Vertical AI: High ACVs Revolutionize Sales Strategies

The Impact of Annual Contract Values on Vertical AI

In the realm of vertical SaaS products, annual contract values (ACV) have long been relatively low. Customer acquisition costs needed to stay below a certain threshold, and the playbook for the market was focused on product-led growth, with sales teams and customer-oriented content. However, the emergence of artificial intelligence (AI) has transformed this landscape. Many products are no longer simply viewed as SaaS but as usage-based and outcome-driven solutions. These products replace human labor rather than merely providing software. At Defy, an investment firm, we refer to this new category of companies as "vertical AI."

Spending on vertical AI does not solely come from a client's software budget, but often from personnel costs, which represent a much larger line item. As a result, ACVs have significantly increased, reaching six- and seven-figure contracts. This evolution has led to a revision of go-to-market strategies, with a focus on more effective tactics for the sales process.

The Resurgence of Direct Sales

Historically, direct sales were only viable at a significant enterprise scale. The cost of an Account Executive's (AE) time was not justified for lower ACVs. Below a certain contract size, the math did not work for high-touch sales. This is why the go-to-market strategy for SaaS shifted towards product-led growth and sales teams.

With vertical AI ACVs frequently reaching six or seven figures, founders now have the opportunity to invest significantly to win each logo. We also observe that these smaller companies are spending relatively more with faster sales cycles, allowing for a higher volume. AEs, in-person sales, and other tactics that were not profitable at scale under the old SaaS economy are now effective. Direct sales are now viable in lower market segments where the old SaaS economy did not allow it.

Key Channels for Vertical AI

Two channels, in particular, have recently favored the distribution and success of vertical AI companies. They are distinct, but we have seen companies succeed with both.

• Private Equity and AI Leads: Many private equity firms are actively pushing their portfolio companies to improve efficiency through AI. Some have even created a new internal role to lead these initiatives. These AI partners are often tasked with gathering and disseminating learnings, finding good AI tools, and integrating them into the portfolio if appropriate. The motivation can sometimes be EBITDA-focused, but it can also be more subtle. Many of these executives seek to add value across the entire portfolio, help companies build AI capabilities, and develop an execution plan. The decision-making structure also varies. Sometimes the firm itself may be the buyer and push adoption within the portfolio. More often, the firm will relay information to the relevant business leaders and leave the decision-making to them. If executed well, this can be a very effective channel for vertical AI companies. An introduction to the private equity firm generates many qualified leads across their portfolio companies. Generally, companies will start by acquiring one client. Positive feedback then circulates in two directions: laterally to similar companies within the portfolio and upward to the private equity investor, who introduces the provider to others in the portfolio. We have found that this works particularly well in sectors where consolidation strategies are popular, such as healthcare services, dentistry, MSPs, accounting, law, financial consulting, insurance brokerage, home services, and industry.

• Industry Conferences: Sector-specific or function-specific conferences are extremely valuable for driving distribution for vertical AI companies. The advantage lies in the focused attention and self-selection of the right buyers. Buyers are captive and open to learning. They come to these events curious to hear about the latest developments in their industry. Attendance allows companies to meet the right buyer, showcase the product live, and generate leads at scale. Sponsoring and participating in dinners represent another opportunity to meet prospects. I would argue that the scalability of lead generation and brand awareness is more important than ever. This requires making your own company known while standing out from others in the market. Buyers are actively building their AI strategies, so vertical AI companies must rush to market. Whether it becomes a sole-source decision or an RFP, the prerequisite is to be part of the overall considerations. For that, your buyer must know you exist, and this is an excellent way to spread the word effectively.

AI has opened distribution for vertical SaaS, and the value framework has shifted from subscription pricing to a labor substitution economy. The go-to-market playbook for vertical AI is now significantly different from that of the SaaS it originated from. Distribution, pricing, and sales strategy have all evolved in concert, with each element reinforcing the others. Buyer demand justified higher ACVs, which in turn justified deeper investment in sales strategy, and new economies opened channels that did not work under the old model.

The companies that stand out are those that combine an excellent product with the right go-to-market strategy. They have recognized that higher ACVs require a different playbook and have adapted ahead of their peers. When the doors to distribution opened, everyone rushed in. The companies that are winning now understand what to do once inside.

If you are a founder building a vertical AI and rethinking your go-to-market strategy, I would love to hear from you.