Category: Blog

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

15 Benefits of Artificial Intelligence in Marketing

Posted on | by Danni White

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.

How to Connect with the Millennial Tech Buyer
Article gives the idea on how to connect millennial tech buyer

How to Connect with the Millennial Tech Buyer

Posted on | by Danni White

With millennials continuing to become the majority within the global workforce between 2020 and 2030, they strongly influence many business decisions. This is extremely true now for technology buying.

A quick takeaway from this is that tech providers need to effectively approach marketing and sales processes to effectively reach millennial minds. This requires an entirely different approach as this audience reacts and behaves differently than other generations.

What Makes Millennial Tech Buyers Different?

To put it simply, millennials are more invested. They care about practicality, authenticity, and trust.

  • Millennials are more tech-savvy compared to baby boomers and aren’t afraid of taking ownership of these processes. They want tools that offer the best in the market and are coping up with the everyday advancement. They want to buy products that can keep up with their pace.
  • Social presence is vital. Millennial tech buyers want to engage with you on platforms they use on an everyday basis. These include social media platforms like LinkedIn and YouTube. If a tech vendor has an established LinkedIn profile with a reliable connection, research has shown that these young decision-makers are more likely to convert.
  • Millennials care about brand personalities. Millennials react to brand narratives and stories. They want to create long-lasting relationships with brands that are more humanized rather than a simple product offering. Tech brands can focus on adding a human element to their marketing campaigns that elude trustworthiness and reliability.

So, What Can a Company Do to Target and Convert Them?

Glad you asked. Here are three ways you can target millennial tech buyers better and gain some conversion along the way: 

  1. Create informative and relevant content

    Before deciding what tech vendors they want to choose, young audiences want to self-research as much as possible. They want information pieces that give them answers easily. Marketers should try using short format content like quick how-to videos or listicle blog pieces over long research papers and instruction manuals.

  2. Build a relationship

    Companies need to focus on establishing and maintain a meaningful relationship with the prospects. Rather than just creating a transactional conversation based on price quotations and sales pitches, try to understand their organizational needs and goals. All communication should have a personalized touch to it to increase customer engagement.

  3. Share real-life impact

    Rather than shelling out purely educational information, focus on diversifying your message. Incorporate product demos and reviews to increase your authenticity in the industry. Research has also shown that industry news and expert opinions can be a high point of influence in the decision-making process for millennial tech buyers.

    Before finalizing your campaign, ask yourself the following three questions:

    • Is your marketing message capable of impacting a millennial audience?
    • Are there enough supporting documents to provide all the information a millennial tech buyer would want to consider?
    • Can the campaign connect to the audience in a personalized manner?

    Armored with information about how to tackle marketing to this generation, do you feel more confident? Remember that millennials are not disrupting your process but rather increasing the likeliness of conversion. All you need to do is create a value proposition in an impactful and meaningful manner.

Want to find other ways to reach millennial tech buyers? Start with an AI-based solution that prioritizes ROI and offers real business results. Contact Byonic.AI today for a demo. Schedule a call today.

The Changing Landscape of Digital Marketing: How Artificial Intelligence Is Shaping Marketing
Article explains how artificial intelligence is changing the marketing

The Changing Landscape of Digital Marketing: How Artificial Intelligence Is Shaping Marketing

Posted on | by Danni White

Artificial intelligence has been around for a while – disrupting every industry, killing many jobs, and creating many more jobs and industries. The impact of AI can be well seen in the field of marketing as well since more and more developed marketing software and martech tools have come into the picture.

Initially, AI was used in e-commerce to create customized experiences for buyers. Now, the situation has changed a lot. According to Salesforce Research’s State of Marketing Study, marketers’ use of AI jumped from just 29% in 2018 to a whopping 84% in 2020. How is it that AI has impacted the future of marketing? To understand this, it is important to know about AI and the areas it impacts marketing.

What is AI Programming?

AI programming is a rather broad term that encompasses all of the various coding languages used to create, train and implement artificial intelligence. While there are quite a few different programming languages that can be used, C ++, Java, Lisp, Prolog, Python, and R are the most commonly used languages.

What are the Core Elements of AI Marketing?

When it comes to implementing AI in marketing, there are a few different elements that are particularly useful. These are:

  • Big Data

    Big data is essentially making use of data mining tools to sort through volumes of data and extract actionable insights from the data. Marketers make use of big data to sort through and manage their databases and create customer profiles that further aid their lead generation efforts.

  • Machine Learning

    Machine learning is a way to feed data into a program and have the code make assumptions based on the data patterns. Marketers make use of machine learning in order to better target their ads to optimize their budgets.

What are the Future Benefits of AI in Marketing?

Making use of AI in marketing has been proven to show amazing results. According to Salesforce Research’s study, 70% of high-performance marketing teams claim they have a fully defined AI strategy versus 35% of their under-performing peer marketing team counterparts. Artificial intelligence has taken the field of marketing by storm and has really helped companies grow.

Here are some of the key areas where artificial intelligence can boost marketing efforts:

  • Improved product and content recommendations

    AI, big data, and machine learning can all come in very handy to help profile the customer base. Once the customer profiling is done, your content and product recommendations to them will also be very precise. This will ensure their loyalty and satisfaction.

  • Better social engagement and customer service

    AI can analyze all the user data and show you what works for each user. Not only that, but it can also keep you ahead of the trends and make sure you are producing the right content and answering all your customer queries.

  • Improved search engine rankings

    Since AI can keep a track of your chosen keywords and content recommendations for your audiences, marketers can focus on creating content around high-ranking keywords. AI can also help marketers assess the SEO strength of their content and improvement areas.

