Friday Updates: Preceden Redesign Progress, Learning Tailwind, Data Survey, Housing Prices Ranking, and Yoga with Adrienne

Photo courtesy of Marius Ciocirlan

What I’m working on at Preceden

Work continues on the site redesign project.

I found a talented designer on Dribble named Asif Howlader who I wound up hiring to put together some mockups to brainstorm ways to improve Preceden’s design.

Here for example is Preceden’s current Case Studies page:

And after a few iterations here’s where the redesigned page stands:

Not bad right?

He’s currently working on redesigning the homepage and later will tackle other areas of the site as well.

The next task is actually implementing this on the site. My plan is to hire a front-end developer freelancer who can knock it out. I’d also like to have him or her transition Preceden to Tailwind in the process which should go a long way towards making the site easier to develop in the future and also standardize a lot of the design elements (right now it’s a hodgepodge of colors, font sizes, margins, etc). Before I hire someone though, I want to get some experience with Tailwind, so this week has had me diving into Tailwind courses and trying to get it set up in Preceden.

This in turn had me upgrading Preceden from Rails 5.2.2.4 to 6.0 and Ruby from 2.6.5 to 2.6.6, which has me thinking about this Malcom in the Middle clip:

What I’m working on at Help Scout

In an effort to get a better feel for where to focus my efforts in the coming months, I created a survey and posted it in our metrics Slack channel for anyone to take. Here were the questions:

Score from 1 (strongly disagree) to 5 (strongly agree):

  1. I rely on data to make decisions in my job
  2. I am satisfied with my ability to use Looker
  3. Looker has reports that are useful to me
  4. Looker has reporting on everything I want
  5. Itโ€™s easy to find reports on specific things in Looker
  6. I am confident that I understand the meaning of the metrics and data fields I use
  7. I trust the accuracy of the reporting in Looker
  8. I am satisfied with the speed that my data questions are answered

Open ended questions:

  1. If you could wave a magic wand and change one thing about our data work at Help Scout, what would it be? (optional)
  2. Anything else you would like to add? (optional)
  3. What department are you in? (optional)
  4. Whatโ€™s your name? (optional)

Two big takeaways from the responses are that people want to learn more about how to use Looker and also that there’s a demand for more product analytics (we have some, but comparatively little compared to our marketing and finance reporting).

What I’m studying

After a few more hours of iterating on my housing prices prediction notebook, I finally made it into the top 5% of scores:

Around 2% of the high scores are cheaters though (because the full data set is public so people can find it and just submit the actual house prices to get near perfect scores) so this score is closer to top 3%. And many of the higher scores cheat in a more subtle way, by creating a model that incorporates the training data (aka data leakage) which gives you an advantage over someone who is just creating a model based on the training data (which is the right way to do it).

I’m at the point of diminishing returns on this though so will probably wrap up soon. I’ve read through a lot of the public notebooks and don’t feel like there’s a ton more to learn, at least relative to jumping into another competition. I’ll likely put together a final notebook and share it on Kaggle next week for others to learn from.

What I’m watching

Too much time at the computer has inevitably led to me to have frequent back pain. A lot of things help though:

  • Standing instead of sitting
  • Weight lifting
  • Chiropractor
  • Yoga

For this last one, I’ve been doing a lot of Yoga With Adrienne on YouTube. Here’s an example:

If you have back issue or just want to try to work more yoga into your life, check out her videos.

Adios for now ๐Ÿ‘‹

Friday Updates: Preceden Design Hire, GPT-3 Response Generation, Housing Prices Progress, Star Trek Discovery, and the Almanack of Naval

Photo courtesy of Josh Berquist

What I’m working on at Preceden

I’ve got this thing where I’m never quite satisfied with Preceden‘s design. It’s not that bad, but when I compare it to a site designed by professional designers like Help Scout or Stripe, it’s clear that there’s a large gap, and it’s not one that I’m talented enough to close on my own.

And so this week I posted a job on Upwork to try to find a designer to help improve Preceden’s design:

I was optimistic that this would receive a lot of applications, but it didn’t work out that way. It received maybe 10 applications, out of which I’d say 9 hadn’t tailored their application even one bit to the job description which is an immediate red flag for me (even just a short “Hey, working on Preceden sounds interesting, here’s a bit about me…” goes a long way). The 1 that did wasn’t a good fit. In the end I did make an offer to 2 people (so I could work with them for a short project then pick one to work with longer term), but one declined saying he was too busy and another wanted a min $3k initial commitment which I wasn’t comfortable with.

At Automattic and now Help Scout, there are some incredibly talented designers who can create mockups and then take that design and implement it in HTML/CSS within the codebase. But this hiring experience reminded me that those people are rare and in high demand and probably not looking for short projects on Upwork.

