News of the Week (December 4-8)
Lululemon; GitLab; MongoDB; Shopify; SentinelOne; Broadcom; CrowdStrike; PayPal; Disney; More Market Headlines; Macro; Portfolio
Today’s Piece is Powered by My Friends at BBAE:
1. Lululemon (LULU) – Earnings Review
The company beat revenue estimates by 0.8% and beat its guidance by 1.2%. Please note that 3-year compounded annual growth rate (CAGR) comps remain very easy due to the pandemic. The firm, with normal comps, expects 15% annual revenue compounding.
Lululemon doesn’t always offer non-GAAP profit metrics. It did this quarter due to provisions and restructuring costs related to its failed Mirror acquisition. The margins listed for Q3-2023 are adjusted for these items. Without this adjustment, gross margin would be 57.0%, EBIT margin 15.3% and net income margin 11.3%. These materially missed estimates which did not include these charges as timing for incurring this type of cost is uncertain. As you can see below, non-GAAP was well ahead across the board when removing this temporary noise.
Beat earnings before interest and tax (EBIT) estimates by 6.2%.
Beat $2.29 earnings per share (EPS) estimates by $0.24.
Beat 57.7% gross profit margin (GPM) estimates by 40 basis points (bps; 1 bps = 0.01%) and beat its GPM guide by 50 bps.
Q4 revenue guidance was 0.8% below expectations and represents 13.5% Y/Y growth at the midpoint. EPS guidance of $4.89 was $0.06 worse than expected.
For the full year, Lululemon slightly raised revenue guidance by 0.3% which would represent 18% growth at the midpoint. This was related to Q3 outperformance as Q4 was again a tad light. For full year EPS, Lulu raised its guidance from $12.10 to $12.38. This is $0.19 ahead of estimates and would represent 22.9% Y/Y growth. Please note that the $12.38 guide excludes the same provision and restructuring charges already mentioned. These charges were not in the guidance it offered last quarter, and were not baked into analyst estimates. Without this adjustment, its guidance of $11.81 is $0.29 light. I say this purely for your information. As the charges weren’t in previous guidance or estimates (and considering the nature of them), I consider this a raise. Mirror impairment charges will go away and are now entirely unrelated to the underlying operating profitability of this business.
It now sees 70 bps of annual EBIT leverage vs. 50 bps as of last quarter and vs. 60 bps expected by analysts.
It reiterated expectations of 200 bps of GPM leverage for the year.
Inventory will be flat to slightly down Y/Y next quarter.
Finally, its 5 year financial targets first set back in 2021 were again reiterated.
d. Balance Sheet
$1.1B in cash & equivalents.
$400M in credit capacity.
Inventory fell 4% Y/Y. This was better than its 8%-12% Y/Y growth expectation due to strong demand. Mirror inventory provisions helped too. It continues to expect markdown rates in 2023 to be stable vs. pre-pandemic periods.
Share count fell slightly Y/Y.
New $1B buyback (roughly 1.6% of float). It has $243 million left of its current buyback program.
“We remain comfortable with both the quality and quantity of our inventory.” – CFO Meghan Frank
e. Call & Release Highlights
Q4 Thus Far & Macro:
The team is “pleased” with its holiday weekend and quarter-to-date performance. It’s seeing strength across e-commerce and brick and mortar with new and existing product lines all working. Full price merchandise continues to perform very well as consumers largely overcome economic anxiety. This is despite materially “deeper discounting” Y/Y from competition during the quarter. Lulu, as always, did not have to match that promotional intensity to find demand – and it didn’t.
“I definitely saw a more promotionally driven environment by some of our peers, by some of the new entries into this category. We didn't deviate. We didn't change. And our results I talked to indicate that we didn't need to. Guests respond to innovative products and that's what our pipeline is full of.” – CEO Calvin McDonald
The one soft spot was men’s apparel in North America – a key growth segment. The team blamed uncertain macro and men being more prone to cutting apparel costs amid that uncertainty vs. women. While this sounded. like an excuse, continued strong market share gains for men in North America point to it being a legitimate one. The market share data is per Circana, not internal claims. This makes it more meaningful. The firm is also taking share across the globe, but there aren’t great data sources allowing it to precisely quantify those gains.
The moderate men’s softness (and still having 2 months left in its quarter) led to leadership’s continued prudent, conservative guidance methodology for Q4. This was repeated several times during the call as a wink to Wall Street. Under-promise, over-deliver. I expect this beat- and
A Promising New Marketing Lever:
Members of Lululemon “Essentials Tier” continue to grow briskly. It doesn’t update the total every quarter, and didn’t this time, but likely will early next year. This is creating a large, highly relevant base of passionate fans to specifically target. That led to it debuting an early access Black Friday promotion for members. The promo resulted in an app download
More Growth Metrics:
Growth was strong in August, cooled in September due to lack of marketing activity and product launches, and again re-strengthened in October.
Other revenue (wholesale, licensing and Lululemon Studio) represented 10% of total revenue vs. 10% Y/Y.
Company operated stores represented 49% of total revenue vs. 49% Y/Y.
Women’s revenue rose 19% Y/Y while men’s rose 15% Y/Y.
North American revenue rose 12% Y/Y which is in line with its long
Every market in Asia Pacific and Greater Europe grew by 10%+ Y/Y.
As previously announced, Peloton and Lululemon have a new 5 year partnership. Peloton is now the exclusive fitness content provider for Lulu’s various subscription tiers while Lulu is Peloton’s exclusive apparel provider. As a result, Lulu will halt content creation just like it halted Mirror hardware sales. This led to impairment charges discussed already in the margin section.
Gross margin outperformed thanks to lower freight costs and utilization. Foreign exchange offset some of this strength.
Sales, general & administrative expenses accounted for 38.2% of revenue vs. 36.8% Y/Y. This was actually 50 bps better than expected. The contraction was well-telegraphed and is due to “strategic growth and brand investments.” It’s leaning in.
