Narthur's Startups

I love these ideas! I’ve recently started using a personal GitHub repo (I call it omnitask) for dumping everything that pops into my head that I need to or “should” or might want to do and then freshgishing that. I don’t know if tying tools like this to GitHub is in your plans but that would make a lot of sense to me!

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@dreev open to it! Any chance you’d be able to get a tad more specific about what you’re hoping for when it comes to a GitHub integration? Like the ability to easily create TaskRatchet tasks from GH issues? Or something else? Would you want to make the decision for each issue individually? Or have the ability to automatically create TR commitments for each new GH issue? :thinking:


After having several conversations with folks, I’ve pretty much decided that I’ll be putting the Narthbugz idea on pause. This is for two primary reasons:

  1. After talking to @dreev, it’s pretty clear to me that Narthbugz wouldn’t be valuable to Beeminder, which means I don’t have an initial customer.
  2. I’m not doing the kind of contracting where Narthbugz would be valuable, at least at present, so I don’t have a reason to dogfood it myself.

If one or both of these points changed in the future, I’d be open to reconsidering the project.

But for now I’m exploring other ideas for a second startup, especially around ADHD and programming, since those ideas are likely to be very valuable to me personally.

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That sounds like the perfect place to start, yeah! Or maybe checklist items within a gissue?

To be clear, that’s not clear to me! But, speaking of clarity, the problem may be that we’re so unclear on what we do need, that we’re not a great first customer for that reason. I don’t know.

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Yesterday I did more thinking about how to measure / systematize an experiment-based approach to product direction.

For a while I tried to think about how to use bayesian reasoning to quantify the magnitude of an experiment’s significance for the purpose of tracking with Beeminder. However, this seems tricky, since I’d prefer to quantify the input (the experimental design) rather than the output (the resulting observation). And from my basic understanding of bayesian reasoning, it’s much more concerned with the actual observation than the design of the experiment previous to the observation.

For example, say I asked people how excited they are about new feature X on a scale of 1 to 10. Once I have the observation (that is, the poll is finished), I think I could relatively easily use bayesian reasoning to approximate the significance of the result.

But how would I define the value of the experiment before running it? There are three properties I might consider–how many people responded, the average value of the response, and the distribution of the responses (e.g., normal, bimodal, …).

Every combination of these properties (that is, each discrete observation) would have a different significance compared against my starting hypothesis, yes? So how would I quantify the experiment’s potential significance to my hypothesis before making my observation?

If you’d like to help me think this through, I’d be very grateful. But be forewarned: my knowledge of this stuff is quite casual, so it may take some back-and-forth before I understand what you’re trying to say.

Somewhat relatedly, I was reminded of something that Dave Farley said in this episode of the podcast Ship It!. He drew the connection between the scientific method and continuous delivery. Basically the idea was that we want to assume we’re going to be wrong a significant percentage of the time and put systems in place that account for that, and then reduce the size of each deliverable as much as possible to reduce the amount of stuff we could be wrong about in each unit.

That reminded me that this is a big part of how science works–coming up with hypotheses and trying to falsify them. I think I had forgotten about the falsifying bit. Instead of thinking of hypotheses as questions, I should think of them as opinions or ideas I already tend to believe, and then look for ways to prove myself wrong.

So here is a list of things I already tend to believe in relationship to my startups that might be good candidates for attempting to falsify:

TaskRatchet

  • Splitting the tasks view into two tabs–Next and Archive–would both decrease the complexity of TaskRatchet’s code and make the app easier to use for users.
  • A recurring tasks feature would provide value to users and increase the number of tasks users create over time.
  • Integrating with additional third-party services would allow me to increase the usefulness of TaskRatchet and increase the number of tasks that users create.
  • Creating official Make.com and Zapier integrations would significantly increase the number of tasks users create.
  • Emailing users regularly, beemail-style, would be a significantly more effective way to gather feedback than my current method of posting to Twitter and the Beeminder forum.
  • More TaskRatchet users would see my UVIs if I posted them to the forum instead of to Twitter.
  • Continuing to develop and add features to TaskRatchet is likely to increase my monthly revenue to a degree that it is worth the effort.
  • Making TR more ADHD-friendly would make it easier for me to dogfood it, and also increase user engagement generally.
  • Switching to a tech stack other than full-stack TypeScript would not provide enough benefit to outweigh the associated costs (learning, development, new bugs, etc).
  • There are no good alternatives to Stripe that support my business model and would allow me to simplify my tax situation at a reasonable cost given my low revenue.
  • TaskRatchet can be a significant piece of how I support myself financially.

