Comment by mvdtnz
3 years ago
> Unfortunately, good enough, often means unhappy customers actively looking for new competitors.
Here's the thing though - it's your intuition that customers are unhappy, but the startup in question has actual data. It's entirely possible that a small group of people similar to you are unhappy but for a majority of the userbase the feature has gone as far as it needs to. Resources are scarce and priorities need to be changed, which sometimes means making hard decisions.
We don't know that, actually; you assume that the company has the data, and speculate that they interpret it correctly. But in practice, "customer loves using the app" and "customer puts up with the app but will replace it as soon as they find anything else" look the same right up until they don't, just as "high interaction" presents the same data as "app is disorganized and inefficient".
Usually the company is quite aware the feature is half finished, but the data shows that hardly anyone uses it, and hardly anyone is asking for it to be improved. So that time would be better spent improving things that there is lots of usage on.
There are multiple ways to interpret the same data. Your interpretation is a valid one. There are other valid ones all from the same data.
If your company sees the simple lack of feedback as a valid signal, then a feature with lots of usage but no feedback means you should not improve it but simply leave it be. It's used, so it seems popular and nobody complained about it, so it must be good enough. Build something else.
Of course your company may also view a simple lack of feedback as not enough signal. If a new feature that is half finished sees hardly any usage this can be taken as a signal that the feature needs to be improved. It's not useful enough in its half finished state to attract usage. Or your users may simply not be able to find the feature because in its half finished state it's too hidden and thus you have neither lots of usage nor feedback on it.
> the data shows that hardly anyone uses it
This is exactly why data can be a horrible guide for product development.
If you develop a half-baked feature, and the data says nobody uses, then maybe, just maybe, they're not using it because it's a half-baked feature.
Alternatively, the rapid failure after IPO is a suggestion that their customers weren’t happy, but the plan was short term pump and dump.
It’s not always easy to say if something is stupid or fraudulent, but sometimes it really is just a scam.
I find it so weird to look at the stock market to approximate this kind of metric. Stock prices have more to do with things like the ebb and flow of the risk profile of institutional investors, than with customer satisfaction with specific features.
Institutional investors care a great deal about metrics like customer retention indirectly because it influences customer lifetime value which then impacts profitability all of which is dependent on customer satisfaction.
Groupon for example has decent consumer metrics, except they couldn’t keep the business partners happy which resulted in their ultimate collapse. Finding weaknesses in companies businesses models like this can both be extraordinarily profitable for institutional investors directly and create an aura of competence to attract more investors.
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We'd need a lot more information about this one particular case but I'd bet almost anything that a 90% drop in share price was caused by something a lot deeper than customers being unhappy at some unfinished features. I intentionally didn't address that half of his comment for that reason.
That’s reasonable, though I am not suggesting a pump and dump is only going to show up in the code base just that it would also look like they described.
Having the data isn't enough; someone also needs to look at the data and draw conclusions. If it's an environment focused on pumping up metrics for the newest thing then this may not be happening.