In a perfect world, we would have access to all of the data we need to measure marketing effectiveness. In that world, it would be easy to attribute sales or leads directly to specific marketing programs, campaigns and tactics. We'd also be able to tell which channels are most effective at driving each stage of the buyer journey. But sadly, this isn't a perfect world—and marketers are often forced to make decisions with imperfect data.
What do we mean by marketing effectiveness?
Marketing effectiveness is a measure of the success of a marketing campaign. Its ultimate goal is to drive revenue, increase market share and build loyalty for your company.
Marketing effectiveness relies on measuring the difference between expected results and actual results. A company may expect its new product launch to generate $100 million in sales, but if it only generates $50 million in sales, then there's a gap between what was expected and what was delivered by way of marketing effectiveness.
Why is marketing effectiveness so challenging to measure?
You’ve probably heard the saying, “You can’t manage what you can’t measure.” Effective marketing requires that you have a strong understanding of how your marketing efforts are performing. This means measuring effectiveness, but it isn't easy.
Measuring marketing effectiveness is highly subjective. Many factors contribute to success in a campaign; it's hard to determine exactly which ones played a role and which ones didn't. For example, if 10 people buy something from you because of an ad they saw on TV and one person buys something from you after seeing an ad online, which ad did more for your business? It's hard to tell without further information about each person who bought something and how they were influenced by their exposure to both ads or neither ad at all (maybe they were already planning on buying what was advertised).
The impact of marketing campaigns is difficult to quantify because they take place over long periods of time (months or years) and often involve multiple channels (such as print media and direct mail). You may be able to measure sales generated by specific campaigns with relative accuracy over short periods like weeks or months; however, when trying to measure the overall contribution made by your advertising efforts over longer periods such as years it becomes very difficult since there may not be any visible results until much later down the road!
That’s why attribution is so important.
Segmentation challenges can be amplified by the sheer number of segments that you have to evaluate. For example, if you're evaluating your marketing effectiveness in the United States and Europe, there are more than 100 different regions and countries that you'll need to segment for.
The process of selecting the right variables for segmentation can be equally challenging. One approach is to use existing data on your customers' demographics (e.g., age or gender) as a starting point for identifying potential segments. Another approach is based on what we might call "intangible" factors such as interest areas and lifestage progression (e.g., from being single through marriage). Each approach has its own set of advantages and disadvantages: individual demographics such as age may be easier to use but don't capture important subtleties like lifestyle preferences; while collective demographic traits can provide some useful insights into group behaviors but require significant effort in order to identify them accurately in advance (and may not even exist).
Segmentation itself can also become an issue because it requires measuring performance at a very granular level—you must know how many people were exposed within each segment before comparing effectiveness across various groups/variants/triggers etcetera!
Attribution lies at the heart of marketing effectiveness measurement
One of the most important concepts in marketing measurement is attribution. It can be defined as the process of determining where sales come from and attributing them to specific campaigns, channels, or other sources. Attribution is not synonymous with measurement - it's simply a part of it. However, measuring brand lift and return on ad spend (ROAS) requires an understanding of attribution so that you can accurately gauge how much value each channel produces relative to its costs.
You may think that measuring ROI would be easy: just measure clicks or conversions against some sort of budget metric. But there are many different ways to measure conversion rates depending on who you're trying to reach and how long they've been exposed to your ads before buying something from you (or someone else).
You need an attribution model (and partner) that can scale with you as you test different channels across numerous segments—that’s where Rockerbox comes in.
Find a balance between what you can measure and what you can't.
You can't measure everything, but that doesn't mean you shouldn't try.
Most tools have limits—and marketers should be aware of those limits. If a tool isn't the right fit for your needs, its limitations will become an obstacle to measurement. This can happen when:
- The tool doesn't measure the data you need to collect from customers (e.g., online surveys don't allow self-reported survey data)
- The information collected isn't timely enough (e.g., email marketing campaigns take weeks or months before they are completed)
- The cost of implementation is too high (e.g., it costs more than $1 million per year for an enterprise organization to implement web analytics software)
That’s why hundreds of the top B2C brands choose Rockerbox for their marketing attribution needs.