Saturday, September 11, 2021

Palantir: Operating profitability and expense trends (Its Saul Goodman)

One of my go to metrics to look at how well a company is operating, is to look as cash flow generated from operations. When a company executes well, the cash flow from operations increases and the 'On balance cash flow from operations' (OBCFO) will increase from quarter to quarter. When this metric increases  quarter over quarter, or year or year, or quarter over quarter last year, these are positive signs of increase in operational cash. The reason, I really like cash flow from operations, is that this is a measure of recurring revenue which is inherent to the day to day functions of the company. The other cash flows are cash flow from investing activities (these include purchases of physical assets, securities, or the sale of securities or assets) and cash flow from financial activities (activities involving debt, equity, and dividends). These latter 2 cash flows are indicators of investment savvy and financial gymnastics of a company and no so much a reflection of how the company operates. The cash generated from operations can be reinvested into the company for growth in term of new tech, acquisitions, product development etc. With that brief introduction, lets look at Palantir and its cash flow for the past 8 quarters.

Cash Flow from operations compared to Stock price.

Figure 1: On balance cash flow from operations compared to stock price for Palantir

It took me a while to change my mindset, that a stock price is not the company and a company cannot be evaluated on basis of stock price alone. A stock price is a marker of the sentiment of what the majority thinks the company is valued. In any case, let compare the OBCFO to price of Palantir's stock. This is shown in figure 1. The price, is the closing price on the week, the results of earnings came out.

One of the immediate things to notice is that the OBCFO has increased over the last quarters and it shows a healthy uptrend. Another important feature in this figure, is what I call “fundamental bullish divergence” (green arrow), this happens when the stock price is trading lower and the OBCFO is actually higher, this usually, a strong clue for me to add to shares or enter a new position (provided I believe in the leadership and company management). This event happened after the March 2021 earnings, where the price was trending lower than its recent high.

Cash Flow from operations compared to reported sales and marketing expense.


Figure 2: On balance cash flow from operations versus Sales and Marketing expense for Palantir

This however is only part of the equation, if for some reason the cash flow is not increasing, like it did in quarters ending 6/30/2020 to 12/31/2020, then we absolutely must look for reasons why. One place which may explain why cash flow from operations was low, is if the company used some of that cash to either grow the operations (either by increasing sales and marketing) or by focusing on research and development. This is shown in Figure 2, as on balance cash flow from operations is falling (blue line) from periods 6/30/2020 to 12/31/2020, the reported sales and marketing expense is rising. So this fall in cash flow was a “good thing” (grey shape - dotted line)

Cash Flow from operations compared to reported Research and development expense.

Figure 3: On balance cash flow from operations compared to Research and development expense for Palantir

I also make it a point to look at R&D expense, after all, if a company is to grow, it needs to continue to innovate and apply those discoveries to further its mission. This is shown in Figure 3, as on balance cash flow from operations is falling (blue line) from periods 6/30/2020 to 12/31/2020, the reported expense for research and development is rising. So this fall in cash flow was a “good thing” (grey shape - dotted line)

 Palantir, in this case has executed flawlessly for the past few quarters and its all good man (In case you did not get the humor reference in title) and this give me good confidence that the company will continue to grow and as consequence of this, the stock will also continue to grow.

 Disclaimer: I am long term investor and own shares of Palantir. The data were obtained from public sources.

Thursday, September 9, 2021

ZoomInfo (ZI) a history of opportune acquisitions

 Today, I wish to provide a little more color on one of my bigger positions ZoomInfo. ZI is US subscription-based software as a service (SaaS) company that sells access to its database of information about business people and companies to sales, marketing and recruiting professionals. Their tag line is simple

ZoomInfo is a leading go-to-market intelligence platform for sales and marketing teams.

