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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What is advertising analytics, and why is it so important? Advertising analytics, particularly digital advertising analytics, is something that takes place before, during, and after a marketing strategy. Through digital marketing analytics, your organization will take a detailed look at what worked, what didn’t work, and how your ads functioned.
Advertising analytics is a field that has been in development for many years. It considers how consumers interact with ads, what makes them more likely to purchase, and what makes them more likely to stick around. How are they reacting to an ad? How does this ad make the consumer see the brand?
Without advertising analytics, an organization can’t tell whether its campaigns are working. How many people are responding? How much are they buying? When are they buying?
And, advertising analytics doesn’t just serve as a self-reflective experience. It doesn’t just tell you how your existing campaigns are doing. It tells you how well they are going to do in the future and what might need to be changed to make them more successful.
So, what is advertising analytics? Potentially the most important part of advertising. But it’s a challenge when it comes to digital advertising.
The major issue with digital advertising is that there’s so much to track. You’re not tracking a single customer coming into a store. You’re tracking dozens, hundreds, thousands, or tens of thousands of essentially anonymous individuals interacting with your brand.
To understand their demographics, you need to dig deep into tracking (such as tracking URLs, context-based tracking, cookies, and more). You need to leverage platforms, often multiple platforms, to get a whole picture of who is interacting with your brand and what they’re doing.
For most businesses, it’s time-consuming and laborious. Companies have to aggregate their data manually, produce reports, and figure out their analytics on their own. But other companies invest in software that streamlines everything; that consolidates the data for the company and creates intelligent, accurate reporting.
The right analytics and data can greatly improve an organization’s effectiveness, just as the wrong data can serve to mislead. With the wrong data, companies can easily find themselves spending far more than they expected.
One of the most important platforms for analytics is Google Analytics. Google provides a number of free advertising analytics tools for websites and their advertisers.
For advertisers, the Google AdWords program makes it possible to run paid advertising on the search engine results page (SERP) or through display ads (on third-party websites). For traffic management, the Google Analytics page also provides detailed information about who is visiting your site, when, and what they’re looking for.
Most companies check their Google Analytics numbers. But Google, like other platforms, has unique ways of registering metrics. As an example, a platform may count “bot” traffic (spiders who are archiving or checking sites) or may only count “user” traffic. A platform may count every download of a file as traffic or may only count a hit to a website as a visit. A platform may count every individual page hit or just individual users.
This proliferation of differences is why many companies need to invest in an intelligent advertising platform. Without a single, consolidated platform that can bring in data and run intelligent comparisons between it, companies are left checking individual services such as Google Analytics and having to figure out the links to their other channels on their own. A single company could be running campaigns on over a dozen different channels.
Still, Google Analytics is one of the most useful tools, because it provides detailed demographic information. Google tracks essentially everyone on their network, which is extremely broad thanks to their AdSense portfolio. Almost every site in the world uses Google Ads, which then makes it possible to track users through a multitude of websites, and also determine what they are most interested in.
Digital Marketing Analytics
So, there are two main types of marketing analytics: physical and digital marketing analytics.
If you run an ad on a radio, you would know that you had run your ad to approximately 30,000 individuals in the metro area who are between the ages of 25 and 55 and predominantly male, for instance. You would have the demographics for the radio station itself and you would know what proximity people had to the radio station. But that’s all you’d know. Maybe someone would mention the radio ad when they came in to make a purchase. But they might not. You could only gauge success by whether you saw a surge in sales.
Compare this to running an ad on Google. When you run an ad on Google, you know exactly how many people saw it, how many people clicked, and (if you configured everything right) whether they bought something. You don’t need to guess at anything; you know, down to the detail, who the people are who clicked on your ads. You know they’re interested in hockey or football, where they’re located, and what their ages and other demographic information are.
But that much information is a double-edged sword. Not only do you have that much information, but you have to have that much information. You have to be able to sort through all that information for important data. That’s where advertising platforms come in. Advertising platforms are able to cull the useless data and leave you with only the information that you’re most likely to be interested in.
From there, the marketers will be able to make decisions on their advertising backed by timely, valuable information.
Data Analysis Advertising
Most ad agencies struggle with data analytics in digital advertising. There are a few major challenges, most of which involve reporting rather than collection.
When it comes to data analysis advertising, data is held in a single silo across each platform. So, you have your Instagram data, your Facebook data, your Twitter data, your website data, and so forth. Marketing analysis techniques only work when you’re able to see the full breadth of your information.
To counter this, ad agencies usually try their best to bring all the information into a single source, like an Excel spreadsheet. But there are clear issues with that. An Excel spreadsheet isn’t going to update itself. The information has to be imported and converted. Manual entry is rife with mistakes and it also takes a long time to do.
Data analysis advertising really requires that companies dig into their data and be able to do that digging in real-time. They can’t be using information from a month ago to manage their advertising campaigns today. The online world works much faster than that.
But with the right consolidated solution, companies are able to pivot faster. They can, for instance, take advantage of a sudden boost to traffic caused by a backlink from a major news site, even if that traffic just occurred.
Advertising Analytics Examples
Let’s take a look at some advertising analytics examples to understand more about how advertising works and what makes it so challenging.
A company has an ad on the search engine results page as well as paid ads on third-party sites. The company then notes that its SERP is performing very well but its paid ads are performing very poorly.
Digging deeper, the company sees the demographic on its SERP is primarily female whereas the demographic on its paid ads are primarily male. Digging further into its information from all venues it finds that its product is primarily female. So, its SERP ad is performing well because they wrote their ad to appeal to women, their primary demographic. But the paid ads are performing poorly because it’s targeted toward men, which are not generally interested in the product.
If the company only had information from paid ads alone it might actually conclude that men are most interested in its products. The ad is tailored toward men and selling toward men, it’s simply that women are more interested overall. If a company were to alter its strategy based on the paid ad information alone, it would be doing quite poorly.
As you can see, all the information is needed. And sometimes that information comes from a different source. Demographic information may be captured by Google, but the only way that you can connect that information with what happens on your website is through linking your analytics.
Advantages Of Marketing Analytics
One of the major advantages of marketing analytics is that it provides a competitive advantage. Marketing analytics makes it possible to make rapid-fire decisions regarding your advertising campaign, often capitalizing on things as quickly as they occur.
More pressingly, if other companies in your sphere are already using marketing analytics, then they may be able to surpass you.
With better marketing analytics, you know where to spend your marketing dollars. That also means that you’re able to funnel your marketing money into where it’s most effective, getting more bang for your buck. For those with lean budgets, that can be extraordinarily beneficial.
Additionally, better marketing analytics makes it possible to see when strategies have to change, and to identify the strategies that are most likely to be effective the first time around.
Advertising Analytics Software
Advertising Intelligence is a category of software designed to connect, transform, and organize advertising data. With Advertising Intelligence, digital marketers can visualize results, create insightful reports, and optimize their campaigns. Advertising Intelligence isn’t just any advertising analytics software. What makes it special is that it’s able to bring in data, consolidate it, and ensure that the data is being properly transformed.
Each platform has its own way of collecting information and consolidating it, so it’s not always possible to have a one-to-one comparison between the data, let alone put it in the same bucket. But an advertising analytics solution with Advertising Intelligence (like Lumenad) transforms data so that it can be consolidated with accuracy. This occurs automatically, without the need for an individual to go through and manually adjust their data.
With the right analytics software solution, companies are able to quickly see all their data transformed, organized, and optimized, in a visualized environment that makes it easier for them to identify patterns and make decisions.