Alteryx Q120, and its new APA platform

AYX - Q120

SSI earnings review:… [with some great thoughts at the start on new product directions being signaled]
Frankdip recap:…
buynholdisdead recap:
Bert take:…
CC transcript:…
CC recap (sarksnz):
CC recap (Edyboom):…
Stocknovice trims:…
Bear trims:…
gmcnatt on CC hints:…
Saul thinks they are sandbagging:…
FourthStooge expects rebound:…
Gaucho expects rebound:

Revenue 108.8M +43.2%, -3233bps seq

  • US 80.5M +52%
  • Int’l 28.3M +22%, -6200bps seq
    ARR >400M
    Adj Gross Profit 99.4M
    Adj Gross Margin 91% +100bps
    Adj Op Loss -3.2M (vs +1.4M)
    … margin -2.9% (vs +1.8%) -3550bps seq
    Adj EPS -0.10 (vs +0.04)
    Opex 102.6M +60%
    CFFO 20.0M +25%
    $NER 128% -600bps
  • Global 2000 148% !!
    Custs 6443 +30%
  • Global 2000 731
    Empl 1478 +58%
    Cash 992M
    Debt (conv notes) 698M
  • Heavy impact from reduced spend in pandemic, expected through Q2-Q3 (esp Int’l)
  • “Abrupt and significant change in customer buying behavior in March”, and lengthening sales cycles; activity quickly resumed in April at last years levels
  • Moderate churn, particularly in Europe (mostly in single-seats)
  • Strength in APAC esp Japan
  • Estimated 25% of ARR is from heavily impacted verticals; of that 6% are SMB
  • 35% of new lands are from impacted verticals
  • Pausing hiring in the near term
  • Working on payment terms with impacted companies
  • 2/3 of rev was from deferred rev, 15% from contract renewals, rest from new biz (~19%)
  • Had to cancel global sales kickoff and EMEA and US annual user conferences, one-time fees of $6M weighed down opex and turned op income to loss
  • Feature Labs acq closed in Q4, adding 200 empl this Q
  • Named a 2020 Leader in Gartner’s MQ for Data Science and Machine-Learning Platforms
  • New CISO role created…

My stance: Obviously, Alteryx had a performance stumble, especially internationally. Many here, including myself, downsized their heavy AYX position in response. It’s an easy choice to downsize any company hitting headwinds, given how many our companies have tailwinds right now with work-from-home. And it looks like they don’t have much vision into the next two quarters, so guidance is pretty abysmal. But all that said, given that this company had 76% growth and accelerating last Q, it’s clearly a pandemic-caused drop in enterprise spending, not a stumble in execution or a competitor suddenly arising. (And let us remember that under ASC-606, 35-40% of contracts are recognized upfront; the effect of drastic slowdowns in new lands gets amplified.)

I’d rather focus on what Alteryx is doing right. Immediately after guidance projected their woes into the next few quarters, Alteryx has finally given us a glimpse at its “big picture” and where it is taking its software going forward. [And in doing so, is directly addressing my only complaint about its product line – that it is Windows-only subscription-based enterprise software, not cloud-based SaaS.]

But first, lets step back to the recent acquisition of Feature Labs. They were an open-source friendly company spawned from MIT that was dedicated to automating “feature engineering”. Feature engineering is basically using ML/AI to help improve ML/AI workflows. What that means is, they created an ML/AI-driven process (an open-source tool called Featuretools) to perform raw data prep and to pick proper algorithms to apply over that data. It boils down to making the analytical tool do all the work - the user can simply define the problem to solve, point it at the data, and the software can then potentially automate the entire data prep and analysis steps. It’s using ML/AI to drive the user towards the best use of their data and the best ML/AI algorithms to utilize over it.

Think about it this way - it’s using ML/AI to MAKE A BETTER TOOL that lets users do ML/AI. This sounds very very useful for Alteryx, with its heavy push towards “citizen data scientists” doing tasks instead of data scientists. This is all about ease of use and flattening the learning curve in doing complex analytics. So being an open-source focused company, Feature Labs was more of an acqui-hire … and those new employees have now become Alteryx Innovation Labs.

PR on the acquisition:…
CD&AO (Chief Data & Analytics Officer): “Automating the Feature Engineering task will not only speed up the process and increase success but will help the modern-day data worker upskill and become more capable at machine learning. Putting tools like this in the hands of the workforce will ultimately accelerate the digital transformation of the enterprise.”