Product Line Highlights:
Its new Wundermost women’s line is its softest fabric to date. This blends Lulu’s edges in “raw material creation, technical construction and fabric innovation to engineer a new sensation and feel for guests.” These competitive edges are highly subjective. What isn’t subjective is Lulu’s consistently strong results.
Men’s shoes will launch in Q1 2024. Its new men’s product lines like Steady State and Soft Jersey performed so well that it’s now “chasing into more inventory.”
“We're seeing enough positive guest signals that we think we have an opportunity in this shoe category. We're going to take a long-term view and build it, but we’re excited about what we're seeing so far.” – CEO Calvin McDonald
Lulu has ample room for rising brand awareness. This is why it’s investing so heavily in growth at this stage. Brand awareness in the USA is at 25% overall and just 13% for men. Total awareness is under 10% in every other market besides Canada (where it started) and Australia. This minimal awareness/long runway for growth with men led Lulu to introduce a successful national joggers campaign in North America for men.
This would be a great quarter for nearly every other player in the space. It’s an average quarter for Lulu simply based on the consistently elite execution & results we’ve all come to expect. The Q4 miss is clearly based on guidance sandbagging while market share gains remain brisk. Was this perfect? No. Is this concerning? Not in the least. Annual guidance was raised and the ambitious 5 year growth targets were reiterated. More execution, more success, and another all-time high for the stock.
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2. GitLab (GTLB) – Earnings Review
We’ve covered JFrog a lot within the world of software development and operation (DevOps), but not GitLab. I wanted to provide a brief GitLab 101 as I introduce this into the coverage network. So what does it do?
First and foremost, GitLab offers Git Repository Management. This is an aggregated destination to store source code and files. Within it, developers can review source code health and alterations while resolving conflicts in a secure environment. In the world of DevOps, this is furthest to the “left” (or earliest on) in a software package’s journey to runtime. It always starts with source code and this is GitLab’s bread and butter.
Beyond the git repository, GitLab also offers continuous integration (CI). This is what automates the testing of source code and apps as well as conversion of source code into binaries. Conversion creates what’s called an artifact. Artifacts are usually binaires which are a series of 0s & 1s that can be read by machines. This is where large players like JFrog Artifactory come into the fold. Machines can’t read dozens upon dozens of source code languages. They can read 0s and 1s.
GitLab is now trying to extend its end-to-end DevOps platform further “right” (or later on) in the process to post artifact conversion. This is being done via products like Continuous Deployments (CD) which, (as the name indicates) involves the binary or software package being deployed into runtime. Its Pipeline product allows for the conjoining of CI and CD into a single step (intuitively called CI/CD). Finally, it offers some observability and security tools to monitor the performance of apps being worked on or deployed. The other functions mentioned, when paired with this one, place GitLab firmly in a “DevSecOps” niche.
Within this quarter’s theme of software platforms distancing from point solutions, that’s what GitHub is trying to emulate in DevSecOps. Considering 75% of organizations will be on one DevSecOps platform by 2027 vs. 25% today, this approach is well placed. It wants to be the single platform to do it all.
GitLab beat revenue estimates by 6.2% & beat its guide by 6.5%. Its 49.7% 2-year revenue compounded annual growth rate (CAGR) compares to 55.0% as of last quarter and 59.5% 2 quarters ago. Note that dollar-based net revenue retention (DBNRR) of 128% is still very good. The 400 basis point (bps; 1 bps = 0.01%) sequential expansion is also comparatively good vs. its peers.
Beat -$5.5 million EBIT estimate & beat its same guide by $10.1 million or nearly 200% each.
Beat -$0.01 EPS estimate & beat its same guide by $0.10 each.
Gross profit margin (GPM) was comfortably better than estimates. It doesn’t guide to GPM.
As part of tax negotiations with global regulatory bodies, GitLab recorded a $254 million income tax adjustment which heavily hit GAAP net income for the quarter. It did this to optimize its tax position going forward.
c. Q4 Guidance
Next quarter revenue guide is 5.4% ahead of estimates
Next quarter EBIT guide of $5.5 million is $11.9 million ahead of estimates.
Next quarter EPS guide of $0.08 is $0.09 ahead of estimates.
Annual guidance was raised across the board as a result of Q3 results and Q4 guidance.
Leadership also reiterated its plans to reach free cash flow (FCF) breakeven next year. It continues to work on de-consolidating from its China Joint Venture called JiHu. Without the operating losses from this segment, non-GAAP EBIT for 2024 would be breakeven.
d. Balance Sheet
$1 billion in cash & equivalents.
Share count rose by 4.2% Y/Y. This needs to slow & likely will as it moves further away from IPO-related equity awards.
e. Call & Release Highlights
The Platform Play:
Just like ServiceNow, Zscaler, Salesforce, CrowdStrike and other software platform plays, GitLab’s full DevSecOps platform approach is working. The depth and breadth of their offering, from code creation to package deployment, is a complete platform for better efficacy at lower cost. That’s why 50% of its total bookings for Q3 came from its full-product subscription tier called the Ultimate Tier. This is its fastest growing bundle. I continue to repeat this same overarching idea for good reason: There’s a clear pattern.
“Breadth and depth of the platform across the full software dev life cycle differentiate us from point solutions and our main competitor, GitHub.” – CEO Sid Sijbrandij
The value proposition led to some compelling customer wins this quarter. A global financial services platform migrated to GitLab after a failed attempt to integrate needed tools with GitHub. The manual stitching together of these products fostered friction, confusion, inefficiency, and higher cost. GitLab displaced Microsoft GitHub and provided all needed add-on products into its single-interface platform. The customer enjoyed reduced costs, 8x faster deployment speed and 4x faster feature delivery.
A large business networking firm saw a similar result when it migrated from GitHub to GitLab. This customer kept hitting usage limits when trying to run software packages through GitHub. As leadership stated on the call, it “was not efficient enough to support growth.” GitLab 7Xed its package running efficiency. It also provided the security and compliance tools needed to displace point solutions – which GitHub couldn’t match.
