Use AI to optimize your subject lines

When a person writes a subject line, there is always an element of bias, not to mention a lack of resources to generate the best outcome. Even expert copywriters will write subject lines with many limitations that can severely hinder the results of the email campaign.This can often lead to content that is not going to be hitting the inbox and is destined to make its way to the spam folder. When this happens, your chances of engagement are completely ruined and your campaign ends up being a very frustrating experience.Using Artificial Intelligence for this purpose is going to help generate subject lines based on pattern matching. AI will make use of algorithms that are going to help generate optimal subject lines depending on your niche and product.
  1. Upgrade email personalization

One of the biggest pitfalls of email marketing is the lack of personalization involved. When people open emails that look like templates, they are very likely to lose interest. With that said, it can be hard to personalize bulk emails due to how long this task would take and how many resources would be required.You can forget about this time-consuming task with the use of Artificial Intelligence. The way that AI handles predictive analytics with the use of customer data and complex algorithms is enough to generate optimal product recommendations, headlines, and many other aspects of your email messages.
  1. Optimize the timing of your emails

The exact time of the day when your emails are most likely to be seen by your potential customers is very difficult to determine. Marketers would usually have to resort to experimenting and split testing in order to determine this factor. This would usually mean spending weeks and even months just trying to find the best timeframes to send their content.When you implement AI into your efforts, you will be able to determine the click volume, the open volume, the best time to send emails, the best days to send emails, and all of this will be customized depending on your target industry.It is important to note that over 90% of marketing emails that receive any clicks are sent on weekdays. This means that the weekend are less likely to be a good time to engage most audiences. It is also notable that the highest engagement was found right in the middle of the week. This means between Tuesday and Thursday.

Final thoughts

AI has become a major component of most successful digital marketing strategies. It saves time and it helps your entire team maintain a more productive flow of work. We gave you 3 of the most essential and useful ways to use AI for B2B email marketing, but the advantages it brings are vast and the ways in which AI can be implemented are growing in numbers as this technology continues to see constant upgrades.It is essential to find quality assistance to help implement new strategies that strengthen your campaigns. Start using AI to boost your email conversions by scheduling a call with the sales team at Byonic.AI today.
How AI Can Accelerate Your B2B Buyer Journey
ai buyers journey

How AI Can Accelerate Your B2B Buyer Journey

Machine learning and artificial intelligence have allowed us to anticipate the behavior of the consumers by analyzing the data stored through sales and interaction on social media networks. Artificial intelligence and machine learning do not only increase sales and reduce man work but also improve the b2b buyer journey.

Artificial intelligence bots can optimize the communication with the leads and prospects to ensure that the answers to all the queries of the consumers are relevant and on time.

Fast interaction with the customer matters

Did you know that more than 53% of the customers never open the website or decide to abandon it if your website takes more than three seconds to load? Quick response to the customer’s query is essential in enhancing the experience. Nowadays, the market is quite saturated. Therefore, the customers don’t wait for you to respond. Instead, they find your company’s alternative in the meantime.

The worst part is most of the competitor companies have your leads’ information. They can call your potential customers and take away your sales.

You are likely to miss customers and sales opportunities unless you respond quickly and in real-time. But how do you grab sales opportunities actively for 24 hours in a day? Simple; AI is the solution to your problem.

Let’s say you work for a clothing brand and someone requests for the store timings in his/her neighborhood. Now, the artificial intelligence assistant on your website or social media messaging app could provide basic information about the nearest store timings in a friendly and conversational manner. Moreover, a Chabot could even email the live location or map to the customer.

The AI assistant on your website will not only upgrade your CRM as per the new information on leads and prospects but will also nurture the leads by engaging in a conversational manner.

Once the customer is satisfied with the initial conversation, a connection could be built and personalized follow-ups from your customer representatives could lead the customer to the sales funnel.

