[Fiahil]

That list explain perfectly why I don't want to work on "marketing stuff" anymore. So much opportunity to waste time and money on trivial things.

A blog ? A "sneeze page" ? What's the point if you don't have anything interesting to write ?

A/B testing landing page and newsletter ? Is that difficult to get honest feedback from people who care ?

[archagon]

I feel this list is intended for full-on, VC-yearning startups. My admittedly limited experience is that if you're going for more of a small business product, you could eliminate about 75% of this list.

The rest is just "industry hacking".

[petra]

What's the 25% left?

[archagon]

Depends on your product, I guess? For me, it's usually: make a splash page, make sure your assets (app icon, screenshots, trailers) are eye-catching and professional, write about different aspects of your product on your blog, condense your pitch down to a paragraph at most, e-mail every publication you can think of (and follow up), post in lots of topical forums and comment sections (esp. HN and subreddits), submit your product to publications that give out awards, try as much as possible to catch the eye of Apple's promo team if you're in the app business... but, caveat emptor, I'm also not great at it yet. It's a hard job.

[pyronite]

> A/B testing landing page and newsletter ? Is that difficult to get honest feedback from people who care ?

Individual feedback doesn't replace large-scale A/B testing. If you're getting feedback from people who care (possibly implying they know you personally), it's also possible that they could deliver biased or unrepresentative feedback.

[Dunedan]

For large scale A/B testing you need a certain amount of visitors first to get the necessary statistical significance, otherwise its feedback is unrepresentative as well. A lot of side projects probably don't have enough visitors for that.

[closed]

I disagree, if a person has to make a decision under uncertainty, and a priori favors neither group A or B, then they might as well use any visitor information available to them to guide their choice.

They just shouldn't be too confident they've made the correct choice.

[encoderer]

You are just using noise then. It's not a matter of opinion, it's statistics.

[closed]

If you are waiting for N observations, so that a NHST will have some level of power, and you assume each observations is drawn from the same distribution (as your test likely does), then you do not see each observation as noise.

You will just be acting under reduced certainty, but if you have to act, any information is better than no information.

(I'd be very interested to hear your statistical explanation).

[encoderer]

The trouble is disproving the null hypothesis. In your test, if one variant beats another, you take that as a weak signal that one may be better than the other. The data doesn't support this. Without applying a standard to your p-value, you cannot disprove the null hypothesis: that your variant is likely no better or worse.

I'm not a statistician, but I've run a lot of b-tests.

[sobani]

The question then is:

Is the available data more useful than a coin-flip, which would be the alternative method of making a decision.

On the other hand, a coin-flip is probably the better tool. If you can't generate enough data for a statistical sample, then you're probably wasting your time creating an alternative version and setting up an A/B test.

[zerkten]

I think people understand the theory, but do most people have enough traffic on a side project to have viable A/B tests?

[XCSme]

Well, you need a landing page so users can actually buy your product. Maybe not A/B test but you should use something like hotjar or userTrack, at least in the beginning to see if your users are having difficulties actually converting.