Source: SEO blog
Less is more when it comes to online advertising, research suggests
Brand recall may decrease when ad exposure rises too much, according to newly-released research. Four or more digital ad exposures brought brand awareness rates down by 3 percent, while two and three online ad exposures increased brand awareness by 6 percent, new study data from Sublime has shown. Campaign
Google Makes YouTube Masthead Ads Available to All Advertisers
Google has eased restrictions on YouTube masthead advertisements, making the premium placement ad type — which had only been offered as a part of full-day takeovers — available to all advertisers. Marketers can also now buy on a cost-per-thousand basis, the search giant recently announced. Search Engine Journal
Social influencers see stardom potential on LinkedIn and Pinteres
Pinterest and LinkedIn (client) are increasingly seeing social influencers utilizing the platforms, and CNN takes a look at how creators such as Goldie Chan and others are finding new audiences and success with online video. CNN
New research uncovers biggest differentiator of effective marketing: Bravery
Bravery plays an important role in digital marketing efforts that go on to win awards, according to a newly-released analysis looking at some 6,000 award-winning campaigns. The new Effie awards analysis looked at successes that often stem from being different and brave. AdAge
Facebook is Letting More Advertisers Place Ads in Search Results
Facebook has begun offering more advertisers options for inserting ads within search results on the social giant’s platform, including new news feed campaign options for marketers, but without keyword targeting yet, the firm recently announced. Search Engine Journal
LinkedIn rolls out new feature to help SMBs promote their service offerings
LinkedIn has begun offering small and midsize businesses new options for showcasing service offerings directly within profile pages, offering digital marketers greater client exposure possibilities, the firm recently announced. Marketing Land
Amazon Takes Google Ad Market Share, Microsoft Advertising Holds Strong
Amazon cut into Google’s advertising market share during the second quarter of 2019, garnering ad revenue growth of 53 percent for sponsored brands and 102 percent for sponsored products, while Google spending growth slowed from the prior quarter. Microsoft’s Bing also saw desktop ad spending growth, its strongest since 2016. MediaPost
Twitter ad revenue up a fifth as user growth returns
Twitter saw digital ad engagements rise 20 percent for the second quarter of 2019, accounting for $727 million, while the firm also saw an average monetizable daily active usage (mDAU) increase of some 5 million, several of the positive results Twitter recently announced. The Drum
With new conversion data tool and product updates, Pinterest solidifies pitch to advertisers
Pinterest has begun testing several new advertising tools that will let buyers share conversion data and have it analyzed by the platform, to discover possible channel overlap, and has also rolled out additional tools for marketers, the visual-oriented firm recently announced. DigiDay
Email Opens by Time of Day
10:00 to 11:00 a.m. is prime time for opening e-mail, while the wee hours of the morning between 2:00 and 3:00 a.m. see the lowest open rates, two of many findings in a newly-released study of more than 10 billion e-mail interactions conducted by Litmus. MarketingProfs
ON THE LIGHTER SIDE:
A lighthearted look at marketing effectiveness by Marketoonist Tom Fishburne — Marketoonist
Man Wondering Why You Only Watched Parts 1-23 of His 74 Part Insta-Story — The Hard Times
BREAKING: Mute Button On Ad Opens Second, Louder Ad — The Onion
‘I’m Funny’ Thinks Man Hitting Send on Tweet That Will Ruin His Life — The Hard Times
TOPRANK MARKETING & CLIENTS IN THE NEWS:
- Lee Odden — The Big List of 103 Marketing Thought Leaders, by Category — MarketingProfs
- Nick Nelson — 10 Tips for Making the Most of Your Webinars, Content Marketing and Digital Advertising — Small Business Trends
- Alexis Hall — What’s Trending: The Power of “Better” — LinkedIn (client)
- Elizabeth Williams — #ICYMI Digital Marketing Digest 29 July 2019 — John Lyons
Thank you for taking the time to join us, and we hope you will tune in again next week for more top digital marketing industry news, and in the meantime you can follow us at @toprank on Twitter for even more timely daily news. Also, don’t miss the full video summary on our TopRank Marketing TV YouTube Channel.
Maybe it’s crossed your mind once or twice before: You know, this would be a lot easier if I just knew how to program. But it’s an intimidating subject, especially if you’re not sure of your technical expertise, and there’s so much to learn that it’s hard to know where to start.
In today’s Whiteboard Friday, master technical SEO Paul Shapiro shares why it’s so important for SEOs and marketers to take the programming plunge, explains key concepts, and helps you determine the best course of action for you to get started when it comes to leveling up your technical prowess.
Howdy, Moz fans. Paul Shapiro here, Head of SEO at Catalyst. I’m here to talk to you today about programming for SEOs and marketers.
Why should you learn how to program?
I think there are really several key benefits to learning how to program.
