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Two kinds of people

Some people will lie, cheat and steal if they think they can get a few bucks out of you. Unfortunately, the really smart ones find ways to do this legally.

Other people will stop you on the street if they see something fall out of your pocket that looks like it has the Visa logo on it, and make sure you get it back. If they find a wallet with cash and credit cards in it at a busy airport, they dig through it, find a business card, and call someone who might know who the Jane Johnson is whose name is on the credit cards. A week later, you get your wallet back, with everything intact.

The best way to do business is to talk to new people you meet like they belong in the “trustworthy” category, and write agreements that assume they might actually be in the other one.

Never do work for anyone unless you are either okay with doing it for free, or you have an agreement.

To repeat: NEVER do work for ANYONE unless you are either okay with doing it for free, or you have an agreement.

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Check your email newsletter for spam words

It’s not in vogue anymore to look for specific words that might be considered spammy.

Email filtering software is too opaque and with all the AI and so-called “AI” floating around, doesn’t it know better than to consider specific terms as being spammy?

Even if that’s true, you can bet there are still terms out there that will get your email stuck in some spam filters.

There isn’t just one spam filter out there; there are multiple companies, each with their own secret sauce. With some recipients, their email might go through two or three different spam filters before finally making it to the inbox. Not checking your email for spam phrases is making a bet that none of the spam filters used by any of your recipients rely on good old-fashioned lists of spam terms anymore.

Check your email for spammy terms

You’re in luck; we couldn’t find anything like this online, so we made our own tool to check email content for spammy words.

We recommend using this with tools like mail-tester.com for best results. This quick, simple list doesn’t check anything except the text you copy and paste into it. No alt text checks, no link checks, no list-unsubscribe checks.

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I wrote this entire post while waiting on hold.

Customer service is marketing.

I want a car loan. I won’t say I need one, because it’s not a need, but I want a car and so I want a car loan.

I went to a nice dealership and spoke with a nice salesperson who put together some information on a nice loan for me that I took home.

I have a question about the loan. I looked on your website, and I didn’t find the answer. I looked for an email address. None. Okay, I can send a message online. Fine, let’s try that.

I put in my information and tried to log in. You didn’t find an account: OK, so the “send a message” function is only possible if I am a customer. I am a customer only if I have a loan. But the problem is, I’m not willing/able to take out a loan from you until I have my question answered.

I dig some more. I found your phone number, finally — it wasn’t easy. Okay, your phone service is available 12pm – 4pm, Tuesday through Friday. Wow, 16 hours a week! Luckily, it’s Tuesday, so I can call tomorrow afternoon during my work day — the luxury of flexible hours.

I called your number. The automated message announces that sending a message online is better and more efficient for your processes. I’m starting to get annoyed. The automated message announces that I can find information about your business hours and services online, and I’m numer 23 in line.

A few seconds of silence.

The message repeats itself. All operaters are reserved, please hold, we will serve you as soon as possible… etc. I’m number 22 in line.

30 seconds of silence. All operaters are reserved, please hold, we will serve you as soon as possible… etc. You are number 21 in line.

Etc.

Etc.

Etc.

I’ve heard your message at least 40 times now. Am I spoiled? Because I’m annoyed.

I really don’t want a loan from you anymore, no matter how glossy and beautiful your website is. No matter what lovely photos you put in your brochure at the dealership.

Sincerely, 

A potential customer.

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How to track pageviews after the initial landing page view using Google Data Studio

When you are looking at Google Analytics data for ads, the real, important numbers are often slightly hidden. For example, if you want to see what pages users are visiting on your site after you just spent $5 per click to get them there, you will need to exclude the landing page views.

Why exclude the landing page views?

If your user clicks on the ad completely on accident, the browser starts to load example.com/widgets/amazing-landing-page, and then the user hits the back button and is off your site, that will still fire a page view!

If you are expecting your users to be moving on to other pages on your site after hitting the landing page (this is especially the case if you are landing them on the homepage), it is very instructive to look at the page views that were not landing-page views (entrances) so you can see what your users are doing.

Are they moving on to any other pages at all? If so, which ones? How many people from your campaign that is landing on example.com/widgets/amazing-landing-page move on to example.com/pricing?

What you should know

A “landing page” is the term used when you’re looking at a full session. It is the page the session started on. So “landing page” will give you a URL, not a number of visits.

When you’re looking at an individual page, and you want to see how many sessions started on that page, the metric you need is called entrances.

How to see the non-entrance pageviews for each page in Google Data Studio

  1. You will first need to have access to a Google Analytics account for the site you want to analyze
  2. Open the Google Data Studio report you want to edit, or if you don’t have one, create a new report and connect the Google Analytics View you want to look at.
  3. Click “Resource”
  4. Click “Manage Added Data Sources”
Manage Added Data Sources Google Data Studio
  1. Click “Edit” for your data source
  1. Click “Add a Field”
Add a field Google Data Studio
  1. Name your field “Pageviews minus landing views” (or whatever your prefer).
  2. For the Formula, use Pageviews – Entrances.
  3. Click Save.
  4. Click Done.
setting up pageviews minus entrances google data studio

That’s it! Now you can use your new Metric in any chart in that report.

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How to extract the plain URL from a URL with query parameters using Google Data Studio

When you have a website, you often have product category pages or search results pages that include parameters. Something like this:

example.com/shop/product-search?term=lawn-widget&maxprice=500

In this example your user searched for the term “lawn widget” and set the maximum price to 500 $/€/etc.

When you have searches for 2,000 different products, it makes it impossible to use your standard Google Analytics data to cleanly compare use of the page overall — eg, the /product-search page.

Here’s how to get just the clean URL in Google Data Studio.

This is handy because it works for all historical data in Google Analytics, whereas if you set up a filter in a new view, that will only apply to pageviews from there on out.

What you’ll need

  1. Google Analytics set up on your website
  2. Access to the Google Analytics account
  3. Create a Google Data Studio report

Steps to extract the page URL without the query parameters

  1. Open your Google Data Studio report if you have one, or create a new one and add the correct Google Analytics account as your source data
  2. In the menu, click “Resource,” then click “Manage Added Data Sources”
  3. For the GA data source you want, click “Edit”
  1. Click “Add a Field”
  1. Name the field “Page URL with parameters removed” (or whatever you prefer)
  2. Copy and paste this formula into the Formula field.
REGEXP_EXTRACT(Page, "^([\w-/\.]+)\??")
  • If you get an error message, manually delete and re-type the quotation marks in the formula.
  • If you still get an error message, re-type with a double backslash in each spot where there is a backslash:
REGEXP_EXTRACT(Page, "^([\\w-/\\.]+)\\??")
  1. Click Save.

  1. Click Done.

You can now create a chart using the new field as a Dimension.

Bonus: To remove the underlining in a chart

  1. Select the chart
  2. Click the link icon next to the dimension name

  1. Change the Type from URL to Text