To The Moon

I have showed some data that highlighted the struggles of software companies. Companies are missing guidance at a historically bad rate, and there wasn’t a clear / obvious answer why. Did macro really get worse? Are AI native software companies starting to eat everyone’s lunch? Did a Q4 budget flush pull forward Q1 deals and create Q1 softness? I think the answer is actually something different - budgets are bifurcating.

Every company from the smallest startup to largest enterprise is looking to transform their business with AI. If they don’t, they risk becoming irrelevant. It’s an existential urgency. And these transformations are not cheap! It used to be trendy to say AI budget was all additive and didn’t cannibalize other budgets (I may have even said this at one point…) but the reality is budgets are inherently zero sum. Giving budget to build out AI capabilities has to come from somewhere.

And companies are not thinking of AI as a “separate” budget, but more intertwined into all aspects of their company building. So for the incremental dollar of spend, the question every company asks themselves is “does this push forward our AI agenda / capabilities or not?” If the former, great! You are immediately able to tap into a large and GROWING portion of the budget. If not, you’re stuck in a stagnant and SHRINKING budget. To summarize - as a vendor you must prove that you help bring the company you’re selling to into the future paradigm, the AI paradigm. You need to be future proof, otherwise your internal champion risks loosing their job in 2 years!

The challenge most public software companies are facing is that when buyers ask “does this vendor help bring us into the future / help with AI” the answer has commonly become “we’re not sure.” And this creates a lot of friction in procurement. A common theme in earnings calls recently has been “sales cycles elongating and increased scrutiny around new purchases.” This makes sense! A lot of software companies are pulling incremental budget from the non-strategic / shrinking portion of the overall budget when buying a lot of these software solutions because they’re not obviously in the “AI bucket.” Or even worse, they’re in the “disrupted by AI” bucket.

When it comes to large enterprises, they procure software in 3-5 year cycles. They want to buy something, set it and forget it, and revisit in 3-5 years. The challenge with AI today is the innovation cycles are so rapid. These large enterprises get very worried that a product or solution they buy today (or commit additional spend to in a renewal), might become “outdated or legacy” in 2 years. And this is something that breaks down their procurement cycles. They need to be SURE that any product they’re allocating incremental spend to will not be made irrelevant by the paradigm shift of AI.

To provide a quick example - I spoke with an individual leading data and ML at a large company with significant total hyperscaler spend (>$75m annually). For data science / AI spend, they are seeing >40% QoQ growth! For spend on the more “legacy” products from their primary hyperscaler provider growth is flat / slightly shrinking QoQ. And if anyone wants to increase spend on the latter category, they need to jump through a lot of approval hoops, and sometimes close an open job rec to make up for the increased spend they’re requesting. Something they said was “we don’t need another dashboard, we need another model.”

In summary - budgets are bifurcating into “pushes our AI agenda / footprint” and “doesn’t push our AI agenda / footprint.” In the latter - it’s really hard to get incremental spend because the former is taking SO much of the total budget. I believe the weakness in Q1 earnings is largely a result of buyers not knowing which bucket certain vendors fall in. It’s not to say they’re definitively putting them in one or the other, but an answer of “ don’t know” is the same as “it doesn’t get AI budget.” The dust is settling.

Quarterly Reports Summary

$Couchbase, Inc.(BASE)$ $Sprinklr, Inc.(CXM)$ $GitLab, Inc.(GTLB)$ $CrowdStrike Holdings, Inc.(CRWD)$ $Guidewire(GWRE)$ $Smartsheet(SMAR)$ $Samsara, Inc.(IOT)$ $Braze, Inc.(BRZE)$ $Docusign(DOCU)$

Top 10 EV / NTM Revenue Multiples

$Palantir Technologies Inc.(PLTR)$ $Cloudflare, Inc.(NET)$ $Datadog(DDOG)$ $ServiceNow(NOW)$ $Snowflake(SNOW)$ $HubSpot(HUBS)$ $Palo Alto Networks(PANW)$ $Zscaler Inc.(ZS)$

Top 10 Weekly Share Price Movement

Update on Multiples

SaaS businesses are generally valued on a multiple of their revenue - in most cases the projected revenue for the next 12 months. Revenue multiples are a shorthand valuation framework. Given most software companies are not profitable, or not generating meaningful FCF, it’s the only metric to compare the entire industry against. Even a DCF is riddled with long term assumptions. The promise of SaaS is that growth in the early years leads to profits in the mature years. Multiples shown below are calculated by taking the Enterprise Value (market cap + debt - cash) / NTM revenue.

Overall Stats:

• Overall Median: 5.2x

• Top 5 Median: 15.7x

• 10Y: 4.3%

Bucketed by Growth. In the buckets below I consider high growth >27% projected NTM growth (I had to update this, as there’s only 1 company projected to grow >30% after this quarter’s earnings), mid growth 15%-27% and low growth <15%

• High Growth Median: 9.7x

• Mid Growth Median: 7.8x

• Low Growth Median: 3.6x

EV / NTM Rev / NTM Growth

The below chart shows the EV / NTM revenue multiple divided by NTM consensus growth expectations. So a company trading at 20x NTM revenue that is projected to grow 100% would be trading at 0.2x. The goal of this graph is to show how relatively cheap / expensive each stock is relative to their growth expectations

EV / NTM FCF

The line chart shows the median of all companies with a FCF multiple >0x and <100x. I created this subset to show companies where FCF is a relevant valuation metric.

Companies with negative NTM FCF are not listed on the chart

Scatter Plot of EV / NTM Rev Multiple vs NTM Rev Growth

How correlated is growth to valuation multiple?

Operating Metrics

• Median NTM growth rate: 12%

• Median LTM growth rate: 17%

• Median Gross Margin: 76%

• Median Operating Margin (10%)

• Median FCF Margin: 14%

• Median Net Retention: 110%

• Median CAC Payback: 58 months

• Median S&M % Revenue: 40%

• Median R&D % Revenue: 25%

• Median G&A % Revenue: 15%

Comps Output

Rule of 40 shows rev growth + FCF margin (both LTM and NTM for growth + margins). FCF calculated as Cash Flow from Operations - Capital Expenditures

GM Adjusted Payback is calculated as: (Previous Q S&M) / (Net New ARR in Q x Gross Margin) x 12 . It shows the number of months it takes for a SaaS business to payback their fully burdened CAC on a gross profit basis. Most public companies don’t report net new ARR, so I’m taking an implied ARR metric (quarterly subscription revenue x 4). Net new ARR is simply the ARR of the current quarter, minus the ARR of the previous quarter. Companies that do not disclose subscription rev have been left out of the analysis and are listed as NA.

https://cloudedjudgement.substack.com/p/clouded-judgement-6724