It's 2008; where's my metric beyond clickthrough and viewthrough? I cannot believe that we are still trying to justify the concept of viewthrough, and that we have not developed something better that has become an industry standard.
As if the exposure of an ad has no relevance to your business? Does that mean that all of print advertising and outdoor cannot possibly be effective because you cannot tell who clicked on it?
But it's not whether you use clickthrough/viewthrough, it's how you incorporate those metrics that's important. Remember, the whole idea is to more accurately know what the impact of your ad spend is.
If your view is that clickthrough/viewthrough should not be incorporated into your thinking, then you don't know squat about analytics, or advertising.
Let me explain the three core issues that have caused most businesses to fail when incorporating those metrics.
- The cookie window. Each ad can have a cookie set. You can see whether someone has an "opportunity" to view your ad and then whether that computer visits your site afterwards. The window that can be set by that cookie is variable. Do you want to track that for a day? A week? A month? A year? All up to you, and that is where most of the first errors occur. If you don't set your cookie window correctly for your business, and know how to derive the proper information from your analytics, you'll be gathering data and just as quickly wasting it.
- Viewthrough is not a causal relationship. Just because you delivered an ad to someone does not mean that they noticed it. They had the "opportunity" to notice it. But this is exactly the same as what print and outdoor offers -- that "opportunity." You cannot be certain that the ad caused the traffic. You can only infer that it could have had an effect.
- The last cookie wins. Every cookie set by one of your ads replaces every other cookie set. If you are using viewthrough and just want to increase your metrics, all you have to do is deliver one ad to as many people as possible in your potential target; instant great metrics that rarely translate into business results. The sites and networks which optimize will do just that, optimize; increasing the perceived metric. Driving numbers for numbers sake but without tying it to business performance. This is where the second errors occur, and where most programs run into "We tested viewthrough and it doesn't work." The other major issue with making the last cookie the winner is that the last ad is the only one that gets credit. If viewthrough does have a cumulative effect, then you are ignoring it. This will cause you to make creative decisions based on faulty interpretations of data.
I will attack these three points and how they can all work together, and then discuss a formulaic approach to your online advertising to solve for this click/view world.
What you are all trying to get at is the impact of your advertising and, more concretely, how to attribute the contribution of online to your overall business. You do not have to do a single thing I say here. It's all about weighing the benefits of knowing that impact. There are many business models in which operating on a direct response click model is sufficient and the resources are not available to do otherwise. Regardless, you should understand the impact of the rest of those impressions.
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The cookie window
If you do not set up a viewthrough cookie window that is long-term, then you miss the cumulative effect that multiple impressions could be having on your audience. I would suggest two months. Most businesses plan online month to month. Having a two month cookie window enables you to see the effect of the previous month's plan in relation to the current month; variability in spend, site selection, frequency, etc. Most clients I know have a one- or five-day cookie window. The reason is that they are attributing all of those users as having been driven from online advertising. That is where the discrepancy lies. You cannot do that.
What you should do is run a blind test of a cohort of users who saw your advertising and didn't click versus those who did. Plot that against frequency of exposure and time between exposures. You should then be able to see the impacted lift of those exposures. In order to do that however, your cookie window needs to be long enough for cumulative data to be of import. You can then extract meaningful information:
Five exposures over one week results in a 20 percent lift in overall response. Over seven exposures in week has no additional lift. Three exposures in one day seems to result in a 16 percent lift. One hundred exposures over a month indicates a 400 percent lift.
It's this type of insight that will enable you to structure your ad buys and your program delivery for optimal results.
Viewthrough is not a causal relationship
Because viewthrough isn't about causation, you should not be using a 1:1 causal metric attributing each view/visit as caused by your ad. It will only be a percentage, a fraction of that traffic, that should be attributed to the ad. This is intimately tied to your cookie window, and that appears to be inversely logarithmic. The more time has passed since the view of the ad, the steeper the curve away from impact. You should plot that curve based on your cookie window and the blind study, and against your spend. There should be an optimal point at which your spend level demonstrates the most efficient delivery. It's not rocket science, it just takes some work to get at the data you need.
Once that work is done, however, you do not have to worry about the complex analysis. Just use your view window data and multiply it by your percentage impact metric. I would suggest rerunning the analysis every six months to make sure the assumptions are still valid. More than that and you're wasting resources.
