Every year, new advancements in the technology space have assisted businesses by creating new opportunities for customer outreach. One of greatest technologies of our time is Artificial Intelligence (AI) which has been creating quite the buzz in the B2B arena. Even though marketers have tested the waters when it comes to machine learning algorithms, there is still major ground to be covered when it comes to predictive analytics, personalization, statistical analysis as well as lead generation. Given its potential, Artificial Intelligence in B2B sales and marketing is here to transform the way people interact with brands, information and services.
A good handful of enterprise giants dread the idea of automating their marketing functions with the use of Artificial Intelligence, however, by measuring the effect of AI in the customer service industry, one can affirm that understanding customer nuance and deriving insights from relevant customer data will not be entirely manual or managed by humans alone.
This article takes a deeper look into how Artificial Intelligence in marketing is doing and how effectively AI scales up B2B sales and marketing in today’s scenario beginning with the digital marketing industry that is steadily incorporating Artificial Intelligence for marketing automation.
Digital marketing as we know it
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 growing by leaps and bounds and online sales have more than doubled in last five years.
Research shows that approximately 70% of US citizens prefer to shop online. Additionally, total revenue generated from online ads has exceeded that of TV, desktop and newspaper ads.
Such real-time statistics highlight how customers are open to making their online presence 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 online marketing campaigns and efforts revolve around how much business value is drawn from the data related to their everyday customer interactions and engagements. Certain factors involved in the data management process make or break the final outcome. So how do you go about manipulating data that offers insights into your customer journey?
Challenges in harvesting precious data
To address every minute requirement of customers and reach maximum acquisition within the B2B marketing space, enterprises should concentrate their 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 or e-mail communication, website visits and purchase decisions. When it comes to organizing, processing and deriving insights in the form of customer mindset, demographics and their behavior from heaps of data — enterprises need to consider incorporating Artificial Intelligence in B2B marketing and sales strategies.
Lack of proper skillset being a major challenge, businesses often miss out on insight as data collected is disposed or mismanaged or considered redundant — resulting in poor pre-sales marketing strategy. This is why, when it comes to harvesting and processing customer interaction data, the presence of intelligent machine learning and Artificial Intelligence in sales and marketing would offer unparalleled and actionable insight resulting in significant ROI.
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, the 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 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.
Whether it is prediction or personalization, marketers will be able to touch all domains of brand marketing through 360-degree navigation of customers’ habits, tendencies, impulses, and buying patterns. To give you a quick overview, Artificial Intelligence in B2B marketing can help in the following –
- 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
Reports on consumer research also suggest that 80% of marketing executives believe that Artificial Intelligence in B2B marketing will revolutionize the field completely in the next five years.
Artificial Intelligence in B2B Marketing leads to empowered 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 software and transform it into smart purchase decisions for customers.
With predictive analytics blending with natural language processing, it becomes easier to predict customer’s future choices and shopping behavior.
We are already seeing the rise of AI-assisted message prompts where customers receive relevant suggestions and purchase offers in the B2C space. The time isn’t far where we see something similar in practice within the B2B space with the amalgamation of Artificial Intelligence in marketing.
Real-time machine learning use cases
- Chatbots and Voice Assistants: 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 customer pulse 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.
Artifical Intelligence in Marketing = more relevance and control
Before the Internet became an 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 widespread advent and adoption of the Internet, B2B sales and marketing suffered from the absence of interactive dialogue. It was hard for potential customers to identify the right solutions given that there were no social channels to share brand experience in words.
Cut to the scene today — things are poles apart. Customers can now control their purchase journey but identify and select their favorites in no time. Online media is now fluid, fast and provides uninterrupted but more importantly, relevant services for customers to avail.
On the other hand, customers can avoid using ad blocking software because artificial intelligence will redefine the way B2B marketing campaigns are conducted. With the incorporation of AI, marketers can target customers with the right context at the right time with an informed approach.
Thus, ineffective and desperate digital marketing will come to a halt and will no longer spoil brand reputation or increase brand abandonment.
Real-time data analysis and forecasting
Online marketing moguls often parrot the term “real time” while describing the performance of 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 along with forecasting future buying trends based on past purchase patterns.
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 smarter budgeting when it comes to online marketing. According to him, such intelligent technology fetches real-time data 24/7 allowing companies to analyze it for generating powerful, actionable insights.
Marketing content gets persuasive and influential
To interact with the target audience, company’s marketers take it upon 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 to. However, with the integration on Natural Language Generation, content curation can be automized based on customer preferences and demographics.
Developing relevant content pieces for your target audiences in order to move them through different stages of the marketing funnel will far more streamlined with the incorporation of AI in Marketing.
Algorithms can be run to collect and collate data from your customers/audience pertaining to what they like to read, their current challenges and concerns with regards to your business or service offerings etc. Post acquiring data that is highly personalized to this extent, marketers can then curate and create content that is relevant and answers their questions either through outreach systems like emails or social media or by incorporating chatbots that can directly converse with their potential customers.
Intelligent chatbot integration will not only will this assist your sales team with their interactions but also directly boost customer engagement as well as conversion rates for any campaigns they are advertised.
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 a 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 via emails, online ads, push messages or social media posts.
Adoption of AI in Sales and Marketing 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 a 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 the 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 the 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.
All in all, it is safe to say that a lot is happening and set to happen in the world of B2B marketing with respect to AI. Acknowledging the fact that Artificial Intelligence has powerful potential to shape sales and marketing is imperative. All the practical use cases suggest that Artificial Intelligence 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. Enterprises need to decide on collaborating with the right technology partner in order to assist them in this paradigm shift and transition of adopting AI within their marketing strategies.
Optimized decision making, shorter sales cycle through ‘predictive’ buying and personalized outreach are some compelling outcomes to result in a WIN/WIN scenario for both — enterprises and its customers.