Artificial Intelligence and Machine Learning
min read

How can Artificial Intelligence help scale your B2B Sales and Marketing?

Discover the role of artificial intelligence in scaling your b2b sales and marketing.
Pinakin Ariwala
Pinakin Ariwala
Updated on Sep 30
Artificial Intelligence and Machine Learning
min read
How can Artificial Intelligence help scale your B2B Sales and Marketing?
Discover the role of artificial intelligence in scaling your b2b sales and marketing.
image
Pinakin Ariwala
Updated on Oct 14
Table of contents
Digital marketing as we know
Challenges in harvesting precious data
AI and Conversational Computing
Customer’s ethos, impulse and buying pattern
Machine learning feeds power to customers
Real-time machine learning use cases
AI means relevance and control in digital marketing
Artificial Intelligence stops brand abandonment
Real-time data analysis
Marketers can forecast customer wishes
Marketing content gets persuasive and influential
Digital operations grow economical
AI for today and tomorrow
Final remarks

Technological advancements have always helped businesses by creating new opportunities for reaching customers. One of greatest technologies of our time is Artificial Intelligence (AI) which is creating quite the buzz in the digital space. Given its potential for storytelling and marketing, Artificial Intelligence in B2B sales and marketing is here to transform the way people interact with brands, information and services.

The world of B2B marketing and its future is poised to be touched by Artificial Intelligence. A good handful of enterprise giants dread the idea of full automation of marketing movements through smart AI technology, however, measuring the effect of AI-powered robots in many customer service industries, one can affirm that understanding customer nuance will not be entirely manual or managed by human power alone.

This blog takes a deeper look into how Artificial Intelligence in marketing is doing and how effectively AI scales up B2B businesses sales and marketing in today’s scenario. Let’s first start with the trendy wave of digital marketing slowly integrating with the machine learning power of AI.

Digital marketing as we know

Top marketing influencers find it unlikely to see advertising regress back to ancient days of marketing with print media, vivid billboards, and repeated ads on radio and TV channels or even physical appearances from door to door. Digital marketing is intensifying and online sales have doubled in last five years.

Research shows that, approximately 70% of US citizens prefer to shop online. Additionally, total revenue generation from online ads has exceeded that of TV, desktop and newspaper ads.

Such real-time statistics highlight how customers (B2B or B2C), are making their online exposure an indivisible part of their lives. This is also a vital indicator of how marketers urgently need to shift their focus on developing more powerful pre-sales strategies to leverage the potential opportunities offered by modern methods of B2B marketing.

However, all the efforts of online marketing campaigns revolve around how much businesses value the data drawn from their everyday customer interactions and customer service engagements. Certain factors involved in the data management process make or break the final outcome. So how do you go about manipulating data that speaks about customer journey? 

Challenges in harvesting precious data

To address every minute requirement of business customers and reach maximum acquisition, B2B marketing space must be filled with concentrated efforts towards learning their customers. Be it end users or corporate clients, each individual leaves behind a plethora of information through their online clicks and search, live campaigns, chat and e-mail communication, website visits and purchase decisions. Myriad of data like this needs a high-caliber automated system like AI that can organize, process it and create powerful insight after learning about customer mindset, demographics and their behavior.

Due to lack of proper skillset, businesses often miss out on insight as data collected is disposed or mismanaged or considered redundant – resulting in poor pre-sales marketing strategy.

Hence, the biggest challenge while harvesting and processing customer interaction data is having an accurate method to make precise interpretation of it. Absence of an intelligent machine learning system makes valuable data insignificant and digital marketing aimless, costing a loss of budget on analytics.

AI and Conversational Computing

Artificial Intelligence is designed to emulate the capacity of human power and surpass their ability to remain accurate across all existing business processes. Made highly intelligent with deep machine learning methods, AI-powered computing system can work towards solving the problems without needing codes for programming. The AI system is taught to learn from human interactions through a predetermined set of rules and convincing illustrations.

AI enables conversational computing and Google relies on machine learning technology to reinvent its existing smart products like Google Maps and Google Assistant. For instance, Google Assistant is one great example of progress made in the area of machine intelligence as it offers conversational experience by making a personalized version of Google for every user. Using the elements of speech recognition and natural language processing, it helps people with their daily tasks such as gadget controls, calendar management, personal outings and meetings, etc.

Products like Digital Assistants and image recognition based Google photos also depend on AI technology.

