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Facebook Lookalike Audiences: What Are They and How to Use Them

Published March 1, 2018
Imagine two people, one who is a loyal customer with a high lifetime value and another who has never heard of your brand. Now imagine these two people have a great deal in common in terms of interests, behaviors, age, and location. What if you could use the profile of your customer to connect with the relative stranger?
 
That’s what Facebook Lookalike Audiences are all about.
 
In this post, we will look at one of Facebook’s specific advertising capabilities: Lookalike Audiences. We’ll cover what they are, how they’re built, and how to use them.

Reporting on Google My Business Listings

Published February 22, 2018
Digital marketers can strive to reach audiences around the world but they can also focus on the users right next door. For brick and mortar businesses, it’s mostly the latter. When your market is your own community, it’s your local website users that are the most important to understand and study.
 
Reporting on local data is an important role for agencies and in-house analysts. To gather information and build action plans, Google My Business (GMB) dashboards hold a number of useful insights about how local customers are finding you online.
 
Until fairly recently, the ability to export this data outside of the GMB environment was fairly limited and required some manual workarounds. Fortunately that’s no longer the case because GMB added some convenient export functionalities. These exports provide easier ways to analyze and leverage this data. In this post, we’ll review some basic considerations, best practices and ideas for reporting on the data you’ll find in Google My Business listings.

 

Tips and Advice for Landing Pages

Published February 15, 2018
Ahhhh, landing pages. Hello, old friends.

Reporting on Display Ads to Clients

Published February 1, 2018
When you read or hear the term “display ads”, it’s easy to immediately associate it with just banner ads. You know – the ones no one ever clicks on, right? And while banner ads certainly constitute one familiar kind of display advertising, let’s be honest, these aren’t your father’s display networks anymore. From traditional text & images to video rolls to native advertising to in-app ads, the formats, reach and functionalities of display advertising networks have never been richer and more promising.
 
However, the performance of display advertising can vary tremendously, particularly when compared to other channels and traffic mediums that clients are more accustomed to. As such, all the cutting-edge capabilities in the world matter very little when you cannot communicate their value to clients.
 
In today’s post, we’ll review 3 higher-level considerations for reporting on display advertising.

The Best Times to Post on Facebook

Published January 25, 2018

“Timing is everything.”

“It’s all in the timing.”

“There is a time for everything.”

There is an endless supply of quotes to reinforce the importance that time plays in all things. But when it comes to social media, these idioms are more than just clichés – they’re science.
There has been copious research to identify the trends that exist in analyzing Facebook post-performance, interaction, and when content has the best chance to be seen on the site. In today’s post, we’ll review some of that data to better understand how to use it as a framework for determining the best time to post on Facebook to engage your audience. 

ALSO IN THIS BLOG

When the client first came to you, you talked up the value of Google Analytics. You emphasized the importance of seeing where your traffic was coming from. You went on and on about how Google Analytics can show traffic sources to pinpoint whether people came from search, social media or a specific site referral, and how valuable this data was. You sold them on it, so much so that your client looked forward to receiving that first report, the magical day when they would finally understand where visitors were coming from.
But then the report came, and it looked like this:

 

 

It showed that 10% of your client’s traffic came from “(direct)/(none)”. What does this label mean? How do you explain Direct traffic to your client? Better yet, how do you explain “none”?
Let’s take a closer look at understanding Direct traffic in Google Analytics and how we can address it with clients.
Digital marketers spend a lot of time focused on PPC and SEO campaigns in order to drive desirable traffic to a website. The phrases we’re ranking for and bidding on get meticulous attention, so much so that we often forget about some of the other ways that visitors find us.

We put a tremendous amount of the effort we put into reviewing organic search data and PPC campaign performance in analytics. But how closely do we monitor referral reports?

If that’s not a channel you review regularly, you may be missing out on seeing traffic that is coming directly from links you’ve obtained around the web, local business listings, news mentions, and more. Many times, links are only considered as a means to an end, a metric that Google uses in determining how to rank sites in the SERPs (search engine results pages). But the fact is, many of a site’s links may be directly contributing to its traffic.

In this article, we’ll review how to look at referral reports in Google Analytics, and some of the many ways to use that data to better inform your web marketing decisions.

 

Remember how your mom told you not to stand too close to the television because it might hurt your eyes?

The same rules can apply to data. If you’re too close, you may miss the patterns and trends that are crucial to understanding your website’s performance. You can’t judge a site’s performance looking at data in the bubble of a single day, you must consider any day’s traffic compared to the days before and after.

Google Analytics makes it fairly easy to analyze trends over long periods of time. But it also allows you to stand right in front of that TV, to look at more granular levels of time, right down to the hour.
There’s a better way to get that close to the data, without burning your retinas. We’ll cover how to analyze traffic effectively in today’s post.