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.
Digital Marketing Data Sources
How do digital marketers know their campaigns are a success?
Digital marketing is far more effective, affordable, and efficient than in-person marketing. But in-person marketing does come with some tangible benefits — namely, you often know when it’s working. Digital marketers need to collect large volumes of data to determine whether their strategies are fruitful.
This data comes from a variety of sources — services like Google Analytics, platforms such as Salesforce, and products like Pardot. Email marketing software, content management platforms, and customer relationship management suites all work together to produce an image of how a campaign is working.
These digital marketing data sources will collect specific metrics, such as visits and lifetime customer value. From there, digital marketers are able to determine which strategies are working best, whether strategies could be flagging, and where the best place to put advertising spend should be. But with so many types of data sources, marketers have an uphill battle.
A company that is running paid advertising, social media, and content marketing campaigns may have over a dozen platforms to track. Without the ability to reliably track this data, however, they won’t know which channels are most likely to be successful — or which channels they should be rightfully focusing on.
In fact, a lot of professional marketing companies and professional marketers have a tremendous amount of data that they aren’t even analyzing. While they’re collecting the information, they can’t consolidate it into something that can be properly analyzed. And when they do consolidate the data, the data is all so disparate and disconnected that it doesn’t yield actionable information.
So, not only do marketers need data. They need to know how to properly use that data. They need a tool that will help them dig down into meaningful information and help them make the decisions that are right for them.
Data For Marketing
The first thing any marketer needs to know is how to get data for digital marketing. Let’s take a simple look at a paid advertising campaign on Google. If you’re running a paid advertising campaign on Google, you’re taking advantage of one of the broadest, most robust third-party advertising solutions.
Google will advertise your site on third-party pages (through their network) and the SERP (search engine results page). But, you’ll need to know how successful that advertising is.
Through Google Analytics, you can access Google’s data for marketing. It will tell you how much traffic you’re getting, what demographics are interested, and whether that activity is shrinking or growing. Google Analytics provides a lot of data in digital marketing — mostly traffic-based, but also for paid advertising campaigns.
But you’ll need to be able to read those metrics. For instance, you might see traffic going up and up — but no one making purchases. Your content is interesting and people want to read more, but they aren’t interested in the product itself. This might be an issue that you have with the type of content you’re producing or you might need to rethink your product altogether.
In this way, data gives you the information — but you still need to be able to analyze it to determine what it really means. And you can potentially interpret incorrectly (such as, for instance, if the product purchasing is actually going down just because the price point isn’t correct).
Marketing Data Analysis
Without the right marketing data analysis, data marketers are paralyzed. But it isn’t as simple as collecting information. Data can mean a lot of things and patterns may not be immediately obvious.
If a marketer pumps $3,000 into an email marketing campaign and they get $10,000 in referrals, they might expect to pay $6,000 and get $20,000 in referrals. But that’s not necessarily true. The marketer might see saturation — they may actually contact everyone who might be interested in their product — so that they see diminishing returns. And that’s one of the simplest types of marketing data.
In a more complex interaction, a marketer might be selling a Bronze, Silver, and Gold Tier SaaS product online. A marketer might see that they’re selling far more Gold tiers in January, but then it suddenly goes down to almost nothing in February. The marketer might conclude that their marketing campaigns have reached saturation or gotten worse.
But what if it’s simply that most companies enter into a new fiscal year — and consequently a new spending budget — in January? Because marketing data can be potentially misleading, it’s even more important to have a solution that can analysis data in-depth.
Digital Marketing Statistics 2020
Marketing stats change significantly year-over-year. You may not want to get into digital marketing statistics 2020 if you’ve got statistics for 2021. Likewise, advertising statistics 2020 may not properly reflect exactly what you have to do to succeed today. The world of marketing operates quite fast.
One of the best resources for marketing statistics is HubSpot. Let’s take a look at some critical stats:
- 51 percent of consumers use Google to search for products they want to buy.
- 45 percent are using voice search, which often alters SEO.
- More than half of all traffic is through mobile devices today.
- Only 25 percent of companies invest in mobile optimization.
These highlight the importance of having a complete digital marketing campaign. Customers today are looking at sites through their mobile devices before they make major purchases. But despite that, very few companies are actually optimizing their marketing campaigns to this mobile audience.
By being able to produce better digital marketing data, you can determine exactly what these customers are looking for and what they’re doing. In turn, you’ll be able to yield better results overall through your marketing — and further your audience reach.
Digital Marketing Statistics 2021
Another great resource for digital marketing statistics 2021 is WordStream and other magazines such as Forbes and Business Insider. WordStream highlights some of the most important advertising statistics 2021, including:
- People were spending more than eight hours on digital media a day.
- Paid search and social search were the best-performing vehicles.
- US sales through eCommerce grew over 20 percent due to the pandemic.
- China was expected to see the greatest amount of eCommerce growth.
But there are some things to consider for 2021. Because it is a “post-COVID” world, advertising changed significantly. There was a lot more online purchasing throughout 2021.
This is something that digital marketers must always consider. Not only are there seasonal changes, but there are changes that occur year by year. Because of this, it’s not just about the statistics themselves, but what these statistics mean.
Digital marketing data sources can help companies determine what is unique to their company, what is occurring because of major trends, and what they should do next. It’s not always a simple, easy answer but the better the data, the better the results.
Data Analysis And Interpretation Of Digital Marketing
A single company can produce reams and reams of digital marketing data. With just a few channels of digital marketing, the digital data sources can still quickly become overwhelming. Marketers need to understand how to analyze digital marketing data specifically for actionable results.
In data analysis and interpretation of digital marketing, one of the most important concepts to understand is comparison. For instance, a manufacturing company cannot necessarily compare itself to every other manufacturing company — there are issues of scale, reach, and product. But what a manufacturing company can compare itself to is its performance week-over-week, month-over-month, quarter-over-quarter, and year-over-year.
Similarly, A/B testing or split-testing occurs when a business conducts multiple advertising campaigns to see which does best.
Consider the following example, which we’ve looked at before. A company knows that its traffic is going up while its sales are going down. There are a few things the marketers could conclude:
- They have reached saturation, so they aren’t going to be able to move any further in this area and demographic.
- Their price point is too high; they need to reduce the price to achieve any better success.
- Their product is seasonal and they won’t be able to increase their sales again until next year.
A marketer can then run three campaigns:
- A campaign that targets a different area or different demographic.
- A campaign that lowers the price point, by offering coupons or discounts.
- A campaign that operates as a control; it does nothing different.
If the marketer sees that all three campaigns continue to perform poorly, they know that it is likely that their market is just saturated. But if the first campaign performs better, they know that they need to branch out into other demographics. If the second campaign performs better, they know that it’s likely to be a price point issue.
Testing is how digital marketers determine which data is truly relevant and what conclusions to draw. But marketers aren’t able to test without rigorous data and methodology. In the above example, the only way the marketer even knew something was wrong was through their data. And the only way they could track the performance of each test was through analysis of that data.