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We are at the onset of some call the fourth industrial revolution wave. The markets and industries have transformed hugely in terms of operations and marketing. AI and machine learning have a huge role in this transformation, and they will play an imperative role in the fourth wave of the industrial revolution.

AI tech has grown by 44% just in the year 2017-2018 and it is playing a huge role in B2C and B2B marketing. 61% of marketers acknowledged that AI and Machine learning were an integral part of their data strategy. Though we have seen a quick implementation of AI and Machine Learning in B2C marketing, it is comparatively slower in B2B for some reasons. When it comes to B2B, one in five companies implements AI in their sales and marketing.

Why Companies Can’t Ignore AI in B2B Anymore

Curiously, a lot of people do not know that they are already using AI in many ways. This includes both customers and company employees. A study found that 40% of the participants weren’t aware of the intrinsic AI features as part of the vendor services they were using. According to Demandbase, half the marketers they asked graded themselves as C+ for their understanding of AI.

Grading B2B Marketers’ Understanding of AI. (Demandbase Report)

A very few marketers have been using AI and Machine Learning for a long time. The initial chatbots, automated personalized emails, YouTube’s video recommendations, etc. are part of AI and Machine Learning. However, now the applications of AI & ML have grown miraculously. The current AI tech can boost a business’s productivity by 40% according to a report by Accenture.

Currently, businesses are planning to invest big time in AI and ML techs. There are various types of AI applications that marketers are looking at. Ranging from Lead generation to personalization, various interesting things are being equipped with AI tech. Here is a small chart by Demandbase that gives us the top things that marketers are planning to implement AI and ML on.

Application Priority Chart for AI Implementation (Demandbase Report)

Over 44% of organizations fear that they’ll lose out to startups if they don’t implement AI soon. Pick up whatever report you wish to and all you would see are numbers pointing towards a fact that AI and ML are going to be inseparable from B2B marketing.

However, in what ways AI and Machine Learning are transforming the B2B marketing landscape? Let’s have a look at that.

Hyper-Personalization With AI

Salesforce in 2016 in its Connected Customer Report predicted that by 2020, 57% of customers would want the company to know what they want before their first interaction. Especially in B2B communications, companies have become accustomed to receiving personalized content, custom-tailored messages and emails, and a hyper-personalized buying experience. However, 73% of marketers say that it is extremely difficult to create personalized content. To better educate your audience, sending personalized content is imperative. Creating personalized videos, blogging frequently, creating podcasts, and sharing them through custom-tailored newsletters can improve your B2B engagement by 23%. Here is a good blogging tutorial to try where AI can help your blogs become more productive.

AI has enabled us to collect data in vast proportions and with the help of Machine Learning, AI, and Big Data, this data can be used to personalize B2B communications and marketing. Various social listening tools help you monitor your real-time reputation. It lets you begin relevant conversations, help you with personalized lead generation using keywords across various social media platforms. Awario is one of the best social listening tools right now.

You can analyze firmographic data, content consumption patterns, browsing habits, and various other attributes with these tools and create hyper-personalized recommendations for each buyer. You can pair it with software like Pathfinder which is a content insight software, to create custom content campaigns.

All of it combined enables you to reach out to your audience timely, and offer them recommendations that add value to them and solve their pain points immediately. It concludes with a wonderful user experience.

Better Customer Interactions

Previously automated customer support has been very limited and even human interactions were limited due to the unavailability of data and patterns. However, with new AI and ML tech, there are more intelligent chatbots to answer questions, provide resources, solve issues, or redirect customers to integrated human support. 33% of participants in a study wanted their chatbot to have a personality and 45% of end-users preferred chatbots for customer service inquiries.

This is enabling companies to identify at what stage of the buying journey they lose their B2B customers. With more informed and predictive tech, it is easier to handhold the customers through the buying funnel, satisfactorily clear their doubts, provide them resources and help them make an informed decision. 31% of marketers believe that Ai powered virtual personal assistants are having a huge impact on their B2B business. 28% believe that automated emails and AI-powered chatbots have a profound impact on their business (PWC).

With pattern recognition, predictive analysis, and ML solutions, it becomes easy to figure out the pain points and provide optimum solutions timely. This increases the UX. 80% of businesses were predicted to adopt AI as a customer service solution by 2020.

High-Quality Lead Generation

AI has been a boon for lead generation. Because of its analytics and predictive qualities, it bypasses various traditional barriers to lead generation and conversions. Any business runs because it eventually makes sales, and generating leads sits in the core of a business. However, AI and ML have enabled businesses to filter out for higher-quality leads, which means gathering leads that are more probable for conversion.

Traditional barriers that marketers and sales reps used to face were that they could not focus their energy and attention on leads that are either not sales-ready or have completed the purchase and now needs to be taken further in the funnel. In case they did put effort into it, it would increase lead acquisition costs, bleed profitability, and harm productivity. To manually prioritize leads would take unrealistic effort, and the personal judgment of individuals likely produced misleading data.

However, AI-powered mechanisms enable businesses to handhold customers from their first interaction and navigate them to the end of the funnel with being accurate in their research, analysis, and judgment. AI lead scoring with predictive analysis allows companies to identify the most probable leads without allocating any extra human resources to them.

Conclusion

The future that many reports and studies predict about has arrived. This is it and it is going to be more complex from here on. B2B marketing, and AI and Machine Learning have become inseparable halves. AI has contributed tremendously and will continue to do so. It is estimated that AI will contribute $15.7 Trillion to the global economy by 2030 and boost the US GDP by 14.5% by 2030.

This is a great time to learn and invest in AI and Machine Learning.

Author’s bio

Kiera Hayes is a passionate Blogger and Marketer. She enjoys reading and writing articles whenever she gets time from her work.