How to think about pricing your AI features
Plus, welcoming AudiencePlus and Logik.io to the portfolio, open portfolio roles, and more.
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🔦 FEATURED CONTENT
How to Price AI In SaaS (May 2023 Edition)
By Jake Saper, General Partner at Emergence
In 2019, I wrote a post on how companies should price their AI-enabled software. I focused on SaaS companies that were developing their own AI and highlighted pricing considerations as they work to improve their models.
Since then, there’s been a meteoric rise of third-party foundational model providers like OpenAI, MosaicML, and more. These “AI as a Service” vendors have enabled any SaaS player to integrate powerful AI into their application. This has created a mad dash to sprinkle AI pixie dust across the SaaS ecosystem. We’ve seen this among the countless newly minted startups and more established public companies like Hubspot and Doximity.
The proliferation of this technology raises many questions, including how to deploy it safely, who will win—will it be focused startups or incumbents with existing distribution?— and more. One important area that hasn’t yet been discussed much is how it should be priced. Below, I lay out a working framework on how to think about pricing the AI in your SaaS application. The space is evolving rapidly, so I’ll update this thinking in future posts.
Start by understanding how much differentiated value your AI features are creating
By definition, these foundational models are accessible to every SaaS provider, so how should you think about pricing what is, in effect, a commodity you’ve integrated into your product? Start with first principles: how much differentiated value does this AI feature create?
By integrating AI features into the flow of your broader platform, you are saving the user time from having to leave their flow to go to the underlying model (ChatGPT, etc.) Keeping the user in context can be a powerful unlock (see our thoughts on Deep Collaboration here).
However, be honest with yourself as to how much value your AI is actually creating. Many AI features in SaaS today are getting a flood of initial tire kicks from curious users but aren’t seeing meaningful sustained adoption. Start by understanding retention and value creation.
Then ask yourself how differentiated your AI offerings are. If the majority of the value your AI feature creates can be garnered by going directly to ChatGPT, don’t try to make a significant margin on that feature. Reselling is not a sustainable value-creation strategy (nor a differentiation strategy, though that’s a topic for another post).
Even if you aren’t able to charge much for your AI features today, they can create meaningful value by making your current product more valuable and perhaps stickier. They can also be used to drive upsell to higher tiers, all of which can result in increased net dollar retention.
Over time, you can leverage initial features that may today just be a thin wrapper around a third-party model to build more differentiated value (more on how below). And when you get to that point, you can consider a more value-extractive pricing approach.
The state of AI pricing in SaaS today: early days
As you launch your AI features, your priorities should be to learn about how/where they add value and to drive user adoption. To that end, many SaaS companies are starting by offering their AI features for free. The leaders we’ve chatted with behind these strategies envision monetizing over time as they learn more about how much value is being created and for whom.
That said, some SaaS providers have already begun to charge for their AI features. Most start with a freemium approach typically gated on usage volume (not features) so the user gets a full taste of the feature’s power before seeing a paywall. The pricing models they use prioritize simplicity, which helps drive adoption. GitHub CoPilot and NotionAI, which have both seen strong adoption, charge on a per-seat basis.
There’s an open question around how much of these foundational model COGS SaaS providers will be able to pass along to their customers over time. It may be the case that for those that provide truly differentiated value, they’re able to pass all of these costs along (and add a healthy margin). Those that provide more commoditized value may not be able to and will thus have lower gross margin profiles than traditional SaaS providers (70-80%). These players may be able to leverage AI to improve their internal operations (e.g., automating major parts of sales and marketing) and recover some of the gross margin loss in their operating expenses.
🚀 GO-TO-MARKET ADVICE
Defining Channel Qualified Leads (CQLs)
By Doug Landis, Growth Partner at Emergence
For years, we've used the following acronyms to help us identify the source of our leads:
MQL for Marketing Qualified Leads
SQL for Sales Qualified Leads
PQL for Product Qualified Leads
In the challenging market we're all swimming in, we're seeing a new lead source: CQL for Channel Qualified Leads. The channel is exploding right now for many companies as it's a great way to expand your sales organization with far less cost. In frothy markets, revenue or leads from the channel tend to be viewed as 'additive' to the pipeline and revenue generated from the direct sales organization. Given how many organizations have made significant cuts, especially across the sales and GTM organizations, the channel has become even more important. Give your channel partners source credit by identifying these leads as CQLs.