However, the parameters for lead engagement are quite different for every company. An AI assistant can easily identify potential leads, answer queries, respond to quick requests and even handle objections. When the assistant has handled the initial communication with the customers, you can hand the follow-up to human representatives.

Artificial intelligence supporting your marketing objectives

AI truly nurtures and supports your marketing objectives by handling customers, engaging prospects, and carrying out conversations 24/7.

AI Chat and email bots can seek specific information on customers, set up an appointment for your clients, and even carry out a smooth marketing journey.

Apart from conversing, AI assistants can also perform reporting and analysis on the marketing strategy. With the help of AI, you’d be able to optimize and run a successful marketing campaign.

AI in marketing is important

Time is of the essence in an organization. However, artificial intelligence does not only optimize your buyer’s journey but also saves a lot of the time that you spend in optimizing sales and marketing strategies. More than 72% of the businesses in the survey agree that AI has played a significant role in reducing work. This has allowed the teams to concentrate more on methods and non-mundane tasks as bots carry out all the repetitive and basic tasks.

How does AI influence the B2B buyer’s journey?

AI can transform your buyer’s journey in the following ways:

Create audience awareness

Artificial intelligence has the ability to target the customers who might want your products and services. This allows you to create buyer personas based on potential customers.

Create interest in your products

Your automation system delivers great information and insights on your products and services. Bots might show research to introduce your product in the market. Moreover, you could also use them to encourage people to sign up for your webinars and newsletters.

Audience considers your products

The consideration stage is where you send personalized messages to the potential customers who are already engaging with your brand.

Evaluate your products

Evaluation is important as customers are keen on comparing prices, weighing pros, cons and finding alternatives. In this stage, it is important to show why they should choose your product over other products in the market.

Interact and promote your products

Once your customers have completed the funnel stage, you could bombard them with satisfactory messages.

Artificial intelligence improves customer experience

Artificial intelligence allows us to focus on high-quality leads by exceeding customers’ expectations. More than 75% of the marketers lose sales because their leads never convert. However, 61% of the businesses agree that artificial intelligence is now one of the most important aspects of their marketing and sales strategy.

Final Thoughts

Artificial intelligence has a long way to go because it has just started. But you can make the most out of it by automating your marketing campaigns and B2B buyer’s journey.

To learn more about artificial intelligence can help move the buyer’s journey of your B2B customers, connect with the team at Byonic.AI.

5 Effective Lead Nurturing Tactics Using AI-Based Tools
lead nurturing tactics

5 Effective Lead Nurturing Tactics Using AI-Based Tools

In recent years, AI has had a revolutionary effect on the marketing world. Harvard Business Review research says AI can increase lead generation by 50 percent and reduce costs by 60 percent. This means it can also increase revenue for businesses.

In addition to that, businesses can analyze and interpret the vast amounts of social media data that exists on the internet today. AI-based tools can provide companies with eye-opening insights about consumers, which leads to considerable improvements in lead generation. Businesses today have access to powerful social analytics and CRM tools that utilize customer behavior to maximize ROI.

What is Lead Nurturing?

In lead nurturing, information and resources are provided to your potential customers at every stage of the buyer’s journey to engage, support, and build relationships.

While some leads generated by your marketing team are ready to buy, many will have some questions and concerns about your product or service, and therefore lead nurturing is necessary to help them move from the awareness stage to the decision stage. 

Artificial Intelligence for Lead Scoring

Lead scoring helps marketing and sales teams avoid wasting time on inactive leads. An individual lead’s importance is ranked according to what action they took in the sales funnel. This is known as lead scoring.

Some companies score leads based on points earned from different actions. If a demo of a product is available, for instance, then sign up for the newsletter may be more beneficial. A lead’s priority is determined by the points it accumulates. Traditional scoring models are not used by everyone. 

The predictive lead scoring approach uses aggregated data to predict a lead’s value in advance through an algorithm-based model.

Effective Lead Nurturing Tactics

1. Content targeting can be leveraged

Lead nurturing isn’t the same for all companies. Enhanced results can be achieved by nurturing leads with targeted content as the research shows. 

