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Alteryx ($AYX ) Investment Thesis
Summary
  • Alteryx is an attractive investment because of it's ability to democratize the ability to make data-driven decisions inside companies.
  • Recent public statements from Alteryx leadership and job postings suggest the company is looking to transition from building on-prem software to providing a cloud SaaS offering.
  • The company has started a free upskill program for customers designed to educate users how to work with data, and they acquired a startup building tools which let users create models without any code.
  • The potential shift to cloud SaaS and investments in no-code tools make the company an even more attractive investment as it could well become the defacto standard way information workers interact with corporate data.**

Background**
  • Alteryx was founded in 1997 and built the first online "data engine" which could deliver demographic based mapping. Their product was used by customers to do demographic segmentation analysis of geographies.
  • Since then, the company has built out a series of products which help customers analyze datasets and identify patterns in their company. Most of their tooling has been used by "data workers", business analysts and non-AI/ML experts.
  • The company's software runs on Windows servers with web clients, and is mostly on-prem today. Some of their products are cloud-first.


Opportunity
  • Cloud SaaS: Recent job postings and statements by the company's leadership suggest they've decided to build a cloud based product offering, or are going to attempt to pivot their existing on-prem product to a cloud offering similar to Microsoft Office 365. Like MongoDB did with Atlas, if successful, I suspect this will have a positive impact on the business.

  • Democratization of AI/ML:
The company's recent acquisition of Feature Labs signals they're interested in helping their customers build more advanced models without them becoming data science experts. Feature Labs was a MIT spawned startup which built software that allowed AI to create models for algorithms with little to no code required.
Secondly, the company also recently announced a free upskill training program for their customers. Their goal is to up-skill all workers into "data workers", train existing "data workers" to become data analysts, and turn data analysts into full blown data scientists.
  • No-Code: By evolving it's current products which require little coding knowledge to use, Alteryx is positioned to create a no-code data analytics platform anyone inside a company can use to generate insights. Instead of waiting for an analyst to build you a Tableau report, newly trained "data workers" can build one themselves.
Risks
  • CSPs might offer their own native solutions to Alteryx's Analytic Process Automation platform. Much of the data companies generate already lands there, and they already have the advanced tooling (things like SageMaker and Big Query) to build upon. Additionally, key influencers like Data Scientists already work in the CSPs consoles day in and day out, so adopting Alteryx might be perceived to come with switching costs.
  • Time to market is another concern I have. Pivoting from an on-prem deployment and sales model to a cloud SaaS model will be a difficult task, and two problems in one. If they're able to get a cloud offering running in short order, upgrading customers to it and training a field on how to sell it will be critical to the company's long term success.
  • Competition from younger companies who already have cloud SaaS offerings is another concern. If Tableau were to invest in building easy to use ETL and model creation tools, they'd be well positioned to compete.

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