- AI-powered predictive analytics can help identify midsize businesses as a potentially overlooked, steady source of sales, rather than focusing solely on larger corporations.
- Marketing automation, while often misunderstood, doesn’t remove the human touch or cause job losses, but instead allows for greater personalized interaction with clients and the ability to reach a larger audience.
- Accountable AI strategies are crucial, with a focus on trust and accuracy, data confidentiality and security, and providing strategic, relevant data at scale to address unique business challenges and drive engagement and value.
Let’s be honest, artificial intelligence (AI) is transforming the business terrain, creating fantastic opportunities and some intriguing challenges. And if you’re a B2B marketer, you want to ensure you’re up-to-speed and leveraging these changes to your advantage. Today, I want to chat about some recent insights concerning AI in B2B marketing, focusing on midsize customers, squashing some marketing automation myths, and introducing smart strategies for AI usage in B2B sales.
Fostering Relationships with Midsize Customers
I’ve noticed that many B2B sales teams focus their energy on big fish – the large corporate clients. While those clients are important, they also come with a long sales cycle and a fair amount of heavy lifting before the deal is closed. We can’t afford to ignore the midsize customers in the pond. As it turns out, midsize customers are a gold mine waiting to be tapped – they might not bring in those colossal revenues, but they provide a consistent, steady stream of sales.
The secret to reaching these hidden treasures? AI. With AI-powered predictive analytics, you can understand and segment your customer base, pinpointing those midsize businesses that could become your most loyal clients. AI can detect patterns and trends that we humans might miss, offering more precision and efficiency in targeting marketing efforts.
Busting Myths About Marketing Automation
Another key piece of the puzzle is marketing automation. But hold on, I can already hear the myths surrounding this topic. Let’s set the record straight.
Some people think automation takes the human touch out of marketing. It’s not true, friends. The fact is, AI-powered automation tools can give us more time to have personalized, impactful interactions with clients. Plus, it allows us to scale our efforts, reaching more businesses than we could alone.
Another myth is that automation means job losses. Let’s be clear, while AI changes the nature of roles in marketing, it doesn’t necessarily mean there’ll be fewer jobs. It means our roles are evolving, and we need to build new skills and adapt to new ways of working.
Implementing Accountable AI Strategies
Lastly, let’s discuss accountability. As we integrate AI into our sales and marketing strategies, it’s essential to use it responsibly. My buddies over at Forbes recommend a three-step approach:
- Trust and Accuracy:Â A core concern around generative AI is its potential to spread inaccuracies, which could be detrimental to corporate outcomes reliant on precise insights. For instance, AI tools may miss crucial details when analyzing competition; for example, identifying ‘Vans’ instead of ‘VF Corporation’ as a competitor to Nike, and overlooking significant competitors like Li Ning and Anta Sports in China. This lack of comprehensiveness and global context undermines credibility and sales efficacy. Businesses and users leveraging AI need to prioritize tools known for transparency, accuracy, and trustworthiness, while taking responsibility for diligent fact-checking.
- Confidentiality and Security: In the era of sensitive data, generative AI tools like ChatGPT pose a risk of data leaks. Several high-profile companies have already restricted such AI tools after discovering sensitive data uploaded into them. However, when managed correctly, generative AI can synthesize real-time proprietary insights from a blend of public and private datasets, offering invaluable business insights while maintaining confidentiality and security.
- Strategy and Relevance:Â AI tools and Language Learning Models (LLMs) are not inherently strategic and might result in information overload if misused. To be genuinely beneficial, AI applications need to offer accurate, relevant data at scale, reflecting unique business challenges and performance benchmarks. A prime example is a cloud-native enterprise SaaS company that used AI to identify a target account’s strategic priorities and matched them to relevant solutions, thereby increasing engagement and value propositions. By replicating this strategy across accounts, they’ve driven significant pipeline growth and improved outcomes for their customers.
Transparency is all about understanding how your AI model works and can explain its decisions. When AI is used to enhance human decision-making, we can create a fantastic blend of human intuition and data-driven insights. Lastly, refining and reassessing AI systems regularly ensures they remain effective and accurate.
In Closing…
The AI revolution is here, friends. Let’s embrace it. By honing in on midsize customers, busting marketing automation myths, and adopting accountable AI strategies, we can navigate the new terrain of B2B marketing. It promises more targeted efforts, greater efficiency, and stronger relationships with our customers.
If this conversation sparked your curiosity and you’re considering how AI can impact your marketing strategy, let’s chat. I’m all ears to hear about your experiences and thoughts. No sales pitches, just good old-fashioned conversation about B2B marketing.
Feel free to book a call – let’s navigate this exciting AI journey together!