Jurassic holds second Lunch & Learn on AI & Demand Generation
As we continue along the early innings of 2024, we're excited to continue adding value to our portfolio companies to enrich and grow the Southeast tech ecosystem. The new year has certainly revealed how B2B customer preferences, desires and spending have shifted, and with it, how companies should execute their demand gen marketing. Last week, a friend of the firm, Matt Cretzman, held a lunch and learn on this topic, bringing together the CEOs and Marketing leaders at all five portfolio companies to walk through his vast experience on how to think about nurturing efficient campaigns.
Matt is a highly experienced B2B marketing and sales expert, the founder of Stormbreaker Digital, Pipeline Accelerator, and more recently and notably, LeadStorm AI — a marketing and sales automation platform specializing in multichannel outreach, handing B2B marketers features like social outreach technology which fully automates cold outreach using a highly effective multichannel strategy to put you in front of your ideal prospects, fill your sales pipeline with the right opportunities, and close more deals.
We had great discussion amongst the teams and thought we would share three of our favorite takeaways below, complete with actions that your marketers can consider:
B2B lead generation has changed due to…
Attention Deficit: The inundation of digital content has led to shorter attention spans among potential B2B clients. This makes traditional lead generation strategies less effective and harder to capture and maintain interest.
Use AI to Segment Audiences: Employ AI tools to segment your audience based on online behavior, interests, and engagement history. For example, if AI identifies a segment that frequently engages with content on cloud solutions, tailor your outreach with in-depth articles, webinars, and case studies on cloud technology advancements.
Leverage Personalized Content: Implement AI-driven content personalization engines on your website and in email campaigns. For instance, a visitor who previously engaged with content about AI in marketing should receive personalized recommendations for similar topics or upcoming events focused on AI advancements.
Interactive Content: Create quizzes, assessments, or interactive demos that are personalized based on the visitor's industry or specific interests, as identified by AI analysis. This could include an interactive tool that assesses a company's readiness for digital transformation, offering instant, personalized reports.
Salesperson Mistrust: There's a growing skepticism towards sales pitches and traditional sales tactics among B2B decision-makers. This mistrust stems from past experiences of overpromise, leading to a preference for self-research and reliance on peer reviews and testimonials.
AI-Enhanced Consultative Selling: Train your sales team to use insights generated by AI, such as predictive analytics on customer pain points or upcoming industry trends, to approach leads with solutions that are genuinely aligned with their needs. For example, if AI predicts a rising demand for cybersecurity in the financial sector, sales pitches can be tailored to address these specific concerns.
Peer Reviews and Testimonials: Utilize AI to analyze customer feedback and identify the most impactful testimonials for specific industries or problems. Highlight these testimonials prominently in your marketing materials and on your website. For example, using AI to curate testimonials that specifically mention the effectiveness of your product in enhancing operational efficiency for tech companies.
Transparent Engagement Metrics: Share engagement metrics and insights with prospects to build trust. For instance, inform a prospect that "Our AI analysis shows that companies like yours have found our latest whitepaper on X to be highly beneficial," thereby demonstrating transparency and a data-driven approach.
Data is Everywhere: The abundance of data available today means that B2B buyers are more informed and have higher expectations. However, it also presents an opportunity for sellers to deeply understand their market and tailor their approaches accordingly.
Data-Driven Personalization: Implement AI tools to analyze data from various touchpoints (social media, website, email) to create highly targeted marketing campaigns. For instance, if data shows a high engagement rate with email content related to sustainability practices in the manufacturing sector, develop a targeted campaign for this segment focusing on your sustainable solutions.
Real-Time Lead Scoring: Use AI to score leads in real-time based on engagement, allowing for immediate follow-up on the hottest leads. For example, if a lead downloads a whitepaper, watches a webinar, and then visits the pricing page, your AI system could automatically prioritize and alert the sales team to this high-intent behavior.
Predictive Analytics for Content Creation: Utilize AI to predict topics of rising interest within your target audience and create content ahead of the curve. For instance, if AI identifies an increasing interest in machine learning applications in small businesses, develop blog posts, case studies, and webinars on this topic to attract and engage this growing segment.
By effectively leveraging AI, companies can navigate these challenges and foster more meaningful, trust-based relationships with potential clients, ultimately leading to more successful lead generation outcomes.