1. Improved developer relations
First, being developer relations. As SEOs, we’re constantly working with developers to implement our recommendations. Understanding why they make certain decisions, how they think is really pivotal to working with them better.
2. Become a better technical SEO
Understanding how to program makes you a better technical SEO. Just understanding the construction of websites and how they operate really helps you do a lot better with your SEO. Automation. As marketers, as SEOs, we all sometimes do very repetitive tasks, and being able to cut down on the time spent to do those repetitive tasks is really key.
It really opens up the opportunity to do things and focus more on strategy and the other things that you can’t leave to automation.
3. Leveling up your data analysis
If anyone is familiar with this number, 1,048,576, that’s the row limit in Microsoft Excel.
As marketers, we’re swimming in a sea of data. It’s very easy to work with a dataset that well exceeds that. I often work with hundreds of millions of rows of data. Utilizing a program language like R or Python is a really good way of handling that amount of data.
It’s becoming really, really more common in the States to be taught how to program in elementary school. So by learning how to program, you’re on equal footing with the children of the world, people that may enter the workplace in the future. So you don’t even have to learn how to program in depth. But I do recommend you at least understand the concepts and logic behind programming.
Which language should you learn?
Oftentimes I hear people say, “I did a little bit of programming in college or high school. I learned so-and-so language.” To them, I say, “You’re in great shape. Stick to whichever programming language you’re comfortable with.” You don’t have to start from square one.
A lot of the programming languages share a common logic. But if you are starting from square one and you need to just decide on which programming language I’m going to learn today, I have two recommendations.
If you’re going down the path of data analysis, your primary reason for learning how to program is to work with data and do more sophisticated things with data, then I think there’s no better language than Python.
Python is very well-equipped. There are lots of libraries designed specifically for data analysis, and it’s a very much more robust language than something like R.
Now I want to go through some basic programming concepts so that you walk away feeling a little bit more comfortable with the idea of learning a program so it’s a little less intimidating.
The first concept I want to go through is the idea of a variable. These are just like algebra, like basic algebra.
So you can assign x is equal to 2 or any other value, and then we can use that later. So x plus 2 is 4. Variables can have any name. We’re using Python syntax as an example. So the first variable we have is a variable called “animal,”and it’s equal to the value “cat.”
This is a string, which is just a bit of text that we assign to it. Now variables could be of many different types. So the variable “number” can be equal to 2, an integer. Or the variable “colors” can be a list, which is a type of Python array. Arrays are just variables with multiple values. So in this instance, colors is equal to red, blue, and green, and it’s just denoted with the brackets.
The next concept I’d like you to understand is conditions, so if/else being a basic condition that we would work with. It reads a lot like English. So if the variable “animal” is equal to “cat,” which it is, print out the text “MEOW!” If “animal” wasn’t equal to “cat,” say it was equal to “dog,”then we would print out “Woof!”
Then the output, since “animal” is equal to “cat,” is “MEOW!” Loops. There are many different types of loops. I’m going to use a for loop as an example. Again, it reads a little bit like the English language. So we have a variable “colors,”which we know is equal to red, blue, and green.
So we want to say for every value in that variable “colors,”print out that value. So for x in colors, print (x). It will go through each one, one at a time and print it out. So the first value is red. It gets printed out. The second value is blue. It gets printed out.
The last value is green. It gets printed out, and the code ceases. Now the last concept I want to explain is functions. Functions very simply are reusable snippets of code. So we have a very basic function here, which we define as moz, so the function moz, which has the value one line of code print (“WBF!”) for Whiteboard Friday.
If we execute the function moz, it will print out the value “WBF!” So all these concepts in themselves aren’t very useful. But when you start really programming and you start stringing them all together, you’re doing all sorts of sophisticated things, and it becomes very, very powerful building blocks to doing much greater things.
So now that you understand programming and why you should do it, I want to leave you with some resources to actually learn.
The first resource I recommend is Lynda. It got rebranded LinkedIn Learning. The reason why I recommend Lynda is because many, many public libraries offer you a subscription for free.
When I was learning to program originally, I actually went to the library and had to take out books and try to do it myself. Nowadays, there are tons of other resources, like Codecademy.
Python for Data Analysis
It also acts as an invaluable reference guide. If you’re interested in learning Python for data analysis, there’s one book that I highly recommend. It is “Python for Data Analysis” by McKinney. That’s an O’Reilly book. McKinney was the creator of Pandas, which is a very well used Python library for data analysis. So hopefully you’ve walked away a little less scared of programming and are excited to learn.
Leave your comments in the section below. Thanks for watching. Till next time.
Did you miss Paul’s awesome talk at MozCon 2019, Redefining Technical SEO? Download the deck here and don’t miss out on next year’s conference — super early bird discounts are available now!