Everything Else

Why SaaS Prices Are Increasing, and Will Continue To

We’ve all felt the squeeze these last 3 years. Higher prices at home, higher prices at work, smaller budgets. Software subscriptions haven’t been exempt from this. In fact, they’ve outpaced almost everything else you’ve been feeling the squeeze on.

This SaaS inflation has been around longer than these last 3 years though. It’s been accelerating for the past 6 years, even when times were better economically.

And this isn’t going to change. In fact, it’ll probably keep accelerating. I’ll explain why.

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The Vertice Report

After looking for more data behind my anecdotal experiences around software negotiations the last few years, I stumbled across Vertice‘ SaaS Inflation Index: 2022 report.

Two key snippets from the report that we’ll dive into:

  1. Software is a significant expense on the P&L
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Vertice’ SaaS Inflation Index: 2022 report

2. Software pricing inflation is outpacing market inflation significantly

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Vertice’ SaaS Inflation Index: 2022 report

Why These Two Points Matter

1 in 8 dollars being spent on SaaS means that this line item should be at the forefront of executive focus. Software is eating more and more budget every year. According to SVB’s State of SaaS 2022, around 37% of companies expect a 6% increase in IT budget. But that also includes IT Services, not just software costs.

Companies will have to eliminate software or renegotiate contracts to align with those budgets.

For the second point, SaaS prices are inversely correlated to 1 year after Global VC stagnations or decreases in funding. Basically, SaaS companies start playing debt catch-up when funding opportunities start becoming scarce. Valuations have been set high but the market has become more competitive.

This means paying attention to fundamental business economics since that next funding day might not come for a while, or will be significantly reduced. To satisfy current investor interests and continue growth in valuation, fundamental business economics must outshine other SaaS companies competing for less available funding.

When this happens there are several levers that can be pulled. Oftentimes multiple are pulled at the same time.

  • Increasing prices
  • Reducing headcount
  • Reducing marketing spend
  • Eliminating discounts

Macroeconomic conditions around rising interest rates, shaky banking situations, and rapidly overcrowded marketing channels due to AI capabilities are suggesting more

One Justification For Higher SaaS Prices

There is a counterpoint that doesn’t make the future look so bleak. After all, not all SaaS companies are just raising prices because of high expectations.

Many SaaS platforms started as a niche solution. Then as they tapped that market, they expanded capabilities to continue growth. This is a great reason to increase prices. The customers save money on a simpler tech stack with less tools to maintain, and the SaaS platform solves more business problems with their solution and can charge more. Win-win.

HubSpot is a great example of this. They started as a Marketing platform, then added their CRM, Service Hub, CMS Hub, Operations Hub, and Sales Hub along the way. Their pricing evolved and increased with these evolutions. They made more money to grow into their expectations, and customers saved money by eliminating other subscriptions and the staff to maintain the tech stack.

The Future SaaS Inflation and What To Do

My hypothesis is that this won’t change in the future. SaaS will continue to become more expensive. And the risk for investing in the wrong SaaS company is rapidly increasing.

If you pick the wrong one, you could be locked in and subsequently squeezed for huge price increases year after year. You also will have significantly less ROI on tools if they increase price without providing additional value to your organization.

AND the more complex the SaaS is to set up and maintain, you’ll also suffer from wasted labor spend to get those tools set up and running. Only for the investment to flop.

SaaS inflation will continue because we’ve seen a stagnation in VC funding. Valuations were super high leading up to 2022 and companies are trying to catch up to those valuations to raise again and deliver for their current investors.

Plus, Marketing and Sales is becoming more expensive for these companies as channels become even more difficult to cut through noise at scale.

Expect pricing to outpace general inflation the next several years.

What To Do When Choosing SaaS

Software is an investment. This is not a metaphor, it needs to be treated like an actual investment where you do due diligence behind the company you’re investing in. Because your business operations literally depend on the software to run. Otherwise, why are you investing in the software in the first place?

This means that when you’re looking at software vendors, you should get as much info as possible on their financials. Obviously for private companies this is more difficult, but it doesn’t hurt to ask the people you’re talking with in the company.

Figure out what their revenue looks like, their operating expenses, revenue per employee, NRR (net revenue retention), average customer LTV, etc.

If they’ve been valued at 20 times their ARR, you know they have to grow into that somehow. They need to increase their number of customers with the same pricing, or increase their pricing with slowing/stagnating customer acquisition.

If they are focused on increasing customers, you might get less support when needed. If they’re going to increase pricing due to slower customer acquisition, make sure you get value in those increases. Ask for better SLA’s or additional functionality after those price increases.

Another major risk to consider is companies going bankrupt/shutting down because of poor business economics. What if they can’t raise again? What if they cut headcount in the wrong places and the platform stops working? Does that company have enough cash reserves to weather the storm?

What To Do During/Between Renewals

If you’ve already passed the evaluation stage and are in a contract/up for renewal, there are still opportunities.

Start with a Tech Stack Assessment/Tech Stack Audit. List every single tool, what you spend, how many users, and their feature sets. Then look at which feature sets overlap, which tools aren’t actually solving a specific business problem, which ones don’t contribute to your company strategy, etc.