  • Smarter ads:

    As online advertisements keep rising in popularity, AI can help personalize the ads that each user sees. This could increase the CTR and ad revenue drastically. Optimizing web-ad performance is vital to the cost-optimization in marketing strategy and beneficial for all stakeholders, building better brands, and more enjoyable experiences for web-users. While AI has many advantages, these are the most prominent ones that can lead to an increase in revenue for the company and betters figures on the KRAs. However, there is a flop side to every coin. AI may seem to be a revolutionary component of your marketing strategy, but it has a few disadvantages. These are: 
    

      

    • AI is expensive – All good things come at a price, as does AI. Incorporating AI software into your CRM and CMS systems as well as training your marketing department to use and implement this software on a daily basis all cost a lot.
      • 

      

    • AI could lead to unemployment – Since AI can take care of a lot of tasks at once, it could render certain team members’ jobs unnecessary. Therefore, it is in the company’s best interest to first evaluate the budgets and needs and then choose the right software.
      • 

      

    • AI might limit creativity – Since AI has ready answers for a lot of questions, it may curb the creative potential of a team and keep the strategy rather monotonous and mundane. Therefore, marketing heads must ensure that the teams are creatively driven and ahead of the curve.
      • 

    

    • 






However, as is pretty evident, the pros of incorporating AI into your marketing stack well outweigh the cons.





Future of AI Software Programmers





IDC reports that 75% of commercial enterprise apps will use AI by 2021. Gartner, on the other hand, reports that by 2021, 80% of emerging technologies will have AI foundations.  The report also states that the number of enterprises using AI in business grew by 270% between 2015 and 2019.  

As more and more companies start witnessing the tremendous potential that AI holds for them, the future of AI software programmers looks bright. However, there could be one notable disadvantage of AI is that it is too advance and may soon be able to write its own code. Therefore, AI software programmers must monetize this opportunity as soon as possible.





Conclusion





Forbes says that 83% of businesses say AI is a strategic priority for their businesses. Therefore, there is a very solid case for how artificial intelligence can pave the way for the future of marketing.





Want to start implementing some of these best practices for artificial intelligence into your enterprise? Contact Byonic.AI today for a demo and get assistance in prioritizing AI-based solutions for greater results. Schedule a call today.

						

				

					

		

					

		

				

			


	





	
	

		Benefits & Uses of AI in Digital Marketing	


	

		Article explains use and benefits of AI in digital marketing	

	

		
Benefits & Uses of AI in Digital Marketing
		

			Posted on  |  by Danni White		

			

	

		

Artificial intelligence (AI) is a field of study that focuses on developing intelligent machines that can think and respond like humans. It has a lot of potential for digital marketing in the future. Organizations are increasingly turning to AI for cutting-edge applications that provide multiple overarching benefits.





As a business owner or marketer, it is time to identify your business’s problems and how accurate insights can solve these issues.





In this article, we have gathered AI data in digital marketing into one place that will help you get precise insight.





1. Machine Learning and Continued Learning





Machine learning techniques assist digital marketers in discovering valuable information from massive amounts of big data.





Machine Learning tools in digital marketing help identify market trends, forecast demand, and provide personalized services to customers. As a result, AI marketing’s Machine Learning tools and algorithms enable marketers to perform revenue-generating operations.





2. Smart Advertising on Social Media





Many social media platforms have built-in advertising systems that brands can use to enhance their marketing operations results. You no longer have to struggle to develop compelling captions and images for your ads when AI tools can do this work for you.





AI can also analyze your ads’ performance and make recommendations to fuel your campaigns’ effectiveness and drive better results. Due to AI, companies will no longer have to waste their marketing budget on ads that don’t work. You can target prospects and customers with the right message at the right time and get them to convert quickly.





3. Bot and AI Chats on Your Website





Businesses are interested in AI and adopting digital transformation to modernize customer communication and improve internal processes. Artificial Intelligence (AI) is playing a significant role in 2021 as it is being adopted by many businesses and enterprises. 





There are many benefits of using AI chatbots on your websites as they are always available. According to the research, over 50% of customers expect a business to be available 24/7. They are designed to reply instantly and consistently. Chatbots are not limited to shopping; they can also be used for repetitive tasks such as arranging meetings and researching a topic.





4. It Reduces Marketing Costs with the Best ROI





Artificial intelligence can fully or partially automate time-consuming and labor-intensive tasks that are causing your team to become overwhelmed. As a result, your marketing operations will require less workforce, and you’ll be able to utilize your ad budget properly. 





Thanks to the data-driven predictions and decisions you make, your campaigns are bound to generate impressive results that contribute to revenue growth.





5. Increased Personalization for Customers





Artificial intelligence (AI) developed marketing strategies, and approaches have evolved drastically over a few years.





In this fast-moving world, marketers need to work fast to keep up – but on the plus side, they have a lot of opportunities opened up for them to be creative. Personalization used to be an excellent option for marketing, but today, it must create a positive customer experience. 





Businesses can make a positive, personalized journey for their customers by micro-segmenting them, providing them with highly relevant content, leveraging omnichannel data, and leveraging AI. 





Personalization improves the customer experience, resulting in higher customer satisfaction, increased revenue, and long-term loyalty.





6: Refined Content Delivery on Social Media





Using artificial intelligence to track your Audience’s social media interests and preferences will give you a clear understanding of how to appeal to them by creating content they’ll want to engage with and share. 





Artificial intelligence allows businesses to gain a better understanding of their target audience and their preferences. They’ll be better equipped to create content that entices their interest and compels them to take the desired action.





7: AI Can Decide Content to Create and Where to Show It





You can use AI to help you decide what content to create and when, how, and where to publish and distribute it. The whole process can be done with a single click.





By outsourcing these repetitive tasks to marketing software, you can increase your productivity and focus your efforts on strategic marketing planning, face-to-face customer interactions, and other areas where humans excel over computers. 





AI marketing automation platforms allow you to segment your customer base and target different groups with the most appropriate marketing strategy. 





You can improve customer experience and strengthen customer relationships by segmenting customers based on their location, the pages they visit, or their buying preferences.