As an aside, these anecdotes remind me of CrowdStrike’s successful competitive journey against Microsoft Defender. More niche players focused on fewer missions are seemingly outperforming the product utility of Microsoft as it juggles dozens upon dozens of product priorities.
When 3rd party security solutions are used, it routinely means developers must pause work to wait for security team verification and scanner results. This lengthens time to source code vulnerability detection and remediation. GitLab has a new security findings workflow tool. This allows developers to access security scanning results from within their GitLab developer environment.
GitLab is working on bringing more project management functions within its holistic platform to consolidate more potential point solutions. This matters a lot. Why? Per the 9th annual Global DevSecOps report, 66% of enterprises want to consolidate vendors and 84% of them use 2-10 different tools for full DevSecOps capabilities. GitLab is in the right place at the right time with a compelling sales pitch.
Customer & Research Organization Case Studies:
Per a GitLab commission Forester study, it delivers a 427% return on investment for clients within 36 months. It also delivers an investment payback period of 6 months.
Gartner ranked it #1 in ability to execute and #2 behind GitHub for completeness of vision in its latest research. Forrester ranks GitLab as the only leader in the space.
Delivered a 114x in product release velocity for Airbus and 99% faster software release times (24 hours shrunk to 10 minutes).
Shrunk T-Mobile’s software release cycle from 18 months to 3 months.
Eliminated 90% of Lockheed Martin’s time spent on software maintenance.
GitLab infuses GenAI models and tools throughout its entire platform. Today, it offers 14 AI features with many more to come. It thinks that the entirety of these tools can 7x software cycle speed.
GitLab Duo is the overarching “suite of workflows” within GenAI to augment developer speed and work quality. Duo Vulnerability Summary generates reports of vulnerabilities and best course of action to resolve issues. Duo Code Suggestions, similarly to GitHub Copilot, is a GenAI code creation tool powering 50% efficiency gains for beta testing clients. It’ll be fully introduced this month. Considering how much potential there is to automate code creation with GenAI, success here will vastly bolster its cost cutting value proposition for clients. This could potentially allow software developers to pocket a full 25% of their total time spent on work. Imagine what they can do with that time. GenAI models and their vast data consumption needs also mean more demand for software packages, which is good for GitLab as well.
Furthermore, Duo Chat creates project status reports, explains code suggestions, troubleshoots CI/CD issues and allows for package testing without context switching (meaning moving in and out of a developer environment). It’s a “natural language AI assistant” like ChatGPT, but with more specific use cases.
Security & Governance Upgrades:
GitLab Dedicated is a tool that provides proper compliance within data isolation and residency. That, in turn, means GitLab can offer its full platform (with all layers of automation) even in the most tightly regulated sectors.
GitLab, like many others, commits to never using a client’s code to train its own GenAI models. It sees this layer of separation and transparency as a key reason why “50%+ of the Fortune 100 trusts GitLab to secure their IP.”
Demand Trends & Macro:
Per CFO Brian Robbins, the sales cycle did elongate sequentially. That was surprising to hear given the strong results. Buying behavior for its largest customers did stabilize, but that was not the case for smaller clients. Importantly, win rates continued to rise sequentially, pointing to GitLab being a clear market share taker. Those share gains will be rewarded with even more business as macro improves.
Similarly to Snowflake, most of GitLab’s revenue (about 75%), is usage based. This means it’s easier for clients to reduce their business with GitLab than with a pure SaaS model like Zscaler. Considering this, the resilient demand is impressive and points to just how mission-critical this platform is in our digital world.
Note to self: Next time Google aggressively scoops up shares of a public company like GitLab, pay close attention. While the company struggled with execution and guiding expectations earlier in the year, those issues have seemingly vanished. Demand and margin trends are both very positive and should get even better as its smaller client cohorts struggle less with macro. Its ability to monetize GenAI tools and take advantage of this current wave is quite compelling and its secular tailwinds are raging.
At 17x gross profit (more than double market averages) and 100x calendar year 2025 operating income, this is one of the most expensive names on markets. It will need to continue delivering fantastic quarters like this one to keep justifying what is a large, large premium. There is virtually no margin of safety here. They must be perfect. This quarter was perfect.
3. MongoDB (MDB) – Earnings Review
MongoDB is a key player in data storage and analytics with a document-oriented setup. I’ll explain what that means later.
Its most exciting product is called MongoDB Atlas. This is its database service to implement a group of servers (or a cluster) used to actually store the data. The nature of MongoDB’s product allows clusters to be easily added to or subtracted from for easier flexing up & down as needs fluctuate. It also offers MongoDB Realm as a mobile environment for app creation, MongoDB Stitch to build apps without servers or any needed infrastructure maintenance and MongoDB Search for data querying. Finally, it offers MongoDB Data Lake specifically for unstructured data which directly competes with players like Snowflake. There are more products, but these are the big ones with new releases discussed below.
MongoDB beat revenue estimates by a comfortable 7.2% & beat its guidance by 7.7%. Its 38.1% 2-year revenue CAGR compares to 46.0% as of last quarter and 42.3% 2 quarters ago.
MongoDB obliterated profit expectations. EBIT was 78% ahead of estimates and 85% ahead of its guidance. It earned $0.97 per share vs. expectations of earning $0.50. This is its 3rd consecutive quarter of greatly outperforming all expectations. Similarly to Nvidia, the magnitude of these consistent beats will likely lead to sell side estimates positively diverging from its guidance over time. It will raise the bar for what is considered a successful quarter. Great problem to have considering it’s based on stellar performance.
Note that some marketing spend was pushed from Q3 to Q4. This helped margins a bit. Still, the large annual increases in profits and margins show that this wasn’t the main source of outperformance.
c. Fourth Quarter Guidance
Revenue guidance is 4.1% ahead of estimates.