Some Facts about ZI which made me invest in it: it has shows a 48% revenue growth over 3 years, 54% revenue growth (TTM vs prior TTM), gross profit margin 87%. Midcap at 24B. Its EPS growth was 50% and has a 97% institutional ownership. It is also part of my 'Hot watch list stocks' which is release every week on Twitter (see image for handle). These are the stocks that are potentially excellent picks long term and doing well in regards revenue and cash flows.  

I am of the firm opinion, that a business that generates positive and increasing operating cash flow is one which has the most opportunities to grow under able leadership. ZoomInfo checks all of those qualities hence is part of my portfolio. 

The stock has done well since I acquired it, and I anticipate it will continue to do well in future. The reason for this is the leadership at ZoomInfo has demonstrated acumen for acquiring companies that add to its value and provide a tremendous growth spurt. They are also exceptionally adept at making the right partnerships to further their business. That being said, here is a timeline chart of ZoomInfo acquisitions. On a side note, DiscoverOrg merged with ZoomInfo to be the company it is today, 2 of the acquisitions early on are this DiscoverOrg/ZI mash but that should not change our assessment of the company.

ZoomInfo: A timeline of acquisitions (blank) and partnerships (orange)

In order to further understand how these acquisitions added to the growth of the company, I have summarize this information in the table below (* represents partnerships).


When acquired

Why was it acquired?

How (did it help?)



pioneer of sales intelligence for the technology industry

Combine iProfile’s comprehensive global professional contact and sales intelligence database with DiscoverOrg’s proprietary sales intelligence and analytics



delivering the most accurate intelligence that sales and marketing teams use

Solidify company’s position as the world’s leading B2B sales and marketing data provider, to accelerate pipeline and revenue growth

Y Labs



To expand its center for product development and security operations.



world-wide leader in technographic data: uses machine learning and proprietary methodologies to capture the technologies

be able to supplement its company and contact information with real-time alerts that enable sales and marketing professionals to sell based on customer technology decisions.



a leading provider of email verification and list cleansing services

enhanced accuracy of in-platform emails, seamlessly verify all email data in their internal marketing and sales systems



Komiko’s AI-powered CRM automation, playbooks, and predictive analytics

to accelerate the sales pipeline with valuable analytics,



a leading provider of artificial intelligence-powered buyer intent data

Streaming Intent, an innovative solution that identifies companies with above-average search volume on business-to-business (B2B) topics within minutes of their web activity



a leading artificial intelligence-powered, business-to-business (B2B) data solutions provider.

EverString gives ZoomInfo a comprehensive business data graph, providing the foundation needed for enterprises to identify their total universe of customers and prospects, define their ideal profiles, leverage granular keywords and attributes to predict success, and focus their go-to-market motions.



a leading B2B demand generation company serving customers in India and globally.

partnership provides companies in India, as well as other countries in Asia, with direct and unprecedented access to ZoomInfo’s leading sales intelligence platform.



business-to-business (B2B) customer data platform provider,

partnership gives sales and marketing teams an unprecedented combination of B2B intelligence with enterprise-level data management and activation tools. Customers of Leadspace can now get access – via new connectors – to ZoomInfo’s leading B2B intelligence, so they can go to market more efficiently and effectively.



the Data Cloud company

Snowflake Data Marketplace to centralize and streamline data delivery. Customers can now use Snowflake’s platform to integrate ZoomInfo’s industry-leading company and business contact data into their technology stacks—with no additional integration or extract transform load required—and generate insights at scale.



a powerful conversational marketing platform that identifies website visitors in real time, uses artificial intelligence (A.I.) and advanced lead routing rules

Initiate real-time conversations, and increases conversions

Lean Data*


a leader in lead-to-account matching and routing

delivers a seamless, elegant product experience for their joint customers. provides customers with the ability to deliver leads to the right sales representatives with greater accuracy and speed, driving revenue growth.



a leader in Conversation Intelligence

Enable Insight-Driven Targeting, Coaching, and Decision-Making for Go-to-Market Teams



an industry leader in data orchestration and revenue operations automation

Enable companies to streamline and execute data-driven go-to-market motions at scale based on high-quality, actionable data.

