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AI in B2B marketing: how to achieve decisive competitive advantages

Using AI to support B2B marketing offers considerable potential.
Image: © SFIO CRACHO / Adobe Stock

AI marketing as a growth market

In the context of increasing digitalization, the use of artificial intelligence in marketing has become one of the industry’s big trends. As the latest figures from GP Bullhound’s report entitled ‘AI and the Services Revolution’ illustrate, the market is experiencing rapid growth: around one billion US dollars were invested in specialized AI marketing companies in Q2 2019 alone. This means that the total financing volume in this area has risen to more than eleven billion US dollars within the last six years. Intelligent technology is also gaining ground in B2B marketing and sales, where its broad range of uses is opening up new market opportunities and securing decisive competitive advantages for proactive marketers.

Comprehensive databases allow effective use of AI in B2B marketing

A comprehensive, high-quality database is essential for successful use of AI in B2B marketing. After all, the strength of this intelligent technology lies in its ability to:

  • analyze huge amounts of data,
  • link data,
  • recognize patterns and
  • derive results and predictions from all of this.

Big data effectively forms the basis via which AI systems gather knowledge, continuously train using machine learning, make decisions and, finally, effectively automate processes. To produce precise predictions and recommendations, special attention must therefore be paid to both data capture and management, which underpin what the AI systems can ultimately achieve in the specific applications.

What AI can achieve in B2B marketing

Data is considered the new currency of the digital revolution. It is not the information as such which provides the real value, but the knowledge that can be derived from it. And this is exactly where AI applications come in, with their ability to systematically analyze information, decode patterns in consumer behavior, provide valuable target group insights and reveal relationships. AI systems then use this knowledge to derive precise predictions and recommendations, thereby valuably supporting predictive campaign management and the planning of B2B marketing strategies.

The use of AI in B2B marketing improves both the quality and speed of decisions. For example, real-time performance analysis enables immediate campaign optimization and eliminates manual effort.

Communication with customers and partners is an example of another area in which AI-based automation offers significant potential. When AI chatbots handle recurring processes and tasks, this not only frees up a lot of time but can also significantly improve the customer experience through specific approaches and new, efficient forms of dialog.

Use of artificial intelligence in B2B marketing

How can artificial intelligence be successfully used in B2B marketing and sales? Although the use of AI in marketing is still in its infancy considering the enormous future potential, there are already a multitude of areas in which it can now be used to deliver considerable cost and efficiency gains, such as:

  • Predictive lead scoring: Predictive lead scoring is a means of analyzing existing customers and using machine learning to produce individual scoring models. These models allow predictions to be made about which leads (customers) are the most promising and most likely to produce the desired outcome, taking characteristics and behavior into account. Through analysis of these factors, predictive lead scoring also provides valuable information that can be used for campaign optimization and to tap into new target groups.
  • Predictive analytics & forecasting: With predictive analytics, AI systems process historical data and use this to predict future trends. For example, US IT giant IBM only recently presented an exciting predictive ad solution with its Advertising Accelerator at CES 2020. The Advertising Accelerator works with the artificial intelligence engine Watson, which is designed to help determine how ad creative will resonate with specific target groups and essentially boost the effectiveness of advertising through targeted engagement.
  • Dynamic pricing: This pricing strategy, also referred to as surge pricing, takes into account current market demand. This is based on an algorithm that can automatically change prices in real time depending on supply and demand, consumer behavior, current price trends and other external factors. Popularized by Amazon & Co., AI-based dynamic pricing is now also within the reach of smaller companies.
  • Conversational marketing & customer support: The use of AI chatbots in messenger marketing or in the form of digital shopping assistants, for instance, offers companies enormous potential to stand out from their competitors in the area of customer service. As AI can support the customer service process in many different ways through its analytical and technical capabilities, companies can focus more on actual needs and providing tailored solutions.

Far-reaching opportunities for B2B marketers from the use of artificial intelligence

There are enormous advantages to be gained in everyday business and personal development from the effective interplay of B2B marketers with their experience on the one hand and the AI systems supporting them on the other. For example, intelligent data analysis opens new doors to often very niche target groups, provides in-depth customer insights and directly delivers the information required for direct, personal approaches. AI also offers great opportunities in B2B marketing to expand and enhance people’s abilities and range of tasks. By automating processes – in other words, by taking on recurring, complex tasks – AI frees up valuable time and space that B2B marketers can devote to partner management or the strategic development of business areas.

Daniel Dodt
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