EBIT guidance is 17.7% ahead of estimates.
$0.45 EPS guidance is $0.09 ahead of estimates.
As a result of the beat & raise, annual guidance was raised across the board.
d. Balance Sheet
$1.9B in cash & equivalents; $1.1B in senior notes.
Share count rose 3.8% Y/Y.
e. Call & Release Highlights
Demand & Macro:
Success for the quarter was powered by existing customer expansion and new customer workload demand. Per leadership, success was “despite continued challenging market conditions.” How is this software standing out in today’s environment? You guessed it… just like all of the other standouts. Demand for its full product platform tier (called Enterprise Advanced (EA)) is raging. Leadership talked up its end-to-end data platform as readily replacing point solutions for bellwether clients like AT&T. It’s striking a currently needed balance of cutting client costs and improving efficacy. As another example, EY migrated to MongoDB for a 50% reduction in data costs while, relatedly, doubling performance.
EA revenue was also helped by more multi-year deals than expected. This revenue is recognized when a contract starts. This is unlike Atlas, which generates revenue mainly based on usage.
“Clients want to do more with less. They want to consolidate vendors and reduce complexity of their data architecture. MongoDB dramatically increases developer productivity and supports a wide variety of use cases, eliminating the need for many point solutions. This combination resonates with customers in this macro environment.” – CEO Dev Ittycheria
MongoDB Vector Search:
MongoDB Vector Search became broadly available to clients this past week. Unsurprisingly, this newer product mimics its other app building tools, but with a focus on GenAI apps. Broken record alert: GenAI apps and models insatiably consume data. The more data, the better; the more relevant that data is, the better. MongoDB provides data scale and secure access to a client’s first party data. First party data is the most relevant data set for client-specific use cases. It pairs these data skills with ample programming language frameworks to free developers to bring their work to their data. Snowflake talks about this same idea all the time.
This new tool offers Semantic Search, which allows clients to seamlessly scrape insight from data. It allows for theme and idea-based querying rather than just word-based. It also provides retrieval-augmented generation (RAG). This pushes semantic search results into associated large language models to uplift querying precision. Per a recent “retool” research study, Atlas Vector search has the highest developer Net Promoter Score (NPS) in the industry.
More on GenAI:
Along the same GenAI theme, MongoDB Atlas Search Nodes (another new product) is a new tool freeing developers to work with 60% faster query times and full infrastructure management.
New Amazon Bedrock integration to bolster the range of LLMs developers can work with. It already has integrations with Amazon CodeWhisperer and Microsoft GitHub Copilot as well as many foundational model builders like OpenAI and Hugging Face.
This is the most important product for MongoDB today. Atlas revenue rose 36% Y/Y to reach 66% of total sales vs. 63% Y/Y. Customer count for the product rose 21.4% Y/Y to reach 44,900. Like Snowflake and GitLab, this revenue is usage-based, not subscription-based. Meaning? Continued strong retention and growth directly indicate how mission critical this company is in our digital world. It’s easier to cut spend here than it is with contracted subscriptions (and easier to spend more during better times). Considering net revenue retention remains at 120%, that’s just not happening.
Consumption trends improved sequentially as expected. They were in-line with company expectations offered on the last call.
Encouragingly, Atlas efficiencies were also the source of the firm’s gross margin expansion and outperformance. This means that as Atlas grows as a percent of total revenue, there should be more margin upside.
Relational Database (Snowflake) vs. NOSQL, Document-Oriented Database (MongoDB):
Legacy relational databases store data in static rows and columns linked by implemented formulas. These databases look like giant excel spreadsheets and use structured query language (SQL) to work. Legacy relational databases cannot seamlessly handle unstructured data like MongoDB’s data lake can. This is a large limitation considering how important unstructured data is for GenAI use cases. Legacy relational databases struggle to scale and unlock the most advanced querying. The datasets are fixed with formatting and filtering more limited. The lack of ability to provide “not only SQL” (NOSQL) can slow performance and diminish value.
MongoDB’s NOSQL database and document-style data storage fix these issues. That’s why the pace of migration continues to ramp up.
Importantly, NOSQL is not better when it comes to structured data querying and data consistency as well. Not superior, just better at certain things. For evidence of this, arguably one of the most disruptive players in the general database world is Snowflake. Snowflake’s data warehouse is a relational database… just a next-gen version. It offers NOSQL, better scalability via separation of data and compute, and unstructured querying. It went with a “make relational databases much better” approach while MongoDB implemented a “move to NOSQL” approach. Snowflake is considered more advanced in structured data. Some would argue its security and governance offering is better too. MongoDB stands out when it comes to flexibility, ease of use and unstructured data prowess. In this light, they technically are complementary tools and can be used in tandem in some cases. Still, both continue to encroach on the other’s territory like we see in other areas like cybersecurity, programmatic advertising and DevSecOps.
Legacy Relational Database Migration & On-Premise Migration:
Customers frequently express frustration over not being able to migrate some workloads to NOSQL as quickly as they want to. They “lack skills and capacity to modernize, but know they need to modernize.” This is where MongoDB’s relational migrator comes into play. This full service tool oversees client migration to MongoDB.
It also holds client hands as they migrate from on-premise to the public cloud. Some industries, like financial services and healthcare, have very strict regulations making cloud migrations much more difficult. MongoDB helps mightily here. It also offers an on-premise version of its product suite; this allows for better client control when it comes to pace of migration.
MongoDB is looking to expand beyond data migration to the “full life cycle of app modernization migration.” It wants to “reduce effort involved” in this tedious process. Like many others, this is code for “we want to displace more point solutions.” To do so, it debuted a query conversion tool to intuitively integrate and onboard legacy apps powered by SQL to MongoDB.
