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How our SaaS startup improved net revenue retention by more than 30 points in two quarters
There’s certainly no shortage of SaaS performance metrics leaders focus on. While all SaaS companies do, and must, home in on acquisition metrics, there’s also massive revenue potential within your current customer base.
I think NRR (net revenue retention) is without question the most underrated metric out there. NRR is simply total revenue minus any revenue churn plus any revenue expansion from upgrades, cross-sells or upsells. The greater the NRR, the quicker companies can scale. Simply put: the power of compound math!
One of the biggest and most impactful changes we made was to move new business, retention and account management all under our chief revenue officer.
Over the course of two quarters, Terminus grew its NRR by more than 30 points, opening up incredible new levels of growth opportunities.
To boost our NRR for the better, I focused on three core pillars within our organization.
People
We took a holistic look at the organization and our org structure. One of the biggest and most impactful changes we made was to move new business, retention and account management all under our chief revenue officer. At the end of the day, it just makes a ton of sense to have acquisition and retention living under the same roof — why bother acquiring new customers if you can’t retain them?
We also rolled out a surround-sound team (around three or four people per customer) who onboard and help customers with their account from day one. In total, we have about a quarter of our company dedicated to this 24/7 support and hands-on guidance to ensure we’re enabling customers immediately.
Process
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5 mistakes creators make building new games on Roblox
With Roblox’s massive IPO this month, game developers, brands and investors alike are wondering what factors cause the most successful games on this $47 billion platform to break out from the millions of user-generated passion projects.
According to Roblox’s S-1 filing, nearly 250 developers and creators earned $100,000 or more in Robux in the year through September 2020 out of nearly 1 million creators on the platform.
From Gamefam’s first game two years ago that topped out at only 25 concurrent players to our current portfolio with 2 million to 3 million daily visits, our team learned to develop on Roblox the hard way — by trial and error and by getting better at listening to the Roblox community’s unique gamer culture and vernacular.
Even the most experienced and talented game designers from the mobile F2P business usually fail to understand what features matter to Robloxians.
For those entrepreneurs just starting their journey in Roblox game development, these are the most common mistakes I have seen gaming professionals (myself included) make on Roblox:
1. Using the established free-to-play (F2P) mobile game mechanics
In the F2P mobile games market, it’s all about layered game loops: play a match with the hero, level the hero up using resources from the match, buy more heroes to merge with the first hero, open up new matches with new rules to win more resources, and on and on. These require ongoing player tutorials across hours of play sessions. These mechanics tend to backfire on Roblox because players have no tolerance for anything but immediate, visceral fun.
Accordingly, in mobile F2P, a robust tutorial for new users is oftentimes one of the biggest investments during development. But in our Roblox game Speed Run Simulator (more than 400,000 daily visits), we saw a significant increase in D1 retention when we removed the tutorial entirely and just allowed existing players to guide new players’ understanding of the game. The differences between Roblox and mobile F2P are not only numerous but also sometimes profoundly counterintuitive.
2. Optimizing to make money off of “whales”
Roblox players spend because they’re getting something they want. They won’t be cajoled or coerced into spending like in a mobile game where progress is restricted or slowed without making an in-app purchase (think Candy Crush).
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Dear Sophie: When can I finally come to Silicon Valley?
Here’s another edition of “Dear Sophie,” the advice column that answers immigration-related questions about working at technology companies.
“Your questions are vital to the spread of knowledge that allows people all over the world to rise above borders and pursue their dreams,” says Sophie Alcorn, a Silicon Valley immigration attorney. “Whether you’re in people ops, a founder or seeking a job in Silicon Valley, I would love to answer your questions in my next column.”
Extra Crunch members receive access to weekly “Dear Sophie” columns; use promo code ALCORN to purchase a one- or two-year subscription for 50% off.
Dear Sophie:
I’m a startup founder looking to expand in the U.S. I was originally looking at opening an office in Silicon Valley to be close to software engineers and investors, but then … COVID-19 🙂
A lot has changed over the last year — can I still come?
— Hopeful in Hungary
Dear Hopeful:
How and where work is getting done in Silicon Valley (as well as in much of the world) shifted during the COVID-19 pandemic. That said, yes, it can still make business sense for many to join the Silicon Valley ecosystem.
According to a recent report from PitchBook, Silicon Valley will continue to be the center for VC investment and high-tech talent, even though several large tech companies relocated out of Silicon Valley and implemented full-time work-from-home policies — and many predicted that “the Bay Area tech scene as we know it would be lost, and VC would find a new home.”
