Comment by chdaniel | Hacker News Reader

Comment by chdaniel | Hacker News Reader

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Wow thanks that helps a lot!

Not really automatic price-setting, at least not by default! I would personally like to have control over the knobs in my product.

It would give you a dashboard where

A) You would be able to set the prices manually (with suggestions, of course, and with taking into account things like extra Stripe fees, rounded estimations so you don't wound up with £28.837 in the UK).

You'd set them manually based on country, so you won't leave money on the table by not charging less in India, for instance.

I'm always mentioning India because Apple is the widest example that comes to mind: Apple one is £15 and £25 in the UK, whilst $1.5 and $3 in India

B) Run tests that you set manually on prices. $19 vs $29 — see, with metrics, which one brings your company more revenue. Or perhaps same revenue, but more users, so more word of mouth — who knows what the test will show?

You'd be able to either schedule (e.g. $19 for week 1, $29 for week 2) or run tests at the same time (show 50% of ppl $19 , show 50% of ppl $29 // OR show ppl in the Uk $19, show ppl in the US $29)

RE: your last comment — the best part would be that it'd be a flat fee per month, no percentages! So every extra cash that you receive from ppl on top of the flat fee is yours to keep for... well for as long as your "LT" in LTV!

How does that sound, you think?

So, essentially, you're building an A/B testing tool specifically for pricing?

Thea complexity you've alluded to in your various descriptions start to get really hairy once you scratch the surface, for example:

You mentioned trading off lower prices for more users. Whether the tradeoff is worth it depends not just on the difference in income, but on the marginal cost of serving another user (which itself may be variable).

You mentioned more users leading to more WOM. That is a huge assumption, you have to actually measure your viral coefficient (which might actually change with different prices) to know whether that hypothetical WOM actually leads to more users.

You may need to optimize for cash flow instead of just income. As one example, you could try a higher monthly price combined with a larger discount (two months free instead of one) for paying up front for a year. That may lower the total number of signups but a greater % pay for a year, improving your cashflow (and with fewer signups, you may have better profit margins on a similar income).

You can add an additional expensive plan to act as an 'anchor' that no-one ever picks but makes the regular plan seem like a better deal.

There are so many ways to adjust pricing, and every part of your conversion funnel (and business model) may be affected, sometimes with counterintuitive results. Figuring out what some change to your pricing plans is really doing for (or to) your business can be really hard. Instrumenting your funnel and business model so you can actually see what a pricing change would really do to the businesses finances over time would be extremely useful.

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