Then cut redundant ones. Explore ways you can consolidate your tech stack to make it easier for employees. Talk to vendors that you’re renewing with and see if they have additional modules/features you can upgrade to so you can replace other tools.


Software is getting more expensive. Low interest rates flooded the market. This resulted in unsustainable pricing and now pricing has to catch up with tightening economic conditions.

Avoid the hurt of investing your operations in SaaS products with poorly run businesses behind them. Do your due diligence.

If this article made you think about your Tech Stack and the subscriptions you have, check out the Tech Stack Audit at

We see and work with hundreds of different SaaS tools every month on behalf of clients. Skip the confusion of trying to evaluate software subscriptions, overlap, and usage in your organization. Reach out to our team instead.

Everything Else

Warning: The bottom 50% of BI devs will be on the chopping block

Like others, I’ve been experimenting with OpenAI technology and all the associated tools that have popped up.

The rate of adoption and integration with existing platforms has been astounding. It’s both awe-inspiring and terrifying.

Mostly, the terrifying part is related to the uncertainty it poses for many economically. OpenAI tech is fundamentally changing how humans work, think, and interact.

It’s making our already crowded social and information channels more crowded. We’re probably spending more time reading AI-generated content with AI-generated images than we’d like to acknowledge. But it’s also vastly increasing the speed to market for internal and external products.

For example, a few months after ChatGPT exploded, HubSpot and Salesforce both announced companion “ChatGPTs” of their own. After testing, it generates quick answers to questions about my specific CRM data that I would have had to hire someone to build or take a couple hours to build myself.

Is the technology perfect? No, and neither are the human workers that it’s been slowly replacing. Does it make mistakes and lie? Yup. But at a fraction of the cost compared to an equivalent behaving human.

Will it replace experts in specific niches, make their caliber of work easy to produce with some short AI training and some refined prompts? Not in the short term (most likely).

What this means for the beginner tier of white collar workers

This is where things get dicey. Do companies cut workers that were doing admin/low-level type of development work? With one person paired with ChatGPT and other similar tools, they’ll be able to be as productive as 3 or 4 of the beginner tier of white collar workers.

Will their output be great for the long-term economics and stability of the business? Probably not, but the majority of companies will take the short-term gain as long as things can still get done to make more money in the short-term.

But as we saw with off-shoring, sometimes the juicy margins are just too juicy to care about the degradation in quality that can occur.

The bottom 50% of BI devs

This sucks to say, because we all were at the bottom 50% when we started learning. But the future doesn’t look bright for those who build BI solutions to simple questions.

With HubSpot and Salesforce, it’s already possible now to ask it a question and have it build simple reports for you. This capability will only creep further into cloud platforms that house your data. I wouldn’t be surprised if in a couple years, you’ll be able to load all your data into Snowflake or AWS, and ask it to generate insights for you.

So what’s going to happen when you need some charts for straightforward KPIs and metrics inside of Tableau? Or PowerBI? Or Excel? Or any other tool? Are you going to go out and hire a $50-$80k/year employee, a $100/hour+ contractor, or ask your AI companion that can spit out an answer that an executive gut checks and then moves on?

More advanced BI solutions will still be valuable. Ones that provide answers driven more by complex architecture and knowing where to look for previously unexplored connections in data. But even that might not be far off (look at the Data Guide in Tableau for example).

Final Thoughts

This topic impacts my own business ( and the consulting areas we focus on going forward. It certainly is going to make our demonstrated expertise beyond the basic topics more and more important

Overall, ChatGPT and other OpenAI tech brings up a lot of questions for the near future of humanity.

Will future generations be handicapped or elevated because they no longer have to struggle through the learning process of the basics?

Economically, how will we restructure to compensate for an explosion in data and less need for humans to manually generate all of that?

What will happen to perceived low value employees? Will they be reassigned to other work or cut entirely?

p.s. Was this article written by me or by ChatGPT? How can you tell? Does it impact how you feel about reading it if I told you it was written by ChatGPT? What if I told you it was written by me?

This is where our future is heading. Real and virtual are getting blurrier. The question is how humans will adapt to the furthering distrust of anything virtual. After all, how can you know it’s real and from a human, for a human? beep boop boop beep

Everything Else

Twitter still hasn’t unlocked the New York Post’s account

Related Article: What could polls be missing for this election?

Update: Twitter finally unlocked the New York Post’s account on October 30th. This occurred after the Senate Commerce Committee interview multiple Tech CEOs, including Jack Dorsey of Twitter.

Disclaimer: I’m a registered voter with no party affiliation. I have a personal interest in tracking major news networks such as CNN, Fox News, Breitbart, the New York Times, and other outlets who publish misleading information since 2008. Twitter is a recent example of a large, influential medium that has now subjectively interfered with information flow to the public.

It has been over 10 days since the famous New York Post story discussing Hunter Biden’s activities with the Ukranian energy firm Burisma. Twitter reacted by locking the New York Post’s Twitter account from any activity, citing they were trying to prevent the spread of hacked information. Twitter CEO Jack Dorsey admits blocking the story was a mistake and ended up reallowing the sharing of the story on Twitter.