Clearly, while the pandemic’s impact on the venture industry will be felt in years to come, VC will continue to be centered in Silicon Valley. In a recent episode of my podcast, I discussed work trends and how to use immigration to support company priorities as well as attract and retain talent in the United States.
The PitchBook report points out that Silicon Valley “has kept a tight hold on fundraising in the U.S., closing on commitments exceeding $151 billion over the past five years, more than the rest of the U.S. ecosystems combined. LPs have continued to funnel capital to area VCs because of the region’s track record of success, which includes 17 of the 22 U.S. companies to ever receive a private valuation of $10 billion or more.”
Image Credits: Joanna Buniak / Sophie Alcorn (opens in a new window)
So while VCs will likely return to the old ways of networking and funding post-pandemic, we’ll see a hybrid of online and in-person meetings because there are so many benefits to in-person networking and exchanging ideas.
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Pre-seed round funding is under scrutiny: Is VC pandemic posturing here to stay?
All successful companies start off as a great idea, scribbled on the back of a cocktail napkin during a late-night meeting of the minds or gleaned from a fleeting inspiration that leaves you with a feeling of “I could do that better.”
For most, that’s as far as entrepreneurship ever goes, because, unfortunately, a great idea can’t raise money, develop a product or disrupt an industry.
It’s only an idea.
Investors’ heightened expectations for monetization potential and a company’s positioning within its competitive landscape are unlikely to lessen in the years to come, even in a post-COVID economy.
New data from the DocSend Startup Index show that for early-stage fundraising, particularly in the pre-seed round, founders need to approach VCs with much more than a great idea to secure funding. Our newest report on the state of pre-seed fundraising shows that investors became laser-focused on sections of the pitch deck that address monetization and business viability — signs that founders need to come to the table with better-defined businesses in order to succeed.
Do not pass go — VCs insist pitch decks meet 3 key criteria
According to the data, overall founder and VC activity took a nosedive in early 2020 once the serious nature of the pandemic became apparent. But as the year progressed and investors adjusted to the new market conditions and remote dealmaking, overall activity quickly surpassed pre-pandemic levels.
Despite this flurry of activity and an unprecedented appetite for new startup pitches, investors made it very clear that strong positioning in three sections of the pitch deck was nonnegotiable.
Image Credits: DocSend(opens in a new window)
- Competitive landscape — When we published our 2019 pre-seed report, the competitive landscape section of pitch decks was firmly in the middle of the pack in terms of time spent reviewing by investors: They averaged around 35 seconds to clearly articulate their own uniqueness and product-market fit. In 2020, the VC time spent on the same section increased by 51% to an average of 53 seconds across both successful and unsuccessful decks (those that did or did not lead to a funding offer).
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How to recruit data scientists without paying top dollar
When it comes to building a data science team, many companies fail at the first step — creating a job posting. These mistakes have been amplified in the age of COVID-19.
The increasing demand for AI and data science experts, driven in part by the pandemic’s economic impact, is showing no sign of abating. Many employers are failing to identify viable job candidates, much less interviewing or hiring them.
What’s the biggest obstacle holding them back? In our experience, it is often a poorly drafted job posting. And with the pandemic completely stopping all in-person recruiting events, hiring success hinges on an effective job rec. Previously tolerable mistakes are now fatal.
At The Data Incubator, a data science training and placement firm, we’ve helped hundreds of companies successfully hire data science teams. Honestly, it pains me to see amazing companies undersell themselves in this area.
When it comes to building a data science team, many companies fail at the first step — creating a job posting.
Companies inevitably gravitate toward the same generic buzzwords, promoting themselves as “cutting edge,” “creative,” “collaborative,” “data driven,” “passionate” or “insightful” (just peruse Indeed for examples of these lackluster postings). Or they delve into industry jargon, which may be lost on candidates who are not familiar with the industry.
To streamline the writing process, we recommend that clients break down their competitive advantage into three buckets: compensation, mission and tech. Only by understanding where their strength lies can they successfully market their job openings.
Compensation
Compensation is an important component of making a position competitive. Managers certainly need to fight to ensure their remuneration range is appropriate for their data science roles. However, budget constraints are difficult to overcome, especially given the ability of tech and finance to pay top dollar for these sought-after skills. How to combat this when you don’t have the same budget? Consider listing compensation in job ads.
If you’re one of (the majority of) employers who cannot afford to compete on salary, this will help job seekers understand what to expect. Neither you, nor a potential candidate, wants to spend hours interviewing just to discover that it would have never worked out because of compensation. Save yourself the time and frustration by listing remuneration upfront.
