When shark roars like a lion: Recovering $400k
Just when you thought it’s always bad news, there’s a small silver lining.
You are probably aware that the TV show is often used either in ads or in emails targeting a more gullible audience, that’s no surprise.
The surprise here is that one shark, Barbara Corcoran, was actually a victim of a scam where her bookkeeper believed it was one of Barbara’s assistants asking for a payment over email. So they wired almost $400k to a German bank account.
Luckily, Barbara and her team managed to freeze the transfer. Her bank communicated with the recipient’s initial bank, before the money was supposed to be transferred to a Chinese account.
It’s weird how even such people can fall victims. Stay safe out there with your (bank and ad) accounts. Usually, the story ends way worse.
New toys to reload your marketing armory
The Crew came across a bunch of tools and we thought of compiling them here under one post, so you can upgrade your armoury with some new toys.
+ Autodraw: The first one here is developed by Google’s Creative Lab and helps you create stunning drawings on your computers, tablets, and smartphones in just a few clicks.
It basically pairs machine learning with drawings from talented artists to help you draw stuff fast.
+ Google Lighthouse for Firefox: It’s an open-source, automated tool that helps you in improving the performance, quality and correctness of your web apps. It uses PageSpeed Insights API to generate a Lighthouse report which even a non-geek can use to easily read summary reports and share insights with clients.
+ Tag Snag: Featured on Product Hunt this week, Tag Snag is a handy Chrome extension that helps you improve your YouTube SEO by extracting the tags used by the creator of any YouTube video.
+ Trends & Tenor: If, like us, you struggle to find the perfect GIFs to go with your content, Google Trends has teamed up with GIF platform Tenor to create a new tool which highlights key GIF trends by celebrity, action, emotion conveyed and more.
You can test the last one by sending us your favorite GIF 😉
🥳 Celebrating the launch of Pipeline by Jumbleberry means a hefty bonus for you!
Oh, you didn’t hear about Pipeline?
Pipeline is a specialized network, with deep relationships with Advertisers, Affiliates, Vendors and Partners that go back over 10 years.
It is an affiliate program built from the ground-up from Jumbleberry’s People, Process and Technology approach that is their Performance Marketing Engine.
So, to celebrate the launch of Pipeline and a cool new look there are a few bonuses on the line for you to take home. Ready? OK!
Pipeline is specifically built to support high volume affiliates and advertisers who capitalize on market trends. This means frequent campaign launches and high conversion rates to maximize short term gains.
So, if you are an affiliate interested in capitalizing on trends by running bigger campaigns with the highest possible EPCs, clockwork-like weekly payouts and the support of the best people in the industry…
What if you are an advertiser looking to have a cap filled with quality, high volume traffic for your newest offer?
Using machine learning to help with your keyword research
One of the basic foundations of any SEO strategy is solid keyword research, which involves lots of time, effort and hours of patience.
Like Andy Chadwick, our keyword research sheets often exceed as much as 20k-50k keywords which we then try and segregate under different categories and sub-categories.
But is there any way to automate the process? Nothing can really replace human intelligence especially when it comes to keyword research but sure, there are parts that can be automated, saving you hours of time.
How? Andy figured out a way to do this using BigML, a freemium tool that helps you speed up your process of keyword categorization.
For most of us, the unpaid version of the tool should do the bulk of the work, unless you want multiple people working on it at the same time or want all available features.
So, what does the process look like?
+ Gathering the raw data: Andy takes an example of a clothing site to guide us through the process.
- He takes a few URLs from the site so he can group his keywords into categories and subcategories. To begin with, grab any of the URLs from the site and plug it into SEMrush.
- Filter by the top 20 keywords and export.
- Drop them into a spreadsheet and add the headings “category 1” and “category 2”.
- Repeat the same process for one of your competitor’s keywords ranking well.
- Export the keywords from SEMrush, add them to your sheet, drop the categories down and de-duplicate the list.
- Get rid of branded terms using a quick “Find and replace” tool.
+ Training your machine learning model: This is where you train the machine learning program for categorizing the keywords on your behalf.
- Save the above keyword file in CSV format and head to the BigML tool.
- Head to the sources tab and upload your training data.
- Once it’s loaded, click the file to open up the settings.
- Click the “configure data source” and ensure the categories are set to “categorical”.
- Close the “configure source” settings and click the “configure data set” button. Then deselect “category 2”.
- Rename the “dataset name” to something like ML Blog Data (Category 1) and click the “create dataset” button.
- Select your new data set in the “data sets” tab.
It has now “tokenized” all your keywords. From here, there are so many exciting models you can train, but for now, let’s stick to the most simple one.
- Navigate to the “one-click supervised model”.
- After it’s finished computing, you’ll see a decision tree like this:
What it has essentially done is that it has created a series of “if statements” based on the data you’ve given it which it will use to work out the probability of a category.
You can also create an “ensemble model” which will give you even more accuracy. You can also split the data and run a controlled test on it so you can see how accurate it’s going to be before you use it.
Anyway, going back to the original process, you have now created a model for categorizing the keywords in category one and can repeat the same for the other categories.
Next, you can plug some competitor domains into SEMrush at domain level and export their whole site’s ranking keywords.
There is also a way to use BigML’s API to categorize your keywords and it’s a really fun process to go through.
Check out the detailed post from Andy here for a more granular and step-by-step walk through of the whole process along with visual charts.
- FACEBOOK ADS: Alex Fedotoff shows off a user-generated content cheat sheet that you might want to take a look at.
- E-COMMERCE: Dan Barker has a list of over 150 e-com tips on Twitter and you can read each of them by category right here.
- SEO: A quick rundown from Tayyab Saqlain Zakki about what he did to rank for over 10k keywords in just under 2 months with a new website.
- FACEBOOK: At least 467 FB and 1.2k IG accounts removed that spent over $1.2M according to the company’s latest Coordinated Inauthentic Behavior Report.
- TIKTOK: Creators get more analytics for TikTok. Unlike previous platforms, TikTok really wants to give its influencers powerful data as soon as possible.
- DROPSHIPPING: Wondered what are some alternatives to ePacket? Check the video by Dayu and see if his suggestions help.
- ATTRIBUTION: It’s always a challenge, even when using powerful tools from Google, FB and others. One thing to help your attribution model? Correct use of UTM parameters. Ahmad Kanani brings the complete guide in this CXL blog post.
Forward I’m heavy, but backwards I’m not. What am I?
You can find the solution by clicking here.
Cool tech, (funny) business, lifestyle and all the other things affiliates like to chat about while sipping cocktails by the pool.
Meet the real Hugo Boss, previously known as Joe Lycett
When companies get really protective of their name, they end up causing the opposite effect they desired.
Take Hugo Boss… They seem to hate when any business, no matter how small, use the word “boss” or similar in their name or in their products, sending countless cease & desist letters. Even to charities.
Comedian Joe Lycett took it upon himself to do something about it. Something pretty extreme.
He even came up with a signature that pretty much reveals his feelings towards the company Hugo Boss.
So next time you mention Huge Boss, make sure you specify if it’s the company or the comedian. Because he’s getting hella’ popular and we might not know which one you mean!
Actually, Hugo Boss the person just overtook the company when it comes to Twitter followers…