Narthbugz

  • Narthbugz, as currently envisioned, would not provide significant value for a small-a agile development team.
  • It would be too difficult for me to find initial customers for Narthbugz.
  • Narthbugz would not currently provide me enough value to warrant the time and effort I would need to spend in development.

I’ve tried to rework any items that started with “I should” into statements of the underlying ideas that lead me to believe that I should do this or that.

Do you have ideas on how I could challenge these opinions? Don’t worry if you agree with me on some of these points–the ultimate goal here is not to reverse my opinion. Rather it’s to put my opinions on a firmer foundation (which may at times mean reversing the opinion, but not necessarily).

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Some thoughts

Do you really need to beemind the quality of your experiments? There is a chance that you will automatically optimize for higher design quality without Beeminder.

My intuition is that TaskRatchet can get you to support yourself 100% on a medium-term timescale, but that you will face the same customer acquisition issue as Beeminder: there are not many people who will recognize the value of your product.

If you really wanted to optimize for money, you might be better off creating a spreadsheet and adding one business-idea per day + some scoring (risk, cost, income according to different timescales).

You might find that there are business ideas out there that could get you to your goal in a relatively short timescale. The difference of revenue * risk is what you lose by sticking to TaskRatchet.

Have you considered in-app surveys? If your customers are procrastinators, they might be more than happy to take 5 minutes for your easy task :slightly_smiling_face:

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@clouedoc Yes, highly likely I’m overcomplicating this stuff!

I like your spreadsheet idea. I do think I’d prefer to use metrics like tasks / user, user retention, etc, rather than revenue directly, since I want to avoid making decisions that are good for short-term revenue at the expense of value to the user.

I have been thinking about in-app surveys. I added a simple feedback form to the app. But I wasn’t sure if there was a good tool for creating surveys like that that I’d like to use. I know HotJar has that as part of their functionality, but not sure I want to start using them just for that one feature.

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Ah, I see you’re a true LEAN startup follower :slightly_smiling_face:! “The value of a startup is defined by the sum of value it brings to their user”.

Maybe a database table whould be more appropriate for your use-case? With an app-native form?

E.g. you could choose to listen to long-time users; users who pay a lot; users who don’t pay that much; inconsistent users that you could fidelize…

Also, Hotjar is a cash-grab :chains::moneybag:

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As I mentioned here, I’m very thankful that @shanaqui is now handling TaskRatchet’s support inbox! I think this will be a big improvement for our users.

I’m still thinking about how to gather feedback on the site. I was thinking about using SurveyMonkey, but they don’t allow embeds unless you’re on a paid plan, which I don’t feel makes sense for us.

I guess one issue is it’s not clear to me where I should be storing these stats. Google BigQuery? Firebase? A Google Drive spreadsheet? Amplitude?

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Have you considering storing your analytics on your existing database and pair it with a Business Intelligence tool such as Grafana, Tableau or Kibana?

Having the power to go the last mile; taking into account data that you didn’t think about in your analytic events can be powerful. E.g. how the account’s creation date influence user satisfaction? I don’t really know what’s relevant for you.

I am preaching for the PostgreSQL/TimescaleDB+Grafana stack for this reason.
In the same database, I have user data, orders, scraped data stored alongside a giant table that ingests tons of events each day.
Having the power to correlate these events with obscure data by doing simple JOINs allowed me to easily satisfy customer questions and improve montiroing. If I had stored these analytic events in a separate system, I would’ve needed to know in advance every attribute that I want to query or do costly app-level JOINs.

Otherwise, Google Sheets seems like an attracting option since you both automated analytics, unlimited storage, OK-ish scalability depending on your amount of data, and all that for free.

If you want the power of PostgreSQL+Grafana without having to do too much backend stuff, you can take a look at Supabase + Grafana Cloud; both have generous free tiers.

  • cost
  • privacy
  • familiarity/learning curve
    • ease of data import
    • ease of data analysis
  • analytic capabilities
    • integration with existing infrastructure
      • you want as many data points as possible
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