It’s more common for different people to tackle these tasks: one to create the design, another to implement it. For round 2 of hiring for this, I’m going to try to split it: find and hire one person (probably on Dribbble) to create the mockups, and hire a separate front-end developer to implement that design in Preceden.

What I’m working on at Help Scout

I shipped a fun little experiment that lets people at Help Scout use GPT-3 to automatically draft a response to customer conversations within the Help Scout editor:

This uses Tampermonkey to add the GPT-3 button using custom JavaScript that’s run on conversation pages, which when clicked takes the customer’s name and last message, posts it to an API endpoint which runs it through GPT-3 and returns the completed text, which is then simulated as being typed out in the editor to look cool.

To be 100% clear, we have no intention of actually building this into the real product. It’s meant to demonstrate GPT-3’s strengths in weaknesses. If I had to boil them down, I’d say that GPT-3 is great at generating text that looks like it was written by a human, but at least in this support context, the responses are terrible because GPT-3 has no knowledge of the product its trying to answer a question about. Maybe down the road there will be some future version of this technology where it can be trained on your support history or docs, but until that happens, GPT-3 probably won’t be augmenting customer service reps in this way anytime soon.

What I’m studying

Still chugging away at Kaggle’s old housing prices prediction competition, managing to break into the top 500 out of 4.6k:

My approach to this is to make as much progress as I can on my own, then peak at others’ publicly shared notebooks to get ideas for how to improve, then iterate on my own notebook accordingly. I’ve been learning a lot this way and probably stick with this competition for a few more weeks until I feel like I’ve maxed out how much I can learn from it.

What I’m watching

Star Trek Discovery:

Unlike most of the older Star Trek series which basically consisted of the ships exploring and getting into different adventures each episode, Discovery (and Picard) have an single story arc that’s told across each episode. It’s really good.

What I’m reading

The Almanack of Naval Ravikant – a summary of his podcast interviews and writings. I’m a huge fan of Naval. If you’re new to him, check out his Farnam Street interview which I’ve listened to several times.

That’s it for now ๐Ÿ‘‹

Friday Updates: More GPT-3 Experiments, ML Courses Completed, Kaggle, Keane, and Picard

What I’m working on at Help Scout

I’m still experimenting with applications of GPT-3, specifically around reducing the amount of time it takes for a user to respond to a support email. While GPT-3 is fascinating, its complete lack of knowledge about Help Scout means it’s probably not going to be that useful for this purpose. We’ll see though.

Building a proof of concept for this has had me diving into Tampermonkey, a Chrome extension that lets you write custom JavaScript files that can be automatically run on certain webpages. For example, automatically adding a download button to all YouTube pages. These custom scripts (“user scripts”) can be shared too. This will enable me to quickly prototype ML tools for Help Scout’s support team to try within the product without going through engineering which would take a lot more time.

What I’m studying

Finally wrapped up DataCamp’s machine learning track!

I wound up exceeding my goal of 1 course/week towards the end because I really wanted to finish and start applying what I’ve learned.

The next day I headed to Kaggle and started on their old House Prices competition. The goal is to take a bunch (80!) data points about a house that sold and try to create a machine learning model that accurately predicts its sale price. There have been about 4.8k teams that have competed and my goal is to keep working on it until I hit top 5% or about top ~240. After about 6 hours of working on it, I broke through top 2000, so making progress but still have a ways to go. I’m learning a lot though and arguably should have been doing more of this sooner vs spending most of my time doing courses.

What I’m listening to

Love Too Much by Keane:

Every now and then I hear a song and wind up listening to it over and over again for weeks. This is one of those. The whole album, Cause and Effect, is excellent.

What I’m watching

Just wrapped up watching Picard on CBS All Access:

It’s probably my favorite Star Trek series after The Next Generation.

Between this and Raised by Wolves though, I’ve watched enough android television series to last me a while.

Hope everyone is doing well ๐Ÿ‘‹.

Friday Updates: Shenandoah Vacation, Experimenting with GPT-3, Timeglider Closure Updates, ML Progress & Raised by Wolves

Last week my wife and I headed out to Luray, Virginia to relax for a few days without our kids. We stayed in a cabin at the Shadown Mountain Escape which is located right outside of Shenandoah National Park. We hiked the Appalachian Trail each day, read a lot, watched a lot of movies, and generally just tried to relax and unwind. It was lovely. If you ever wind up going, tell Karen and Ralph that I said hi.

What I’m working on at Help Scout

I finally got access to GPT-3 a few days ago and have been playing around with it and brainstorming applications at Help Scout and beyond. Specifically I wanted to see what kind of responses it would generate to support emails customers had sent us.