Thus every single partnership or acquisition ZoomInfo management has made, has been synergistic to the business and has propelled growth.

Disclaimer: All the information has been collected from public sources.  I own shares of ZoomInfo.

Wednesday, September 8, 2021

There is so much more to Pinterest (PINS) than the eye can see

Millions of people use and interact with Pinterest. This interaction generates data that Pinterest can use in turn to make search better. The process is a positive feedback loop. Better data makes for better personalization, more relevance. 

To better understand the innovative ideas and projects at Pinterest, I reviewed the information at Pinterest Labs. I am a 'visual' person and like to see information mapped out as a figure or a graph, as is with much of my company assessments, I generated a unsupervised network map of projects Pinterest is involved in.

The 'engine under the hood' is involved in user modeling and recommendations this is done mostly through Machine learning algorithms to understand the users behavior as well as product/image relevance. 

Pinterest: A visual discovery, engagement, shopping and advertisement engine (click to zoom)

Pinterest is researching visual discovery. Pinterest Lens allows users to get recommendations from real world objects. The company has some of the largest datasets of visual objects. The focus is now to improve recognition and visual search. It is also looking at understanding video and moving images. Additional innovations in real world visual discovery, take search, engagement, advertisement and shopping to the next level.

With the troves of data that Pinterest generates, they are able to take a systematic approach to explore trends and track changes. This allows pinterest to be ahead of the curve so to speak in knowing what trends and tastes are evolving. This is crucial information for advertisers. Pinterest is in effect a recommendation service. The massive troves of data leads it be one of largest-scale recommender systems. A very important statement caught my eye,

"Right recommendation to the right person at the right moment"
Beside the operational side of the platform, the business side will also see significant growth. The platform is visual discovery, shopping engagement, social, search, marketing platform all in one package. Pinterest with its advanced data science, visual search analysis and a 300 billion and growing repository of human curated ideas will be able to do it! 

Disclaimer: I am an investor in Pinterest (PINS). The data were collected from publicly available sources online and from company websites.


Uipath (PATH), a landscape of integrated technology solutions

Today we will look at Uipath in context of its integrations with other tech services. This type of visualization would be similar to ones I have done in the past for Palantir (Palantir - contract landscape), Teladoc (Business network) and even one on leadership (Crowdstrike governance). Before we being I would recommend looking to a couple minutes read into the background of network visualization, if you have not done so already. Such type of analysis allows for deep study of the companies that you are interested in investing. With that short introduction lets begin.

UiPath is an interesting company, no doubt. It is a leader in Robotic Process Automation (RPA) where repetitive tasks can be identified, and software codes can be used to automate those tasks. This is immensely helpful as one can imagine. I recall the days as a graduate student spending countless hours doing data extraction for analysis. RPA would have cut short much of that time so that more time could be focused on analysis and interpretation. This is one example of what RPA can do. So, to look at what else is RPA and specifically Uipath involved in, I looked at its integrations with other tech services. The company calls these "Technology Alliance Partners" whose task is to 'automate more within your existing technology stack'. Furthermore, UiPath natively integrates with the enterprise applications that are commonly used to extend their impact. This would an excellent clue to what other areas RPA would be useful for.

Based on the information collected from Uipath website manually (how I wish I had Uipath RPA to extract this data, they have the capacity in case you are wondering), I generated a network model of all of its technical integrations as of September 8, 2021. The graph is provided below.

UiPath Integrations with Enterprise Applications (Click on image to zoom)

The Nodes in yellow are companies that are part of the integration. The larger nodes (red through blue, in essence all non-yellow nodes) are the technologies that Uipath is integrated with these companies. 