What if you are one of the few employers able to pay major-league salaries? Congratulations, but don’t throw away your hard-won budget! Companies develop reputations for compensation. Unless you are one of the select firms with a reputation for paying top dollar, you will need to signal that to top talent. Otherwise, strong candidates may assume the remuneration is low and not apply, defeating the purpose of paying a high salary in the first place.
Obviously, listing salaries is controversial and there are plenty of reasons why employers are weary of listing salary ranges. However, a recent survey by SHRM found that 70% of professionals want to hear about salary upfront and Glassdoor.com reports that salary is the No. 1 consideration for 67% of job seekers. With all these benefits, employers should seriously consider being more upfront and transparent about what they are able to pay, if only to save themselves time and frustration.
Mission
In the COVID-19 workplace, employees are finding themselves increasingly isolated. With work from home poised to stay even after the virus has dissipated, the risk of isolation will continue. Companies need to double down on articulating their mission and galvanizing employees around that. This doesn’t just start with employment but the very first step of the hiring process: the job posting. Emphasizing mission in the job posting will attract employees.
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Dear Sophie: What type of visa should we get to fundraise in Silicon Valley?
Here’s another edition of “Dear Sophie,” the advice column that answers immigration-related questions about working at technology companies.
“Your questions are vital to the spread of knowledge that allows people all over the world to rise above borders and pursue their dreams,” says Sophie Alcorn, a Silicon Valley immigration attorney. “Whether you’re in people ops, a founder or seeking a job in Silicon Valley, I would love to answer your questions in my next column.”
Extra Crunch members receive access to weekly “Dear Sophie” columns; use promo code ALCORN to purchase a one- or two-year subscription for 50% off.
Dear Sophie:
A friend and I founded a tech startup last year. Like a lot of other startups, we’re looking for funding. Should we come to Silicon Valley to meet with venture capitalists?
How should we begin that process? What type of visa should we get and how easy is it to get?
—Logical in Lagos
Dear Logical:
Thanks for reaching out to me from the entrepreneurial hotspot of Lagos!
In a recent episode of my podcast, I spoke with Esther Tricoche, director of investments at Kapor Capital, who offered up many words of wisdom to founders. She also mentioned that in many emerging entrepreneurial markets, including Lagos, accelerator funding and Series A funding are relatively easy to find, but pre-seed and seed funding are not.
Getting yourselves and your startup in front of Silicon Valley investors that focus on pre-seed and seed funding will be important to rapidly scale. Esther mentioned that even in U.S. cities, such as Atlanta, that are entrepreneurial hotspots, investment dollars are not as plentiful as they are in Silicon Valley. Moreover, investors outside of Silicon Valley tend to be more risk-averse.
Image Credits: Joanna Buniak / Sophie Alcorn (opens in a new window)
So, yes, you should meet with Silicon Valley investors, but be aware that most U.S. embassies and consulates remain closed to routine visa and green card processing due to the ongoing pandemic. Given that, you can start requesting virtual meetings now; and you will have to wait until the U.S. consulate in Lagos comes back to full capacity to apply for a visa to come to the U.S. I like checking for visa availability through the Waypoint Embassy and Consulate Directory (full disclosure: I am an advisor to Waypoint).
As always, I recommend that you consult an experienced immigration attorney when you’re ready to take the step of actually applying for a visa.
Once U.S. consular offices reopen, if you aren’t eligible for ESTA, you can apply for a B-1 visitor visa for business. With a B-1 visa, you can request an initial stay of up to six months. This is a great status for business meetings such as to talk to prospective investors, negotiate contracts and incorporate a new business. However, you can’t work in the U.S. You must be aware that no hands-on work for pay (or even the chance of future remuneration) by a U.S. entity is allowed.
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A crypto company’s journey to Data 3.0
Data is a gold mine for a company.
If managed well, it provides the clarity and insights that lead to better decision-making at scale, in addition to an important tool to hold everyone accountable.
However, most companies are stuck in Data 1.0, which means they are leveraging data as a manual and reactive service. Some have started moving to Data 2.0, which employs simple automation to improve team productivity. The complexity of crypto data has opened up new opportunities in data, namely to move to the new frontier of Data 3.0, where you can scale value creation through systematic intelligence and automation. This is our journey to Data 3.0.
The complexity of crypto data has opened up new opportunities in data, namely to move to the new frontier of Data 3.0, where you can scale value creation through systematic intelligence and automation.
Coinbase is neither a finance company nor a tech company — it’s a crypto company. This distinction has big implications for how we work with data. As a crypto company, we work with three major types of data (instead of the usual one or two types of data), each of which is complex and varied:
- Blockchain: decentralized and publicly available.
