SaaS is still open for business, but it’s going to take longer to buy and sell

The “Great Restructuring” continues and tracked 80,000 lost jobs in tech in January 2023. This brings the total to well over 230,000 from more than 1,000 companies since 2022. Yet, despite all the negative headlines, the SaaS market continues to see steady growth. Gartner predicts software spending will increase by 11.3% this year, but my company’s internal data leads me to be slightly more bullish.

The fourth quarter of 2022 and the first quarter of 2023 show steady increases in both spending and requests for new purchases. We analyzed more than $2.5B in SaaS spending from 18,000 deals across 2,500 suppliers and anticipate that SaaS spending will increase 18% this year.

Yet while software spending continues to grow, buyers and sellers face immense challenges dealing with the impact that layoffs and underlying economic uncertainty will have on the software market.

The bottom line? In 2023, SaaS is still open for business, it’s just going to take longer to buy and sell.

A flat renewal is the new “upsell”

One of the most direct and immediate impacts of recent tech layoffs on the SaaS sector is a decline in seat licenses. A quarter of a million layoffs equals tens of millions of individual seat licenses lost for SaaS suppliers.

We analyzed more than $2.5B in SaaS spending from 18,000 deals across 2,500 suppliers and anticipate that SaaS spending will increase 18% this year.

We have seen average contract value (ACV) going up in some of the most popular software categories. This includes cloud data integration (which includes products like Fivetran and Celigo) up 82% as a category, mobile device management (which includes products like Jamf and Kandji) up 84% as a category, and project management tools (which includes products like Asana and up 78% as a category. Even so, we predict that SaaS vendors across the board will see contraction at renewal, not expansion.

Suppliers can expect a distinct downturn in both the growth rate and share of wallet (the amount a customer spends regularly on a particular software vs. buying from a competitor). We have seen suppliers attempt to recoup lost revenue with renewal uplifts as high as 20% (compared to the typical 3-5%.) Unfortunately, many customers aren’t in the position to approve that much of an increase. The sooner SaaS vendors can normalize the idea that even a flat renewal is a massive win in this economy, the better off they will be.

Mitigate the impact of layoffs on purchase and renewal cycles

Over the past six quarters, renewal cycles have remained consistently above 60 days on average. The fourth quarter of 2022 represented a breakthrough, as renewal cycle time decreased 11% –– from 63 days in Q3 to 56 in Q4.

Unfortunately, we predict that continued layoffs and restructuring will drive that number back up in 2023. Early Q1 data validates this hypothesis, with renewals increasing 2% to 57 days and net new sales cycles increasing 10% to 46 days.

A study by SAP showed that 55% of companies with more than 50,000 employees claimed that staff shortages have significantly slowed their procurement operations. Two-thirds of those same companies blame increasingly distributed teams for purchase decision delays.

SaaS is still open for business, but it’s going to take longer to buy and sell by Walter Thompson originally published on TechCrunch

Product-led growth is propelling a wave of sales tools startups

This might be the year when we see more companies adopting sales tools that bridge the gap between traditional CRMs and product-led growth models to help sales teams more effectively convert leads with the help of usage data.

Why is this happening now? Well, companies are going hybrid, whether with their business model or their pricing. For instance, more companies are adopting usage-based pricing models, but they’re often mixing it with existing pricing models, such as subscription tiers.

Along the same lines, many companies have adopted product-led growth (PLG) without abandoning their traditional sales efforts. The two motions typically work in tandem, with self-serve adoption driving most usage and sales reps dedicated to closing larger enterprise deals.

However, sales reps don’t qualify accounts the way they used to. Why would they be cold-calling anyone or spending money on marketing when there might be much warmer leads in the existing user base? This has led companies to adopt a new approach known as product-led sales.

In product-led sales, the concept of “marketing-qualified leads” gives way to “product-qualified leads” (PQLs). This is a major shift because to truly provide sales teams the data they need to upsell or cross-sell existing users, companies must closely align and connect their product usage data with their sales tools and CRMs.

Product-led growth is propelling a wave of sales tools startups by Anna Heim originally published on TechCrunch

Building a PLG motion on top of usage-based pricing

I spent several years as a general manager at Amazon Web Services and my teams launched two Tier 1 services: Amazon CloudSearch and Amazon OpenSearch.

Like every product at AWS, these were scaled with a product-led growth (PLG) market motion. There were no gated features or subscription tiers to choose from. Instead, a usage-based pricing (UBP) model has always been used to charge based on consumption, directly correlated to the value being delivered to the user.