1. There is a surprising degree of versatility seen in these integrations.Uipath shows integrations with Artificial intelligence (AI)/ Machine learning (ML) companies, Dynamic Case Management (DCM)/Business Process Management (BPM) companies [Dynamic Case Management (DCM) as name suggests is dynamic, adaptive process improvement for unstructured processes. While Business Process Management (BPM), is automating processes to automate repeatable task, reducing error and human intervention], document and text understanding, natural language processing, chatbots and digital assistants. The largest share of integration is with the infrastructure, cloud and Software as a service (SaaS) technologies. Smaller forays in other areas include analytics, test automation, Banking, security and Enterprise content management (ECM)

2. The Cloud - SaaS - Infrastructure cluster shows 2 distinct sub-clusters, those that are on Platform side (Amazon web services, Google cloud, Microsoft etc) and those that are on the architecture side (Oracle, Citrix etc).

3. Smaller group of companies in areas such as analytics, banking, security etc.

I anticipate that the number of companies that integrate with the larger services  (e.g. AI/ML, Cloud, SaaS) will grow. I would however, also like to see smaller node services get more take (analytics, security and compliance) which would demonstrate the true versatility of the Uipath platform. The company has promise, and is a clear leader but it is working in a crowded space. As with some of the other companies at this time I will wait at least 3 quarters worth of earnings (so I can get a sense of revenue, growth, cash flow) to consider investing. 

Disclaimer: The above analysis is part of my personal deep dive into investing in specific companies. This is not financial advise to buy or sell securities. All of the information is publicly available on company website. I do not hold shares of Uipath (PATH) at time of this article

Monday, September 6, 2021

Upstart (UPST) and its AI lending, is it working? a real world impact

DISCLAIMER: I am not a financial person. Analysis below is based on my understanding of the complex financial jargon and terms. If you find any discrepancies and wish to connect, find me on twitter (handle in figure). All data is collected from publicly available sources. I own shares of Upstart Holdings Inc.

INTRODUCTION: Upstart is an AI lending platform that partners with banks and credit unions to provide consumer loans. I wrote an article few days ago outlining the financial ecosystem that Upstart has created. It uses a proprietary  artificial intelligence algorithm to predict creditworthiness. I analyzed data from Kroll Bond Rating Agency (KBRA) regarding Upstart to see if it was indeed doing what it was supposed to do. Following is the charting and analysis of that data.


Consumer loan Asset backed securities (ABS): financial securities backed by income-generating assets.

Weighted average interest rate: The interest rate is the amount a lender charges a borrower. Weighted average is for the loans in the collateral pool for that cut-off period.

Weighted average FICO score: Weighted average FICO (Fair Isaac Corporation) score for borrowers for the loans in the collateral pool. This is a measure of creditworthiness. Higher FICO score means borrower will have a lower interest rate on loan and vice-versa.

Weighted average original term: Weighted average of loan term of the loans in the collateral pool. Longer term loans are for those who want to borrow large amounts or want to have a lower monthly payment. 

Weighted average seasoning: Seasoned issues tend to be associated with less risk and are more favorable. An entity dealing with loans would like duration for seasoning to shorten making the loans more favorable.



A Temporal analysis of Upstart lending parameters (click on image to zoom)


Every successive assessment by KBRA shows that consumer loan ABS transactions have increased from 65 million to 485 million, which is a 646% increase from 2020-2 to 2021-3 time period (Panel A, top left). This indicates Upstart has been exceptionally successful in securing increasing number of loan transactions.

 Borrowers in Upstart have an increase in weighted average interest rate panel B (top middle) Most lenders look at borrower risk—how likely you are to pay back the loan. Upstart is facilitating lending to borrowers at higher interest rates, indicating these are borrowers who would not otherwise qualify for a loan. Potential borrowers with higher credit scores tend to get more favorable (lower) interest rates, so the fact that this is trended higher but stabilized at around 18%. Based on data from Experian average interest rate on a personal loan is 9.41%, according to Experian data from Q2 2019. Depending on the lender and the borrower's credit score and financial history, personal loan interest rates can range from 6% to 36%. Thus the rising interest rates offered are a glimpse into Upstarts algorithms approving additional borrowers.

