
Show HN: AddAI – A better alternative to A/B testing (Startup School project) - addai
https://addai.io/
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addai
After the first attempt at a Show HN accidentally got eaten by HN's spam
detection and only rescued too late, here's another shot (ok'ed by @dang -
thanks again for helping and your advice).

This project is something I've been meaning to work on for quite a while,
mostly because I think it needs to exist and also because I think I have the
background to do it. Most of the work has happened over the weekends since the
start of startup school (this is one of the "accepted by accident" projects
where they sent out an acceptance email to everyone they were planning to
reject, then another rejection and finally a "sorry for the messup - we're
letting you join" \- so let's see how things go ...)

The idea is the following: there has been this thing where companies basically
kill off everything that doesn't work too well with their mainstream audience.
This has been happening on a large scale (e.g. with Google killing Reader and
now Inbox), on a smaller scale with companies removing features and on the
micro scale it has even been automated with a/b testing (where you basically
try to explicitly measure which option works best for the average user and
kill the others).

This project is basically trying to attack the problem from this micro scale
while hopefully later moving up that chain or at least motivating change there
as well. The way it works is that we change the original goal of a/b testing
from "what's the best option on average overall?" to "what's the best option
for this specific user?" and try to automatically show him that (using
reinforcement learning internally to make it happen). Right now this works on
websites where we use JavaScript and some CSS magic to make it work in a way
that's easy to use for developers - but longer term we're planning to look
into other places as well.

I think the tricky part right now is to not move in this adtech direction it
could easily be, but rather towards what chatbots tried and failed at - at
least so far. There's gonna be another blogpost about this topic, but the
tl;dr essentially is that the interesting part about chatbots is not the
natural language interaction, but that they are - by lack of ui - basically
forced to focus on thinking about "how do I find out what the user really
wants and get him there as quickly as possible without shoving irrelevant
stuff in his face?" \- and this way of thinking could also be really useful
even if you have ui - and ideally automated using AddAI.

~~~
rajacombinator
My 2c: sounds like you’re trying to force too many buzzwords, ie reinforcement
learning, chatbots, google killing off product lines. And you’re avoiding
embracing the actual offering which is simply segmented ab testing. Chatbots
are a massive scam and failure, you really should avoid comparison with or
aspiring to emulate them.

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wingerlang
I don't understand the difference between this and A/B testing. The fact that
you slowly surface/chose the winning variant automatically?

~~~
addai
The difference is that we don't assume there is this one winning variant.
Let's say you have a product that works for both, large enterprises and small
businesses. Both visitors end up on your pricing page at some point - the
enterprise customer has clicked around in the documentation looking at SLAs
and other enterprise stuff and the small business visitor has focused on
getting started pages primarily. When they end up on the pricing page you
would ideally want to focus on showing/highlighting enterprise pricing and
mentioning all those enterprise features again for the enterprise customer,
while the small business customer gets to see small business pricing and that
it's easy to use. AddAI automates figuring out those combinations and over
time learns to show the right thing automatically.

~~~
wingerlang
How do you differentiate the users?

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zubairq
This could be very interesting. It wasn't explained so well on the home page
but I liked it