AWS pioneered the product-led movement by offering its entire suite of offerings on a fully pay-as-you-go basis when it came to market in 2011. Developers could immediately begin using the services in the free tier to realize value, and there was no mandatory bundling or gatekeeping account managers. In 2011, AWS was far ahead of its time. It is only now that we are seeing companies of all sizes pivoting to a product-led motion.

Usage-based pricing is an essential component of any PLG strategy. In fact, it’s my belief that you cannot have true PLG without UBP. To be truly product led there should be no friction when adopting the product and realizing value. The doors should be wide open and new users should be able to come in and use the tools.

To succeed with any product-led strategy, it’s essential to have real-time awareness and granular visibility into what your users are actually doing with the product, which features are being used and how value is being realized. The following steps are informed from the process we followed in the early days of launching and scaling services at AWS from day one. This process allows you to remove emotion and gut feel from pricing and product decisions while allowing customer usage and consumption to lead your decision-making and help your business scale.

When the time comes to make decisions about product packaging and pricing, the first place you turn to should be the metering pipeline for historical usage data.

Step 1: Invest in usage instrumentation

Usage data is the foundational building block of any product-led motion. Usage provides the intelligence that drives all other functions, from pricing and packaging to sales, support engagements and even product roadmap development. This data shows which features are driving traffic and adoption and where you need to scale your efforts to continue meeting user needs.

Most organizations cannot easily implement usage instrumentation at scale, and the existing tool sets for monitoring and observability do not deliver on requirements for total accuracy and auditability. Metering solutions were born out of this need for a new category of technology that could accurately track usage for any resource, at any scale, in real time and make this data available for analytics and reporting.

Continue to instrument new features and products as they are developed to curate an exhaustive set of usage data that you can analyze and base business decisions on.

Step 2: Make usage data available throughout your business

Consistently assess and ensure that each department has access to the insights they need to do their work. In a product-led motion, the product is the primary vehicle through which you engage with customers; other go-to-market actions are designed to provide support. Roles across the organization can effectively leverage usage data with the correct tools and strategies.

Ensure that your meter data pipeline is the single source of truth for data on usage and consumption. You should take care to identify what product and usage data each role across your organization needs to be successful. The data should be indexed and accessible to permissioned users.

Building a PLG motion on top of usage-based pricing by Ram Iyer originally published on TechCrunch

Q1 2023 market map: SaaS cost optimization and management

When engaging with our portfolio companies as well as with new investment opportunities, we’ve noticed that “profitability” and “efficiency” are two words that are often grouped with “growth” in every sentence.

Three months into 2023, investors continue to use buzz words like “responsible growth,” “business efficiency” and “quality marketing” when explaining how VC-backed companies should do business this year. That may be true, but there is no textbook for how a company can actively reduce its budget without slowing down growth in the near term.

Over the past few months, we have examined, demo’d and reviewed over 30 companies that we define as “first-degree, gross-margin-enhancing businesses.”

What does this mean? The “first-degree” part of that has to do with the now. Investors are knocking at the door to see improvements every quarter. Companies that can help you with long-term efficiencies will not help you when you next look to raise money in six, 12 or 18 months.

The “gross-margin-enhancing” part of this definition is important because simply reducing costs in lieu of growth will not work. Likewise, maximizing growth with little sensitivity around costs won’t work in 2023.

saas cost optimization

Image Credits: Ibex Investors

In this article, we’ll look at emerging companies that can efficiently and effectively support organizations in their efforts to deliver growth while optimizing and managing costs in the near and long term.

Given the market right now, investors want to see companies following forecasts more than ever.

The value proposition of the companies in this mapping is to help businesses continue their growth journey while optimizing and reducing costs in their current business structure. That said, there is no-one-size-fits-all solution. For this reason, we have defined three key categories of gross margin enhancement:

  • Cloud infrastructure cost optimization and management.
  • Vendor stack cost optimization and management.
  • Next generation FP&A tools.

Cloud infrastructure cost optimization and management

There is a constant struggle to balance stepping on the gas to improve product (i.e., raise cloud spend) and pushback from the CFO’s office when it is time to cut back.

CTOs and technical leads know how to cut cloud costs, but it can be difficult to pinpoint to what degree a certain change can negatively impact a company’s top line, not to mention the time it takes to execute reduction and optimization requests repeatedly. Companies want to continue to grow and do it rapidly, but they simply cannot allow themselves the freedom to flex their cloud spend like in past years.

Several companies are solving these problems with different focuses: Finout, Cloud Zero, Vantage and Anodot support both enterprise and middle-market end users and offer solutions to manage the cloud as well as Kubernetes. Some of these players provide solutions not only to support key cloud providers but also other cloud infrastructure vendors (such as Data Dog and Snowflake).

