How I’m building a job board for Data Analysts, Update #12 - 2023 Full Year Recap

Hi all,

on Dec 19th I launched DataAnalyst.com - this is the 12th update - looking back at the full year 2023.

Want to make sure I document the journey, and keep myself honest, so each month I will be making a post about the statistics, progress, some thoughts and what are the next steps I want to be focusing on.

So, just a reminder that early stages vision is to become the #1 job board for data analysts - hand-picking interesting data analyst job opportunities across industries.

TLDR:

It’s going to be a long one, so I’m going to share one key learning that I’m taking from the last 12 months, and that I would like each and every one of you to at least think about.

The power of consistently showing up - how much can one achieve, if they spend 30 mins, every day on an activity or a set of activities contributing to a goal they have in mind.

Even though from the $ monetary side it’s been an unprofitable year, the amount learnings I’m taking from operating the site can’t compare to doing anything else in my career so far.

From developing skills to build the site, experimenting with growth tactics, writing and creating content, tinkering with UX/UI design, to actually making at least couple of sales and mainly, helping people on both sides of the job market.

30 mins, every day - it’ll all add up

Two graphs to kick us off, monthly stats to see the month on month progression, and full year stats to see it all come together.

DataAnalyst.com Statistics

Monthly view of growth over 2023

Full Year 2023

Where we started?

When DataAnalyst.com launched, I aimed to bring data analyst jobs from the US, UK and European markets.

After 3 months, I decided to no longer cover Europe & the UK region, putting the main focus on
the United States.

There were couple of reasons for that.

First, salary transparency is non-existent in most European markets. Second, out of those jobs that were posted and included salary, majority of them would be in the local language. All in all, I simply realised that I wouldn’t be able to consistently add quality data analyst jobs for the individual market, which would eventually lead to poor job seeker experience - simply put, if there aren’t quality enough listings being added over the course of the week, you’ll extremely likely not to come back.

UK market for similar reasons - lack of salary transparency, but also the market is largely being operated by recruitment industry, resulting in lower number of direct company listings.

Tech-Stack

Webflow - Website + CMS
Jotform - Form + Stripe payments integration
Airtable - database with job posts
Make - automating the flow
Placidapp - generative pre-populated images for social media
Jetboostio - smart filters + autoarchive + some other customisations (could be replaced by Finsweet for filters, which is free, but haven’t had a chance to dedicate time to making it work)
Buffer - social media posts scheduling
EmailOctopus - newsletter
Nocodelytics - for visitor, pageviews and apply now button tracking
GSCTool - for faster Google indexing
Ahrefs - using free version, also offering monthly free credits to conduct a free site audit

What we’ve done?

Paid job posts

To get this one out of the way.

From monetisation perspective, my original thinking was that paid job posts will be the primary revenue driver. While that may in the future be the case, at least in the first year it fell very short of expectations.

Simple reason -  I did not really do any sales. Honestly, full stop.

I can’t expect organisations to proactively find the site, with very little historical authority, and pay for a sponsored job post.

Now, saying that, this is still a two-sided marketplace - applicants looking for roles, and companies looking for qualified candidates.

I believe I couldn’t convincingly sell the site to organisations in the first year, and therefore decided to brute-force the job postings side first.

What this means that every single day I shared curated data analyst jobs (all including salary), interviews with experienced professionals, and salary insights across experience levels, industries and various states.

All in the hopes of being able to consistently attract the best data analyst talent on the market to the site.

On a positive note, there were two organic paid job posts, and couple of experimental collaborations with companies  who found the site, and reached out.

I’m very happy to say that after struggling on other platforms, those who posted with DataAnalyst were able to make their hire within one or two weeks after sharing the job opening - that to me indicates the calibre of data analysts visiting the site daily is extremely high, exactly what I was building toward.

Now I have multiple successful examples that I can build on going forward. (That doesn’t change the fact that I still very much dislike selling, but at least that’s a “me” problem)

With this out of the way, onto some of the activities that I spent time on, and what were the outcomes.

SEO optimisation

I’ve spent some time over the summer using tools such as SEMRush / Ahrefs / Moz to run some high level audits and understand how the site performs on the SEO front.

This led to a lot of time spent on making significant on-page changes to improve keyword optimisation, rewriting meta descriptions and adding alt descriptions to all the images on the site.

The structure used to achieve this, was to programmatically target the following long tail searches:

• Data analyst jobs in p(State) - i.e Data analyst jobs in Illinois
• p(Industry) data analyst jobs - i.e Financial data analyst jobs
• p(Industry) data analyst salary - i.e Financial data analyst salary
• p(Experience) data analyst jobs - i.e Entry level data analyst jobs
• p(Experience) data analyst salary - i.e Entry level data analyst salary

What I’ve also done, is to optimise data analyst jobs for Google Jobs Schema - so all the jobs that are posted on the site, are immediately also listed on Google Jobs - therefore expanding the reach.

