By Saima Rashid, SVP of Marketing and Revenue Analytics at 6sense. 6sense were finalists in the ‘BestAI Platform‘ category at The 2024 A.I. Awards.

Nothing gets under marketers’ skin like pouring time, resources, and effort into generating demand, only to hand it over to sales and watch it die on the vine.

Of course, the sales folks have their side of the story too. Selling takes more effort than ever before. With a list of potential opportunities to work and only a finite amount of time in which to work them, it’s only natural that some will hang out on the back burner.

Still, when marketing creates demand and sales works the opportunities it sees as most promising, a dreaded “dead zone” develops in the middle where demand goes unworked — and that’s a major source of friction for revenue teams. Even more importantly, it leads to a poor experience for prospects in that dead zone who aren’t getting the follow-up they need to make their decision.

Here’s one of the most compelling use cases for generative AI in sales and marketing: By bringing an AI agent into the fold, the demand marketing worked so hard to develop gets the attention it deserves — without increasing workload.

Why Demand Goes Unworked

Unworked demand stem from what we call lead “B2B inflation” — the phenomenon where more resources are required to achieve the same revenue outcomes. On my team, it now takes twice as many touches to move an account to a qualified pipeline stage compared to just a few years ago. McKinsey reports that B2B buyers now use twice as many channels for vendor research as they did before. Furthermore, Gartner tells us buying committees have ballooned, now including between 14 to 23 stakeholders.

Despite these increased demands, revenue teams aren’t getting additional resources. Many now work with smaller teams and budgets than before. This leads to a ‘capacity gap,’ where BDRs focus on accounts they believe are most likely to convert, leaving others untouched.

Given the importance of timing when connecting with accounts showing interest — companies have only a 16% chance of winning a deal if they are not the first to connect with the buying team — any delay can have serious revenue implications.

AI as a Solution

Generative artificial intelligence (AI) offers a transformative solution to managing the perennial challenge of unworked demand. By implementing an AI agent to step in where BDRs don’t have capacity, revenue teams can achieve three big objectives:

1. Putting control back into the hands of marketing teams to drive the prospect experience,
2. Improving that experience by ensuring interested accounts receive engagement at exactly the right time, and
3. Reducing friction between marketing and sales by guaranteeing no efforts go to waste.

The first step in using AI is to find the tasks that are most taxing for your BDRs and where balls are most often dropped. Analyze which parts of the outreach process require human touch and which can be handled by AI. This strategic deployment of AI allows your team to conduct limitless, contextually relevant conversations with prospects, thereby increasing the number of opportunities you create and accelerating deal velocity, all without adding headcount.

How One Company Used AI to Boost Production by 63%

Data management company Reltio faced the B2B inflation challenge of scaling its business development efforts without additional budget or headcount. With increasing pipeline targets and the same number of BDRs, the company needed a solution to manage and enhance interactions from sources that were not immediately sales-ready. These prospects were interested but required nurturing until the right time to engage them. The goal was to keep BDRs focused while also expanding their reach and maintaining depth in account engagement.

To address this, Reltio integrated AI solutions to automate the management of aged leads, event follow-ups, event registrations, and low- to no-scoring leads. An AI agent handled the preliminary interactions and identified opportunities for engagement, ensuring that BDRs could focus on high-priority accounts. The AI worked collaboratively with the team, operating as an extension of the BDRs, which allowed them to work more effectively and efficiently.

The results were impressive. Overall smart activity levels increased by over 500%, with email open rates averaging 28% and peaking at 36%, significantly higher than industry averages. AI-driven conversations surpassed 6,000, saving over 900 human hours and boosting pipeline production by 63%. The use of AI as a collaborative partner allowed Reltio’s team to maintain consistent activity levels while increasing pipeline production.

Human interact with AI artificial intelligence virtual assistant chatbot in concept of AI artificial intelligence prompt engineering, LLM AI deep learning to use generative AI for work support. EIDE

Long-Term Benefits and Future Outlook

We hear a lot about the “future promise of AI.” But the reality is that AI is here, and its impact is already transformational. We see that in Reltio’s successful implementation of AI. I’ve also seen it firsthand at my company, where we’re currently driving 15% of our pipeline generation with AI while reducing the efforts of our BDR team. This isn’t just about doing more with less; it’s about smarter, more strategic engagement across all stages of the customer journey and improved alignment between marketing and sales teams.

The benefits of integrating AI into marketing strategies are profound and multifaceted:

• Increased pipeline quality and quantity: AI helps identify and nurture accounts more effectively, ensuring a richer pipeline.
• Improved customer experience: Personalized, timely interactions are facilitated at scale, enhancing the overall customer journey.
• Reduction in workload and stress for teams: AI automates routine tasks, allowing teams to focus on more strategic initiatives.
• Autonomous pipeline generation: AI’s predictive capabilities enable proactive demand management, reducing the chances of accounts going unworked.
• Significant savings in work hours and resources: AI can drastically reduce the time spent on manual tasks, reallocating resources to where they are needed most.

The strategic integration of AI tools within marketing and sales processes is proving indispensable in transforming demand management practices. By automating and personalizing customer interactions, AI not only enhances the efficiency of these processes but also significantly improves the quality of engagement and outcomes.

For businesses aiming to optimize their demand management and drive meaningful growth, now is the time to embrace AI — not just a tool, but as a collaborative member of the revenue team.