Category: optimization

SEO optimization for suckers

Post author By Yoav Aner
Post date 18 March, 2019

There’s a famous Jewish, Yiddish phrase:

Man plans and God laughs.

I think the same applies to SEO and Google nowadays.

Man SEOs and Google laughs.

I was always a bit suspicious of SEO, and let’s face it, the sea of snake-oil SEO salesmen doesn’t help to establish credibility here, does it?

But I think that I’m becoming even more cynical of it every day.

The problem with getting good advice for SEO is that there’s no money in telling you “Don’t do anything”, “It’s a waste of time”, or “Focus on valuable content for your audience”. But there’s tons of money in doing a site audit, in telling you about best strategies to extract link juice, or why alt tags for images are important.

But it works

marketing optimization

why I stopped using Intercom

Post author By Yoav Aner
Post date 8 February, 2019

This post has been on the back of my head for a couple of years now. I think we actually switched-off Intercom in 2016 or so… But the reasons should still stand now, or might even be stronger. Of course, things might have shifted, so please forgive me if some features are totally different by now.

For those who don’t know intercom.io (now intercom.com), well, I think you probably do know it, but maybe not by name. It’s the technology (or company) that adds those little “bubbles” on websites, with friendly faces offering to help.

How intercom works (taken from intercom.com)

Of course, intercom.io isn’t the only one now, and there are a few competitors in this space. The principle is pretty similar though. I think intercom was the most successful company doing this, or the first, or both. But it’s not really important. It’s mostly about intercom as a concept, rather than a specific implementation.

TL;DR

The short, simple, and most crucial reason: it didn’t work. How do I know? We A/B tested it. Over a fairly long time and a large number of people.

optimization Performance rails ruby

The dark side of Rails Russian Doll Caching

Post author By Yoav Aner
Post date 1 December, 2018

Rails Russian Doll Caching is super cool. It’s simple, effective and makes caching much easier to reason about.

There’s a dark side to it though. Not in the negative, evil sense. But rather the hidden, unknown, confusing sense.

monitoring optimization Performance python Technology

a scalable Analytics backend with Google BigQuery, AWS Lambda and Kinesis

Post author By Yoav Aner
Post date 1 April, 2016

On my previous post, I described the architecture of Gimel – an A/B testing backend using AWS Lambda and redis HyperLogLog. One of the commenters suggested looking into Google BigQuery as a potential alternative backend.

It looked quite promising, with the potential of increasing result accuracy even further. HyperLogLog is pretty awesome, but trades space for accuracy. Google BigQuery offers a very affordable analytics data storage with an SQL query interface.

There was one more thing I wanted to look into and could also improve the redis backend – batching writes. The current gimel architecture writes every event directly to redis. Whilst redis itself is fast and offers low latency, the AWS Lambda architecture means we might have lots of active simultaneous connections to redis. As another commenter noted, this can become a bottleneck, particularly on lower-end redis hosting plans. In addition, any other backend that does not offer low-latency writes could benefit from batching. Even before trying out BigQuery, I knew I’d be looking at much higher latency and needed to queue and batch writes.

monitoring optimization Performance python Technology

a Scaleable A/B testing backend in ~100 lines of code (and for free*)

Post author By Yoav Aner
Post date 20 January, 2016

(updated: 2016-05-07)

tip-toeing on the shoulders of giants

Before I dive into the reasons for writing Gimel in the first place, I’d like to cover what it’s based on. Clearly, 100 lines of code won’t get you that far on their own. There are two (or three) essential components this backend is running on, which makes it scalable and also light-weight in terms of actual code:

AWS Lambda (and Amazon API Gateway) – handle the requests to both store experiment data and to return the experiment results.
Redis – using Sets and HyperLogLog data structures to store the experiment data. It provides an extremely efficient memory footprint and great performance.

For free?

optimization Technology

AlephBet – javascript A/B Test framework for developers

Post author By Yoav Aner
Post date 6 June, 2015

I recently created AlephBet: a new javascript A/B Test framework, built for developers. This post tries to capture the motivation and some background for creating it in the first place, especially with so many commercial and open-source frameworks and services available for A/B testing.

coffee optimization

Coffee A/B Tasting – Results

Post author By Yoav Aner
Post date 27 August, 2014

This is the final post on this series. I started by covering the method for A/B testing coffee, as well as the motivation and approach. I later wrote about the first test session using Hario V60, comparing those beans by making Espresso and the last post described two preparation methods Aeropress and Cappucino.

I repeated a similar process using various combinations of A, B, C, D and E coffee beans. This post will be more brief, with the “results” based on my personal preferences and how I ended up scoring all 5 types of beans.

coffee optimization

Coffee A/B Tasting – aeropressoccino

Post author By Yoav Aner
Post date 6 July, 2014

On previous posts I covered the method for A/B testing coffee, as well as the motivation and approach. I later wrote about the first test session using Hario V60. The last post was comparing those beans by making Espresso.

This post will cover two tasting sessions of the same mysterious A and B beans: Aeropress and Cappuccino.

coffee optimization

Coffee A/B Tasting – Creme de la Crema

Post author By Yoav Aner
Post date 25 June, 2014

On my previous post, I covered the first blind A/B tasting session using the “Gingerlime Tasting Technique” ™. You can read some more background about the motivation and method, as well as a full list of coffees I’m comparing on the first post in the series.

After the first taste using pour-over Hario V60 filter, I was anxious to find out whether both A and B coffees will show similar characteristics using other preparation methods. Namely: Espresso, Aeroproess and Cappuccino. Would B stay my favourite when served with milk? Would the Aeropress extract different flavours out of A than I managed with the Hario?

coffee optimization

Coffee A/B testing – first A/B taste

Post author By Yoav Aner
Post date 20 June, 2014

This is the second post in a series, exploring the “Gingerlime Tasting Technique” ™. You can read some background on the previous post, where I explain the motivation, testing method and how I started exploring A/B testing for coffee. Different tasting sessions comparing two types of beans and trying to choose the best out of the two.

A taste test

The first tasting was between coffee A and B (still unknown to me at this point in time). The test was actually a series of 4 different tasting sessions. Each session used a different method of making coffee: Hario V60 filter, Espresso, Aeropress and a Cappuccino.