Are You Fully Leveraging Your Advertising Data?

Optimize your digital ad campaigns

Data Standardization Worksheet

This worksheet begins with the standardization of your performance data. We’ll walk you through how to combine these mismatched data sets in a step-by-step process so that every metric is speaking the same, common language. With all of your data standardized, it’s easier to locate the strengths of each platform and hone in on ways to optimize campaign performance.

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Advertising Data

Advertising is nothing without its data.

Imagine that you create a marketing campaign. How do you know whether it’s successful? You can gauge the success of an advertising campaign through something called “metrics,” such as how many people are responding, how many people are actually making a purchase, and what their average purchases are. Advertising data is how you know whether your campaigns are working and how you identify potential trends.

With the right advertising data analytics, you can tell:

  • Which customer demographics are more likely to respond to your advertising campaigns.
  • Which advertising campaigns are most likely to be successful.
  • How much you’re spending on your advertising vs. how much you’re making.

In short, an advertising campaign really can’t be successful unless you have the right advertising data. Nevertheless, many companies are collecting large volumes of advertising data and not analyzing it correctly. They may not know exactly what metrics they should be tracking, or may just have incomplete data that doesn’t give them the full story.

Advertising platforms today can provide comprehensive advertising data analytics. One of the most popular analytics services is Google Analytics, which is attached to the Google AdSense, Google AdWords, and Google Webmaster suites. These analytics functions can help companies coordinate their paid advertising campaigns.

If you’ve ever wondered whether your campaigns are being fruitful, why your campaigns are yielding inconsistent results, or why you can’t seem to break through to your audience, the key may already be in your advertising data. At the same time, it can be difficult for many to consolidate and analyze their advertising data without help. Many marketing professionals study analytics and analytic suites for years.

Digital Advertising Dataset

Why is it so hard to collect digital advertising analytics? Part of the problem is that each digital advertising dataset tends to be individually siloed.

If your organization is currently advertising through a website, Twitter, Instagram, and paid advertising (such as Google), you likely have data analytics from each platform. Your advertising dataset for your email newsletters will be entirely separate from your advertising dataset from Google Analytics.

Even if each platform and each advertising dataset is tracking mostly the same data, the data isn’t going to be unified. Google Analytics might be tracking respondents from 19-29 while your email newsletter platform might be tracking age groups starting from 18-25. Because of these differences, it becomes tremendously difficult to consolidate and analyze data in meaningful ways.

And this is very important. Today’s multi-channel advertising campaigns are highly inter-related. Without the right management, you may miss key information regarding your digital advertising campaigns. You need a consolidation platform to get better, big-picture information about your advertising campaigns. Otherwise, it may be too difficult to see the forest for the trees.

While companies can continue to analyze performance case-by-case, it’s usually detrimental. They may miss larger trends that are important. Moreover, having to analyze everything per platform makes analysis much more costly, in terms of time and labor. The more time it takes to analyze data, the less time is available to actually optimize and improve it. And the more it costs in terms of advertising spend.

Advertising Analytics Software

Advertising analytics software solutions can pull in data from multiple channels, so it can be consolidated and analyzed as a single, complete data set. Marketers are able to see exactly how trends are forming both amongst all their advertising channels and individual advertising channels, so they can draw better conclusions about the data that they’re collecting.

A few advertising analytics examples:

  • A company might see that their demographics are moving away from Facebook and toward Instagram, and therefore change their advertising spend.
  • Companies may see that their customers across the board are purchasing less frequently, but they’re purchasing larger amounts of products.
  • A company may see that their social media advertising is actually boosting their website sales, so while it seems their website is performing better, it’s actually their social media.
  • Companies may see a sharp dip in their products and become worried, even though this dip actually happens seasonally every year and is something that they can plan ahead for.
  • A company may start losing traction to a competitor. Without the right analytics, they may not know which competitor, or know what keywords and descriptions they need to focus on.

But even with large volumes of data, it can be difficult for a human to comb through and analyze it. This is where Advertising Intelligence comes in. Machine learning algorithms and artificial intelligence can be used to identify key patterns in advertising metrics.

AI excels at understanding patterns and trends, often in ways that people simply cannot. Because AI can comb through exceptionally large and varied data sets quickly, it can find answers that a person might not be able to — it might, for instance, be able to see that teens are purchasing very frequently every time a payday comes around, or it might be able to see that certain products and services are waning but only on specific platforms.

When armed with more specific analytic information, companies are able to strengthen their advertising and their marketing spend. Once advertisers understand how individuals are reacting to their marketing strategies, those marketing strategies can be further fine-tuned and optimized.

Mind-Blowing Facts About Advertising

You might not realize how effective advertising actually is. Let’s take a look at some advertising statistics 2020 and 2021 and explore some of the most mind-blowing facts about advertising.

  • Video is actually the fastest-growing advertising type; about 90 percent of mobile users will view video ads once a week. Video is one of the most engaging forms of media.
  • By 2020, many people are going to be using AR and VR. AR and VR open up some great opportunities for marketing, but they’re yet another marketing channel that marketers will need to track.
  • Email marketing remains one of the most effective types of marketing, in terms of ROI. Despite there being many marketing channels, the one-on-one nature of email marketing is startlingly engaging.
  • 90 percent of marketers believe that the ability to collect and analyze marketing data is their top priority. Without marketing data, it’s impossible to say how successful a campaign really is.
  • About 70 percent of users would prefer to learn about products through content rather than advertising. Content marketing is becoming one of the most common ways to educate customers about products.
  • 71 percent of customers will recommend brands to others when they’ve experienced a positive social media experience. This is the type of experience that may need to be tracked through surveys and marketing analytics.
  • 94 percent of marketers now use Facebook. Many people have Facebook accounts today, almost as many who have email accounts. But this data still has to be analyzed and collected.

At its core, advertising is actually about solving problems. Customers already know that they want something; your goal is to make sure that you can provide it. Through advertising, you make them aware of your solutions and educate them on the solution right for them.

Misleading Statistics in Advertising Examples

While many statistics show that advertising is effective and that advertising is booming, it’s important to note that there can be misleading statistics as well. Misleading statistics occur when a platform wants to pretend that it’s more effective than it really is. Sometimes they happen intentionally, but other times the platform may simply be bugged.

Let’s take a look at some misleading statistics in advertising examples:

  • A social media platform might count “views” or “clicks” even though a user immediately bounces from the site. This is especially bad if you’re paying per click or per view for an ad campaign.
  • A tracking link might report that you’ve made a sale as long as the individual makes a sale at any time after clicking the link. Even if the individual has gone in through another channel.
  • A paid advertising campaign may report that your traffic is going up continually, even though it’s staying relatively flat; it may count individual files loading (such as images) as individual page views.
  • A tracking link may attribute sales to new customers even though they are existing customers if it cannot track customers over multiple channels. This could make you feel that you’re gaining a larger audience even though you’re not.
  • Similarly, a company may falsely attribute sales to recurring customers, by confusing customer accounts, which may make you feel as though you’re retaining customers when you’re not.

Why do these statistics in advertising examples exist? They serve to mislead you into thinking an advertising platform is more useful than it really is, thereby securing your advertising spend and preventing you from diversifying.

Many marketers hesitate to diversify across multiple channels because they want to keep their spending in a single place. You may not want to have to go through multiple analytics services and you may feel as though you’ll lose control over your advertising dollars that way.

But a multi-channel advertising campaign will almost always be more effective than a single-channel one. It’s absolutely important to diversify, you just need to have a solution that will help you consolidate your advertising data rather than keeping it silo’ed.