8: Automated Marketing Process





Much like automation, artificial intelligence applications make it possible for machines to complete fundamental human tasks. Visual perception, speech recognition, decision-making, and adaptability are common skills that AI is currently imitating. 





Marketers can create many campaigns and journeys without worrying about which one to send to each customer next because of AI. Marketing automation can be improved by using AI models to quickly identify all available campaigns for each customer and determine the following best action for them.





9: Processing Big Data





Big data is a broad concept that encompasses data collection from a variety of sources. It is a valuable tool for running digital marketing campaigns. Big data enables digital marketers to segment large data sets and send personalized content to customers conveniently via a chosen communication channel.





10. Understanding and Predicting Customer Behavior





When AI and consumer behavior are closely related and used together, they provide valuable insights. To survive in the marketing world, AI is being used to analyze customer online buying behavior. 





Customers are compelled to check out the brand’s offers due to new AI features behavioral marketing such as customized marketing messages.





The use of AI appears to be speeding up the growth of behavioral marketing. Chatbots, personalized feeds, and machine learning tools that track behavior have turned marketing on its head, with traditional methods no longer bringing the needed results. Artificial intelligence is something on which marketers can rely, and it benefits both brands and customers.





11: Better Business Intelligence





Users can derive meaningful insights from raw data with the help of business intelligence. To help organizations make more data-driven decisions, business intelligence (BI) incorporates business analytics, data mining, data visualization, data tools and infrastructure, and best practices.





The value of traditional business intelligence is undeniable. This practice’s ability to be nimble and scale as new norms are adopted is restricted in an environment where increasing competition, speed, and the need for accuracy are required.





More importantly, our blind spots may be hindered by allowing what has worked to continue to be the go-to solution. Because of this, we tend to miss critical insights that would have been apparent under an AI framework.





12: Better User Experiences





People prefer to do business with companies that offer excellent customer service. Customer satisfaction and retention, on the other hand, begin with getting to know your customers.





You will be able to understand your audience’s preferences and get closer to them by incorporating artificial intelligence into social media.





This gives companies an edge to create content, target ads, and make product or service changes to enhance their users’ experiences.





You can identify problem areas and fix them right away and respond to issues and complaints promptly to provide the best user experience.





Conclusion





Artificial intelligence (AI) is becoming more pervasive, a basic understanding of the technology is essential for long-term business success. Whatever role you hold in your business, understanding AI may help you solve problems in new and innovative ways, saving time and money. It may also assist you in developing and designing future products and services with a low or no budget.





Want to start implementing some of these best practices for artificial intelligence into your enterprise? Contact Byonic.AI today for a demo and get assistance in prioritizing AI-based solutions for greater results. Schedule a call today.

	


	





	
	

		10 Ways Intelligent Marketers Can Succeed with AI	


	

		Article gives how intelligent marketers can grow with ai	

	

		
10 Ways Intelligent Marketers Can Succeed with AI
		

			Posted on  |  by Danni White		

			

	

		

AI marketing is thought to be the most effective method for predicting consumer behavior and providing a better customer experience. The majority of AI principles help digital marketers further understand consumers’ web behavior and buyers’ preferences. As a result, experts in this field can create a perfect picture of the target audience.





Overall, AI marketing improves digital marketing, email marketing, and SEO processes of digital marketing strategies. As a result, expert marketers can quickly boost the return on investment.





However, digital marketing’s most distinguishing characteristic is that you don’t have to install anything manually. Artificial intelligence has many marketing advantages. The main reason marketers should use this technology is to pinpoint the key places where they need to work extra hard to earn consumers’ loyalty.





Here’s a list of how Intelligent Marketers can boost their growth with AI:





1: They help you learn more about your customers





AI is used to gather data from the targeted group. When you know everything about your clients, your marketing staff will be able to interpret their behaviors, often asked questions, motivations, internet interests, and so on. 





This data is important because it enables you to develop customized social media marketing campaigns. Remember that the most successful strategies for increasing sales are personalized marketing campaigns. However, without AI marketing tools, you won’t be able to build them.





2: AI-improved PPC Advertising





Most marketers well understand the value of pay-per-click budgets and resources like Facebook and Google AdWords. Google now owns 40% of the United States’ digital market, while Facebook owns 20%. 





Most PPC companies handle pay-per-click promotions. In this situation, AI’s main focus is to help marketers discover more new and profitable advertising platforms. Finding advertising outlets that the rivals don’t use is extremely difficult. 





With the aid of AI, marketing professionals can easily test new advertising tools and improve targeting. Facebook is now using this technology to improve the effectiveness and personalization of its ad campaigns.





Overall, machine-learning algorithms can be used if your job entails optimizing large-scale PPC campaigns. They will undoubtedly assist you in identifying the right audience and improving the effectiveness of your marketing strategies.





3: Smart customer engagement





ML algorithms help find customers who are likely to choose your competitors’ services. In such cases, AI-powered tools help gather data, create a predictive model, and test it on real clients. 





The thing is that it is tough to re-engage quick-churn clients. But the client who have already used your products or services can easily be re-engaged. When the system sees a user spending less time viewing the offered products, it will send relevant offers.





AI-powered churn prediction is a powerful tool that can help you boost your sales to new levels. Every company has their own unique churn prediction that helps to acquire more customers.





4: Chatbots





Machine-learning algorithms will help you identify consumers who are likely to prefer your competitors’ services, in addition to making your marketing campaigns more personalized. 





In such situations, AI-powered tools can assist in the data collection, the development of a predictive model, and the testing of the model on real clients. The problem is that re-engaging quick-churn clients is difficult. 





Many that have already used your services or checked your goods, on the other hand, can be easily re-engaged. When the system notices that a customer is spending less time looking at the items on sale, it will automatically give them specific offers to keep them engaged.





Overall, AI-powered churn prediction is an effective method for increasing sales.





The problem is that every company’s churn prediction is unique. This knowledge is the most powerful tool for gaining new customers.





