The weekly top 10 for B2B tech operators · Every Friday
Expanding on post #4 from last week is a revisit of NDR and its cousin, GDR. Modern SaaS is all about acquisition, retention, and expansion; it's a bowtie, not a funnel. Crunchbase has done the work to calculate what good NDR benchmarks should look like.
Now expanding on #1's bowtie above - I referenced Gross vs. Net Retention Rates a couple of weeks back, but Chartmogul also has retention trends benchmarks for 2023, which is essential because Companies with best-in-class retention grow at least 1.5-3x faster than their peers - but in this market, it's now more challenging than ever. BTW: According to a report from SaaS Capital, yearly contracts don't actually increase NRR.
Crack open up your tech dictionaries to add in this term. Reverse Trials are a play on freemium, where new users start with a time-limited trial of all your paid features. At the end of the trial, they can either buy or downgrade to a fully free tier - this article also explains how Airtable does this well. The benefit here is that, emotionally, the users experience loss aversion, where the pain of losing something is twice as powerful of a motivator as the pleasure of gaining.
Want to compare how your Pitch Deck compares to others? Here is an absolute MONSTER resource link for you (and your pitch team). Pitches from AirBnB, Uber, Shopify, lesser-known startups, and famous flameouts (such as Fyre) can be found on Billion-Dollar Pitch Decks and Pitch Deck Hunt. A cool approach on OpenDeck that lets you search by Category/funding year. If you want to see a breakdown/analysis of pitch decks, then look at Alexander Jarvis - he has over 500 decks broken down by the good and the bad things people do. Added Bonus here - this tweet from earlier last year is liley now redundant thanks to OpenAI (of ChatGPT fame)- Katelyn Gleason observed that no real generation-defining startup has been founded since 2014. But we now have one outlier - OpenAI (2015)
In startup land, there is a long tail of BS founders need to navigate, and in a surprise to no one, much of that is legal. So check this huuuuuge article from Clerky on legal concepts all founders need to understand (incorporating, vesting, notes, etc.)l. Ready to get started drafting some documents? Here are some great resources for free legal docs to stick to the mission: Avodocs- 3 free per month. In addition, Cooley Go has a library of documents for the US and UK from Penn State Law School - a startup Kit bundle, and for all you Kiwis, Simmonds Stewart has a comprehensive library of agreements and templates.
You need your Tech Acronym Book open for a new entry. IDPs (Internal Developer Platforms). Stack Overflow's latest developer experience (DX) survey shows that most developers are running a bunch of CI/CD, DevOps, and automation tools. Still, only ~40% had a Portal or Platform to access the right tools and services. According to Forrester - good IDP is key to increasing productivity. Here are some popular players: Roadie, env0, and CloudQuery.
The 2023 edition of Pilot's State of Startups is out. The first slide shows we're an optimistic bunch - with 74% of those surveyed being optimistic about their startup's outlook (and view on layoffs) - but less optimistic about revenue growth compared to last year (2x vs. 4.9x). In addition, 56% are remote/office-less, and just over half of startups surveyed have more than 12 months of runway.
For my daytime business, demos play a pivotal role in our sales process to experientially show and discuss the value we can bring to a prospective customer. The team at Content Beta analyzed a bunch of Product demo videos (100+) and reported back on places where these videos went wrong, so yours don't have to.
This is a bit of a pitch deck - but the PDF is packed with really interesting slides on Venture - it's called the Data-driven VC Landscape 2023 (report, I guess?). The pitch is........that VC is pretty latent in terms of digitization - hah! 84% of VCs want to increase data-driven capability, but only 1% have initiatives deployed, and Machine learning models can outperform human investors in deal screening. Talent is distributed equally, but capital is not, with North American startups raising more capital proportional to population than anywhere else, and in terms of accuracy and recall, Machine learning models are on par with the best investors (80%) and relatively outperform the average/median investor by 40%/33%."
The path to ChatGPT from Rama Ramakrishnan of MIT - Rama gives a long (104 Slide) informal explainer on how ChatGPT was built (including what GPT actually means - slide 42, of course).
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