Understand your buyer personas by working to identify them. Using this information, you can then craft an assortment of content sites based on the characteristics of each persona, such as their interests, goals, and objectives.

2. Paid Ad campaigns that are laser targeted

You can use AI-based solutions to break down your social media data into vital and reliable target lists. This grouped list of prospects can prove vital for your paid ad campaigns. 

Various social media platforms such as Twitter, Facebook, and Instagram make it possible for businesses to upload customer lists they intend to target precisely. By uploading the lists created using AI-based means, you can greatly reduce your CPA and increase your lead generation rates.

Besides, you can use social platforms to generate lookalike audiences according to your data. This audience is made up of consumers that have similar qualities like gender, age, demographics, profession, and interests with your current customers. This is again a great way of locating target customers that’ll be particularly interested in your brand.

3. Send personalized emails

One highly effective method of nurturing leads is email marketing- and how personal those emails are have proven to produce better results. According to research by Accenture, 41 percent of clients switched businesses because of a lack of personalization.

You can personalize your emails in several ways to improve your lead nurturing technique. It is possible to send triggered emails when a web visitor does something like downloading content, clicking a link, visiting a particular page on your website, or spending more time on your site. 

4. Separating prospects

Consumers of different ages, professions, demographics, and cultures regularly consume social media content. Therefore, it can be challenging knowing and narrowing down the potential list of people that’ll be the best fit for your business.

Businesses can create highly targeted and hyper-personalized ads, content, and emails to improve lead generation by using their segmented lists.

5. Higher brand awareness

Social media data is broad and spread across different platforms. It is difficult to manually organize data, analyze it, and design campaigns on it to increase lead generation.

Tools that are based on artificial intelligence collect data, information, and metrics of social media engagement in one portal. So, anytime a user engages or makes contact with your business, the data will be kept in your analytics tools.

Conclusion

Since a lot of buyers will not buy your product or service from the first point interaction, you need lead nurturing to facilitate a more personalized approach that increases your chances of conversion. The goal is to create and nurture a relationship with every prospect through honest interest and progressive trust. 

To learn more about demand generation marketers are using AI tools for effective lead nurturing results, connect with the team at Byonic.AI.

Ethical Considerations for Artificial Intelligence
Article is about ethical artificial intelligence

Ethical Considerations for Artificial Intelligence

A revolutionary change has come into existence in our society due to the rapid growth of technology. Tech experts are trying to invent new robotics and machinery to perform specific tasks that humans cannot achieve accurately. Artificial Intelligence is one of the consequences of these attempts.

What is Artificial Intelligence?

John McCarthy was the first person who uses the term “Artificial Intelligence” in 1956. It is actually a replacement for human intelligence. It performs various functions with its complex computer algorithm system.

Machine learning and deep learning are the two main applications of artificial intelligence. Many other applications of artificial intelligence are also continuously performing several prognostications of different diseases in the medical field. Google translator, face identification in-camera, receive online orders, and approve credit card transactions are some other usages of AI.

Ethical Concerns

For using AI, you should know about its ethical concerns. Many instructions and admonishments are dickering with the problem of ethical artificial intelligence. The European Commission has brought out significant guidelines for ethical AI. The prime focus of its suggestions is principles of ethical artificial intelligence in the medical industry. Let us discover all principles one by one.

1.      Philanthropy and non-sensuality principle 

If you are using artificial technology, you need to be aware of its ethics. To preserve human dignity, you make sure that AI is beneficence for individual patients in the field of medicines.

The process of prognostication can defile the guidelines of ethical artificial intelligence because it gives false hope to patients. You can get rid of this puzzling situation by keeping information personalize. After the deep analysis of the report of a patient provided by the AI technology, describe a patient’s condition. It can be very valuable to escape from probabilistic and unethical AI methods.