“To be clear, application modernization will take time to ramp, but is one of the largest long-term growth opportunities for our business.” – CEO Dev Ittycheria
Another wildly impressive quarter for this company. Leadership clearly continues to aggressively under-promise in light of macro uncertainty. That macro uncertainty is not leading to diminished demand – hence the sheer magnitude of beats and raises throughout 2023. At 108x next 12 month EBIT and 160x next 12 month FCF, expectations are set very high and command outperformance. It has delivered that in spades this year and that must remain the case to continue justifying the premium… Just like for GitLab and many other software names that have aggressively run as of late. Great quarter.
4. Shopify (SHOP) – 2023 Investor Day
There were no new financial targets or product announcements from this event. What it did offer investors was a fascinating view into the inner-workings of Shopify. It covered the subtle differences in infrastructure and organizational structure that have powered its rise. It was a bit of a philosophy lesson which I, as a nerd, thoroughly enjoyed. I’ll highlight the key details here.
First Principles Thinking:
Founder/CEO Tobi Lutke talked at length about First Principles thinking. This is an approach to problem solving that aims to break down challenges into separate, fundamental pieces. The philosophy aims to solve these pieces individually in ways that can repair and rebuild from the ground up. It involves original thinking, rather than relying on existing solutions as conventional wisdom to be followed. The original issue Tobi solved to create Shopify was tearing down the friction-fostering barriers to starting an online business.
They did so by building a rock-solid foundation to build on. Tobi describes the foundation as gasoline, with product applications derived from it as the gas pedal. A solid foundation is vital. Focusing there first is how Shopify delivered 99.99999% up-time this holiday weekend vs. competition only with 3 or 4 9’s after the decimal. This may seem irrelevant, but when handling tens of billions in volume, it’s not.
The founder-led nature and culture of Shopify, the team thinks, have put it in an ideal spot to practice this form of thinking across all business lines. Founders more frequently possess an ownership mentality (like Tobi surely has with his large stake) and a longer-term view that leads to prioritizing key hurdles over quarterly profits. They’re, generally speaking, more willing to assume risk and delay gratification.
In practice, Shopify focuses first on building the best products for its merchants under this frame of thought. Priority 2 is making money from these products to ensure it can keep building better and more.
More on Culture & Systems Creating Subtle Edges:
Shopify’s executive roles are filled by nerds (my favorite kind of people) and developers, not managers. Their leaders are former entrepreneurs and coders who, through direct experience, have a keen understanding of what merchants need to succeed and how to give it to them. They’re also fixated on “merchant obsession” or listening closely to wants and needs. These are not promoted middle managers who are great at relaying task delegation and not much else. In 2022, the team actively shed layers of middle management to cut costs and get more efficient. Meta and many other firms did the same thing. This streamlined bureaucracy and morphed Shopify back into the “Crafter’s Paradise” label that it yearns for. The result? Senior engineers spend 22% less time in meetings, engineer productivity is up 37% Y/Y and project completion rate is up 56% Y/Y. More with less. This also has helped sales team productivity rise 150% Y/Y.
It doesn’t just build great software for merchants, but custom software for its own operations too. A lot of this work happened in the last 12 months and has allowed Shopify to eliminate several third-party vendor contracts. It’s this piece of software that mines company data and follows pre-set instructions to organize and delegate work.
“So most companies develop heuristics like person with X title gets to make Y decision… Titles are a really dumb way to determine expertise. We don't want Shopify to be governed by an org chart, so we built a piece of software.” – COO Kaz Nejatian
GST is its internal operating system which “provides visibility on all projects across Shopify.” To double-check the quality of project prioritization/work, Tobi, Glen Coates (VP of Product) and COO Kaz Nejatian meet twice a quarter to review them all. This means “at most, any mission in the company can only be 6 weeks off track.” This may sound simple, but is rare for a company of this scale. It shows that, aside from the 2021-2022 irrational spending spree, this firm still clings to its start-up culture which required efficiency, agility and execution. This quote put a large smile on my face (lessons learned) and lends credence to their strategy:
“We are desperately trying to forget about mistakes made in 2021.” – Founder/CEO Tobi Lutke
It’s also the agility that allows them to implement new AI models and tweak existing models in real-time without ripping and replacing old systems. This puts them in the perfect spot to leverage the rapid innovation taking place within that area right now.
This custom software on its own is an operational edge. For example, it includes automation of human resource tasks which cuts work time by a full 50%. This means more hours to build and innovate rather than maintain.
Bigger Fish & Scalability:
The idea above about obsessing over infrastructure and footing first leads to another key edge: Shopify merchants can endlessly scale with that best-in-class uptime. They can also do so with best-in-class checkout flows that convert 15% better than competition (36% better than Salesforce Commerce Cloud). They can do so without making concessions over which products and which integrations they need. There is no reason to ever leave Shopify because you can have whatever you want, build whatever you want, enjoy a superior user interface and grow as large as you want on the platform. If Shopify doesn’t directly offer the product, it has a market-leading commerce app store for developers to fill in the blanks. These apps are intuitively and neatly integrated into Shopify’s platform (emulating the look and feel of the ecosystem) with a deep set of application programming interfaces (APIs).
That’s nice to say, but do we have any evidence aside from financials? Yes we do. For mid-market merchants, Shopify wins 43 merchants from competition for every 1 merchant that churns. For larger merchants it’s 26-to-1 and for merchants over $125 million in annual revenue, it’s 38-to-1. Shopify is taking share from all competitors and across all merchant sizes. As a related aside, Shopify added Carrier as a large new B2B brand this past week.
It Just Does More:
Glen Coates walked us through a review of everything Shopify offers. The breadth of its offering is unmatched and I think it’s worth covering again. Shopify is the only firm to come close to combining all of the following items:
Fully integrated admin for online and offline selling.
Ability to expand internationally with one click.
Ability to sell to consumers and businesses in one integrated system.
Ability to sell through any marketplace and social channel you can think of.
Front and back office support without the need for a separate vendor.
Ability to sell on mobile or desktop through a single system.
Ability to enjoy complete inventory and marketing management across all channels. All of them.
