The rhetoric surrounding artificial intelligence (AI) as the panacea for solving business problems has created some skepticism among marketers. It can also be overwhelming.
AI might seem like a cure-all for the issues with your data or marketing and sales analytics. In reality, the technology is none of these things, and AI applications can be classified into several categories, depending on the purpose. There are three “AI’s” that I believe are critical for marketers:
• Automated integrations of data, processes and external events intelligence to enable faster and real-time decision-making.
• Actionable intelligence for organizations, powered by a powerful platform for developing insight.
• Augmented intent data that aggregates multiple data types per market to ensure that it can be easily understood and used by marketing and sales organizations.
For certain, the use of AI by marketers is taking hold. Revenue increases from adopting AI are reported most often in marketing and sales, while other benefits include the ability to predict the likelihood of buying, cost reductions and customer service analytics, according to McKinsey. And with projections that the global enterprise AI market will reach $53.06 billion by 2026, it’s too tantalizing not to consider the transformational potential of AI and machine learning for B2B marketing.
AI has clearly moved beyond the hype; algorithms are continuously learning and can self-correct, giving them the ability to transform work and create a competitive advantage.
Understanding AI’s potential and its benefits can help you and your business benefit from the technology rather than being overwhelmed by it. To prepare, businesses should standardize their definition of AI, assess their readiness for AI solutions and define measurable and transparent ROIs for AI initiatives.
Here are five ways I believe B2B marketers will use AI in the next few years:
Increase lead generation capabilities. One of the core functions of AI is the ability to collect data and extract insights — in this case, from marketing and sales data using machine learning and predictive analytics. Additionally, some AI tools can provide insights about prospects and customers to improve the customer experience and conversion rates.
Gain more actionable customer insights. AI is used to gather information and analyze it to engage more effectively with customers and prospects. Predictive analytics will help forecast purchasing decisions based on buying patterns. This is important and immensely useful because it’s harder to see buying patterns in a B2B model than in a B2C one.
Create more powerful personalization. Marketers can use AI to craft personalized messages throughout the customer lifecycle. With AI modules that tailor experiences, email campaigns can be optimized and personalized based on user behaviors.
Enhance targeting and segmentation. Customer data will be analyzed to create more targeted segments, so campaigns can be modified for different segments. AI will be embedded into location data, which will enable advertisers, DSPs and other users to measure campaign performance, operational efficiency, and ultimately, the ability to make decisions in real-time.
Drive intelligent automation. This is an approach where AI is applied to improve the efficiency and/or performance of repetitive tasks, according to the 2021 State of Marketing report by Drift and the Marketing Artificial Intelligence Institute. Automation can accelerate revenue growth by improving a marketer’s ability to make better predictions. Marketing automation tools can also make content creation and delivery more effective and efficient.
What to Look for in an AI Platform
A platform should be adaptive, open, scalable, easy to use and secure for all markets. It should also include a number of reusable and configurable AI modules that are specific for B2B environments. Turnkey AI does not work; it has to be laser-focused for B2B.
It’s also critical to find an AI partner that provides speed, quality and accuracy.
These are the attributes I believe an ideal AI platform should include:
• The ability to harvest data, enriches data in real-time, verifies data security and leverages robust SLAs (service-level agreements) that focus on 100% accuracy.
• The ability to process data at scale across all regions and languages.
• Data that is always fresh, complete and secure.
• AI algorithms that continue to provide additional intelligence, including deep learning techniques to fill missing data points along with scoring of data across first- and third-party intent.
• A collection of APIs that activate continuous data flows from proprietary datasets, licensed datasets and strategic partners’ datasets, so clients can easily integrate their own data.
The Insights You Can Derive
Using a combination of data science, deep learning models and predictive analytics, the ROI from an AI platform has multiple layers. Marketers stand to benefit from reduced data preparation, onboarding and integration costs, as well as faster data activation time and higher SLAs.
They also have the potential for omnichannel conversions and higher conversion rates.
If this isn’t compelling enough, regulatory compliance is dynamically managed without the need to build multiple, expensive compliance systems. And finally, B2B marketers will have the ability to better predict the performance of data and campaigns and can make recommendations for how to optimize them to achieve maximum ROI.