Customer’s ethos, impulse and buying pattern

For businesses, customers are true heroes and work as an inspiration for establishing new channels of communications developed through unique innovations. There is no better place for businesses to invest in Artificial Intelligence solutions than customer service and engagement. The proactive use of AI robots and algorithm will enable B2B marketers to assemble and organize more data to properly imbibe the functioning of their existing business network made up of customers, suppliers, partners, distributors and marketers.

From prediction to personalization, marketers will be able to touch all domains of brand marketing through 360-degree navigation of customers’ habits, tendencies, impulses, unusual spirit and buying patterns. Thus, artificial intelligence in B2B marketing can help:

  • Predict potential customers
  • Discriminate between buyers and visitors
  • Identify special trends and choices
  • Personalize various online campaigns
  • Improved lead generation
  • Smart decision making
  • Increased efficiency
  • Drive more sales and revenue

Latest reports on consumer research also suggest that 80% of B2B marketing executives believe that Artificial Intelligence in B2B marketing will revolutionize the field completely in the next five years.

This means that soon we will see AI-enabled solutions driving a big chunk of marketing and sales of many companies. Through converting huge loads of customer data into actionable insight, Artificial intelligence will pave the way for marketing professionals in making confident judgments about customer behavior and their purchase journey.

Machine learning feeds power to customers

Machine learning + intelligence + digital marketing = empowered customers.

The adoption of artificial intelligence in B2B marketing will not only help businesses, but it will also touch customers by empowering them by giving them more than they can expect. This is where marketers can reap insights from their intelligent software and transform it into smart purchase decisions for customers.

When predictive analytics blends with natural language processing, it becomes easier to predict customer’s future choices and shopping behavior.

As digital marketing executives can send AI-assisted marketing messages, customers receive most relevant suggestions and purchase offers that can help them on their shopping roadmap.

Real-time machine learning use cases

  • Chatbots and Voice Assistants: Retail Chatbots and digital voice assistants are quintessential examples of conversational computing combined with powerful AI to drive seamless user experience using transient data like Google Amazon and Facebook.
  • User Engagement: Making a predictive analytics model derived with the help of active machine learning, as done by Urban Airship and Microsoft Azure will help merchants run their commerce more efficiently by proactively sensing the pulse of customers and boosting retention rate.
  • Natural Language Processing – Machine learning can be further expanded with natural language processing to enhance digital advertising and data organization as well as build far more accurate predictive models that work on most relevant keywords as done by QuanticMind.

AI means relevance and control in digital marketing

Before the Internet became everyday part of our life, real-time advertising was a cul-de-sac. Limited to sending random ad messages to customers in order to drive sales and engagement. Traditional one-way means of advertising and customer service ruled the market, generating no sufficient response. Prior to the wide spread advent and adoption of the Internet, B2B sales and marketing suffered from absence of interactive dialogue. It was hard for customer to track the best deals given that there were no social channels to share brand experience in words.

Cut to the scenario today – things are absolutely different. Customers can now control their purchase journey and select their favorites in no time. Online media is fluid, fast and provides uninterrupted services for customers to avail. With machine learning being an integral part of AI, businesses can eliminate the need for sending annoying pop ups and irrelevant messages.

On the other hand, customers can avoid using ad blocking software because artificial intelligence will redefine the way B2B marketing campaigns are conducted. Thus, ineffective, desperate digital marketing will come to a halt and will no longer spoil brand reputation.

Artificial Intelligence in B2B Sales and Marketing

Artificial Intelligence stops brand abandonment

A great part of B2B marketing and sales depends on how much end users are satisfied with a brand. The entire business network of distributors, suppliers, partners and customers can remain well in harmony if customers keep wanting more of your brand. But in worst case scenario, if they keep receiving annoying messages at the wrong time with irrelevant offers, you have to be ready to see them abandon your brand and quit their loyalty for your brand.

This is where AI and marketing go hand in hand since AI-powered messages are tailored for target customers and triggered at the right time and are highly contextual. This is an informed approach that can not only inspire customers to consider your brand, but it will also make them feel less annoyed and more cared, saving brand abandonment.

Real-time data analysis

Online marketing moguls often parrot the term “real time” while describing the performance of a pre-sales efforts or customer service. But, the arrival of machine learning in the face of intelligent marketing has made it quite possible. Artificial intelligence in B2B marketing has successfully broken all the barriers that stopped businesses from reaching their prospects. Customers can now see changing offers and promotions every minute. All it takes for a machine is to process the online data created by their behavioral pattern to produce relevant, customer-specific solutions.