Recurrent ANNs are using the new techniques of Artificial Intelligence. They are utilizing more probable information through their datasets. If a person is in the Intensive care unit and his condition is not stable, doctors use ethical AI to predict his state. It proves very beneficial for individual patients.

2.      Equality Principle

Unintentional injustice is a significant drawback of AI technology for individuals. The algorithm system of AI technology can lead the issues of inequalities and discrimination among different patients. The two main problems present below.

  1. There are many chances that AI algorithm yields fake results. It can mention the rare life probabilities for those patients related to discriminator biomarkers like the weight of the patient’s body. If you continue to detect, test and audit the AI results, you can quit this AI risk.
  1. Different cultures drive cultural biases. Humans train artificial intelligence model. So, there are many chances that they accidentally build an algorithm that affects specific community and environment.  

The problems mentioned earlier can solve if training of AI models excludes age, gender and environmental changes. For the establishment of patients’ health and dignity, you should train unbiased AI models. It will help to accurate prognostication of the course of any disease and supplies justice among patients. 

3.      Autonomy of patients as an AI principle

The respect of patients’ decision regarding their critical condition is necessary for the ethical use of AI technology. Sometimes, the decision of a patient and his caretakers creates a considerable risk of a patient’s life. This situation leads to the ethical examination of personal behavior.

If you predict patients’ health through AI technology, you need to know that it may be a false report. If you try to solve this falsifying state of a patient, it will not be possible through artificial technology.

According to the empirical research, the patients do not fully trust the physician’s probabilities because they estimated results through AI. So you should present possibilities of recovery in such a way that prove non-maleficence and beneficence for patients.

If you disagree with your patient decision, AI cannot be able to resolve your issue. You can find the solution to this issue by mutual agreement. You can discuss prognostications with your patient for getting approval of your point of view.

4.      Explicable principle

The principle of explicability is recently added to the list of ethical artificial intelligence in medical science. It is interlinked with all other AI principles.

Often, we face issue in the results of different patients’ cases. Actually, it happens due to the uncompleted input to AI models which are providing output.

Doctors handle the algorithm tools as “black boxes,” if they are not aware of the step of critical reflection. After analyzing the prognostication provided by the intensivists, a patient can appeal to justify the result. A patient can take this step if they feel trust issues regarding the probabilities of their report.

Some data science experts say avoiding AI technology if you want to build patients’ trust and get the authentic information. If you are still willing to use ethical artificial intelligence, test your AI models timely. It will help you to avoid inadvertently false prognostication.  

5.      Confidentiality 

Privacy is still an essential aspect for humans. When you are dealing with patients, you will definitely use their data in your AI algorithm system. So you need to care about the sensitive information of your patients.

Human rights are a crucial part of the constitution of any country. In Europe, General Data Protection Regulation (GDPR) adds new guidelines regarding data processing for ethical artificial intelligence technology. These instructions guide you to avoid the unethical use of artificial intelligence.

Final Thoughts

The sole purpose behind this article to inform you about ethical artificial intelligence. The abovementioned ethical considerations show that AI is an important technology that provides comfort in our lives through probabilities and has some drawbacks in the medical field too.

If we further improve and refine this artificial intelligence system, there is no doubt that it will provide error-free prognostications about the disease of the patients. AI model can become the correct element in the intensive care unit of any hospital. But we should implement all these artificial intelligence principles with the legal ethics of medical science.

How AI and Intent Data Work Together
how ai and intent data works

How AI and Intent Data Work Together

AI is revolutionizing the world. It reduces costs through automation, and for some companies, it enhances customer experiences. AI can be used everywhere; especially, it helps in the B2B industry. AI and Intent data work together for the advancement in data collection to analyze true customers’ intent. In intent data, AI can be used for content processing and analysis.

Many corporations have used AI to automate processes, but those that use it mostly to replace workers would only see short-term improvements in productivity. Our research, involving 1,500 firms that found Humans and Machines working together, produces the most important performance improvements and a better understanding of customers’ preferences.

