
Show HN: Did not find automated personalization for websites and created this - alexeykudinkin
https://www.landy.io/
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gk1
As a CRO consultant this is interesting, but I'm skeptical. (It's not
particularly your fault. Nearly every marketing tool promises nirvana, but
very few of them deliver.)

It sounded great until I realized that:

1) I would still have to think of variations and create them myself.

2) Even after that, this would only be useful if things like location and time
of day really did have a significant effect on conversion rates.

3) And even after that, this would only be _worth it_ if those effects were
not obvious to me and could only be discovered with ML. For instance, it
doesn't take ML to hypothesis that a visitor who came from an ad link
(&utm_campaign=dogs) is more interested in seeing a page about Dogs. And that
hypothesis can be tested for free with Optimizely.

In other words, ML is cool and all but I don't see what value this adds to
conversion optimization.

Maybe my assumptions are wrong and I'm missing something, in which case I hope
this is useful feedback.

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mrtsepelev
1) Yes, the problem with creating variations is still here and is worth
mentioning. Today you need to know your product well and know your visitors
well to create a valuable hypothesis. And this is what we're working on right
now (disclaimer - I'm one of the co-founders of Landy).

2) The idea here is that with ML you should not analyze every dimension
separately. ML is taking into the account all available characteristics and
making decisions based on all of them together (like if the guy on OS X, who
came from NY from the Facebook campaign in the evening - prefer to watch
product video instead of watching screenshots - no problem, we'll show him
video).

3) The real power of ML comes out when you could not obviously split your
traffic based on the ad link (like utm_campaign=dogs). Direct and search
traffic on your homepage are great examples in this case. Also, manual
targeting requires a bunch of analytic folks, who will continuously analyze
your traffic, setup and adjust optimization campaigns. Even in this case -
it's still difficult to adapt to dynamic changes in traffic (like a new type
of visitors, season changes, etc). So ML could not only improve results but
also decrease the amount of human resources which is currently required for
solving such complex problems.

So what I'm trying to say is that your assumptions definitely make sense in
some cases. But we believe that there are still plenty of cases when ML could
drastically increase your results and save your time.

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thecolorblue
I had a similar idea but couldn't convince people on my team to try it out.
Glad to see someone is trying this. Adding a SaaS model is a good idea.

Have you tried switching out parts of a page? I tried switching react
components in an admin interface. It took into account the user id, so in some
cases, the user would get a 'customized' UI.

I had trouble tuning the data to make the output actually useful, so the
project has been shelved for now. Hope this works out for you guys.

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ghosttie
I was disappointed that the landing page wasn't personalized as a
demonstration

~~~
mrtsepelev
Actually, it is. We're currently running simple personalization campaign with
two versions of landing pages which has different design, messaging, etc.

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mchahn
This makes sense. Ads have been personalized for a long time so why not pages?
Some work is needed to create these but for people trying to squeeze every
conversion they can out of visitors is may be worth the trouble. It also might
help prevent fast bounces.