Large checkout conversion edges over substitutes.
And finally, the ability to simply integrate all missing pieces into Shopify in a way that emulates the look and feel of the rest of the site. As a reminder, Metafields and app blocks allow these 3rd party apps to be dragged and dropped throughout any part of a merchant’s site. It turns the emulation of fully custom builds into lego blocks. Importantly, it does so without forcing Shopify to ever build from scratch for a single merchant. It’s these edges that, per leadership, make it a bad decision to start a business anywhere but on Shopify.
“We solve more problems in the box than any other platform.” – VP of Product Glen Coates
More common merchant problems it plans to alleviate in 2024 mainly include improvements to existing focus areas:
More complex product descriptions coming along with better description integrations across marketplaces.
Mixing order types (For example, half buy online, pick up in store and half delivered).
Improved local payout support.
Perfecting B2B sales rep permissions to ensure they always have access to what they need. Nothing more, nothing less.
Further localizing international product experiences to bring service levels up to par with North America.
Show Me the Money:
It’s no secret that I love Jeff Hoffmeister as the firm’s new CFO. He transformed the approach into one that balances growth with profits. He led the sale of the fulfillment network and the shift in mindset to one that fixates on demand AND free cash flow. He sought to make a bloated company a lean, mean, fighting machine… and he has made ample progress already. The margin trends for the company are well documented, but there’s another key piece of evidence.
Shopify has cut paid search by $100 million Y/Y. It has prioritized more affordable channels of customer acquisition (such as consulting partnerships) and has seen these channels explode in growth contribution. While making these paid search cuts, new merchants from this single channel have still spiked higher. It’s spending less to acquire more merchants. This added channel segmentation has also given Shopify a much better sense of exactly which marketing dollars are working best. This will lead to some fine-tuning of budget allocation and better payback periods in the future.
While there wasn’t much time spent on GenAI and Shopify Magic or Sidekick, there was one interesting idea shared. Tobi sees this technology moving from “imperative to declarative.” He offered a simple analogy to explain what this means. A consumer (or merchant) doesn’t want to know how a car is put together, why it turns on and how to make it work. It just wants an Uber to take them where they need to go. They simply want to see the end result. Needing to know the inner workings of the car, or GenAI model, is what he means by imperative while simply needing to tell the car where to go is what he means by declarative. GenAI is moving to a stage of consumer-facing applications where you can tell it where you want to go.
GenAI is only as good as the products that models augment. They can only do what those products can actually do themselves. That’s why product perfection BEFORE the GenAI wave sets companies with the best suites up for continued success. The winners before GenAI are more likely to be the winners after than some assume. The other reason for this is simply that GenAI models need large databases for proper training. Shopify’s commerce database is relevant and massive.
Shopify shared a blurry graphic showing its online market share vs. direct competition doubled from 24% to nearly 50%. Unfortunately, there was no timeline offered on the X-axis… for some reason.
We already knew that Shopify represented 10% of total North American e-commerce in 2022. What we didn’t know is that it’s at 6% in Europe and 4% in the rest of the world.
It expects to generate $450 million in point-of-sale revenue this year.
Shopify Audiences reduces customer acquisition cost (CAC) for merchants by up to 50%.
Shopify Capital has a 70% loan renewal rate. That is not normal for a lending product.
It has a $20 billion gross merchandise value (GMV) pipeline from system integrator (SI) partners like Deloitte and Accenture.
18% of its mid-market accounts are growing 40% Y/Y and 25% of its large accounts are growing over 40% Y/Y.
Gartner named Shopify a leader in digital commerce in its most recent graphic. It’s #1 in ability to execute, but still behind Salesforce and SAP in completeness of vision.
G2 named Shopify’s point of sale offering as the only leader in the space. It’s well ahead of Square and Lightspeed.
Lifetime revenue bookings mean the estimated revenue from the sale of products to merchants for a given period. While growth was sequentially flat for a few quarters, it has since spiked higher while margin associated with these bookings has risen at an even faster clip.
68% of point-of-sale customer wins last quarter were from merchants not currently using Shopify for E-commerce. This is becoming a new customer lead generator.
Shopify’s cohorts over the last 8 years have delivered a 24% CAGR vs. a market average of 13%.
Shopify has 65 countries with over $100 million in GMV vs. 29 as of 2019.
30,000 Ft. View:
Shopify, in my view, is in The Trade Desk and CrowdStrike’s league of truly elite companies. Its culture is one that can actually deliver on its goal of being a 100 year company. Its valuation premium certainly reflects that and means this firm will need to keep dominating the competition for the stock to be successful in the near term. I candidly view the near upside as quite limited but think the longer term opportunity is anything but limited. Risk/reward has deteriorated in recent months given the run-up, which is why I sold a chunk. Still, I want this special company to be in my portfolio. Please always feel free to disagree with this subjective opinion.
a. SentinelOne (S) Earnings Snapshot
SentinelOne directly competes with CrowdStrike, Microsoft Defender and Palo Alto in endpoint security. It specializes in small and medium business clients.
SentinelOne beat revenue estimates by 5.1% and beat its guidance by 5.3%. The 71.2% 2-yr revenue CAGR compares to 80.6% as of last quarter & 89% 2 quarters ago. It also beat annual recurring revenue (ARR) estimates by 0.9%. This is the most important demand metric for the company.
1,060 $100K+ ARR clients vs. 994 Q/Q & 917 2 quarters ago.
115%+ net revenue retention vs. 115%+ Q/Q & 125%+ 2 quarters ago.
Beat EBIT estimates & beat same guidance by about 47%.
Beat 76% GPM estimates & beat same guidance by 320 bps.
Fourth Quarter Guidance:
Beat revenue estimate by 1.4%.
Beat EBIT loss estimate by 25%.
Beat 76% GPM estimate by 100 bps.
Full year guidance was raised as a result of Q3 results & the Q4 guide.
$800M in cash & equivalents.