Despite advancements in data collection around shopping habits, companies still struggle to create better customer experiences. But Artificial Intelligence is rapidly taking over this smoothly and making it easy for firms to understand consumers’ intent.

Traditional analytics software, which is struggling to keep up with the fast-changing technology world, is still behind AI. Consumers today are constantly connected through numerous devices, making paths to purchase more like Gordian knots rather than straight, well-behaved lines.

Expanding the Usefulness of Intent Data

However, since intent data is still a relatively new tool, it comes with some challenges as its usage spreads rapidly across revenue operations. Companies want to normalize data from various sources and handle data handling across departments more effectively.

Here, we will discuss the AI (artificial intelligence) intent data on b2b marketing:

  • The current impact of intent data on B2B revenue operations
  • The growing number of business use cases for intent interoperability across strategic areas,
  • The challenges that many companies face when it comes to handling and incorporating intent data
  • Moreover, there are opportunities to improve productivity and increase the impact of purpose data.
  • More detailed buyer personas
  • More enticing deals that result in conversions
  • Email campaigns that are well-personalized
  • Landing pages that convert effectively

Marketing methods for artificial intelligence (AI)

It filters through the false positives and removes them, saving marketing teams’ time and effort. It reveals the false negatives – businesses that suit a marketer’s ideal consumer profile but did not appear on the intent data list.

Insight of Powered AI that Building a Smoother Path to Prospects

Getting intent data is like having a single piece of a 1,000-piece puzzle. The rest of the picture is provided by Marcom software that uses AI and machine learning. Although purpose data reveals one dimension of corporate activity, AI Marcom solutions can detect and categorize hundreds more. AI analyzes more than 40 billion data points to create more than 400 detailed corporate characteristics, such as the company’s products and services and the problems the company is trying to understand and solve for consumers.

The AI tool then creates “lookalike” profiles that fit sellers’ ideal customers in terms of scale, budget, and readiness to buy, as well as any other ABM-related metrics.

Multiplying the Number of Ideal Prospects with AI-Powered Insight

AI targeting tools show various businesses that might never appear on intent data lists, in addition to finding the best customer matches from the intent data. Many more companies that fit a seller’s ideal customer can be discovered using AI research. These businesses do not engage in internet searches that appear on purpose data lists, but their corporate profiles and recent actions make them potential “best customers” for sellers.

Intent Data Help Companies to Understand Consumers Preferences Better

Intent data is a great place to start looking for patterns that could suggest a company’s willingness to purchase a product or service. It’s only one of the signals that can help advertisers find and target their ideal customers.

By solving the two most significant problems with purpose data, AI-powered Marcom solutions help sellers extend their marketing efforts well beyond it.

As a result, they have a more complete, comprehensive, and reliable list of prospects that are closer to their ideal clients and information to help them communicate with them through tailored messaging.

To learn more about how we integrate artificial intelligence and intent data, connect with the team at Byonic.AI.

What is the Difference Between Artificial Intelligence vs. Machine Learning
Difference between machine learning and artificial intelligence

What is the Difference Between Artificial Intelligence vs. Machine Learning

In the twenty-first century, you’ve almost certainly heard the words “artificial intelligence” and “machine learning.” This is the technology era, and it is estimated that in 2021, 80% of emerging technologies will be AI-based. And, internationally, 37% of businesses are using AI in some way to boost their day-to-day operations.

Amazon, for example, reduced its delivery time by over 225% thanks to machine learning. So, if you’re not sure what these words mean and how to identify the difference between them, we will discuss their significant differences below.

Overview of Artificial Intelligence

Artificial intelligence, or AI, is the creation of a human-made machine mimicking human intelligence. The system has a computerized brain that can learn and solve problems in the same way that the human brain does. AI is achieved by first researching how the human brain thinks and how humans learn, determine, and work when trying to solve a problem and then using the outcomes to develop intelligent software and systems. When all of the ingredients are present, you can think of algorithms as a recipe that the computer must follow.