Then one must ask, why is the New York Post’s Twitter account still locked?

If the decision was reversed, why isn’t the New York Post’s account unlocked? Why isn’t the New York Times account locked due to releasing Trump’s tax returns that were clearly stolen or “hacked”? Especially after the New York Times declined to share their evidence? Here’s a quote from the NYT article where they decline to share:

“…Alan Garten, a lawyer for the Trump Organization, said that “most, if not all, of the facts appear to be inaccurate” and requested the documents on which they were based. After The Times declined to provide the records, in order to protect its sources…”

So no records have been released “in order to protect sources”, which isn’t an explanation as to why the actual documents haven’t been published. You can publish tax returns without exposing your sources (for an example, look at all of the WikiLeaks releases over time). Ironically, by publishing the tax returns, you’ll force the hand of Trump to actually release his returns. Instead, all we have is the NYT claiming to have records that they won’t show and have obtained without permission. So why is the New York Post account locked and the NYT account not?

A speculation

Maybe the answer lies in Twitter’s rules and policies, which give plenty of wiggle room by utilizing “exceptions” that they alone determine is best for the public interest. Apparently unverified and unreleased tax returns are important for the public interest, but direct evidence of high-ranking US politician’s family member receiving a highly paid position without prior credentials is not of concern to the American public.

Maybe it turns out that Twitter is in fact biased? Considering it’s difficult, if not impossible for a human being to truly be entirely objective, Twitter’s review units are undoubtedly biased themselves since they’re made up of humans. Should there be insights into who makes up the committees that Twitter uses to review posts and their potential biases? Either way, the main question is; why are they subjectively trying to change the flow of information to the American public?

You’ll have to come to your own conclusion on that.

To be transparent, this is my opinion.

Any institution (private or public) with the power to influence outcomes of anything at scale, are incentivized to take a side. Since humans make up these institutions, they are inherently biased, no matter how hard they try to be unbiased. The resulting bias from the institution’s parts eventually come through as the bias of the whole institution. It’s inevitable and unavoidable, and this is what we’re seeing on Twitter’s decision to lock the New York Post’s account but not the New York Times.

The New York Post should be able to post their own articles without limitation unless other media outlets are restricted as well (such as BuzzFeed news). Unless every single news article is researched by a transparent committee with their justification on blocking/allowing it, one side will always benefit.

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Everything Else

What could the polls be missing in this Presidential election?

Recently I wrote an article on the New York Post’s Twitter account still being locked. This is still the case, and it made me brainstorm many other topics associated with elections . This thinking session brought up the topic of polls and predictions. How accurate are they? Why were many polls so far off in 2016? Why do polls seem to tighten the closer to election day? [1][2]

Many polls are predicting Biden to win by a large margin, and many of the points I make below indicate factors that could make the margin much smaller. The one factor that could cause a greater margin than predicted would be an increase in Black and Hispanic voter participation. This is due to the fact that Biden still holds majority over those demographics so an increase in the total number of voters would benefit him the greatest.

Here’s what I think the polls could be missing

Narrowing party registration gaps, especially in swing states.

There are indications that Republicans have significantly closed the registered voter gap, especially in swing states. Trump narrowly won the 2016 election in many of these states, so a lesser difference between registered Democrats and registered Republicans could indicate Trump holding his lead in swing states. Of course, non-affiliated voters still hold a large chunk (often 20%+) in swing states, so nothing is set in stone.

Unwillingness for people to truthfully poll, especially for a candidate like Donald Trump.

Some studies have shown that people are unwilling to share their vote choice with polls. The study linked states that around 11.7% of Republicans don’t share their truthful choice with polls, 10.5% of non-afiiliated, and 5.4% of Democrats. That’s certainly not insignificant.

Shifting demographics in the Black and Hispanic vote.

If the Black and Hispanic vote turnout is the same or less than 2016, this will be a net negative impact for the Democratic party. Trump closed the polling gap from 2016 between both these demographics (although still doesn’t poll above 50% for either demographic). So if the total pie of votes for Black and Hispanic voters doesn’t increase, Trump takes a bigger portion of a pie the same size as 2016.

Increasing distrust of media and technology amongst conservatives.

If a person doesn’t trust the news, believes they’re being censored, or is generally less trusting in institutions, why would they answer truthfully to polls? Why would they participate in the polls in the first place? Are polls even further off than the “shy” voters study linked in the truthful poll section above?

Unknown voter turnout for the Black and Hispanic vote.

2016 saw a decrease in participation with these two demographics. If participation is higher than anticipated, it will significantly benefit Biden and result in a landslide win.

Wrapping it up

While many polls try to adjust for factors like these, it’s impossible to accurately measure all the variables associated with elections. For example, every time that Florida has seen under a 4% party registration spread, Republicans have won the state, anything above 4%, the Democrats have won. Right now the spread is under 2%. But mail-in voting will be at an all time high, so will overall participation increase or are only active voters shifting their voting method?

Many polls will correctly predict the election within their margin of error. The only issue is that it’s not useful in states consistently decided by less than the typical margin of error (like Pennsylvania and Florida).

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