Here’s a real conversation I received today in the Preceden inbox:

Hello,

I upgraded my Preceden account this month, but it turns out its not a tool I will be using. My project management system can create a grantt chart and that is sufficient for my company’s needs. I would like to request a refund.

Thank you, Edna

Plugging that into the script I set up for this (which I seeded with some examples of real responses in Help Scout):

Hello Edna,

I’m sorry to hear that you won’t be using Preceden. I’ve refunded the account for the remaining days of the month.

If you have any other questions, please don’t hesitate to contact us.

Not bad right?

Thing is, it doesn’t have any idea what it’s talking about. For example, Preceden charges yearly and I give full refunds (not prorated) so the response about the partial refund for the month isn’t accurate.

Still, pretty interesting.

What I’m working on at Preceden

A worthwhile investment I made a few years back was creating this list of timeline maker tools. It is IMHO the most comprehensive list out there and over time it has come to rank well for search terms like “timeline software”. Because Preceden is at the top of the list of course so it winds up driving a decent amount of leads and sales.

This week I added two new tools, Kronoli and ChronoFlo, bringing the total to 35 tools.

What I’m working on at Timeglider

I recently decided to shut down Timeglider, a competitor timeline maker tool that I acquired last year.

After I cancelled the active subscriptions, I emailed those people as well as anyone who had used it in the last year to inform them about the closure and how to migrate their timelines to Preceden if they wanted.

But what about everyone else who had used it prior to that? All time, Timeglider had about 500k sign ups. Emailing everyone though seems unnecessary because many of those never did anything in the app. Limiting it to those that had created at least 11 events got the number down to 100k.

I imported their detailed (email, sign up date, timeline names) into a database in Preceden and then set up a rake task to email a bunch each day to inform them about the closure (I chose a rake task because signing up and trying to use like Mailchimp to email 100k people with a new account seemed like a bad idea). Here’s an example email:

Hi Elijah,

You’re receiving this email because you signed up for Timeglider in 2018 and still have 2 timelines on the site.

My name is Matt and I purchased Timeglider from its prior owner last summer. There aren’t a lot of people using it these days so I’ve made the tough decision to shut Timeglider down at the end of November. This will allow me to focus my efforts on Preceden, my primary timeline maker tool.

Here’s a list of your timelines:

* French Revolution timeline

You have a few options:

* If you don’t care about your timelines anymore, there’s nothing you need to do

* You can download a CSV of your data so it’s not lost when the site shuts down

* You can download a CSV and import it into Preceden to continue working on your timeline

* You can use the Timeglider jQuery widget to host your timeline on another site

For instructions on all of these options and answers to common questions, check out our Timeglider Closure FAQs.

Sorry for any hassle this causes.

Please don’t hesitate to respond if you have any questions.

Matt Mazur

info@timeglider.com

I started small and ramped up the daily emails as I gained confidence that the message was solid and that Timeglider didn’t have any issues that might cause problems (it had a few).

The last of the emails went out today:

Preceden uses SendGrid to its emails, including these going out to the Timeglider users. Over the course of sending out these emails my reputation score dropped from 99% to 79% due to a fair amount of bounced emails (since many of these users signed up 10+ years ago) and a few spam reports.

Scores between 70% and 80% are categorized as “This is considered a poor reputation and you should consider taking action to identify and fix problems with your sending practices.” Fortunately since its through the 100k emails this should start to rise back up to shortly.

The responses were overwhelmingly positive with lots of people thanking me for telling them and wishing me luck on Preceden.

I haven’t set up reporting for this yet, but it did seem to drive a lot of Preceden sales too as these people moved their timelines over to Preceden.

What I’m studying

I finished DataCamp’s Introduction to Deep Learning in Python, Introduction to Deep Learning with Keras, and Advanced Deep Learning with Keras courses. The last one there was probably the most difficult course I’ve done yet. Four courses to go.

Also started reading Hands-On Machine Learning with Scikit-Learn and TensorFlow which is fantastic. For anyone interested in machine learning who doesn’t want to go through an online course, this book is a great place to start.

What I’m listening to

Chai Time Data Science, a podcast where the host, Sanyam Bhutani, interviews folks in the data science community with a focus on those who compete in Kaggle competitions. It’s got me pumped about diving into Kaggle in the coming year to level up my ML skills.

What I’m watching

Speaking of AI, I’ve been watching Raised by Wolves on HBO. If you like dystopian sci-fi movies, you’ll enjoy this show.

You can watch the entire first episode for free on YouTube:

That’s it for now my friends, thanks for reading ๐Ÿ‘‹