Adinton is one great example of a company that provides machine learning solutions to businesses across the globe. CEO of Adinton confirms that machine learning has triggered new opportunities for making smart online marketing budget. According to him, such intelligent technology fetches real-time data 24/7 allowing companies to analyze it for generating powerful, actionable insights. For any online business, it is important to have real-time data analysis in place.

Marketers can forecast customer wishes

Based on what we have learned about AI’s machine learning capabilities, this could be a far catch. Earlier, marketers and companies had showed interest in knowing in advance what customers would want in nearest future. Artificial Intelligence can drive marketing prophesy and help predict the customer demand based on trends and purchase patterns. Brand marketing specialists can get tremendous kick from AI’s concrete results, enabling sales and marketing teams to perform well in their pre-sales phase as they get to know what customers are likely to want.

Through informed suggestions, artificial intelligence in B2B marketing can help boost marketing effectiveness, weaving future requirements of customers in their campaigns. Algorithm of AI helps brands come up with suggestions for custom deals and recommendations, merchandise management, fraud discovery, and most searched products, etc.

Marketing content gets persuasive and influential

To interact with the target audience, company’s marketers take it on themselves to use gathered insight to design email campaigns and compose creative ads. The content writers have to be intelligent enough to make precise guesswork about what customers can and will relate with. This might sound impossible without the help of deep learning of AI.

Artificial Intelligence accurately learns about customer preferences to include them in online marketing material. The AI algorithm reads and analyzes the sentiments of customers, enabling marketers to know how to pitch and what customers want to hear. For e.g., Twitter is where it is easy to keep watch on social engagements and find out what is exactly making rage. Based on their findings from comments, marketing writers can compose strategic content that sits well within the pre-sales stage and which can influence customers as well as enhance overall brand image.

Digital operations grow economical

One of the dreadful challenges of marketing is optimizing the cost involved. With the entire business cult getting online, machine learning sounds like a great choice to tackle marketing challenges pertaining to cost.

Since AI’s deep learning ability involves minimal human power, such automated system can reduce considerable amount of expenses in the process while also increasing work efficiency. This unique approach in the digital marketing sphere also helps diminish business communication cost further since customers get auto-responses and machine-enabled suggestions on latest offers via emails, online ads, push messages or social media posts.

AI for today and tomorrow

So far, AI has been widely used by a lot of leaders in IT domain. Google launched its Pixel last year using the potential of machine learning tool called Doubleclick. It helped increase the number of viewable impressions based on historical data. Google saw hike in placing the most relevant ads to the relevant audience, gaining more impressions with the tool than other campaigns that didn’t use the tool.

Thus, AI allows marketers to predict the future outcomes using previous history. In a recent survey, more than 90% of top marketing influencers confirmed that smart people combined with machine learning will be a future of B2B marketing.

Instacart also resorted to Google’s open source machine learning platform TensorFlow to predict how shoppers will follow the sequence to purchase items at store.

Coca-Cola also depends on AI to reinvent consumer engagement on smartphones. The same goes with Walt Disney Co. as it relies on natural language processing to play an audio soundtrack while reading a story to your child.

Final remarks

Undoubtedly, artificial intelligence in B2B sales and marketing is the future growing visible to all of us. All the practical use cases suggest that AI and machine learning can help manage the wild flow of data for businesses to create real-time predictive models and effectively engage with customers while simultaneously gaining competitive advantage. Marketers will harvest new opportunities by using artificial intelligence in B2B sales and marketing by being a great storyteller. AI will push the boundaries of creativity, crafting interactive user experience that will ultimately boost business revenue.

Pinakin Ariwala
About the author
Pinakin Ariwala


Pinakin is the VP of Data Science and Technology at Maruti Techlabs. With about two decades of experience leading diverse teams and projects, his technological competence is unmatched.

Posts from this authorred-arrow
card1
Artificial Intelligence and Machine Learning - 12 MIN READ
How can Artificial Intelligence for Customer Support assist Businesses?
Discover how artificial intelligence can hugely embrance the customer support service for your business.
blog-writer
Pinakin Ariwala
card1
Artificial Intelligence and Machine Learning - 8 MIN READ
How Artificial Intelligence Is Revolutionizing Logistics Management
Leverage the best of artificial intelligence to streamline the logistic processes and overall efficiency.
blog-writer
Pinakin Ariwala
card1
Artificial Intelligence and Machine Learning - 11 MIN READ
7 reasons why Conversational Interfaces will replace Web Forms
Working with webforms can be tedious. Check how conversational interface will replace the webforms.
blog-writer
Pinakin Ariwala