5: Content creation





Content marketing is an effective method for attracting new consumers and increasing revenue. Humans, on the other hand, create stuff. Furthermore, it appears incredible that AI can provide knowledge base content such as a report or an eBook. On the other hand, AI tools can generate engaging emails, customized messages, and social media posts.





Machines can now generate brief hotel descriptions, benefit summaries, and basic business reports. All of this will save marketers time and provide them with immediate access to data.





6: Personalized website experience





You can’t build a new website from scratch with AI features. However, with the aid of intelligent personalization, you can enhance your users’ online experience.





To begin, intelligent algorithms can be used to personalize the web experience. AI will look at demographics, venue, and website engagement to recommend the most profitable offers for your users.





Second, intelligent algorithms can be used to customize push notification messages. As a result, you’ll be able to contact your customers when they’re ready to place an order. 





It’s possible that your push notification would convince them to use your services or buy your goods. According to a survey, 33% of marketing professionals use AI software to create customized web offers. Increased conversion rates and better customer service were reported by 63% of people.





7: More effective email content





If you’re a marketer, you know how difficult it is to develop effective email content. Experts in this field spend a significant amount of time designing and arranging correspondence. 





Furthermore, all emails must be classified into separate customer segments. Personalization is used by 77% of advertisers in newsletters, according to estimates. Such email campaigns are more successful.





This is where AI has the potential to be a game-changer. Subscribers AI algorithms track subscribers’ experiences and interactions with your content. They will use this information to identify appropriate content for a specific user and send customized emails.





8: Automated image recognition





Today, it’s challenging to find a person who does not use Google Drive. Today, the machine is capable of accurately recognizing both images and people. 





Furthermore, new technologies have improved their ability to recognize photos. For example, Amazon, Pinterest, and Facebook are now using AI image recognition to recognize users based on their images.





Some stores also use image recognition software to track customer visits in-store and connect the data to their online profiles. Store owners can use the information to create real-time promotions and welcome deals for specific customers.





Furthermore, facial recognition software can be used to monitor the offline results of your online marketing campaigns.





9: Monitoring new trends and finding new opportunities





Digital marketers’ key aim is to build successful marketing campaigns. They must, however, look for new business growth opportunities. They can be more powerful thanks to modern AI software.





They can search data and evaluate current marketing patterns. They will also assist in the development of new techniques by helping in forecasts.





10: Marketing automation





Time and effort are required for manual and repetitive activities. Some of them take a long time to complete. As a result, modern marketers want to automate as much as possible. Remember that with the aid of influential AI patterns, most manual digital tasks can be automated.





Conclusion





In the twenty-first century, every company must embrace the new opportunities provided by AI tools. This isn’t to say that the technology is without flaws. A solid IT infrastructure is needed for an effective AI-driven marketing strategy. Placed, high-performance hardware is needed.





Even though AI is our future, the industry is relatively new. Data storage is limited in some companies. This means they won’t be able to use some cloud-based vendors’ services.





Want to start implementing some of these best practices for artificial intelligence into your enterprise? Contact Byonic.AI today for a demo and get assistance in prioritizing AI-based solutions for greater results. Schedule a call today.

	


	





	
	

		What is Enterprise AI?	


	

		Article explain all about what is enterprise ai	

	

		
What is Enterprise AI?
		

			Posted on  |  by Danni White		

			

	

		

Enterprise AI uses advanced artificial intelligence and other technologies such as machine learning to help companies transform and enhance growth within businesses. Large corporations can develop and run dozens or hundreds of enterprise AI applications to meet various business needs.





Best-Suited Cases That are Used for Enterprise AI?





Typically, enterprise use cases for advanced capabilities such as AI and machine learning that includes:





  • Advanced analytics The former uses machine learning and large amounts of quantitative data to allow businesses to efficiently mine data, identify trends, and uncover hidden facts. These capabilities will enable you to better understand operations by combining insights from several large and disparate data sources. Ideally, it will allow you to make significant and timely decisions and accurately predict future outcomes.





  • Scaled data governance through an automated organization You can also use enterprise AI to auto-tag content and data and automatically route and organize it to the appropriate channels. This will improve not only content discoverability but also findability.





  • Augmented categorization and classification of data Machine logic is used to organize data based on similarities between contents, meaning, and users in augmented categorization. In an ideal world, the computer learns to identify organizational and management principles that aren’t explicitly stated in a text, such as emails and helpdesk requests.





  • Semantic search and NLP Semantic search tries to figure out what search words mean in context. The method entails more than just running queries against keywords. It also gives you the freedom to add, modify, and boost data flows easily. The technology makes it easy to incorporate new data sources to help you answer questions you haven’t heard of yet.





  • Discover relationships from disparate sources A recommendation framework in AI enterprise applications works by establishing a relationship between contents. This ideally offers an exceptional understanding of how things can fit together and create a better user experience for consumers searching for new facts and insights that would otherwise be lost in normal practices.





The Impact of Artificial Intelligence in Industries





  • Intelligent Automation Intelligent Automation (IA) is a technology that combines robotic process automation (RPA) and artificial intelligence (AI) to enable end-to-end business process automation and accelerate digital transformation.





  • Labor and capital augmentation Labor and capital augmentation make more efficient use of the workforce and capital assists. It complements and enhances the human ability and helps to add human values to their work. It improves capital efficiency.





  • Innovation diffusion uses AI to stimulate new ideas. AI complements technologies from new collaboration and helps create new revenue streams from data generated with social benefits.





  • Practical AI Applications in Enterprises Large and small business leaders recognize that artificial intelligence is likely to be a new catalyst for economic development and that embracing AI will help them significantly. Practical use cases appear daily, and many businesses are transforming.





  • Enterprise Decision Management (EDM) Enterprise Decision Management, a modern approach to decision-making focused on AI, aims to automate data collection within organizations and make data-driven decisions. Artificial intelligence (AI) systems can help with data processing and analysis. It can also connect various infrastructure sectors, allowing them to exchange knowledge and best practices.





