How to Go from GTM Bloat to Velocity

Growth or profitability?

For years, operators have been led to believe these two critical business objectives are mutually exclusive. Conventional wisdom dictated that pursuing growth meant burning cash to acquire customers at all costs.

While chasing profitability required austerity measures that stifled innovation and stagnated revenue growth.

But what if I told you this is a false choice - a myth perpetuated by legacy technology limitations? Advances in artificial intelligence are now making it possible to have your cake and eat it too.

In this article, I'll walk through how AI can transform your go-to-market engine to achieve accelerated growth AND increased profitability.

The Rise of Go-To-Market Bloat

Over the last decade, low interest rates and easy access to cheap capital led companies to prioritize hypergrowth at the expense of profitability and efficiency.

To fuel that hypergrowth, businesses hired larger teams and bought lots of point solutions and tools that only solved one workflow out of the many hundreds of workflows required to run their go-to-market organizations, merely papering over the problem. 

Marketing automation, CRM, sales engagement, data enrichment, the list is long. But this go-to-market sprawl led to data and process fragmentation. Teams became even more siloed, using one-off tools that didn't talk to each other.

And most of the valuable workflows were still done manually by overworked team members, or worse yet, not being done at all.

Teams wasted time manually copying and pasting data passing leads from tool to tool, losing the rich and valuable context in the process. Data was trapped inside tool organizational data silos, unavailable for powering AI driven, platform level insights and action recommendations.

While growth soared in the short term (at least for a handful of high flying startups), the cracks soon started to show across industries.

Customer acquisition costs skyrocketed and lifetime values plummeted as competition used the same cheap capital to flood the same go-to-market channels with the same messages. 

The investments into growth at all costs over the last decade has not paid off for the average company, and it killed many others in the process.

Investors have taken notice, demanding a path to profitability and a return to efficiency. Every company is now scrambling to “do more with less”. But legacy technology has failed us all, perpetuating GTM Bloat.

Tool sprawl, hyper-specialized personnel, disjointed data, and manual processes have been destroying company bottom lines. And companies are realizing that that next new hire is unlikely to be the “magic bullet” that will fix what’s broken. 

The status quo isn’t working, and transforming our go-to-market organizations requires a better approach.

The Opportunity for GTM AI

Artificial intelligence now offers a powerful solution to the go-to-market bloat problem.

Powerful AI with automation can help companies achieve systemic leverage - empowering every individual to accomplish more both scalably and consistently. Each new workflow magnifies the force and compounds across the organization.

But most AI tools created today are specialized point solutions targeting small, insignificant problems.

For example, sales reps might use an AI assistant for email outreach. But email is just one step in the customer journey. Optimizing one email by itself provides limited impact to the entire go-to-market organization.

To truly transform go-to-market, AI needs deeper integration across tools, teams, and data.

The solution is a GTM AI Platform that sits above your tech stack – ingesting data from all sources and powering automated workflows across teams. This unified approach allows AI to inform decisions holistically across the customer lifecycle.

You need to infuse AI across the entire go-to-market engine. On a single, unified platform.

GTM AI Use Cases

Imagine a world where AI handles manual busywork, while amplifying human creativity and strategy.

Where insight flows seamlessly across departments, leading to coordinated targeting and outreach. Where every employee is empowered to accomplish more each day. This future is possible with unified GTM AI.

Let's walk through how it works to solve key use cases across the customer journey:

Lead Enrichment & Prioritization

• AI analyzes raw prospect lists - considering attributes like industry, company size, technologies used - to automatically score leads with real-time data, live from the web, not stale, out-of-date data from expensive data providers.
• Highest value leads are routed to sales reps, while others go to automated nurture campaigns. The content for both channels is created and optimized by AI.
• As prospects engage with campaigns, AI adjusts lead scores dynamically based on engagement. Hot leads are fast-tracked to reps for white-glove touches.

Realtime Account Research 

• AI scans the web and public databases to build detailed company profiles - including where companies are making bets for growth, and what challenges they’re likely to face.
• These rich profiles enable reps to personalize messaging and navigate complex selling processes. Aligning their solutions to the things that company executives truly care about.
• AI also surfaces relevant connections to tap for warm introductions and referrals.

Content Creation & Curation

• Based on lead attributes and context, AI recommends the most relevant content to share - be it internal collateral, external content, or customized collateral generated on the fly.
• Over time, AI learns which content drives the best engagement for different prospects. Transcripts from sales calls become critical inputs for a “content flywheel,” becoming the basis for SEO and thought leadership marketing content.
• AI automates the content waterfall, repurposing content for landing pages, ads, social media, blogs, etc. AI also translates and localizes content instantly. 

Powering Operations

• AI should be thought of as infrastructure that powers GTM processes, not just as tooling that solves small use cases.
• By integrating seamlessly into the existing stack, a GTM AI platform should meet users where they are – like Slack and Salesforce – instead of requiring yet another app to switch between.
• Companies can avoid the long tail of change management and get instant time to value by taking a systematic, operational approach to integrated AI.

And this is just the beginning. Unified go-to-market AI powers breakthrough efficiency gains across all facets of sales, marketing, and customer success - combining siloed data and automating manual workflows.

The result? Reduced costs, accelerated pipeline velocity, and increased lifetime value from hyper-personalized journeys.

Go-To-Market Velocity, Achieved

Legacy technology created a complex web of go-to-market solutions that delivered diminishing returns. But new advances in AI present an opportunity to break free of legacy limitations and achieve true, sustainable GTM Velocity.

Unified go-to-market AI sits above your tech stack - ingesting data, informing decisions, and automating workflows across the customer journey. This amplifies human productivity, compounds efficiencies across teams, and optimizes the end-to-end experience.

Growth and profitability. With AI, you really can have it all.

You can get the most out of all your GTM investments, achieve an attractive financial profile for investors, and provide maximum value to your customers. 

You can future proof yourself and run a high-performance, high-velocity GTM engine.