- Product: large and real-time.
- Financial: high-precision and subject to many financial/legal/compliance regulations.
Image Credits: Michael Li/Coinbase
Our focus has been on how we can scale value creation by making this varied data work together, eliminating data silos, solving issues before they start and creating opportunities for Coinbase that wouldn’t exist otherwise.
Having worked at tech companies like LinkedIn and eBay, and also those in the finance sector, including Capital One, I’ve observed firsthand the evolution from Data 1.0 to Data 3.0. In Data 1.0, data is seen as a reactive function providing ad-hoc manual services or firefighting in urgent situations.
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Does your VC have an investment thesis or a hypothesis?
Venture capitalists love to talk investment theses: on Twitter, Medium, Clubhouse, at conferences. And yet, when you take a closer look, theses are often meaningless and/or misleading.
OpenVC is a new, open-source initiative to collect and analyze all publicly available VC theses to help founders more efficiently find the right investors — and vice-versa. For the first time, we are sharing here our initial conclusions. We hope you’ll upload your own thesis to benchmark yourself. We’ve identified six common patterns of how VCs articulate their theses and some best practices in doing so.
Our analysis is based on two complementary datasets:
- 125 theses so far submitted by investors into the OpenVC database.
- 36 theses pulled directly from U.S. VC websites by David Teten and Sam Sabin, co-founder of Hireblue.
Our four primary conclusions:
- Public theses are often inconsistent with how firms actually deploy capital.
- VC theses are often so vague that they’re meaningless.
- We found seven categories of VC theses, plus an eighth: the non-thesis.
- Investment theses are just hypotheses; the portfolio shows how accurate the hypothesis was.
For the sake of simplicity, we will consider “investment thesis” and “investment criteria” as equivalent terms moving forward, although we argue that the thesis leads to the investment criteria. We summarize how they interrelate in the table below.
1. Public theses are often inconsistent with how firms actually deploy capital
A typical VC thesis: “We invest in tech startups in Europe at an early stage.” However, our experience shows that in many cases “Europe” means a handful of countries, for instance, France, U.K. and Germany; and “tech” means B2B SaaS/fintech or consumer apps.
Thirty-four VC firms in OpenVC call themselves “early stage.” Yet 30% of those don’t actually invest in pre-revenue startups. The phrase is quite ambiguous; we suggest quantifying check size so that your investment preference is clearer.
Almost every VC says that they invest in the “best” founders. However, according to PitchBook Data, since the beginning of 2016, companies with women founders have received only 4.4% of venture capital deals. Those companies have garnered only about 2% of all capital invested. This is despite the fact that the data show you’re better off investing in women.
This lack of transparency results in confused founders who chase the wrong investors. In turn, investors are overwhelmed with poorly qualified opportunities.
2. VC theses are often so vague that they’re meaningless
Christoph Janz from Point Nine Capital wrote on Twitter:
The modal VC thesis is: “We invest in great teams addressing large markets with disruptive solutions.” Who invests in lousy teams addressing tiny markets with outdated solutions? Theses also tend to use the same words across many firms, e.g., “daring” and “bold.”
In particular, in our second dataset, we found a disproportionate number of theses focused on “technical” companies (vaguely defined) and focused on companies attacking “problems of the future rather than the present,” in various permutations of that language.
| Top Visible Heuristics (in dataset of 36 U.S. VCs) | Occurrences |
| “Technical” companies (i.e., any mention of a focus on tech companies) | 26 |
| Local affinity or bias | 10 |
| Attack problems of the future rather than the present (or some variant) | 9 |
| Technical founders | 7 |
Why are the investment criteria so imprecise on the VC websites? We have three theories, in descending order of importance:
- Option value. Investors don’t want to be too restrictive and miss out on a deal. However, we’d argue that for most smaller managers who are not brand names, it’s better to be highly identified in your niche than being a generalist. Most limited partners we speak with agree.
- A desire to look “sexy” and politically correct as opposed to being honest. This is probably a major reason. For example, saying publicly, “We invest mostly in white/Asian men who went to Stanford like us” accurately describes numerous VCs, but doesn’t sound very politically correct.
- VCs are afraid to give out their secret sauce. We think this doesn’t make much sense; you can share your criteria without telling the whole logic behind them. Many top-tier VCs share detailed public theses.
3. We found seven categories of VC theses, plus an eighth: the non-thesis
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Dear Sophie: What are the pros and cons of the H-1B, O-1A and EB-1A?
Here’s another edition of “Dear Sophie,” the advice column that answers immigration-related questions about working at technology companies.
