This is the Information Age. Specifically, it’s been called the age of Big Data. There are statistics about almost anything you might think to ask, and many things you wouldn’t. Running an ad campaign generates a lot of data. To many people, that tells the entire story, and context is meaningless. They also ignore the human component of advertising, assuming that the majority of people are logical. They also don’t take care to make sure that their choice of statistics is right for their campaign, favoring instead default selections or overwhelming themselves with every statistic under the sun. While following these concepts may work out it’s not worth counting on, though.
The Importance of Context
Data is never, in itself, the whole story. Context is always a factor. For example, when running a social media campaign and focusing on popular hashtags, the stage of the hashtag has a major effect on the success on the campaign. If it’s on the way out, even an otherwise good campaign may flop. If it’s ascendant, even a lower-quality campaign could do well. It’s important to understand the impact these metrics have on each other. And these metrics exist on the other end as well. The late Andy Grove, former CEO of Intel, referred to the idea of paired metrics, focusing on the fact that decisions such as sales have impacts beyond what the individual campaign’s results display. An ad during a sale may bring in more customers, but it hurts profit margins and customer retention. There has to be a focus on the impact of the broader world on the campaign, and on that of the campaign on the company as a whole.
Humans are Unmeasurable
People like to think they act in a logical, organized fashion. However, that’s simply not true. And that wreaks havoc on statistics. For example, it would be logical to assume that people prefer fast websites. Google has even designed its search algorithm to favor them. However, studies don’t bear that out. So, you’ll need to be prepared for results that don’t make sense, and ready to adjust as necessary. You could also end up in a situation in which the statistics – though normally accurate – don’t accurately consider the behavior of your customers or target audience.
Many metrics are designed to be – and presented as – answers to a trick question. They’re supposed to make it clear and simple to determine whether or not your campaign succeeded. But “Did my campaign succeed?” is a very subjective question. There are many different definitions for success. And while companies are always adding metrics for more specific situations, they’re far from covering every situation. Moreover, these metrics don’t account for the point your company is at in its size. Comparing your company to a much bigger one – even one in the same field with the same goals – means always concluding that your campaigns failed, which isn’t helpful.
This isn’t a full list of the issues with plain data. But it is a window into some of the issues that you’ll encounter working directly with metrics on a regular basis. You’ll need to set precise milestones, so the success of a campaign can be determined later. You’ll need to adjust when confronted with illogical results. And you’ll need to be conscious of the ramifications of the world on your campaign’s success, as well as those of your campaign on the company and its customers. When you’ve got it all under control, though, you’ll be a step ahead of everyone else, with many successful – and useful – campaigns to show your clients.
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