Then right after earnings, a new platform was announced.

Alteryx is finally showing that they are thinking about the next-generation of their product line, and their new platform looks to be taking steps in several new directions. Their disparate products are now under a more cohesive platform, with a strong focus on team collaboration, ease-of-use (automation), and leveling up skills (training).

Platform Layers:

  • Input layer = get the data into platform
  • Data layer = quality & prep
  • transform
  • enrichment
  • insights
  • Data layer = analytics & decisions
  • predictive ML
  • AI
  • geo-spatial analytics
  • prescriptive analytics
  • code-free UI
  • Output layer = put the results somewhere

Now, go read the SSI blog’s take on this quarter, in particular the opening section “Dissecting Alteryx Product Architecture”. He spotted a few CFO interviews with a lot of additional clues, plus spotted several new job listings that pointed to what is coming in Alteryx’s new platform.…

CFO interview with CML:…
CFO interview with TheStreet:…

CFO: “At some point, I imagine, for some class of customer, we’ll introduce a cloud version. Frankly, in doing so, the concept of Designer and Server may end up blending together. Because we would essentially offer much of what Server offers through that service. But really, the focus is on, how do we help our largest clients massively deploy Designers through a browser rather than a thick client install.”

So Alteryx is starting to think outside of their normal environment (Windows-specific software), and beginning to embrace the potential in the cloud, likely as a new SaaS service to control and manage processes under this APA platform. These moves to automate and upskill and now leverage the cloud all combine to greatly increase the potential market for their solutions (anyone can do it) while easily shows its value (no longer need to employ expensive data scientists).

Then they showed their first cards under this new APA platform, with Analytics Hub as a new centralized core and collaboration tool for their new platform, and Intelligence Suite, an add-on to Designer and the new Hub, starting to automate the data prep and analytical processes.

New products: Analytics Hub & Intelligence Suite:…

Alteryx Analytics Hub

  • new centralized collaboration platform
  • automate, share workflows, communal discovery, security & governance
    […possibly the new core of their next-gen APA platform]
  • Windows-based server software; client is web browser

Alteryx Intelligence Suite

  • new add-on for data discovery in Alteryx Designer & the new Analytics Hub
  • new “Assisted Modeling” automation capabilities, with focus on user training
    [… at least partially arose out of Feature Labs acq]
  • augmented ML - no-code UI to select best analytical model & perform complex statistics, guide data transformations, and compare and manage models (track decisions, validation, & re-trainings)
  • text mining - no-code UI with natural language processing features, to work with un/semi-structured text data (identify categories, discover topics, detect underlying sediment)

Alteryx Multithreaded Processing (AMP) Engine

  • greatly improves speed and capabilities in working with larger datasets and more complex processes

So… we have a company now very clear about the future of its product line and where the next-generation of it will lead. It’s now focused on:

  • collaboration and management of data analytical processes
  • ease-of-use through the automation of data prep and analytical workflows (using ML/AI to do ML/AI!)
  • training users to improve their skill sets around ML/AI processes

And now beyond that, we have several hints as to what is coming next (esp in their job listings):

  • new job listings are a huge sign that they are moving away from just having Windows-based applications (Node-js for microservices, Javascript for browser apps, AWS cloud skills)
  • hints they are looking at a lighter-weight browser-based Designer client
  • … which means the compute workload will be done server-side, which points to cloud-based product (as a SaaS service, or perhaps still self-managed like Alteryx Server is)

They are tying together their product line into a cohesive whole that clearly shows its value ( less-expensive employees can be doing analytical work). Even in a challenging environment, Alteryx continues to focus on lowering the complexity of doing ML/AI, by adding more automation and more training. To me, this all equals more value to its customers, and ultimately considerably more TAM, as the number of users greatly expands. I am retaining a good-sized position in AYX in anticipation of this company resuming its formerly superb execution as enterprise spending resumes, right as it enters this next phase of its product line around a centralized, collaborative, automated platform.

long AYX


Although I did send Muji a direct note of my appreciation to Muji using the “Email this Reply to Author” feature, I think it is well worth a few words of the OT variety to take a moment to publicly recognize the amazing content and contribution that Muji makes to this community on a very frequent basis.

The knowledge, time and commitment it takes to routinely put these ER breakdowns into a digestible and extremely informative format is genius.

Thank you Muji for all you do for the board!