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TOP 10 IN TECH
​a weekly tech newsletter

Curated SaaS and tech insight from around the web repackaged for people to put to good use

Top 10 in Tech - What to know for Week ending October 30, 2020

10/30/2020

 
  1. SaaS METRIC OF THE WEEK: Net Dollar Retention - Sammy Abdullah of Blossom Street Ventures backs up my on-going opinion that net dollar retention (and by-proxy Up-sell) is the most important metric in SaaS. NDR comes in a variety of different efforts though so take a read of this article to get a better grip of the nuance and then ask yourself: "Does my startup need to increase customer acquisition/marketing spend?" Tomasz Tunguz writes in detail about this and Crunchbase do the work to calculate what good NDR benchmarks should look like. 
  2. CUSTOMER SERVICE:  In this current age of the customer, enhanced by COVID,  SaaSx make the argument that Customer Success is actually the product. Want to start building out that product? Check the HubSpot guide on getting started with your customer team.
  3. HANDOFF: To add onto above, the customer journey will have plenty of touch points and handoffs. Chartmogul provide some great tips on customer handoff from sales to Customer Success teams.
  4. NPS: To add onto the add on above. Customer Service and Success have many metrics to track and NPS makes the top of the list. This White Paper from Ask Nicely reviews NPS (among with other common customer experience metrics) and explains how to measure and calculate NPS. Neil Patel then gets into a 3 step program of how to leverage NPS for your business.
  5. ANALYTICS: Being a "growth hacker" is just putting a shiny label on high fidelity analytics mastery but many analytics efforts result in failure - it’s all about the data, not the tools, check this primer on the topic. McKinsey provide five pointers on how to make analytics work in B2B Sales. And once you get good at collecting the cold hard data, check the following article on how to perform a sales analysis (step by step).
  6. PERSONALIZATION: Did you know that personalization can reduce acquisition costs as much as 50% and 87% of companies see a lift in key growth metrics when they employ personalization? SaaS marketers have been leveraging personalization to increase conversion rates, improve customer success, and increase the quality of sales/marketing funnels for some time so here is a great article from Chart Mogul on the (modern day) personalization fundamentals.
  7. PRIVACY: The Debbie downer from above, let's not get too personal. Privacy concerns are rightfully growing and rules around the globe are tightening (FYI the California Consumer Privacy Act goes into effect in 2020). This is creating significant challenges in the digital advertising industry, so Google has created a playbook, collecting best practices and case studies from this forward-thinking, privacy optimized,  group of marketers. 
  8. FIRST PRINCIPLE THINKING : Want to be more like Elon? Take a read here on the concept of  First Principles Thinking. Not gonna lie, I've re-read it again this week and it still makes my brain hurt. Want more? Fine. Here is a full guide/website. Now that you are an expert on this principle, here is how First Principle Thinking can be applied IRL - in this example towards a Product Lead Growth business.
  9. ROADMAPS: Always seem a bit too waterfall-y for Agile teams -  old-school, clunky and rigid. But Agile teams absolutely need them as the teams still need some overarching direction and sense of what’s to come beyond Sprint cycles. Read here on the reasoning why along with 5 roadmap templates to use. I'm personally a fan of  how Atlassian have designed their public access roadmap - it gives me hope.
  10. DEATH: Of the SaaS kind. Y-Combinator (via the SaaStr Blog) lists 5 things that kill startups (and what to do about it). It's a way deeper article than it sounds (and it ain't just 5 things)

BONUS: There is no real category for this post, but I think it's awesome. Entitled 'A Few Rules'

POD OF THE WEEK: Expanding on #5 above, just having data is not enough: it takes an entire system of tools and technology to extract value from data. a16z explore the evolution of data architectures.

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