I also communicate this to people I work with since I'm not always in full ownership of what needs to get done. I am highly capable of deeply working on several wildly different things per day but if I get pulled around too much, sometimes for great reasons, then I can't maintain the energy for as long as I would if I fully owned my work. I think it's a compromise I have reluctantly (yet happily) made: sometimes allowing this to happen and being individually less productive in order to remove bottlenecks for the org.
My biggest issue is when I use 100% of that context-switching capacity at work and then have little to give after work. It's cyclical that I do this well, then poorly, then well again. But it does feel like I'm doing this significantly better than I was 3-5 years ago.
Bounce rate just means that someone came to your site and did not interact with the analytics DB in any other way. A user can scroll up and down 50x, stay until 29 minutes and 59 seconds, leave, and it will be a bounce. Bounce rate is a terrible leading KPI to look at. It's easy to understand and a classic vanity metric that doesn't matter. Applying an old favorite of mine: you can't pay your rent with a good bounce rate. Time on site is the same.
To combat this, you can set up scroll tracking. There are some GTM templates out there. Every time someone scrolls to a percentage of the whole of a page (for instance, 25% of the page but you can set it for pixels too), you can push data to the server. This artificially reduces bounce rate (yay?) but it gives you a much better idea of if people are actually getting anywhere in your content. It's actionable to know how far people are willing to scroll down your page.
Facebook Ads, like many platforms, have terrible placements by default that get mis-clicks that drive lots of clicks in the Facebook UI. Lots of these people click the back button before they even get to your site so analytics does not fire. A good example is an in-app ad where a user gets a reward for watching your ad. They may accidentally thumb it. Turn off all placements except Feed for FB & IG. These are the most expensive but the most reliable and highest quality for a small budget.
Ads are ruthless in the early stages unless you have a truly unique product/service and can run Google Ads. If I had a unique offering ("world's only data center ____ solution" then I would start there.
If you're a me-too company or just offering services, I would evaluate ads vs other channels like sales.
>I would evaluate ads vs other channels like sales.
This is probably the best advice when it comes to this specific topic; however, there are some other options which I still suggest you play in (see below).
>Ads are ruthless in the early stages unless you have a truly unique product/service and can run Google Ads.
There are entire companies that exist solely to dominate search results for branded and non-branded search terms related to businesses that already have product in market. You're NOT going to compete with companies spending multiple millions of dollars a month in Paid Search.
What you can do, however, is work on dominating Organic Search results via SEO. While these same companies are competing with best-practices in SEO, they cannot win with investment alone. You too can follow the same best practices and potentially get the search engines to pay attention to you too. If you can land on the first page of results, you have a real shot.
> Bounce rate just means that someone came to your site and did not interact with the analytics DB in any other way.
Oh god how many times I've tried to explain this to people. High bounce rate can even be a sign of a really good landing page in that if you don't interact with the content in any other way that could mean you found all the information you were looking for and didn't have to navigate elsewhere digging for stuff. Of course, if you have a conversion / funnel you'll be measuring that as well, and then bounce rate becomes even more useless of a metric.
With SQL, there are many different ways to write a query and to get the correct result returned to you. Instead of "1+1=2" being the only answer, it'd be more like: "1+1=2", "2+0=2", and "0+2=2". All are correct.
In my experience on SO with both SQL and Python, there are usually a number of correct answers for every question. How correct it is depends on things that usually aren't in the question: size of the data set, dependencies or processes that may break as a result of answer, etc.
I just double-checked my real-time analytics and looked back in the last 30 days to double-check. It's all coming through GA while I am in Firefox or other users are using Firefox.
The first vs. third-party cookies are confusing as hell.
I'm a marketer tinkering with Python. Since Python is so versatile, lots of uses for a marketer like me. I started off with a few Coursera courses going over the basics (Programming 4 Everybody) and read the book with it.
Then I tinkered with some basic functions: how to strip a list of URLs for a specific Product ASIN, automating some Photoshop image creation, and searching a 10k row Excel doc for specific phrases. All were bad at first, but they worked eventually.
I then did the Automate the Boring Stuff course on Udemy, super fun and deepened my knowledge. Helped me improve some of the programs and start working on others. I started to work with the Facebook Ads API and Pandas to automate reporting. So fun. That program is just getting to the Excel/Sheets automation part which will save me a ton of time every week. I spend a solid amount of time manually analyzing data each week. If I can cut that down, it'll get me quicker insights so better for my clients.
