What Investors Are Looking for in SaaS
The SaaS market has exploded in recent years and with the impact of COVID, has seen dramatic tailwinds as industries go through an accelerated digital transformation. In 2020, the SaaS market grew to $104B according to Gartner, in revenue and they expect the market to reach $140B by 2022.
The IPO market for SaaS remains robust with recent public debuts of companies like Palantir and Snowflake in 2020 leading the surge.
As Seed and Series A enterprise tech investors, we think a lot about the characteristics that are representative of an exciting early-stage business. When it comes to SaaS startups, we look for the following:
- Sticky product characterized by high usage and low churn: In early-stage businesses there isn’t a lot of predictive data. However, early customer traction and increasing usage is always an important metric to track. Companies that focus on this early can build a strong customer base that has very low levels of churn. We typically see 90-95% Gross Retention1 and 120-140% Net Retention2 for the top performing SaaS companies.
- Clear Ideal Customer Profile (ICP): Companies that clearly understand their target customers have a higher chance of success when it comes to product building and efficient selling. At the early stage, entrepreneurs should develop their ICP through unique insights about their customer base which comes from a combination of their past experiences, extensive “Voice of Customer” Research, and/or an industry insider with deep domain expertise (typically an early customer or ex-entrepreneur). Some of the tangible benefits of a well-defined ICP are:
- A more efficient targeted go-to-market (GTM) strategy
- Shorter sales cycles - since you have clear focus on a repeatable pain point and value proposition
- Highly focused product roadmap driven by exact customer pain points
- Efficient growth managing deal size vs. customer acquisition cost (CAC): Companies need to be laser focused on their early GTM allowing them to iterate quickly as they grow. While 6-figure ACVs are always an encouraging sign, we believe that a more repeatable selling playbook, even at lower ACVs, is more important to establish early on. Because of this, we want to see a Gross Margin Adjusted CAC Payback3 below 12 months as an important metric.
Exciting Trends in Vertical SaaS
Digital transformation has created new demand for vertical software plus companies are now applying AI-powered technologies and product-led growth strategies to achieve new successes.
Radius is an example of a newer vertical SaaS company providing a mobile-first CRM designed for real estate agents and brokers. Their software enables agents to track tasks, find property leads, and efficiently match buyers with on and off-market listings. Given traditional CRM solutions don’t have many of these integrations and unique data, Radius is tailor-made for the new real estate market.
Another company that has perfected their GTM is Reify Health. Reify Health provides collaboration and workflow software for pharmaceutical companies and their clinical research partners to efficiently sign up patients for drug trials. Reify’s ability to understand the end user pain at research sites was the key lever in their ability to scale. The ease of adoption has resulted in a growing network of sites using the product.
These targeted vertical solutions have become easier to sell as companies have a clear understanding of their ICP and the specific needs of their target industry. By developing a refined GTM approach, and through strong word of mouth through customers in that industry, these businesses have developed a strong foothold.
The Growth of AI-powered SaaS Applications
Artificial intelligence (AI) has an important role in enabling modern software to automate work for users. At its core, AI can be trained on increasingly larger data sets and be further enriched with customer-specific data, enabling users to automate tasks and make better informed business decisions.
Some examples of SaaS companies building AI-powered applications include:
- Yalochat - a conversational AI platform that enables enterprises to communicate with vendors and customers without the need for a live agent.
- Zeni - offers startups and small businesses a suite of AI-powered financial services including bookkeeping, invoicing, and financial reporting. The AI automatically labels and organizes expenses while ingesting the company’s accounting data to create actionable insights and robust dashboards.
More information on what we look for in AI/ML companies specifically can be found here.
Embracing Product-led Growth Strategies
Recently, SaaS companies have started to build consumer-like products for businesses, employing what has become known as a product-led growth (PLG) strategy. This category has emerged as SaaS products have become business critical across all enterprise functions. Companies embracing PLG typically sell to a single business user or enterprise department that is motivated to purchase tools that make their job easier and more productive. Once these users begin using the product, there’s typically a viral element that enables the product to spread across teams and organizations.
This breed of companies has capitalized on a few trends including:
- Easier purchasing - “swipe a card and go”
- Shortened buying decisions and sales cycle - technology purchasing has been distributed across the enterprise
- Fast deployment - cloud-based
- Intuitive onboarding and adoption - sleek UI
Krisp, a noise-canceling app, is a good example. They went from 0 to 600 paying enterprises and $0 to $4 million in annual recurring revenue in under a year. Krisp developed a machine learning model deployed via an extension, app, or SDK that eliminates background noise while the user is on a call. Users are delighted with the experience and are eager to recommend it to their colleagues and friends. Additionally, participants on the other end of Krisp-user calls are shocked at the lack of background noise, which then leads to more downloads.
Polymer Search, is another example of a SaaS company with a PLG strategy. Their business intelligence tool enables non-technical spreadsheet users to quickly and effortlessly analyze data across multiple, disparate spreadsheets. Their product saves users countless hours, and through their easily-shareable workspaces, users are able to invite more people to use the product.
We’re excited to meet the next wave of entrepreneurs building great SaaS companies. If you’re an entrepreneur working on building the next great SaaS business, reach out to Vignesh Ravikumar at firstname.lastname@example.org.
For more information about our Investment Thesis visit our Thesis Page.
Check out the SaaS companies in our Portfolio.
1Gross Retention: Is the total percentage of recurring revenue retained in a given period of time relative to the starting total of recurring revenue after accounting for churn and downgrade revenue.
1-Churn + Downgrade Recurring Revenue in periodRecurring Revenue at beginning of period
Please note: 1) recurring revenue type (ie ARR or MRR) should be same for numerator and denominator 2) Period is a week, month, quarter or year
2Net Retention: Is the total percentage of recurring revenue retained in a given period of time relative to the starting total of recurring revenue after accounting for expansion, churn and downgrade revenue.
1-Expansion+Churn+Downgrade Recurring Revenue in periodRecurring Revenue at beginning of period
3Gross Margin Adjusted CAC Payback in months: Period of time (days, weeks, months, etc) to recover CAC for a single customer.
Average CAC / (MRR * Gross Margin)
Please note that in order for this to be an accurate measure CAC must be fully loaded and the time frame for calculating Average CAC must approximately match the timeline for when revenue is booked. For example, if a sales cycle for your business is 6-8 months, then looking at just the spend in the last 3 months ignores the spend that would’ve contributed to acquiring that customer. Furthermore, in fast growth businesses increases in spend could cause you to overstate CAC relative to MRR growth.