Artificial intelligence can be divided into three types:

  • Narrow AI
  • General AI
  • Super AI

Overview of Machine Learning

Machine learning is a computer science subfield which is also known as predictive analytics or predictive modeling. Its goal is to create new and leverage existing algorithms to learn from data to develop generalizable services that make accurate predictions or find trends, particularly with existing and new unseen data.

Machine learning, as previously mentioned, uses algorithms to automatically model and find patterns in data to predict a specific output or response. Statistics and mathematical optimization are extensively used in these algorithms.

The process of optimization entails determining the smallest or largest value (minima or maxima). The process is also known as a loss or cost function in the minimization case. Gradient descent is one of the most common optimization algorithms in machine learning, and the normal equation is another.

In a nutshell, machine learning uses learning algorithms and optimization techniques to learn a highly accurate predictive or classifier model automatically or discover unknown patterns in data.

Machine learning is also divided into four different categories:

  • Supervised
  • Unsupervised
  • Semi-supervised
  • Reinforcement

What is the Difference between Artificial Intelligence and Machine Learning?

Artificial IntelligenceMachine learning
Artificial intelligence (AI) is a technology that allows a computer to mimic human actions.Machine learning is a subset of AI that allows a machine to learn from past data without programming explicitly.
Goal: The goal of AI is to make an intelligent computer system like humans to solve complex problems.Goal: Machine learning aims to allow machines to learn from data and produce accurate results.
Scope: AI has an extensive scope.Scope: Machine learning is constrained in scope.
Task: AI builds an autonomous system able to perform a variety of complex tasks.Task: Machine learning aims to create machines that can only perform the tasks for which they have been trained.
Results: AI systems are concerned about maximizing the chances of success.Results: Machine learning is mainly concerned with accuracy and patterns.
Wisdom: AI leads to intelligence or wisdom.Knowledge: ML leads to knowledge./td>
Outcome: Artificial intelligence can evaluate a variety of options before selecting the right one.Outcome: Machine learning will choose the only answer it sees as the best, regardless of whether it is the best.

Final Thoughts

Artificial intelligence and machine learning are both science and mythical inventions. The idea that machines could think and perform tasks in the same way that humans do dates back thousands of years. Cognitive truths expressed in AI and ML systems are also not new. Artificial intelligence is the best and most logical next step in the evolution of computers and technology. Machine learning makes significant progress toward that goal when creating true AI. Moving in the right direction, having a clear vision, and having a distinct and unique purpose can help all of humanity.

To learn more about the variations in AI and ML and how both can be used as tools to advance B2B marketing initiatives, connect with the team at Byonic.AI.

15 Benefits of Artificial Intelligence in Marketing
Benefits of AI in Marketing

15 Benefits of Artificial Intelligence in Marketing

Artificial intelligence is a technology that assists in accomplishing specific tasks based on a computer-based algorithm system. It proves to be at least a partial substitute for human intelligence in almost every field. Marketing is one of those fields which utilizes this type of technology. AI enhances the functionality within companies to meet their marketing goals. From demand forecasting to multichannel reach, AI can be used in multiple ways among marketers and demand generation specialists.

Here, we will discuss 15 benefits of the use of artificial intelligence in marketing.

1. Uncover new opportunities

According to the Narrative Survey, 61% of business executives are using AI in marketing. It reveals new opportunities and predicts the latest market trends with the help of an AI database system in 2016.

Data-driven insight through AI is a helping hand for marketers to innovate their services and products. Without any human assistance, AI executes various more beneficial tasks than those who do not apply artificial intelligence to their businesses.

2. Demand predictions

The report (Sizing the prize) of PwC shows that artificial intelligence or deep learning proves very fruitful for decision-makers to analyze customers’ behavior.

Sentiment analysis uses to explore customers’ likings for a specific product or a service. The foundation of it lies in machine learning which is an application of AI. It tells about the customer preferences and predicts the demands of the upcoming orders from different customers.