Upstart had  a reduction in the FICO scores of the borrowers over time (Panel C, top right) which in my opinion, speaks to the effectiveness of the AI algorithms that Upstart uses to offer loans. I expect this to keep dropping until it reaches a lower limit, as the AI keeps getting better and better at assessing creditworthiness. For those banks that would use FICO, these borrowers with lower scores would either not qualify at all or would qualify at very high rates. However, Upstart would be able to tap into a huge pool of potential borrowers who have low FICO scores (thus penalized by a non-upstart lending entity) since its AI would identify credit worthy borrowers in this pool. Also note that a score 670 and up includes 'Good', 'Very Good' and 'Exceptional' categories (captures 66% of American Market), while a score of 580 and up includes 'Fair' along with other groups and captures 84% market. That Upstart is able to identify worthy borrowers for loans with 'Fair' score is a credit to its AI based determination of creditworthiness. Whether or not it will dip to 580 or below is not know, but what is clear is that its algorithms capture a larger market share than conventional lending.

The weighted average original term (Panel D, lower left), which is the loan term dropped in 2021-1 assessment likely a reflection of COVID-19 effect on borrowing. However, this has quickly bounced back and gone up to 55 months from a starting of 53 months. Longer term loans are for those who want to have a lower monthly payment. This anticipate this will also rise until a limit and would be a reflection of those borrowers who qualified, could pay but prefer lower monthly payments. The weighted average seasoning of the collateral pool has also dropped to 4 months from a starting value of 8 months. Thus the time to 'season' has reduced. An entity dealing with loans would like duration for seasoning to shorten making the loans more favorable. 

Thus based on the KBRA data, Upstart is making more loans to an increasingly FICO score marginalized population. Which means, its AI algorithm is working as planned and is actually improving every successive iteration. This in my opinion is a better solution to solve a huge problem for human beings making UPST a disruptor stock.

The Topology of Crowdstrike (CRWD) Governance - what can we learn from it?

As investors in companies, we pay significant amount of attention to the fundamental metrics of a company. Revenue, cash flow, products sold, growth, sales, debt etc are all important parameters to keep track of when assessing the health of a company. Others may seek value in investing, or may track price action and base their trading decisions on those rules. However, to have a comprehensive understanding of a company is, it is vital to know who leaders and executives are. Unfortunately, many analysts do not focus on the elements of human capital to same extent as other assessment of a company or stock. 

Corporate governance for most part has 2 groups: Executive team (company leaders) and Board of Directors.  The Executive team is responsible for day-to-day decisions, keeping the company going, and business running. Board of directors have comprehensive responsibility for the activities of the company. A corporate board is responsible high level decisions, oversight, big picture, vision and change of course for a company when needed. They have a duty to the shareholders and are tasked to keep company efficient. Thus company executives can be seen a inward looking, looking to the workings of the company and focusing on the critical moving parts that make it work, while Board of Directors is outward looking.

Before we delve any deeper I would encourage you to spend a few minutes reading up about network analysis and how it can assist in improving understanding of underlying data.

We can apply principles of network graph visualization to study the work experience of corporate governance. 


Figure 1: Crowdstrike Executive Leadership (Click on image to zoom)

Figure 1. shows a network representation of Crowdstrike executive team (green nodes), their roles in the organization (violet nodes) and past work experience (red nodes) or present obligations to other companies (like being a board of director - yellow node). The graphs has a concentric layout which is typical for a company structure (expected) but also shows some interesting insights. One cluster of executives (McAfee-Intel cluster, blue shape) includes executives that have help past positions at McAfee. The president of global sales worked at Intel security (also owned by Intel). A second cluster that emerges is the US Federal government cluster (green shape) comprises of the President (S. Henry) and Chief information Security Officer (J. Dixon). Both have a background working in cybersecurity in context of federal government. Sharing similar backgrounds, and translating past experiences and leveraging those relationships can be useful for company growth.