  • Predictive Maintenance To a large extent, manufacturing businesses depend on reliable machinery activity. By predicting failures, predictive maintenance systems will ensure the necessary stability. It continuously tracks your equipment’s condition and performance and can predict when you should inspect or fix specific parts. In the enterprise, artificial intelligence (AI) aids manufacturers in reducing or eliminating downtime and increasing production.





  • Chatbots Chatbots, which use natural language (NLP) technology, have reshaped working processes in call centers, online retailers, and customer service organizations. Chatbots have several advantages for both companies and customers: they process requests immediately and without hesitation, and they eliminate the need to wait in line to talk to an operator.





  • Self-Driving Vehicles Self-driving cars that use computer vision technology, GPS, and IoT sensors to follow the exact route will deliver parcels without touching them. Autonomous vehicles are also often used to categorize and position goods on shelves in vast warehouses. E-Commerce and retail businesses profit from this strategy. The list of realistic AI use cases is endless, and AI-driven businesses can be found in various industries.





Enterprise AI Benefits and Challenges





AI-enterprise technological or industrial advancements together brings massive opportunities and daunting challenges.





Benefits of Enterprise AI





Because cognitive technologies operate at a far higher level than human specialists, implementing AI for businesses has several advantages.





  • AI’s ability to easily manage vast volumes of data leads to more incredible data processing speed, opening new market opportunities.





  • Due to optimized manufacturing, process automation, and predictive maintenance, maximum revenue generation is expected.





  • AI and ML algorithms’ ability to anticipate customer needs and provide tailored recommendations leads to higher customer engagement and satisfaction. Besides that, providers would be able to conduct more efficient sales and marketing campaigns.





  • Improved customer service is made more accessible by chatbots and other intelligent assistants.





  • AI protection systems that can detect and protect against advanced cyberattacks take cybersecurity to a new level.





AI Enterprise Challenges





Intelligent technology implementation has as many advantages as it does challenges for companies, includes:





  • Inflated expectations AI is used in a variety of industries, but it is not yet ideal. Speech recognition, for example, there are still many issues with the transcription of dialects and slang. This means that computers cannot (fortunately) fully replace humans, and you should have reasonable expectations to avoid disappointment.





  • Lack of technical capability You can use deep learning algorithms for simple scenarios without an extensive computational infrastructure, which is fine. However, you’ll need a lot of computational power and a sophisticated technology stack to train multilayer algorithms to perform complex tasks. Take it into consideration before putting AI into production.





  • Initial costs are high AI integration is supposed to increase sales while lowering total costs. But keep in mind that incorporating algorithms into an existing framework, as well as building and implementing the code, would mean a substantial investment. As a result, the early stages are likely to require a significant amount of effort, ability, and investment.





  • Regulation and control issues AI systems can act unpredictably at times, deviating from training and producing algorithms that are hard to understand by humans. One striking example is when two Facebook chatbots developed their language after being taught English.





  • Lack of skilled workers Having enough employees skilled in a particular AI technique can be difficult. As a result, a skills deficit is a significant impediment to AI adoption in enterprises.





  • Impact on the labor market Artificial intelligence is transforming many facets of our lives, including the labor market. Many people fear losing their jobs because they believe employers would replace human employees with more powerful intelligent machines.





Final Thoughts:





Businesses should devise an intelligent transformation strategy. The most significant change brought about by integrating artificial intelligence into business processes would be the way humans and machines interact.





Artificial intelligence (AI) can benefit businesses and change people’s lives. Artificial intelligence (AI) can provide a fresh, creative way to function, entertain, and live.





Want to start implementing some of these best practices for artificial intelligence into your enterprise? Contact Byonic.AI today for a demo and get assistance in prioritizing AI-based solutions for greater results. Schedule a call today.

	


	





	
	

		5 Enterprise AI Best Practices	


	

		ai best practices	

	

		
5 Enterprise AI Best Practices
		

			Posted on  |  by Danni White		

			

	

		

Artificial intelligence is a massively growing aspect of the technology industry. At conferences and trade shows, artificial intelligence is forming the foundation for new products and services.





Companies integrate products and features to create virtual assistants, and chatbots answer customer questions on a range of tech support issues to product information. Simultaneously, many companies are working to integrate AI as an intelligence layer across their entire tech stack. 





Machine learning, computer vision, and natural language processing have all progressed in recent years, making it simpler than ever to incorporate an AI algorithm layer into your app or cloud platform.





Practical AI applications for companies can take several forms, depending on your organization’s needs and the BI insights obtained from the data you collect. Companies can use AI for various tasks, including mining social data, driving interaction in customer relationship management (CRM), and optimizing logistics and productivity in asset monitoring and management.





Machine learning has and will continue to have a pivotal role in artificial intelligence development. It incubates AI startups and helps companies incorporate AI on top of their existing products and services.





Currently, recent progress in machine learning is driving the interest and use of artificial intelligence. There is no single breakthrough you can point to, but the business value we can extract from ML is now off the charts. What is going on right now regarding enterprise business processes such as planning and control, scheduling, resource allocation, and reporting may be disrupted. We’ve gathered some expert advice to clarify the steps companies should take to incorporate AI into their operations and ensure effective implementation.





Top 5 Enterprise AI Best Practices





1. Get Familiar With AI





Modern AI can do a lot to grow your business, but it requires time to understand AI’s scope and how you can implement it. The TechCode Accelerator offers startups an array of resources through partnerships with Stanford University and AI-focused corporations. Take advantage of the wealth of online information, remote workshops, resources, and courses to gain familiarity with AI’s basic concepts. Doing this can be an easy way to start integrating predictive analytics within your organization.





2. AI Can Solve All of Your Problems Quickly





Once the basics are straightforward, any company’s next step is to begin exploring different ideas. Think about ways you can incorporate AI into your new products and services. More importantly, your business should consider particular use cases in which AI might solve business problems or bring value. 