🔗 TRENDING TOPICS
What we’re reading at Pier 5
Apple is planning on transforming the next iPhone using generative AI. The company has recently posted 28 new job opportunities in AI, including the role of “Visual Generative Modeling Research Engineer” who will be part of “a group that will shape the way generative AI technologies transform Apple’s mobile computing platforms.”
Nvidia saw its valuation soar to $1tn, making it the fifth most valuable American company and one of the first major corporate beneficiaries of the hype around. “The chipmaker has been a major, and in some cases, dominant player in several industries for years. But no development has raised its profile – and its potential windfall – as much as the current excitement around generative AI.”
Media and entertainment companies are rapidly turning to cloud storage in efforts to upgrade their security measures. “Survey findings highlighted that, while M&E organizations are still relatively new to cloud storage (69% of respondents had been using cloud storage for three years or less), public cloud storage use is on the rise, with 89% of respondents looking to increase (74%) or maintain (15%) their cloud services.”
According to a recent Gallup poll, an estimated 44 million American adults are experiencing "significant loneliness." Now, some Americans are turning to artificial intelligence for help dealing with some mental health issues.
More artists are embracing artificial intelligence, not fighting it. “Even as artificial intelligence tools like Midjourney, Stable Diffusion, and DALL-E that turn text into images draw lawsuits from copyright-holders who claim the apps are stealing their work to train algorithms, AI-generated art is being legitimized by mainstream institutions.”
📰 PRESS
Our team featured in the news
The Wall Street Journal | Investors Continue to Back Logistics Tech featuring Joe Floyd
Business Insider | Welcome to the final phase of software eating the world. SaaS companies beware, you're on the menu this time featuring Jake Saper
Forbes | How Generative AI Could Give Us Back At Least 40% Of Our Time featuring Jake Saper
Fortune | How to land a job in venture capital, according to 4 top VCs featuring Lotti Siniscalco
TechCrunch+ | Factors to consider before pricing AI-enabled SaaS featuring Jake Saper
💸 PORTFOLIO NEWS
Welcoming AudiencePlus and Logik.io to the Emergence portfolio!
Emergence is delighted to announce that we have led AudiencePlus’ $5 million financing round as the company begins to transform the marketing automation industry. We are thrilled to partner with Anthony Kennada and Tyler Sparks, who we believe represent the perfect ‘founder-market-fit’ to reinvent how B2B companies go to market and fuel company growth. Read more about our investment and the company’s early success here.
We are also thrilled to announce that Emergence has led Logik.io’s $16 million Series A, partnering (for the second time!) with co-founders Chris Shutts and Godard Abel as they transform once again the B2B selling model from one that is complex, convoluted, and expensive, to one that is consumerized, low-touch, and efficient. Knowing the power of Chris and Godard working together and their understanding of exactly what the next iteration of CPQ should be, we are delighted to work with them again nine years after leading SteelBrick’s Series A. Read more to learn about our investment in Logik.io.
🔮 PORTFOLIO JOBS
Looking for your next role?
Check out the open opportunities at our portfolio companies.
G&A & Operations
Forma: Accounting & Financial Operations Lead (Remote)
Gusto: Head of Payroll Tax Compliance - Symmetry (Scottsdale, AZ)
Hi Marley: Associate General Counsel (Hybrid, Boston)
Eng, Product & Design
Bill.com: Senior Director, Growth Data Science & Analytics (Hybrid, San Jose)
Gusto: Head of Engineering, Members (Hybrid, San Francisco)
Ironclad: Principal Designer (San Francisco, New York, Remote)
Oyster: Director, Product - Payroll (Remote)
GTM & Business
Maze: Director, Product Marketing (Remote)
Oyster: VP, Global Sales (Remote)
UpKeep: VP, Sales (Los Angeles, Hybrid)
Zoom: Head of Product Marketing (Remote)
We have ~840 open roles on our portfolio jobs site. Check them out!
