Worth listening to as my notes are sparse and don’t capture how incredibly well AYX appears to know their market. Any errors are mine, apologies for grammar and all that.
Community.alteryx.com - to see use cases
Why revenue accelerating? Good execution, tailwinds of IPO due to recognition. Tailwind from digital transformation, how to turn data into asset.
Some think of alteryx’s product as expensive, ayx thinks it is cheap compared to data scientists, SAS.
Macro IT spending is it sustainable? AYX sees no change in spending , in other downturns ayx’s performance has actually improved. Don’t see any change if macro dislocation. Right now focused on growth but if conditions change can easily pivot to profitability.
Verticalize sales force, public sector, healthcare, ? mostly tuned out on this one, did say sales cycle is lengthening due to shut down.
Are you engaging with partners any differently? 20% of revenue from resellers, msft, tableau, click. analytic consulting firms are increasing which is driving growth at ayx.
International growth? Global phenomenon for data analytics, impressive growth. Same playbook, land and expand. Going public increased their visibility.
Competitive landscape? Prep from tableau? Ayx doesn’t see prep very often, called it, “lightweight” Ayx is focused on the hard problems. 100 millions of rows of data, multiple databases, trillions of points of data. Prep focuses on combining two spreadsheets together. Very different market.
Cloud, data switching to the cloud and residing there? Data gravity is beginning to shift to the cloud but is nowhere near where most people thought it would be. Again mentioned that hadoop is dying. They haven’t seen a massive move to the cloud for complex analytics they are driving today. Most ayx is on prem. Ayx can be installed in azure or aws. But most still on prem.
Data analytics competitive market - a whole bunch of tools that do one thing real one on one database, i.e azure ML, sagemaker. Analytics world will never be on one database, data will be disperate forever which AYX covers. Need a full feature capability to bring in data . 37% of analysts time is spent finding data. Ayx makes all that easy. Machine learning needs AYX to feed it data.
Market opportunity - expanding SKUs to cover end to end market. This got a little into the weeds of their products, I glazed over a bit. My takeaway was they are developing new skus to make their platform more and more useful and time efficient.
See a lower price offering? Never had an issue with price. Analyst typically spends 26 hours a week copy and pasting in excel. Data science background thinks that AYX is inexpensive compares to SAS. Looks expensive compared to exel. Currently low single digits penetration, once they get to 20-30% they might need to introduce a lower priced SKU. A long way out from lowering price, more inclined to raise price.
Convertible bond offering, 400 million in cash. Uses, M&A? Did convertible for general purposes. Very fragmented market in data science and analytics, most companies in the space won’t be here in 2 years. Always looking for unique IP that can fit into platform. Or looking for customers. Careful about M&A, have enough capital to do something meaningful if opportunity presents itself.