When working with any organization, we start with an overview of its vital tech programs and issues. We want to show how natural language processing, image recognition, machine learning, and other technologies integrate into such products, typically through a workshop with its management. The details vary from industry to industry. If the company does video monitoring, applying machine learning to the process will add value.





3. Prioritize Concrete Value





You must evaluate the market and financial potential of the numerous AI implementations you’ve found. It is easy to get caught up in “pie in the sky” AI discussions; the researchers emphasized the importance of explicitly linking the initiatives to business value.





To prioritize, build a 2×2 matrix with the dimensions of potential and feasibility. This matrix should allow you to prioritize near-term visibility and determine the company’s financial value. Managers and top-level executives must usually take responsibility and accept these moves.





4. Acknowledge the Internal Capability Gap





There’s a big difference between what you want to do and what you can accomplish in a given time if you have the right organizational skills. Before diving into a full-fledged AI implementation, a manager should know what it can and cannot do in terms of technology and business processes.





The first step in resolving the internal capability gap is identifying what you need to acquire and processes you need to build before you start. Established projects or teams, depending on the company, may assist specific business units in doing so organically.





5. Call-In Experts to Set Up a Pilot Project Easily





It’s time to start developing and integrating the company until it’s ready from an operational and technological perspective. Starting tiny, having project objectives in mind, and, most importantly, being mindful of what you do and don’t know about AI are the most critical factors here. Bringing in outside experts or consultants who know the topic well can be highly beneficial in this situation.





Typically, 2-3 months is a good range for a pilot project. Companies need to build insufficient bandwidth for storage, the graphics processing unit (GPU), and networking to achieve this balance. Security is an oft-overlooked component as well. AI requires broad access to swaths of data to perform the task well. Ensure that you understand the types of data involved and usual security safeguards such as encryption, VPNs, and anti-malware.





In Summary





Bringing external experts and internal team members together and a tighter time frame will keep the team focused on business goals. After completing the pilot, you should decide the longer-term aspects of the project and whether it is valuable enough to make sense for your business. It’s also essential that experts from both sides—the people who know about the company and the people who know about AI—are merged on your pilot project team.





Want to start implementing some of these best practices for artificial intelligence into your enterprise? Contact Byonic.AI today for a demo and get assistance in prioritizing AI-based solutions for greater results. Schedule a call today.

	


	





	
	

		How AI and ML Will Affect Organizations in the Future	


	

		ai and ml	

	

		
How AI and ML Will Affect Organizations in the Future
		

			Posted on  |  by Danni White		

			

	

		

According to a published research paper by Accenture Institute for High Performance, artificial intelligence can double the annual economic growth rates in several developed countries by 2035. This growth is proof that the world is about to experience a phase where tremendous technology-driven change through AI and ML will help us remedy a plethora of challenges in achieving desirable growth. AI and ML can be applied in several ways to build outstanding infrastructure for next-generation education systems, agriculture, healthcare systems, power, and telecoms in the future.





This article will offer some ideas to consider on how artificial intelligence will change the future.





  • Market and customer insights
    




    Machine learning and artificial intelligence will play a crucial role in analyzing your customers and target market. Predictive analytics can integrate data generated from social media, web matrix, and system matrix to design a new and improved product. Through customer insights, you can maximize customer experience as much as possible.
    




    Artificial intelligence offers an incredible benefit for start-ups. Start-ups will explore several opportunities to operate on various thought processes and develop innovative solutions for their business growth. Predictive maintenance will enable start-ups to reduce maintenance costs via regular quality checks.
    




    Most customers will probably be on social media, and many businesses must take place online. Organizations can utilize artificial intelligence and machine learning to understand essential measures of online social networks. Companies can use data mining strategies in the analysis of many forms of social media traffic. What makes AI and ML so incredible are that they can learn, unlike purely statistical approaches. The learning aspect makes it possible for them to evolve with any changes in the market behaviors in the future and continually improve performance as you generate additional data.





  • The growth of virtual assistance
    




    Many organizations are either utilizing or planning to adopt AI for virtual assistance. There are several reasons why companies deploy chatbots. The most prominent area is customer service. Although many individuals are not convinced of the concept of customers speaking with a robot as it might malfunction at specific points, regardless, there is a massive potential in machine-based assistance with human-based customer service.
    




    For instance, in the case of airline inquiries, an AI application can help answer fundamental questions such as the flight’s timing, alternative flights, and flight status, among other things. This will allow human personnel to concentrate on more complex issues. Marketers can effectively use chatbots to interact with their prospective customers seamlessly. Virtual assistants and chatbots will play a significant role in the way customers interact with technology. In the future of AI, virtual assistants would become a substantial component of our business lives, and many organizations are going to leverage this to move customer service to a greater level.





  • Efficient process automation
    




    Automation is one thing that has been on a steady rise for the last couple of decades. Many machine learning automation tools are being developed and upgraded, facilitating the agility of business processes. Today, advanced machines are collaborating with humans in different industries.
    




    Industry giants have predicted that with the tremendous rise of ML and AI, we are about to witness a new era of automation. AI is rapidly automating repetitive cognitive procedures. Intelligent algorithms are becoming more and more useful in different industries such as financial institutions, hospitality, and retail. These algorithms or machines will not only execute a highly proficient task but also will operate 24/7 nonstop.





  • Enhanced data unlocking
    




    In the past, the volume of data an organization generated was a relatively small set, which determined how it was structured. Capturing and storing the data in a database was easy. Business owners could obtain insights from the data mined for the organizational needs.
    




    However, the situation has changed today. There is no longer structured data, and the more significant segment of the available information is unstructured data. In fact, approximately 80% of the data received from online platforms is unstructured. Hence, the most impactful factor for any organization over the subsequent decade will be analyzing unstructured data.
    