Other companies focus on more specific use cases. For example, Kubecost focuses on Kubernetes management. There are also companies that aim to help you cut costs: Zesty (for cloud) and Cast (for Kubernetes) fall in this space.

Q1 2023 market map: SaaS cost optimization and management by Ram Iyer originally published on TechCrunch

Building a lean B2B startup growth stack

Growing a B2B business is becoming increasingly complex. The market is inundated with products thanks to the explosion of SaaS, it’s getting harder to leverage ad platforms and email, and identity management is Byzantine.

Today, a prospect is a lot harder to understand than a user. Tracing the thread connecting an ad impression to a website visitor, their business identity and a record in a CRM is really, really difficult.

It’s not easy to go to market as a B2B company, but it is easy to think that a new tool or platform will help you “fix” things. It turns out that the cost of implementing and managing a new platform often outweighs the cost of using what you have to better effect. It’s critical to implement tools according to the stage of a business.

I’ve spent years trying to understand which tools give you the most bang for your buck and which are just not worth the overhead. In the guide below, we’ll cover tools in four major categories that startups need based on their stage of growth:

  • CRM and data warehouse (your source of truth): A CRM is where you store data and records on people and the company, and take action. A data warehouse is where you aggregate all your data to perform analyses.
  • Third-party data sources (how you find/target people).
  • Analytics (how you measure your impact).
  • Engagement platforms (how you reach your audience).

We will not be covering:

We shouldn’t have to call it the “lean” B2B growth stack; it should just be the B2B growth stack.

  • Task management and productivity tools.
  • Team composition/communication tools.
  • Website, SEO and creative tools.
  • CDPs (because there is no good B2B CDP).
  • PLG specific tools (All of the tools below are relevant to PLG companies, but there will be other tools they’ll need that we aren’t covering).

Early stage (seed to Series A)

What should be in your stack

  • CRM: Hubspot
  • Data source:
  • Ad Platforms: LinkedIn Ads, Google AdWords
  • Analytics: Google Analytics
  • Other: Outbound email domain management (e.g., Lightmeter)

What shouldn’t

  • Salesforce: The Hubspot CRM has come a long way. It’s less customizable than Salesforce, but that’s a good thing because you shouldn’t waste your time on too much customization at this stage.
  • ZoomInfo: Go with Apollo. It’s cheaper and will let you access data to test outbound. Their new enrichment product allows you to do inbound enrichment as well. Caveat: If your target market is not digitally native, e.g., electrical contractors, ZoomInfo has significantly better coverage than Apollo.

Biggest early-stage mistake

Overinvesting in tools that correspond to a specific acquisition strategy without understanding if that strategy actually works yet.

For example, people spend $36,000 a year on Zoominfo because they’ve hired a head of Sales who says they need it. But you might realize six months later that it’s too premature to start building an outbound engine and you’re stuck with a hefty annual subscription.

Always test your way into things. In this case, it would mean starting off with a cheaper data provider like Apollo.

Midstage (Series B to Series C)

What should be in your stack

Building a lean B2B startup growth stack by Ram Iyer originally published on TechCrunch

How to turn an open source project into a profitable business

Despite the premise of open source software distribution being “free,” multibillion dollar companies like RedHat, MongoDB, GitLab and Elastic have already broken ground building profitable businesses with open source at their core.

But is it possible for a smaller open source project to find its way into this land of commercial opportunity?

COSS is accelerating

In general, the trends in commercial open source (COSS) are encouraging. New products like Meilisearch and Supabase are gaining traction exponentially faster than the legends of COSS like MongoDB, which were founded much earlier.

Let’s give some more context to the graph above. From 2010 to today, the number of GitHub users has exploded from 500,000 to 103 million. It might be tempting to suggest that this influx of new users into the community would be the driving force behind the increase in stars.

Your open source project can begin as a pet project but only if you can devote time to it.

But, at the same time, the number of projects (repositories) has grown at an even higher rate: from 600,000 to 359 million. And investments in open source products have almost tripled from 58 deals in 2015 to 144 deals in 2021.

Importantly, the average number of users per repository has shrunk from 0.8 to 0.3. This means the competition for GitHub stars is now higher than ever, which suggests the superstars above are indeed outliers and it’ll be difficult to replicate their success.

Judging from these numbers, investments and star dynamics, COSS is in a sweet spot at the moment.

That said, we must keep in mind that COSS and developer tools still only occupy a niche. After all, there are only 25 million to 30 million software developers in the world. Even though productivity in this industry is much higher than in many others, this number is only a fraction of other big markets like finance or retail.

Moreover, monetizing products built for developers is still, to a certain extent, an open question.

How to monetize open source

There are multiple strategies for earning money from open source.