Share count up 5.3% Y/Y. That must slow, and (like for GitLab) likely will as it moves further away from the IPO and controls hiring pace.
b. Broadcom (AVGO) Earnings Snapshot
Broadcom beat revenue estimates by 0.2% and beat its guidance by 0.3%.
Beat EBITDA estimates by 1.3% and beat guidance by 0.3%. It missed $8.45 GAAP EPS estimates by $0.20, but beat $10.96 EPS estimates by $0.10.
Full year revenue guidance was 0.4% below expectations while EBITDA was also 0.4% below expectations. EBITDA margin was in line with expectations.
$14.2 billion in cash & equivalents.
$39.2 billion in debt ($1.6 billion is current)
Basic and diluted share counts are flat Y/Y.
6. CrowdStrike (CRWD) – Investor Conferences
We got another classic CrowdStrike shot at the competition from CFO Burt Podbere this week. Keep in mind that these come frequently from this team. The shots are irrelevant unless backed by great results and market share gains. In CrowdStrike’s case, that’s the reality. Microsoft’s legacy tech was called “inferior” with upgrades greatly lagging the pace of adversary sophistication improvements. To be fair, he praised their powerful bundling capabilities, but didn’t praise anything else.
Burt called out a “crisis of trust taking hold” through frequent breaches caused by Microsoft Defender vulnerabilities. He cited the Outlook hack from July and how, months later, the State Department explicitly said it was Microsoft’s fault. This is not an anomaly, but is instead becoming a cliche. Microsoft does many things extraordinarily well. Endpoint security is just not one of them. It relies on its powerful bundle to cling to market share.
Burt called Microsoft’s pricing “gotcha pricing.” By this, he means they’re baiting and switching customers by offering free licensing, but all-but-mandatory up-sells making its service anything but free.
As a quick review, Burt was asked how gross margin is improving so sharply. He reminded us of the previous investments in infrastructure that are now leading to leverage. But there’s another key theme here: The platform. It offers a single, light-weight agent on one console. This allows it to constantly recycle data and insight to build new products. It also allows it to onboard these new products for clients wildly easily. The result is virtually zero incremental cost for CrowdStrike after it sells module #1 to a client. It has 26 others to sell. This is why long-term gross margin targets just continue to rise.
More on Competition and Generative AI:
Burt explicitly called out Copilot pricing from Microsoft. Charlotte AI, CrowdStrike’s GenAI offering, will undercut Copilot. As an aside, capabilities here will get a large upgrade early next year. Charlotte AI will soon be able to conversationally tell clients what to build or how to improve computing hygiene. It will then do it for them when prompted. Falcon Foundry, its no code developer app building tool, meshes perfectly with this. Together, the two products will allow CrowdStrike to enable more custom use cases without building from scratch or incurring more cost. This should make Falcon even stickier than it already is with its sky-high 98% gross retention rate. Interestingly, Charlotte AI will also recommend needed modules for customers to make up-selling more intuitive and seamless. Based on the smaller volume nature of small client deals, discounting rates are lower and margins are higher.
At $20 per endpoint per year, this will meaningfully contribute to net new ARR growth next year. It will take longer to materially contribute to total ARR.
This will be a large unlock for smaller client growth. Why? It will up-level beginner security analysts to experts and diminish the need to employ large teams here. Falcon Complete, its fully managed offering, helps a lot with SMBs too. It gives small clients access to its world-class security team at a fraction of the cost of employing their own.
Demand is “definitely still there” for CrowdStrike, but budgets “are still tight.” They’re taking longer to close, but deal sizes are also getting bigger as CrowdStrike becomes a more powerful vendor consolidator.
CrowdStrike sees the MAJORITY of net new ARR coming from its cloud business eventually. It’s just 10% of its total business today and rapidly growing. It sees cloud infrastructure and app security as the two most promising growth vectors and so the two focus areas.
CrowdStrike continues to hammer home the message of offering an agent-based and agentless solution as a real source of differentiation. Agent-based means the product is installed directly into cloud workloads. Agentless doesn’t require any installation work, but just utilizes existing infrastructure. Agent-based automates relevant data collection (so does agentless) to provide broader security and observability over cloud environments and faster uncovering of issues. It also introduces tech layers and complexity into an environment. Agentless creates no additional overhead and is easier and cheaper to use. Visibility lags compared to agent-based, although CrowdStrike would argue visibility levels are still stellar. Different companies have different levels of need. So? It offers both. Agent-based is considered the more mature technology with agentless growing faster.
Burt talked about no other vendor doing both under one architecture and system. CrowdStrike does. Others have tried to partner to stitch these two offerings together. That approach hasn’t been successful in his mind.
2025 Investment Priorities:
LogScale and Security Information and Event Management (SIEM). It plans to accelerate hiring in areas like this one as some key players have been acquired this year. The index-free nature of its logging technology allows for far faster data querying at far larger scale and far lower cost vs. legacy competition. Log management and SIEM are ripe for disruption. It’s already well on its way to being that disruptor.
Cisco buying Splunk is creating a lot of customer and talent churn that CrowdStrike is successfully leveraging to accelerate its own growth.
CrowdStrike doesn’t charge for 1st party data logging, only 3rd party. This is yet another reason why the Humio Log Management acquisition was so key here and for extended detection and response (XDR). XDR is basically EDR, but with ample 3rd party data sources aggregated to uplift protection.
Identity Security. Again, not as a competitor to Okta or Ping which are identity managers/brokers. Instead, CrowdStrike aims to secure the managed identities.
Data Loss Prevention (DLP) investments.
7. PayPal (PYPL) – Amazon & Revving Up
a. Amazon (AMZN)
When new PayPal CEO Alex Chriss took over, one of his commitments was to never chase unprofitable growth. Old PayPal leadership, through 2021, did things like offer cash burning promotions to developing markets with zero chance of ever receiving positive paybacks. It did this to prop up its total account number to impress Wall Street when, in reality, the move meant little revenue and less profit. Chriss is determined not to make these mistakes.