    Understanding consumer conversations is another aspect that has great potential to make your organization a global giant. Your organization can be among the few businesses that utilize their consumer conversations to determine their personality types with Artificial Intelligence’s help so that those consumers receive compatible services. AI and ML will help many organizations to unlock massive data in the future.





  • Better personalized customer experience
    




    Artificial Intelligence and Machine Learning offer organizations the opportunity to drive a personalized experience to their consumers/customers. AI can be used to analyze extensive data far more efficiently. It can easily identify threads in the information – like previous purchase history, credit scores, purchase preferences, and other common patterns. Transactions can be examined daily to facilitate personalized services to individual customers.
    




    The use of actionable sales intelligence will help businesses analyze a particular buyer before, during, and after purchase behavior. This enables organizations to develop a highly personalized experience and initiate customer engagement at every point of interaction. Predictive intelligence has the potential to help organizations engage their customers authentically and effectively. An AI-based application can also help to personalize the sales cycle, enabling enterprises to engage the proper customers with the right content at the appropriate time.





In Summary





Machine learning and artificial intelligence across various industries have helped both small and enterprise businesses execute tested and effective methods to realize better business goals. Start-ups continuously have a competitive advantage through AI and ML, while big organizations are paving the platform to develop innovative solutions.





From working as a robot in a production plant to autonomous-driving vehicles and voice-activated resources in complex medical procedures, AI and ML have become a crucial part of reality. The future of AI and ML promise tremendous business solutions.





Want to start implementing machine learning and artificial intelligence based tools into your marketing and demand generation strategy? Contact Byonic.AI today for a demo and see how we can streamline your marketing and sales process and get results. Schedule a call today.

	


	





	
	

		11 Ways Machine Learning Can Improve Marketing and Sales	


	

			

	

		
11 Ways Machine Learning Can Improve Marketing and Sales
		

			Posted on  |  by Danni White		

			

	

		

According to an article published on Forbes.com, 75% of enterprises utilized artificial intelligence and machine learning to enhance customer satisfaction by 10%.





Additionally, according to one Demandbase report, since 2018, 84% of marketing companies have expanded or implemented AI and machine learning within their teams.





These statistics help to emphasize the importance of using machine learning in marketing and sales by businesses worldwide. 





How can machine learning improve marketing and sales?





The short answer is, well, there are a couple of ways. Below, we will discuss some of the key ways organizations can use machine learning in their marketing and sales departments:





  • Sentiment analysis and reputation scoring Advancements in natural language processing can help rank copy such as social media posts, online reviews, and customer testimonials by favorability. Sentiment analysis can help predict feelings expressed by customers as well. A reputation index can also be compiled by extracting the text you mention in your product or service. This type of analysis can be effective in understanding ways to improve with deep learning advances.





  • Customer personalization With machine learning, you can learn more about your customers through the behavioral data it provides, including descriptive data or click patterns. For better business growth, delivering a highly customized and personalized experience and support to your customers’ journey is essential. Aside from this, customized pricing is another area of personalization to consider here as well.





  • Lead scoring You can find a range of tools for lead scoring across the market. These tools often rely on human usage as well as experience to determine what makes a lead good. However, the generic nature of these tools is a significant drawback. No two businesses or markets are the same, and the same applies to customers. And this is where models based on neural networks will come into action. These tools can help to find hidden patterns and cut the guesswork. Ultimately, identifying a lead and providing accurate scoring becomes possible.





  • Customer churn and lifetime value modeling Both lifetime value modeling and customer churn go hand in hand. The customer’s churn risk measures how likely they are going to stop interacting with the business. However, on the flip side, a customer’s lifetime value predicts the revenue they will generate for your business. Machine learning can help to model both for your sales and marketing teams to intervene with high lifetime value customers and high churn risk and bring them back with attractive rewards. Sometimes, you can automate the retention strategy as well.





  • Customer segmentation and discovery Clustering can help identify data patterns and define how to categorize or label customers depending on different factors, including interest, location, age, and income, among other factors. Gathering more information about your customers will help you make more accurate clusters. However, after that, you can label each cluster with ease. These can quickly help you customize your marketing approaches according to the goals you need to reach.





  • Recommender systems Propensity models serve effectively to cross-sell or upsell your customers during their online shopping experiences. According to Mckinsey.com, 35% of Amazon customers and 75% of Netflix customers prefer to buy or purchase what they see in recommendations. Recommender algorithms based on machine learning can be one of the best ways to optimize your message’s accuracy while targeting customers. Doing this can help reduce marketing waste.





  • Chatbots and virtual assistants Have you ever interacted with a virtual assistant such as Alexa or Siri? If so, then you might have noticed how advanced they have become over time. It seems that the marketing future is going to be full of virtual assistants and highly sophisticated chatbots. Voice recognition and natural language processing have grown by leaps and bounds within the past few years. Even more, their progress is showing no signs of slowing down.





  • Minimize marketing regret A/B testing is an essential tactic that almost every marketer knows. The issue with this tactic is that plenty of opportunities get lost during testing. However, machine learning algorithms can minimize the regret of these lost opportunities. One reason is that these algorithms can help you sample better options naturally and more often.





  • Text extraction and summarization Another great natural language processing application is the ability to extract and summarize text automatically. Such kinds of applications can be one of the best and quickest ways to process information, such as news articles after a significant product or service launch, to gauge the market’s reception. Ultimately, correcting the launch score will also become more manageable when needed.





  • Marketing mix optimization The marketing mix portfolios are based on intuition and experience, but these can perform remarkably well. Machine learning can remove the guesswork and provide more optimized solutions in this regard. For more effective solutions, machine learning algorithms typically look at prior marketing spends on different channels, including radio, TV, social media, CPM, CPC, and sales. After that, well-optimized funds can be allocated for each channel to ensure maximum return on investment.





