Explaining too much

One of the things that i occasionally think about when writing the blog is whether I’m providing too much information.  Not so much for my competitors as for my customers – the entire issue of explaining how a sausage is made.  Of course, we aren’t making sausages but at times, I’m not sure it makes much sense to provide vast swaths of information either to current & potential customers that they might not want or need.

It’s quite clear we run a business. Like most for-profit businesses, the goal is to make as much profit as possible. Since the sole-owner of this business is myself, that translates eventually to making myself the most money.  On the other hand, stating that fact up-front can annoy people or put them off. Sure, we all understand that businesses are there to make a profit, but flaunting that fact can often be a detriment.  Small businesses are meant to be an underdog – underdogs don’t drive Porsche’s. (And no, I don’t drive a Porsche. I’ve got a 10 year old Honda Civic if you’re curious). Still, it’s one of the reasons why I don’t talk about our actual sales here – it’d be counter-productive.

Another aspect of the business that doesn’t seem to make any sense to go into too much detail is the margins. I’ve talked about it before, about the way choosing the right markup is important.  I’ve also talked about the pressures from customers who would always prefer a lower price, and to some extent, the pressures from our publishers / distributors as they increase costs to us.  Yet, breaking it all down doesn’t seem to affect or benefit sales and might even harm them, as customers start feeling put-upon.

Then there’s the boring things that we do on a regular basis.  Who wants to read about cleaning toilets or chasing off the homeless from our docking bay? Of cleaning up wastes and other, nastier items. Or how often we have to do stock counts and re-arranging our warehouse to make things work just a little more efficiently? Or the numerous phonecalls and excel sheets we use to keep track of data. None of that is either exciting or interesting, and it takes away some of the ‘magic’ of making things work.

Of course, there’s the other side of the equation. The blog itself isn’t too prominent and those who come here to read are interested in details about the business. Compared to the vast majority of our site visitors, actual visitors to the blog are miniscule. So perhaps these people really do care about our the boring aspects of business.

The problem with attribution

I’m going to get a little technical here. I’m going to talk about online marketing and attribution. Firstly, as an online store, we are able to track a lot of the data from visitors who come to our site. There are 2 major ways this data is collected – logs & cookies. Log files tracking basically runs on the basis of tracking the requests a customer makes to our server. Every time you load a page, you request information from us to load it – we can track this data and theoretically assign it to individuals. With cookies, we drop a ‘cookie’; a piece of code into your browser which tells us what you are doing on our site. Cookies are also useful for minor things like keeping track of what you have in your cart, whether you are logged in and the like.

The big difference between cookies and log file tracking for the purpose of analytics is that customers can clear or refuse to take cookies at anytime. If you do that, we can’t track your data if we are just using cookies. For log files, because you have to call information from our site, we can track every visitor. The minus of course is that it’s very hard to track visitors over multiple sessions. And yes, I’m simplifying greatly. If you’re curious, Starlit Citadel do a bit of both.

As an online store, what we want to know / attribute is what kinds of marketing work for us. We want to know if advertising on Facebook makes a difference rather than say, Youtube advertising. I’ve discussed these kind of decisions before, but let’s talk about one of the biggest ‘plagues’ for us – attribution.

Traditionally, the only way to tell why a customer purchased was via their last clilck – the last place they came from. This meant that if a customer came to us straight from a bookmark and/or typed us in directly, we’d consider them a ‘direct’ sale and if they came from a Google search, we’d attribute the sale to Google. Of course, how many of you have read an article or thought of a store you wanted to visit, typed in their name in Google and gone to the store that way? I know I have, numerous times. Now, we’re attributing a sale from other forms of marketing (say a mailer sent to you) to Google because that was the ‘last click’.

In the past, we could filter some of these out by ignoring any searches that used our brand name. These days, Google has removed all that data, ‘stripping’ it in from the information that gets sent to us in the quest for privacy (really, just to make us pay more for advertising).

These days, more information is being added by tracking visitors when they leave the site. For example, Google now ‘tracks’ other interactions, keeping data and how you interacted with our other forms of media like Facebook, Twitter, etc. Again, there’s a lot of leeway here – you could see a Twitter post by Starlit but you don’t click on it, so it wouldn’t get tracked. Still, it does keep track of what you interact with, before you buy.

Now, let’s step outside of talking about our main tracking platform (Google Analytics) and talk about advertising networks. Most other advertising networks, for their own reasons, track conversions.  These conversions can vary depending on how they attribute the data and it can often not lineup with the data you get from other analytics you might have.

Advertising networks might be attributing conversions over a period of time (i.e. you clicked on an advertisement they served, so if you buy in X days, they’ll consider it a ‘win’ for them), based off impressions that you might have on the advertisements and the like.

At the end of the day, when you are looking at this information; you need to work out which data you trust, understand what the data that you are trusting is based on and then, most importantly, decide what your cut-off point is.  Are you willing to take an ROI of 3? 5? 10?