Again, nothing works incredibly well but it all works. And all of them save me time going forward. Automating image files will save a team member 3-6 hours/month and reduced errors by probably 90% (And their stress. We've already used it for 2 months so that's reduced their stress level from the errors they made manually doing it).
I'm basically just carving out an hour a week at this point after shooting for 5+/week for the first 6 months. I might increase it if I slow down on client work or hit a blocker that needs more time.
I subscribe to Always Be Learning, since that is a cornerstone of my own well being, so there is no real goal. I figure if I have a system for it then I'll make progress. And everything I learn is really a bonus for myself, my clients, or any developers I work with.
There's no shortage of interesting ideas to pursue with it so that won't be a problem anytime soon.
I've had to relearn concepts 2-3x and deal with silly mistakes I made, rewriting some programs.
I know a little bit about databases so that gave me a good foundation to work with. If I was 18 and starting from scratch, some of those concepts may have taken longer to learn.
Other than that, pretty awesome. I went in thinking that I would need a few hundred hours of work before I would feel comfortable and I think that was about right. So I just enjoyed it along the way!
As a climber and marketer, this is how I feel. You may need some help on sales copy but this is a marketing problem--who is this for and through what channels can i reach them?
There are definitely places where chalk is frowned upon. Try calling the gyms near those crags and sending them some free bottles to give out to their employees and gym climbers. Without any real differentiation for a large segment of climbers, the best you can do is use this small group of people who need to care about chalk residue and the even smaller group of people who do care, but don't need to.
I do think you could define the problem more clearly and try low-cost test channels like Google Ads & Facebook Ads (show ads in the geo's where chalk on rock is frowned upon).
After I read about the feelings about chalk from non-climbers, I can certainly understand why people care about it. The issue is real. It's just not a problem that most people know enough about to care yet. The challenge there is that it's hard and expensive to try and sell people on a new problem they don't know they have. It's much easier to replace an existing pain point they feel right now.
It's certainly worth talking about and fixing--the difference between segmentation and discrimination. Like in the HUD case mentioned in the article, discriminating based on age, gender, race, etc. are actually illegal. Not every industry is as regulated nor are they all at risk of it because of this.
To me, there's not a question of "should we make this better?" because we're talking about basic rights: the right to not be discriminated in the pursuit of a roof over your head or a job to pay you a living wage (housing and employment). IMO, a very different question when you advertise anything outside of those basic rights. Plenty of grey area to talk about there.
If I’m advertising a $20M luxury penthouse overlooking Central Park, am I permitted to advertise only in the WSJ and Robb Report (or whatever rich people read)?
Does that change if I learn those publications skew overwhelmingly male?
It's more explicit now. Most sites add the Facebook Pixel as they want to track conversions on their site. Most brands have this on their site. Facebook can do all of the analysis that Google can with that, such as knowing how many people add something to their cart, checkout, etc.
The power is in combining that data, like one of the grandparent comments mentioned. They will know if you buy a SUV (since the dealer uploads the data as an offline conversion) and that you're browsing baby clothes on Walmart/Target. Now you're a "new or expecting parent".
Some of these interest categories are not that explicit but the lookalike audiences are. That's a whole other post :)
Some SMB's that I have met over the years are great at pretending they don't have money when hiring but are very profitable. I think that fits the "bad company, no financing" and is worth mentioning.
This thread is interesting because we're talking about success for different people. Success for the founder? The money? The employees? The answers are relative to the stakeholder we're talking about.
Success as a product company relative to others. I'm talking about simple selection bias.
A no-financing company with a decent head count is probably in the top 1 percentile among peers. Chances are they're delivering real value.
A VC backed startup hiring a bunch of people is perfectly average. The top 1% for startups would probably be post-IPO/exit/very-late-stage.
So it seems perfectly normal to me a VC backed startup in most cases will look like a total trainwreck compared to a bootstrapped company of the same size.
The vast majority of bootstrapped companies die before they even had a chance to hire anybody. Unlikely you'd ever have to deal with them.
Yea, the functioning/viable business piece has a place in this discussion. I can understand why the author wouldn't include it but it serves us here. To take on debt like mentioned, you have to have some confidence in the business model and not be searching for product/market fit like many early-stage companies. If you already have cash flow then you can leverage it.
My biggest issue is when I use 100% of that context-switching capacity at work and then have little to give after work. It's cyclical that I do this well, then poorly, then well again. But it does feel like I'm doing this significantly better than I was 3-5 years ago.