  • Computer vision Some companies use image recognition to detect the right time to post branded collateral in blogs or social media. However, businesses can use computer vision to analyze extensive user-generated content in blogs, social media posts, forums, and other sources to uncover better ways to connect with promoters and consumers more effectively.





Conclusion





Overall, you can use machine learning in marketing and sales in multiple ways, as we have described. These ways aim to improve your business’s growth with effective customer experience, enhanced customer satisfaction, and improved brand recognition. You can also incorporate machine learning in marketing and sales in any of the ways mentioned above to start reaping the benefits.





Want to start implementing ML/AI based tools into your marketing strategy? Contact Byonic.AI today for a demo and see how we can streamline your marketing and sales process and get results. Schedule a call today.

	


	





	
	

		What is AI Marketing?	


	

			

	

		
What is AI Marketing?
		

			Posted on  |  by Danni White		

			

	

		

AI marketing is the use of artificial intelligence technologies to make actions and decisions about data analysis, personalization and data collection automated. AI marketing can also take audience trends, spending trends, retail trends, and economic trends to make significant observations and outcomes on overall marketing efforts. When speed and quality is of the essence, AI tools can help marketers relate to customers with tailored messaging and specific product or service details when they need to make a decision. Buyer personas and customer profiles are used to tailor these messages so human marketers don’t have to get involved. With AI marketing, marketers can save much of their time and effort on more strategic and tactical tasks.





The Importance of AI Marketing





AI tools allow customers to accumulate large volumes of marketing analysis data from emails, social media pages, and the world wide web while helping them to boost ROI and campaign performance. AI marketing can also result in better customer relationships between brands and their clients as well as automated real-time personalization at the right time in the consumer lifecycle. Additionally, with so many data points and campaign metrics to keep up with, dashboards that put AI to use can allow for a more thorough and comprehensive view of channels, budgets and outcomes. 





Using AI Marketing





Artificial intelligence technology can be used in the following ways when it comes to integrating it in marketing campaigns and measurements: 





· Take conversion management to the next level





Data gathered from AI is enough to find out whether a buyer is interested in the product or not. There’s no need to ask strategic and difficult questions to the audience. 





· Understand buyers





With AI marketing solutions, you get to know how your customers feel, talk, interact, and prefer. The tools join real-time conversations to gain large chunks of data. 





· Follow current trends





Having difficulty in knowing what is working and what is not working in the industry? AI can help decipher fact from fiction and give you analytical insights into your customer base and trends they are following. 





· Automated ad targeting





Marketers are using software-driven technologies to make the buying process easier and shorter. 





· Use of conversational bots





Customer service chatbots assist the customers with queries and problems 24 hours a day. 





· Voice recognition





Marketers make use of speech recognition to convert people from traditional shopping to voice shopping. 





· Content creation





Content intelligence is used to generate personalized content for self-sustaining websites including infographics, charts, financial reports, etc. 





· Personalized Pricing





Marketers are now using AI to determine the dynamic pricing of a product whenever the demand increases or decreases. 





Elements of AI Marketing





There are several elements to keep in mind when using AI and marketing. Some of these elements go hand-in-hand with AI itself while others serve as components to the overall strategy.





· Big Data





AI and big data go hand in hand when it comes to working with large quantities of data and get insights in real-time. 





· Machine Learning





Machine learning helps a user to highlight trends, consumer behavior, and expected responses to marketing campaigns. 





· Robust Solutions





Predictive marketing analytics solutions by AI allow marketers to predict user-intent and consumer behavior. 





Benefits of AI Marketing





  • High campaign performance and increase in Return on investment
  • Improved recommendations and content personalization
  • Better management of campaigns and consumer reports
  • Improved team efficiency
  • Advanced personalization and a better understanding of consumer behavior
  • Data-driven and fast marketing decisions





Challenges in AI Marketing





AI marketing tools are still in their development stages. Therefore, marketers face certain challenges integrating them, such as: 





· Lack of data quality and training time





Marketing teams require proper and extended training sessions to gather quality customer info, preferences, trends, and historic data. 





· Lack of Data Privacy





Data breaches are not allowing organizations to use consumer data ethically. Thereby, damaging their reputation. 





· No measurement Abilities





It is difficult to explain the value of AI marketing tools to stakeholders. Marketing teams should be able to measure the success and conversion rate and help stakeholders to agree to AI investments.





  • Adapting to the ever-evolving era





Day-to-day marketing operations are evolving, thanks to AI. However, many marketers are not ready to leave traditional marketing strategies behind. 





Examples of AI Marketing





  • Target the right audience
  • Convey the right information
  • Advanced personalization and recommendations
  • Better user experience through automated conversational bots
  • Real-time data processing for predictive analysis of marketing campaigns
  • Dynamic product pricing





Current trends and predictions for AI Marketing





Headed into 2021, there are three main predictions and trends that you will want to know: 





· AI is developing…always





It is just the start and content creators and marketers will have to adapt to the many nuisances and changes. Brands already using AI tools are gaining outsized benefits such as heavy traffic, better website rankings, increased reach, and customer satisfaction. This list will only continue to grow as AI becomes more refined in its approach. 





· Marketing teams are exploring AI options





AI has yielded benefits in almost every industry imaginable. Sooner or later, it will be used by all future marketers to convert from outdated processes to real-time data extraction process and using data analysis for real-time outcomes. 





· AI users will be dominant in the industry





Consumers go with brands who are open to adaption and change.  With AI-powered SEO and marketing strategies, futuristic marketers will be dominant and will replace those who oppose the use of AI tools in marketing. 





Final Thoughts





Marketers are implementing creative and innovative AI solutions to their marketing stack every day. If you have not implementing an AI-based marketing tool in your strategy, it may be time you use advanced learning algorithms to take over the marketing industry. Byonic.AI is a fully integrated demand generation platform that blends account intelligence, content and creatives, as well as analytical insights into a single platform. Ready for a demo? Reach out to us today and see what Byonic.AI can add to your marketing stack.