Return on Investment in Marketing and Marketing Budgets
Return on investment, commonly abbreviated to ROI, is a very simple business concept to grasp. In essence, it measures the money that you put into something (a campaign, a product, a sales tactic, etc.) against the money that it makes you. This kind of business action is also called capital expenditure, appealing to the old adage that you have to spend money to make money. However, return on investment works differently for marketing investments due to the inherent risk that a marketing tactic simply will not work. That's how marketing is perceived at many companies – as a gamble that may or may not pay off.
So, how do you calculate the return on investment of a marketing tactic, or even of your marketing budget in general? The simple formula of net income divided by investment doesn't really work, and it doesn't offer the kind of comprehensive answer needed to accurately judge the effectiveness or ineffectiveness of your marketing tactics and budget. As a result, the analysis of return on marketing investment, or ROMI, is a different beast altogether from standard ROI approaches. Many companies feel uncertain about using analytics or about assessing the efficacy of their marketing tactics. In this article, we're going to talk about how to measure the tangible impact of marketing tactics using modern analytic metrics. Before we get to that, we'll also take a look at the history of marketing analytics, where they've been in the past, and how they relate to modern constructions of social media, web presence, and online marketing in an internet-based marketing strategy.
The history of marketing analysis
To understand why many companies feel reluctant to trust marketing analytics and the data that they produce, we have to take a step back and look at marketing history. Back before the internet when companies used in-store revenue as the primary determinant of the success or failure of marketing, the marketing divisions for these companies would run an advertisement – a television or radio ad, or something in a newspaper. Then they'd analyze the change made to their in-store revenue over the next sales period to see how effective it was. If the in-store revenue went up, then the advertisement must have worked, and if it went down or stayed level or didn't improve enough, then the advertisement must not have worked. It was a simple calculation with what seemed like a straightforward cause-and-effect relationship between marketing and sales figures. It's obvious now that this is a pretty reductive method of analysis that doesn't take into account the many factors which make up the market, even within the context of a relatively small local business.
Take a step forward to the early days of the internet and the origins of e-commerce. All of a sudden, marketers had concrete data about their web presence – they could see the number of clicks on a banner ad and the exact figures for web traffic through search engines. Again, the impact of marketing tactics seemed easy to calculate – more clicks from a search engine meant that the marketing investment made into optimization for that search engine directly paid off in improved sales figures. The equation for return on investment was a little more complicated, but seemed more accurate as a result. Unfortunately, this wasn't the case, and simply measuring clicks from a search engine doesn't take into account the many ways that a customer may have gotten there.
Given the incredible inaccuracies that have existed in the measurement of marketing performance, even performance backed up by statistical data, it is no surprise that many companies are leery of marketing analytics. These companies have access to their marketing data, but they don't know what to do with it, and this makes the prospect of judging the effectiveness of their marketing and marketing budgets incredibly daunting.
Using analytics effectively
Analytics are a powerful tool, but they're one that you have to know how to use. That, along with the generally unfavorable track record of marketing analytic methods means that there are a lot of companies out there who aren't making the most out of the marketing data available to them. In this section, we're going to talk a little about the tools you can use and how they can be employed to improve your marketing and effectively analyze your budget. The three main metric tools available for advertisements of all types are impressions, frequency, and reach.
Impressions are a marketing term for when someone sees an advertisement. It's one of the key parts of determining an advertisement's overall reach, which is calculated by multiplying the impressions it generated by their frequency, or the number of times they see it. Notably, this metric does not take into account the relative effectiveness of an advertisement, and even an advertisement with very high reach can be ineffective for many other reasons. Impressions are sometimes also called exposures.
Frequency calculates the number of times that a viewer sees an advertisement within a certain time period. Typically, frequency is tabulated into an average to then make broader claims about the effective concentration of advertisements within a population. Frequency is sometimes difficult to calculate without conducting a survey, especially in traditional media such as television, radio, and print advertisements.
As we mentioned a moment ago, the reach of an advertisement is determined by multiplying how many people see it by how often they see it. Measuring an advertisement's reach lets you take a look at its overall breadth, giving you sort of a wide-angle view of who is receiving it and where. Reach is typically mapped on a Venn diagram.
There are also a number of common metrics that are more exclusive to web analytics, namely page views, clickthrough rate, and cost per click.
Page views are similar to impressions in many ways. Both of them measure the number of people that receive the information in an advertisement. Notably, page views should not be confused with hits, which count the interactions with the files on the page, and which therefore serves as a metric of web design as well as traffic. Like impressions, page view statistics do not correlate to the quality of a page or its content.
Similar to frequency, clickthrough rate is a measure of a customer's sustained interaction with a website. Sustained interaction with a site is taken as a sign of customer interest, and websites with high clickthrough rates boast that they hold the attention of customers. However, it should be noted that clickthroughs only represent a step toward customer conversion – a positive one, certainly, but a step nonetheless.
Cost Per Click
The method for determining cost per click is very simple: divide the advertising budget for a web element by the number of clicks it generates. The smaller the ratio, the better the advertisement has performed. Cost per click was one of the earliest web metrics, and as we discussed above, it is a foundational element of cost-benefit analysis for web advertising, but it is one that has vital information missing from it. The fact is that you must rely on other metrics to fill in information about customer habits and the in depth details of the conversion process.
Measuring the tangible impact of marketing practices is something that it is incredibly difficult to do. This has always been the case, and even the analytics offered by web marketing practices do not completely describe every step of the marketing process. The fact is that marketing is and will always be a risk of some sort. However, the benefit of analytic methods is that you can control that risk based on your brand, your customers, and your localization. Metrics and analytics offer companies the ability to tailor marketing in a whole new way, and to analyze the performance of marketing projects on a much closer level than ever before. By learning a little about metrics and how to read them, you will greatly improve the return on your marketing investment.