Specialist
Former executive at H2O.ai Inc
Agenda
- H2O.ai’s operating environment and competitive positioning vs DataRobot and Dataiku and large public cloud vendors such as AWS (NASDAQ: AMZN), Microsoft (NASDAQ: MSFT) and Google (NASDAQ: GOOGL)
- H2O’s product offerings, differentiation and roadmap
- Threat of competing AI and machine learning offerings and related strategy around market longevity, including stickiness and verticalisation strategy
- Go-to-market strategy, customer segmentation and pricing
- Demand durability in a recessionary environment, industry consolidation and 2023 outlook
Questions
1.
Could you describe H2O.ai as a company, including its key value proposition, product portfolio and the associated use cases for products such as MLOps and machine learning interoperability?
2.
What are your views on H2O’s product roadmap? Are there any product gaps that came up from customers, or anything that customers requested be focused on or where they may have had to look elsewhere because H2O still had a gap in its product coverage at the time? What are your expectations for where the company is best-positioned to focus on developing further products, such as potentially more pre-packaged solutions, data-labelling capabilities or anything else?
3.
Can you outline your views on H2O’s current positioning in the competitive landscape? Where is the company still differentiated in the landscape, if anywhere? How are its offerings becoming more commoditised as the industry tends to move more towards the different services or solutions, as you mentioned?
4.
Could you describe H2O’s positioning and differentiation vs Dataiku and DataRobot? When H2O wins and loses in the market vs these two companies, what are the primary factors driving that outcome?
5.
Could you estimate the win rates across H2O, Dataiku and DataRobot? Is there any kind of material difference in price? Who is undercutting whom, and how?
6.
Could you speak to H2O’s positioning vs the AWS SageMaker product and any other competing products that AWS has in its portfolio? How significant a threat is AWS to H2O, and how do you see this threat playing out over the next 12-24 months?
7.
How sticky are H2O’s products and what are the most common reasons cited by customers related to churn? Given the competitive pressures we’ve discussed, where do you see H2O as being most at risk of being squeezed out of the market?
8.
Can you expand on the churn on the commercial side? When customers were churning, what comments were you getting? Was there a sense of where they tended to go to, whether a competitor or in-house developers? What did those dynamics look like?
9.
Was the majority of churn at the one-year mark? When was that occurring?
10.
Could you roughly estimate what the churn rate was?
11.
How do you see H2O currently positioned vs competitors such as Microsoft or Google? Are there any other market disruption risks that you see the company as immediately exposed to?
12.
How well is H2O penetrating the citizen developer market? How is the company capitalising on the trends it speaks about around democratising AI vs competitors? What kind of customer feedback is it getting in that regard?
13.
Some estimates place the global MLOps TAM at USD 1.1bn in 2022, growing to USD 5.9bn in 2027 at a 41% CAGR. I’ve also seen estimates placing the machine-learning-as-a-service TAM at USD 33bn by 2027, growing at a 38.6% CAGR. How do you think we should go about sizing the TAM for H2O? Do you have an estimate there?
14.
How would you characterise H2O’s growth over the last year? What have been the primary drivers?
15.
How do you assess current end markets or adjacent market opportunities to pursue new logo growth for H2O? You’ve answered this, at least geographically, but is there any other way to segment the market, perhaps by vertical or customer size? Where might be a good growth opportunity for the company?
16.
How would you characterise H2O’s primary customer segments and how they have evolved? Could you estimate the split or concentration across them?
17.
What would be your estimate for the split of revenue growth between new logo and upsell to existing customers? You referenced a 30-40% YoY growth rate. Could you break that down roughly across those two areas of revenue?
18.
What features or products are driving the up- and cross-sell motions, respectively, and how are these opportunities increasing revenue per customer? You mentioned H2O’s product can be very sticky for enterprise accounts, so could you speak to dynamics for the enterprise upsells and cross-sells and then also for commercial?
19.
Let’s say a customer starts out with H2O for its financial function and the company is able to upsell to sales and marketing functions. For customers where you’re seeing that play out effectively, what’s a realistic amount of upsell growth across functions? What exactly do these growth motions look like?
20.
Could you describe the key components of H2O’s partnership ecosystem and channel strategy, and how this impacts growth? Could you also discuss how coopetition is playing out in these partnership dynamics with the large cloud vendors?
21.
Could you comment on sales team efficiency? Does H2O have the right headcount, incentive and quota mix to support further growth? You mentioned the company is having problems with sales attrition. Could you also speak to what those challenges are that it’s having with attracting and retaining employees in the sales function and perhaps in any other function?
22.
What are your thoughts on H2O’s current management team and its strategy? If you had management’s ear, what would you tell it?
23.
Do you view H2O as a potential acquisition target? You suggested that you might. Why is that the case, and what type of company profile do you think most likely represents a potential buyer?
24.
Would you like to share any concluding thoughts on H2O that we haven’t covered? Could you summarise where you think the company is today and where you see it going in the next 2-3-5 years?
