A stat that's been making the rounds recently has some marketers reeling. According to comScore and the Internet Advertising Bureau, as much as 36 percent of all web traffic is not viewable or driven by bots and manipulated through other blackhat tactics. This traffic fraud is a major problem facing the growing digital video industry, though we shouldn’t be too surprised by it. After all, the industry is exploding, with TV budgets shifting to digital video - everyone wants a piece, legitimate or not. “Gray markets” like this commonly develop around young, growing industries.
Looking back, we’re facing today what display advertising faced a few years ago. The solution isn’t in targeting bots and bot-makers directly. As the industry evolves, it will develop tools and techniques to help eliminate the issue. Today, however, fake web traffic highlights a larger challenge digital video companies and brands face: the creation and adoption of effective measurement that speaks to real-world results from real-world people.
As budgets shift and brands invest more and more into digital video, marketing executives are under pressure to deliver bottom-line results. Effective measurement must track these results, and the consumer actions that can lead to them. Results-oriented measurement is important for a number of reasons, not least of which is the fact that it helps identify false traffic. Savvy companies are using measurement to optimize their efforts, determining targeting, frequency, and a myriad of other factors based on granular data from previous campaigns. Finally, you can’t determine a real ROI if you can’t connect your investment to the purchases it led to.
Technology is improving so rapidly that we already have the tools to go beyond impressions and track what really matters. Yet, most conversations around measurement in the industry continue to be centered around the metrics of the last generation of digital advertising: impressions, clicks, social media shares, etc. Without diminishing the importance of tracking these general statistics - after all, these are terms that most executives can relate to - we can, and must, go deeper.
So what’s stopping us? Why do impressions and completion rates continue to be the industry’s benchmark for success? Partially this is symptomatic of the space’s rapid growth. The technology to drive and measure success has improved more quickly than our vocabulary has for describing that success. Further, the space is new enough, relatively speaking, that it can be confusing for professionals who aren’t wholly dedicated to digital advertising. And, of course, it’s hard to deny the allure impressions can have - what marketer doesn’t love to report a statistic that is in the thousands or millions?
Though it will always be tempting to note impressive completion rates, this can actually lead to lowering the perceived value of digital advertising. Completion rates, inflated by bots, paid-for traffic, etc, can bury the results you did achieve. The conversation surrounding analytics must move forward and focus on more robust measurements that relate to the data that actually matters for a brand on an individual level.
While there’s not - and shouldn’t be - a one-size-fits-all approach to better measurement, there are a few integral metrics brands can consider when tracking campaigns. Some of these metrics are already at your fingertips when running a personalized campaign; others would require a partnership with a data company that can help connect the offline world to the online one. None of them are possible without first changing the way we think about an ad’s viewers, understanding them as real people with individual purchasing preferences and viewing habits.
It’s important to note that the new measurements available to marketers aren’t only for online sales. Many brands are experimenting with hyperlocal advertising designed to get consumers into brick and mortar stores. This is a trend that will only increase as iBeacon and similar products roll out. With personalized, targeted advertising tying into CRM data, you can determine the percentage of in-store buys that came as a result of a geo-targeted campaign.
Soft buying indicators.
A soft buying indicator is an action (or series of actions) a consumer performs, after seeing an ad, which typically leads to a purchase decision. Examples include test-driving a car, requesting a quote for a service, RSVPing for a customer event, etc. It can be tempting to skip these soft buying indicators in favor of the end result - did a customer purchase or not? - but doing so is a huge missed opportunity to understand where your leads are coming from, and to use historical data to correlate soft buying indicators to actual sales.
In this context, purchase decision is measured in regard to which products viewers have been exposed to via advertising and which products they have not. In other words, did your campaign for Product X generate an uptick in sales for that product specifically, or did you raise general brand awareness that led to purchases across your brand’s products? Knowing which provides valuable insight for your future targeting efforts.
Share of purchase.
Share of purchase is an exciting new metric available to marketers who are tracking campaign results on a 1-to-1 level. In essence, it measures the difference in total spend between those who have seen ads in a campaign versus those who have not. Knowing how many viewers converted to customers through a campaign is great, of course, but knowing if those customers are on average more or less valuable than those who didn’t see an ad will help you further determine the effectiveness of your content and the true ROI of your campaign.
Tracking performance data isn’t a new idea - the industry has been measuring clickthroughs and email opens for years now. However, this measurement is again a priority today for two primary reasons: the rise of bots and fraudulent traffic, as discussed previously, and new tools which allow campaigns to be adjusted and optimized on the fly, while they are occurring. Advertising is no longer a “set and forget” activity - the stakes are too high to not take advantage of real-time performance data. Is the viewer of an ad that visits a website afterwards more likely to purchase than a viewer that signs up for a newsletter? Are women responding more favorably to an ad than men? In either case you’ve identified valuable information that can be used to optimize the campaign while it is in motion.
Performance data is also where capturing fraudulent traffic can come into play. Once you are tracking performance data, it is fairly simple to see what is coming from a real person and what is coming from a bot. The viewing habits, and therefore the performance data, will be completely different.
Beyond the measurements above, there is a huge range of metrics specific to certain industries that can be valuable to track for an individual brand. Each company should develop its own standards of measurements based on what matters to itself and its bottom line.
It’s an exciting time for digital video advertising. More consumers are online than ever before and new technology means we can reach them in highly effective, relevant ways. We can drive more results than were previously possible, but we need to improve the ways in which we talk about and track these results. Measurement matters; we must go beyond impressions and develop specific measurements that speak to the real world, and consumers as individual people.
Not only will these measurements aid in understanding audiences and optimizing campaign results, but they also will confirm to brands that their advertising placements are high quality, real and effective. If we’re able to move towards a world in which each viewer is understood as an individual human being with unique actions and preferences, bots will no longer be able to masquerade as legitimate traffic and the industry will find its way to eliminating these exploiters one way or another.