3. Meliorating revenue

According to the combined survey of EverString and Heinz, almost 50% of business-to-business (B2B) marketers use some form of AI in marketing. There is a significant role of AI in B2B marketing. B2B marketers believe that it boosts your revenue with its complex algorithm system.

4. Insightful 360 customer view

From marketing to pricing, every company’s activity impacts the increasing or decreasing sales of its company.

So, it is crucial to find the views of customers to get more leads or revenue. For this purpose, companies integrate Artificial Intelligence into their CRM that presents a single view after analyzing and concluding a heavy amount of data.

5. Discover maturity level among your customer bases

By exploring the data of each customer, you can find out the maturity level of any customer. Social networking sites, tools, and apps play an indispensable role to gain insights from customers.

AI in marketing collects data of campaigns, database, and social media reports and prepare a conclusion. Companies analyze this final data and drive sales.

(Also Read: What is AI Marketing?)

6. Convert leads into sales

A company requires not only leads but also sales to get revenue. Without sales, leads are useless for organizations. It is a fact that there is an enormous difference between leads and sales of any company. With the help of machine learning, companies find and target those leads which have more chances of converting into sales.

7. Never miss a sales opportunity

If you want to grow your business, it is super necessary to be proactive and never miss a single chance of sales opportunities.

The needs of customers, the right time to sell, and competitors’ analysis are three main factors to get more sales opportunities. You can increase sales and make better strategies for the future with the optimized data provided by the Artificial Intelligence system.

8. Avert loss of revenue 

Revenue loss is a disastrous hurdle for any company. With AI, you can cope loss of revenue of your company.

You can analyze why customers are leaving your products or services and why they are going to other brands. You can purpose mindful strategies to provide excellent services to your customers with data-driven insights of Artificial Intelligence.

9. Automated lead scoring

Leads score are very crucial for a company. AI automates the process of lead scoring and accurately certifies more leads.

Marketers get their projects done without any strenuous efforts and involvement of humans. All lead scores qualify by machine learning.

10. Data segmentation

It is a process which concise heavy amount with AI. It is one of the proven benefits of AI in marketing. You cannot get these benefits if you use human intelligence.

AI provides deep insights or datasets. You can quickly achieve various marketing goals with the help of AI datasets.

11. Personalization

It is always important to know about your previous customers’ behavior to make them regular customers of your company.

AI draws data analysis based on customers’ sentiments and feedback against your product or service. You get not only lead generation but also the engagement of your customers for your marketing company.

12. Customer behavior

It is no doubt that you can use different sources to know the visibility of customers. Email, Mobile phones, websites, and social media platforms are gaining popularity to find new potential customers for your marketing company.

AI provides support to count the action of your customers too. With a deep learning approach, you can find out the interests of your customers.

13. Personalized user experience

AI is a handful of tools to personalize the experience of users. Many companies use artificial intelligence to get the personalization of users.

For example, Amazon suggests to their customers for purchasing various products by analyzing their previous data or browsing history. It is actually an example of the use of AI in marketing. It would be best to integrate AI into your system to suggest products or services to their customers.

14. Multidimensional reach

There are different sources like messenger, SMS, Facebook, and Email to reach your diverse customers. There is enormous data on these sources. So, it is hard to find valuable data of your potential clients.

AI assists in getting authentic information about your customers. It analyzes the data of each customer for marketers that is a bit difficult for a human.

15. Near perfect timing estimates

If you do not act on time, you cannot get valuable results. With Artificial technology, you can estimate when you should take action and when a response could be expected from your customers.

After judging all marketing plans and datasets, timing is another crucial element to get success for your marketing business.

Final Thoughts

No doubt, Artificial Intelligence draws a remarkable change in the marketing field. The sole purpose of this article is to give information about the benefits of AI in marketing. We hope you get a piece of valuable knowledge about AI after reading it.

To learn more about the benefits of AI in B2B marketing and how you can start seeing results, contact Byonic.AI today for a demo. Schedule a call today.