“Your questions are vital to the spread of knowledge that allows people all over the world to rise above borders and pursue their dreams,” says Sophie Alcorn, a Silicon Valley immigration attorney. “Whether you’re in people ops, a founder or seeking a job in Silicon Valley, I would love to answer your questions in my next column.”
Extra Crunch members receive access to weekly “Dear Sophie” columns; use promo code ALCORN to purchase a one- or two-year subscription for 50% off.
Dear Sophie:
I’m an entrepreneur who wants to expand my startup to the U.S. What are the benefits and drawbacks of various types of visas and green cards?
The ones I’ve heard the most about are the H-1B, O-1 and EB-1A.
— Intelligent in India
Dear Intelligent:
I’m happy to hear you’re considering the O-1A extraordinary ability visa and the EB-1A extraordinary green card! Individuals often assume they need to have won a Nobel Prize or some other major award or be well known in their field to qualify for either the O-1A or the EB-1A — and that’s simply not the case.
Image Credits: Joanna Buniak / Sophie Alcorn (opens in a new window)
“Particularly for folks from Asia, being a self-promoter is massively looked down upon. Humility is important,” says Navroop Sahdev, a pioneering economist and blockchain expert I recently interviewed for my podcast. Sahdev is founder and CEO of The Digital Economist, a Connection Science Fellow at Massachusetts Institute of Technology and a partner at NextGen Venture Partners.
She spoke with me about her immigration journey to the United States, which included two H-1B visas, an O-1A visa and an EB-1A green card.
Here are the pros and cons of each visa and green card that you listed.
H-1B visa
Overall, the requirements for the H-1B specialty occupation visa are not as stringent as those for the O-1A visa and the EB-1A green card, which is why many employers sponsor international students who are on an F-1 visa and recently graduated or on OPT (Optional Practical Training) or STEM OPT for an H-1B.
Because demand for the H-1B far exceeds the annual supply of 85,000, U.S. Citizenship and Immigration Services (USCIS) holds a random lottery to determine who can apply for an H-1B. (That random lottery is slated to switch to a wage-based selection process next year.)
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Deep Science: AI adventures in arts and letters
There’s more AI news out there than anyone can possibly keep up with. But you can stay tolerably up to date on the most interesting developments with this column, which collects AI and machine learning advancements from around the world and explains why they might be important to tech, startups or civilization.
To begin on a lighthearted note: The ways researchers find to apply machine learning to the arts are always interesting — though not always practical. A team from the University of Washington wanted to see if a computer vision system could learn to tell what is being played on a piano just from an overhead view of the keys and the player’s hands.
Audeo, the system trained by Eli Shlizerman, Kun Su and Xiulong Liu, watches video of piano playing and first extracts a piano-roll-like simple sequence of key presses. Then it adds expression in the form of length and strength of the presses, and lastly polishes it up for input into a MIDI synthesizer for output. The results are a little loose but definitely recognizable.
Image Credits: Shlizerman, et. al
“To create music that sounds like it could be played in a musical performance was previously believed to be impossible,” said Shlizerman. “An algorithm needs to figure out the cues, or ‘features,’ in the video frames that are related to generating music, and it needs to ‘imagine’ the sound that’s happening in between the video frames. It requires a system that is both precise and imaginative. The fact that we achieved music that sounded pretty good was a surprise.”
Another from the field of arts and letters is this extremely fascinating research into computational unfolding of ancient letters too delicate to handle. The MIT team was looking at “locked” letters from the 17th century that are so intricately folded and sealed that to remove the letter and flatten it might permanently damage them. Their approach was to X-ray the letters and set a new, advanced algorithm to work deciphering the resulting imagery.
Diagram showing X-ray views of a letter and how it is analyzed to virtually unfold it. Image Credits: MIT
“The algorithm ends up doing an impressive job at separating the layers of paper, despite their extreme thinness and tiny gaps between them, sometimes less than the resolution of the scan,” MIT’s Erik Demaine said. “We weren’t sure it would be possible.” The work may be applicable to many kinds of documents that are difficult for simple X-ray techniques to unravel. It’s a bit of a stretch to categorize this as “machine learning,” but it was too interesting not to include. Read the full paper at Nature Communications.
Image Credits: Asensio, et. al
You arrive at a charge point for your electric car and find it to be out of service. You might even leave a bad review online. In fact, thousands of such reviews exist and constitute a potentially very useful map for municipalities looking to expand electric vehicle infrastructure.
Georgia Tech’s Omar Asensio trained a natural language processing model on such reviews and it soon became an expert at parsing them by the thousands and squeezing out insights like where outages were common, comparative cost and other factors.
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