This is probably something that could (and should) have been done a lot earlier. Having said that, it’s now something that I pay attention to with each update that I make on the site.

Results:

Personally, as mentioned before, I hate this - I am publishing somehow duplicate but not exactly duplicate pages, for the sole purpose to please the SEO overlords. I understand that going step too far would have a massive hit on the user experience, so I am trying to be very intentional to ensure the key information is consolidated and easy to find.

Overall, the content of the site is now ranking between 1st - 100th result on Google, for approximately 3,100 search keywords.

The biggest win is being able to rank between 10th - 20th place for “data analyst” search, as well as consistently showing up high enough to get some attention for “data analyst jobs” search, which drives most of the organic clicks.

Between optimising for Google Search Results, and Google jobs, the site has seen approximately 1,21 million impressions on Google - almost 1 million happened from September to December, right after my summer optimisation efforts.

Backlinks

Similarly to SEO optimisation, having authoritative sites linking back to DA.

In the first experiment, I found a .xls spreadsheet online, with approximately 1,700 educational institutions in the US and their admissions’ email address.

Mistake #1 - timing - I thought with Universities/Colleges starting in September, it would be a good time to get on their radar - just as they new students coming in and discovering what those institutions have to offer. Truth is, it’s also the time when you have an enormous amount of freshers spamming the admissions office looking for directions to their dorms.

Mistake #2 - audience - on the topic of admissions office - they do not care of anyone reaching out to build partnerships, literally, that’s probably the last thing on their mind.

Put the two together, and I ended up with 2 (thanks but no thanks) replies out of appx 800 emails sent. Silver lining - the email still had appx 50% open rate, so no harm done to email deliverability (spam score).

Learning from the experience, I decided to tailor my approach.

I’ve pulled together a spreadsheet with information about the University, Career centre or Course detail (i.e MSc in Data Analytics etc), direct link to the section where they are currently sharing resources, and emails for both someone from the department and the career centre.

Results:

With 30 institutions identified, results where much better this time (after appx 5 follow up emails, because, yeah…):

Uni 1 - gained 1 backlink to both DA and BA,
Uni 2 - in the review process to be added on the site in their next refresh in January 24’
Uni 3 - call scheduled to discuss partnership opportunities

I’ve also hit the popular directories / communities (such as ProductHunt or YourStory) to submit DataAnalyst on their site, with some backlinks gained as a result.

As a side-note, some people will claim that getting listed on University’ career pages is extremely easy for niche job boards - after-all, the job board is providing free-for-students alternative to find opportunities to kickstart their career.

At least from my experience, this couldn’t have been further from the truth, so don’t count on your backlinks before they are linked.

Newsletter

When starting, I wanted the newsletter to be sent on a weekly basis, containing the latest jobs. The more I thought about it, the more I became against the idea - after-all, people could visit the site and see, why spam their emails? At the same time, the point of the site is to help people find a role - once they would, they wouldn’t really need weekly emails with latest jobs.

Secondly, since I really haven’t put much thought into the structure of the newsletter, I had no subscriber segments identified - so even if I wanted to send out tailored job alerts, the current workflow simply doesn’t allow it.

So, for now the newsletter will stay as is - sharing important guides updates, monthly market summaries, new interviews, and highlight promoted job opportunities.

Results:
Overall, newsletter open rates have stayed pretty consistent, at around 60%, with CTR rates hovering between 5-7%, indicating that people are reading, and are engaging.

I don’t want the list to grow just for the sake of a bigger number, so I did go through pruning, unsubscribing people who haven’t opened any of my emails in the last 6 months.

Market Summary

Since the first month, I wanted to utilise the job data available to create monthly market insights - a deep dive into the data analyst job market, where we can have a look at the job openings and provide insights on the latest hiring trends - which industries are hiring the most, remote working and salary fluctuations

With me being the one curating the jobs that end up on the site, it could be argued that these trends are not really representative of the overall market.

Result:

Saying that, I do still believe that even the said monthly snapshot, and the month-on-month comparison can provide some useful tidbits and observations - so, every month for the past year, a monthly job market summary was published.

I’m perfectly happy to accept that it does not provide extraordinary value, primarily because:

1. even if only few people find it useful, that’s a win in my book
2. the content still shows up in search results, helping drive more people to the site
3. it provided me the platform, the structure and the data required to consolidate all the information to create the Data Analyst Salary Guide.

Salary Guide

With approximately 1,650+ data analyst jobs listed on the site up to this date, analyze data to develop data analyst salary guide (updated quarterly)

Results:

Visitors can now find the data analyst salary breakdown, by these areas:

Industry - breakdown by specific industry, overall minimum, maximum, median and average salary + salary breakdown by years of experience

Years of experience - breakdown of all jobs on the site by years of experience - entry level (0 - 3 years), senior (3 - 5 years), lead (5+ years)

State - this is where it gets tricky. Now, as it usually is with this kind of exercise, lumping the data all together you come up with an insane range. On the other hand, if you split the data in 52 different ways, you’ll get a whole different set of issues where N is not large enough to draw any conclusions - and for some states, there’s simply no data at all (not to single any state out, but I’m looking at you, Wyoming).