Through profit sharing agreements and some heavy promotional activity to motivate usage, it’s likely that Venmo Checkout on Amazon was not a profitable business for PayPal. We’ll wait to see what leadership has to say, but if I had to guess, I strongly believe this is Chriss saying no to repeating PayPal’s 2021 mistakes. Regardless, the volume from this partnership was tiny and shouldn’t have any material impact on overall results.
But what if I’m wrong? What if this is a sign of no product-market fit? What if Amazon truly just didn’t want the tens of millions of users on Venmo to have that option? That wouldn’t be the end of the world either, despite being a larger negative.
Venmo needs to copy Cash App’s product suite. It should be the consumer destination for financial services and leave branded checkout to PayPal. Ideally, it could’ve done all of these things, but Venmo’s use cases just aren’t in branded online checkout. It’s social and service-oriented in nature. It’s more intuitive to split an Uber with Venmo and checkout on Nike with PayPal. While this removes a margin lever opportunity, it likely allows the firm to focus on higher probability margin levers going forward. It needs to keep leaning into local business profiles, incorporate sponsored listings for these local merchants and find more success with its credit and debit offering. These items become more vital in a world where branded checkout is no longer a focus area.
b. Revving Up
Alex Chriss is accelerating the pace of product upgrades for PayPal. Considering how slow-moving this firm was under old leadership, this is vital. For context, previous leadership took several quarters just to implement its latest checkout flow for not even half of its largest merchants. That is in no way, shape or form acceptable in 2023. Under operation “Quantum Leap” Chriss has demanded more rapid product improvements to compete with Stripe and Apple. Chriss thinks they’ve fallen behind the competition, which is a common opinion, and this is his push to rapidly address that. They’re looking to fast track these needed upgrades and have them rolled-out by March. While I don’t think PayPal is a dinosaur, I do think it needs to innovate more and move faster. Chriss seemingly agrees.
8. Disney (DIS) – Proxy Fight & More News
a. Proxy Fight
As previously discussed, Nelson Peltz’s Trian renewed a proxy battle with Disney. This week, Ancora announced support for Peltz and requested he be given a board seat. It accused Disney of just saying the right things and wanting Peltz on the board to ensure they carry out their promises. They also rightfully accused the company of politicizing the brand, although I think it has finally learned from those mistakes.
Regardless of what happens, this is a positive for Disney shares. There are two potential outcomes here. First, the board and executives feel more pressure to deliver on their promises and Peltz loses the vote in May. Still, they feel that hot seat heating up further and know that performance will be scrutinized. Secondly, he could win and keep pushing for the positive changes already being made and more positive changes like executive compensation reductions. I’ve discussed how Peltz’s desired Disney evolution is already coming to fruition without him. I candidly don’t understand why (or care about why) he’s still pushing so hard when they’re doing what he wants (unless they aren’t keeping their word). Regardless, I view this as a Disney shareholder win — heads or tails. Go get ‘em, Nelson.
b. More News
The actors' strike has been resolved. Writers and actors are now both back to work. Time to go make better content.
As expected, Disney’s streaming bundle is now starting to roll-out.
9. Market Headlines
Google’s latest multi-modal GenAI model, called Gemini, was demo-ed this week. It was pretty darn cool to be blunt. They showed off some use cases such as drawing a duck step-by-step and the model knowing exactly what the drawing was as it was created. The demo showed Gemini a world map and it created a game on the spot using the image. It compared objects with each other in real time as they were swapped out for each other. All of this shows continued rapid advancement by these still nascent models, but it may have been staged. TechCrunch released an article showing how Google fed Gemini data and instructions to make it look more advanced. Not a great look for what should still be a leader in the GenAI arms race. Not a great look… but also probably a blip on the radar.
SoFi Technologies (SOFI):
SoFi was fined $2.6 million by FINRA for securities lending supervision. Being fined by regulators is almost a rite of passage for banks. Unless this becomes a trend like it is for the big boys, it’s irrelevant to me just like SoFi exiting its microscopic crypto business is irrelevant to me.
A Bank of America survey uncovered some promising and unsurprising Amazon news. 64% of respondents (1000 total) search Amazon first when shopping for a product. Google is the next closest at 14%. All in all, 42% of respondents plan to raise e-commerce spending Y/Y vs. 32% for last year’s survey.
Uber Technologies (UBER) and DoorDash (DASH):
In response to laws in New York City, both Uber Eats and DoorDash added new ordering fees and cut the option to tip before an order has arrived. As previously stated, New York City drivers for Uber earn about $50 per hour on average. This new law requires them to be paid $18 on average. So? While the firms say this is necessary in the new regulatory climate, it’s likely just an excuse to bolster margins. Works for me.
Meta Platforms (META):
Meta debuted end-to-end encryption as the new “default service” across its messaging products with added privacy controls too. It also revealed a new GenAI image generator.
Output and Consumption:
The S&P Global Composite Purchasing Managers Index (PMI) for November was 50.7 as expected and stable last month.
Services PMI was 50.8 as expected and vs. 50.6 last month.
Institute of Supply Management (ISM) Non-Manufacturing PMI for November was 52.7 vs. 52 expected and 51.8 last month.
Atlanta Fed GDP Now estimates for Q4 sit at 1.3%.
JOLTs Job Openings for October were 8.73 million vs. 9.3 million expected and 9.35 million in the previous month.
ADP Nonfarm Employment Change for October was 103,000 vs. 130,000 expected and 106,000 last month.
ISM Non-Manufacturing Prices for November came in at 58.3 vs. 58 expected and 58.6 last month.
Unit Labor Costs for Q3 fell 1.2% vs. -0.9% expected and 2.6% in the previous quarter.
I didn’t have time to cover Match’s investor conference this week in detail. I skimmed it to make sure there was no breaking news or alarm bells. There weren’t. I’ll cover it in detail next weekend.