Let us next look at the specific skill sets that each executive member brings to the company. This will be crucial for company growth, and its vision to be a leader in the markets.

McAfee-Intel Cluster: 

George Kurtz (CEO and co-founder) is a security expert, an entrepreneur, and public speaker. His style is entrepreneurial innovation. Mike Carpenter's  (President of global sales and field operations)  skill set is building global, high-growth sales organizations spanning both the private and public sectors. His style is strategic planning, out-of-the-box thinking, risk-taking, and teamwork to the sales process. Mike Sentonas (Chief Technology Officer) has vast experience in cybersecurity, public speaking. J.C. Herrera (Chief Human Resources Officer) has deep expertise in building effective global HR organizations and systems to focuses on achieving strong and consistent business results. 

Federal US government cluster

Shawn Henry's (President) unique skill set is the experience he gained overseeing half of all Federal Bureau of Investigations (FBI) investigative operations, (criminal and cyber investigations) worldwide, international operations, and the FBI’s critical incident response to major investigations and disasters. He style is proactive, leading investigations and mitigating targeted attacks on corporate and government networks. J. Dixon's (Chief Information Security Officer) skill set is industry expertise on risk mitigation, incident response and proactive security. Mr. Henry and Mr. Dixon having worked in leadership roles in federal government bring a unique perspective to the company. This resonates with both perception of cybersecurity threats and implementation of mitigation strategies.

Other members

Colin Black (Chief operating officer) oversees building and scaling CrowdStrike’s internal infrastructure. This is to support a growing workforce and an expanding global operations footprint. Amol Kulkarni's (Chief Product and Engg. Officer) ability is to execute and deliver the product, platform vision and roadmap. Burt Podbere (Chief Financial Officer, CFO) has extensive knowledge of domestic and international finance, SaaS businesses, and international operations. His style is strategic planning, financial management and global expansion. Marianne Budnik (Chief Marketing Officer, CMO) handles  the company’s global marketing strategy. Ms. Budnik brings deep experience working with cybersecurity companies, high-growth technology startups, and Fortune 500 companies. Adam Meyers (Senior Vice President of Intelligence) skill is combining human intelligence and intelligence derived from technology to transform cybersecurity. He brings unprecedented insights into the activities of cyber threat actors, providing strategic and technical guidance.  Cathleen Anderson's  (General Counsel) expertise is wide-ranging legal experience to support companies growth.


Figure 2: Board of Directors (Click on image to zoom)

Figure 2. shows a network representation of Crowdstrike Board of Directors. As mentioned previously the responsibility of the board is high level decisions, oversight, big picture, vision and change of course for a company when needed. One cluster of board members (McAfee cluster) comprising of Mr. Kurtz, Mr. Sexton, Mr. Watzinger, and Mr. O’Leary. As with the executive team, sharing similar backgrounds, and translating past experiences and leveraging those relationships can be useful for company growth. This also applies to the outward looking big picture stuff that the board is responsible for. A smaller (could be coincidental but not sure) grouping (Green shape) is Ms. Schumacher and Ms. Austin both have connections to Abbvie and Abbot Laboratories. Ms. Austin has been or is on the board of directors for several notable companies. Ms. Schumacher has deep understanding and insight into complex corporate transactions, challenges associated with complex, highly regulated industry and corporate governance. Board members with present affiliations are noted as yellow nodes and notable ones include Mr. Sexton being on Board of Pager Duty Inc and Snap Route. Mr. Davis is the Director of several companies in SaaS space, cloud security, cyber security (yellow shape). Mr Gandhi is a partner at Accel a VC firm notable for funding several successful tech and other companies. Mr. Sullivan has more than 30-years of technology and business leadership experience as past CEO of Splunk Inc.  

Closing comments: At the conclusion of this analysis I feel confident in the leadership at Crowdstrike to deliver on the company values, mission and the expertise they all bring to the company. I own shares of Crowdstrike (CRWD) and am invested in their long term success. This information was collected from publicly available information and from Crowdstrike's website.

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