Good Day PROs!

The requirements for efficient GTM seem to be outpacing the tools we've used for years. Does AI require us to change our approach?

AI: What Is Realistic?

Last week on the gtmPRO podcast we had the good fortune of hosting Jesse Oullette, Founder of LeadMagic but more importantly, equal part sales leader / revops data junkie.

Jesse has been aggressively using AI for prospecting/outbound since before it was cool and continues to explore the art of what's possible. So we were excited to explore what he's learned along the way.

There is a ton of excitement and skepticism about the promise of AI in GTM, but things are moving so rapidly it is hard to know where it will land.

This uncertainty (stress?) is further heightened by the very challenging market environment, where even the very best and biggest are fighting headwinds.

This reminds us of the late 1990s / early 2000s; we can smell the exuberance and know that there is a lot of "vapor," but at the same time an entirely new operating system is being formed in the mist.

The prudent path forward is to wade in with eyes wide open and start putting some of these tools to work.

Outbound Reimagined

Here are a few key points we discussed with Jesse, specifically for Outbound.

Redefining Value in Outbound Interactions

Focus on providing actionable insights and solutions rather than just pushing for a sale. For example, if your data shows a prospect is expanding their team, share a guide on scaling operations or an invite to a webinar on effective team management. This approach positions your company as a thought leader and trusted advisor, not just a vendor.

Build a Technically Savvy Outbound Team

Move beyond the traditional SDR model by developing a team that combines sales acumen with technical expertise. Equip your team with skills in data manipulation and API usage, empowering them to create highly targeted and personalized outreach campaigns. This skill set shift transforms your team’s approach from volume-based to value-based interactions.

Creating a Feedback Loop for Continuous Improvement

Implement a system where outbound interactions feed back into your strategy. Analyze what messages perform best and why, then iterate based on this data. This not only improves your outreach effectiveness but also keeps your messaging fresh and relevant.

Leveraging the API Economy for Personalized Outreach

Start by harnessing the power of APIs to integrate diverse systems and data streams. This approach enables real-time data utilization, enhancing the relevance and timeliness of your communications. For instance, tapping into job board data via APIs can allow you to tailor messages to prospects based on their current hiring needs, making your outreach significantly more contextual and valuable.

Optimizing Outbound Tools with Custom Integrations

Utilize platforms like Clay or other data enrichment tools to automate and personalize at scale. By setting up workflows that automatically pull in relevant data (e.g., recent company activities, market news) and craft personalized messages, your team can engage prospects with information that directly aligns with their interests and current challenges.

The Hard Thing About Hard Things

We look at the points above and think to ourselves, "this makes sense." But then we go back to our teams, without making any changes to structure, priorities or incentives and ask them to "think strategically."

Here's the thing. This begins and ends with us … Revenue Leaders (even the CEO).

It's all about capital allocation, which, in software and services, is people and their time.

We don't just magically fabricate a "more technical team" who design "feedback loops" with "optimized tools."

This takes reimagining the GTM org for the current environment. One that is here to stay. One where our Buyer has an abundance of choice and a scarcity of time. One where we need both growth and efficiency.

Need some help thinking this through? Just DM Gary or Andy on LinkedIn. We are here to help.

Bonus: Here is a graphic Jesse developed as a framework for an AI-informed system.