Company view - as an experiment (and primarily targeting SEO benefits) I’ve also included average data analyst salaries at all the companies that are listed on the site.

Truth be told, until the amount of jobs per company gets into at least double digit numbers, it’s probably a useless metric, but I am hoping to rank for some of the long tail “what is a data analyst salary at X” keyword searches.

As the site grows, and the number of jobs on the site increases, I do still believe that I’ll be able to bring an addition source of information about salaries, complimenting those already available on other sites.

Interviews

Alongside the job board, my other focus is to bring interviews with data professionals across the experience levels to share their journey, tips and advice.

Overall, we’ve published 8 interviews, that I believe bring different point of views, stories of growth and sharing unique paths that each individual took to navigate their careers.

There’s an absolute ton to learn from these:

• how to land data role internally within an organisation
• the power of showcasing and reframing your experience outside the direct data analytics field
• and how moving into more leadership roles requires more than just being a data wiz

A lot of the people who took their time to share are also Redditors, so just wanted to give a shout out and say THANK YOU again.

Insights from these interviews are also incorporated in the how to become a data analyst guide, which was published in the second half of the year.

How to become a data analyst

Over the long term, I would like DataAnalyst.com to grow - not just as a job board, but also as an educational hub - from interviews with experienced professional, best practices, to advice about getting into the industry.

I wanted to build even further on our knowledge base of interviews, insights and resources, and put it all together in the first version of a guide to becoming a data analyst.

Result:

First version released, with the guide covering topics such as:

• understanding the role and responsibilities of a data analyst
• becoming a data analyst, and what it obtains - from education, experience, to technical and soft skills
• the well known not-so-secret hack - building your own portfolio
• career development and salary guide (yes, our own!)
• incorporating insights and quotes from interviews with experienced professionals

The goal is for the guide to be a living document - constantly evolving and incorporating new findings, advice and insights.

What’s next

Now that the structure and processes are fairly optimised, and the site getting traction with attracting aspiring and experienced data analyst, the main “thinking / action” that I have on my plate is to figure out the path to successful monetisation.

Some of the avenues that have proven to work in the market:

Company paid job posts

• as previously mentioned, this is where I thought revenue would be coming from
• will require selling and outreach from my side
• could consider both one off payments but also subscription type of a service

Reverse job board / candidate database

• users create profiles, specify their availability (freelance, contract etc) companies pay access to that pool of candidates - this requires very little screening, and the main effort is just in developing the membership aspect
• in addition to this, it would be an interesting idea for member profiles to look like mini-portfolio sites - which is something that pretty much all data analysts should have and be able to share

TopTal-like proposition

• heavy screening and testing candidates to only have the top 3% of data analysts who are available for freelance/short term contract work
• requires a lot of effort, particularly for the screening / tests / attracting the best
• company pay for access and % of salary upon hire

My main concern with both Reverse job / Candidate pool is that once you start handling user information + sensitive info in CVs, I think it gets really, really tricky with privacy laws, data storage and security overall - particularly a danger of laws being different across regions.

Ads

• not a fan of having ads on the site, but maybe could be tailored sponsor ads to the audience (data tools, data courses)
• would open up opportunities for sponsored posts in the newsletter

Coaching / interview / CV help

• would not prefer this, not really scalable + there’s tons of people more qualified than I am

Subscription based for data analysts

• I’ve noticed some niche job boards that have struggled attracting companies, have shifted to subscription model where applicants pay a monthly fee to access job opportunities
• Personally not a fan of this, it’s stressful enough to be looking for a job, let alone to also pay for access, however, job boards that went this route found that people were willing to pay and support, and eventually they were able to make profit and reinvest back into growing the site

Things in the pipeline

• New data analyst jobs, added daily
• Actually launching the weekly newsletter with the pick of best jobs directly to your inbox
• Monthly US data analyst market summary
• Improving the overall site experience (this one is a never ending activity)
• Continuing to bring you Data Analysts across their experience levels, to share tips, tricks and their thoughts

3 ways you could help

1. Looking for a new challenge? Check out the website - I’m adding new jobs daily
2. Looking to hire a data analyst to your team? Do you know anyone looking to hire? Shoot me a message at alex@dataanalyst.com and I’ll upgrade your first listing for free!
3. As I mentioned, we have an ongoing “Day of a Data Analyst” series. For those of you who are open to do an email based interview about your data analyst career journey, please just send me a message and we’ll organise something - would love to get you featured and share your experience with our readers!

Thank you all again, and see you in a month.

Alex