Let’s start with a simple one: crowdfunding and donations. Grant money falls into the same category as donations, as the only difference is in how you raise the money. Foundations are a vehicle for collecting donations from large sponsors or from a great number of sponsors.

Sadly, such earnings are unlikely to cover the costs of a growing COSS. Take PostCSS, a widely popular CSS framework built by Andrey Sitnik. Through an Open Collective hub, with 27,000 stars on GitHub, he collects only about $12,000 per year despite the fact that massive companies like Meta or Google use PostCSS and could potentially support the product.

How to turn an open source project into a profitable business by Ram Iyer originally published on TechCrunch

Using predictive LTV to juice up marketing campaigns

As a marketing veteran, you’re likely familiar with the concept of LTV (lifetime value) and its importance in determining the success of your acquisition strategies. But, are you utilizing predictive LTV in your day-to-day decision-making? If not, you’re missing out on a powerful tool that can give you a competitive edge and an opportunity drive growth for your business.

Predictive LTV is a method of precisely estimating the future value of a customer, based on their historical behavior and other relevant data. By combining this prediction with traditional metrics such as CAC (customer acquisition cost), you gain a new dimension of knowledge that was previously inaccessible to you. This allows you to make more informed decisions that balance the cost of acquisition with your predicted return on investment.

In a sense, not using predictive LTV to inform decisions is like going on a hike, not knowing where it will end and how hard it will be. You may have a general idea of where you’re going, but without advanced tools and technology, you could easily get lost, sidetracked or miss your destination altogether.

Identifying high-value customers early in their life cycle is one of the biggest benefits of predictive LTV. You can use this to build more targeted, effective acquisition strategies, that focus on acquiring and retaining customers. In addition, you can decide how much to invest in acquisition and retention efforts based on your customers’ predicted lifetime value.

CAC-only optimization

a chart depicting CAC-only based acquistion

CAC-only optimization. Image Credits: Voyantis

CAC and predictive LTV optimization

CAC and predictive LTV optimization. Image Credits: Voyantis

Balancing risk and growth with predictive LTV

Before delving into the different approaches to predictive LTV, it’s important to understand the type of decisions that predictive LTV can inform. Predictive LTV can play a crucial role in shaping a business’s day-to-day decision-making. Here are some examples of how it can be incorporated:

Using predictive LTV to juice up marketing campaigns by Walter Thompson originally published on TechCrunch

Optimizing freemium products: Challenges and opportunities

Building a freemium product or service is only the first step.

Once you’ve done the work to build and launch a freemium product, you will have to collect initial market reactions and see how the funnel behaves at each touch point. You will then have to decide whether to optimize the freemium experience, keep it the way it is currently or remove the funnel altogether.

Each funnel has a set of metrics:

  • Acquisition.
  • Activation.
  • Retention and engagement.
  • Monetization.
  • Expansion.

There are many ways to improve each step so you must consciously reevaluate your strategy to avoid over-investing. There may be situations where unit economics are not yet working, but the increase in conversion required to break even is very small. You may learn that new users find it difficult to activate and move to a paid tier. Or you may find that your users are excited about the free tier and see no reason to upgrade.

What to optimize?

Enabling freemium, especially for established products, can bring organizational and operational challenges even if it adds value to the business.

As described above, you need to analyze how your freemium funnel performs to understand where the biggest problems are.

In general, the main areas of optimization are:

  1. Limitations that you set on freemium (both on the base use case and advanced features).
  2. Conversion paths.
  3. User activation.
  4. Supporting product changes on freemium.

The first two are primarily to do with monetization, the third is related to retaining free tier users, and the last is a cost you have to bear to support changes to the freemium product.


The more data you generate about freemium use, the more ideas you will have about whether you have chosen the restrictions correctly.

There are two types:

  1. Direct limitations to the basic use case.
  2. Inclusion (or exclusion) of other features.

The first point is fairly straightforward — it relates to the use case and the extent to which you allow free tier users to engage with the base use case. Experimenting with limitations is a must because you need to find a balance between serving the use case in its simplest form and pushing users to upgrade.

Suppose your model allows unlimited use of the base use case. In this case, you can include limitations such as the ability to invite other users to the account, the experience of collaboration and so on. This is the second type of limitation that you can work on. It is possible to over-engineer freemium by providing access to additional features that make the basic use case “complete” — e.g., analytics, notifications, etc. This is another area where you can experiment.

Conversion paths

Since your free tier users use your product for the basic use case, creating conversion paths that allow them to understand the benefits of your paid plan will be a problem. Should they go through a trial period before paying for your paid solution? Should you ask for their payment information if they want a free trial?

Optimizing freemium products: Challenges and opportunities by Ram Iyer originally published on TechCrunch