The last cookie wins
The first impact of this is your creative. It's about the corpus of messaging; the whole enchilada, not just a single piece of creative. A single banner creative is useless. It means nothing. Stop micro-data-analyzing as if it did; pouring over weekly analytic reports, tweaking this placement or that so much that your head is so buried in the sand. You are burning through resources and accomplishing what? A 0.025 improvement in your click metric?
Use your resources effectively and look at the big picture. You have your program so tightly wound, so tweaked, that you've micromanaged yourself into a corner. Any change crumbles your precarious house of banners. Or does it? Don't touch it for two weeks. What was your efficiency hit? Calculate it in dollars. Could that two weeks, all those hours of your resources and agency resources being burned have been used to set up something that will provide an exponential success, not an incremental one? Calculate just the time your agency billed you? Can you recover that by using your time more efficiently?
Use the performance metrics of creative as guidelines. They all work together. If some of your creative is really outperforming others, it is relevant. Use the learning from what that creative is doing, but do not seek to constantly tweak existing creative messaging on stuff that is not working. You may have different goals with that creative so judge it on that. If the goal is to communicate a point of difference of your product, and that is important long-term, then measure it on that.
The tools are out there
Look at the bigger picture; the longer term. Did you use Dynamic Logic or Insight Express to set up ongoing effectiveness studies for attitudinal effects on consumers that translate into higher site usage? What about ForeSee providing customer satisfaction information on your site and marrying it with ad entry? How about Net Promoter score tracking over time with exposed, non-exposed groups to your online efforts? No? Are you a marketer or a luddite?
Atlas has developed some new technology to try and get at the overall exposures of creative, and multivariate testing from companies like Memetrics, Omniture and Optimost have enabled direct marketers online to hone the funnel experience. But what is the real effect of all of those ad exposures? Omniture acquired Visual Sciences last year and integrated it with their own Site Catalyst tool to create a system that is extremely robust in analyzing the full funnel effect of people into your online presence.
They can run test models and allow you to do "what if?" scenarios. But unless you are a large scale enterprise that can afford such systems, you are left in the dust. BuzzMetrics allows you to track the internet hum across the blogs, message boards and substrata of the web. There are even econometric modeling solutions from the major media players but they still mostly fall short. The traditional economic modelers tend to develop models that, when they incorporate online, get so chaotic as to become useless. They are all approaching it from the wrong side of the equation. Absolute Data is the only company I have seen that starts at the digital end and works backward in its modeling. That's where all the data is. And it seems to work.
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So what do you do in a click/view world?
So what if you do not have the huge resources necessary for large-scale, enterprise-style support for your analytic efforts? The Dynamic Logic, Insight Express, Omniture nirvana? What if, like most people, you are strapped for resources, strapped for cash, strapped for time and fumbling through the sea of available options? Are you relegated to just using click and view metrics as your analytic barometer? Don't fret, you are not alone. The vast majority of internet marketers are click- and view-based monkeys. What's important is that you become a smarter monkey.
If that is the universe in which you are forced to play, make sure your analytics are providing you with the actionable data you need to make decisions that balance both your short-term performance and long-term brand equity needs. Develop a formula; you remember what those are, right?
What was important to the business I was in was searches. For you it could be registrations, page views, time on site, ad exposure on site or any number of things. But whatever it is, your business has a fundamental need that your online programs serve. Your job, any marketer's job, is to make sure that what you are bringing in equates to more income than expenditures for the company. Again, not rocket science, but sometimes short-term goals maximizing that effort lead to customer erosion over time, which works against your long-term goals.
That's why I always suggest a dual formula system. One which focuses on the core short-term need and includes a "balancing" metric to make sure short-term goals don't come at the expense of long-term customer satisfaction.
As an example, a core metric for a search company would be: CPMS (cost per thousand searches) = (cost of media/searches) * 1,000. Cost of media is the dollars spent on that media, and searches attributed to the program is derived from the metric you develop to overcome the three barriers to viewthrough.
What you are trying to do is most closely align this formula with your actual business performance. You need to test various combinations and arrive at a formula that your internal analytics team placed a very high confidence on as being attributable to online. That metric needs to be verified once a quarter. But what establishing it enables you to do is concentrate on your programs instead of being mired in your analytics. You can provide that metric to the various sites with performance targets that they need to hit.
But you need to develop a formula that is meaningful to your business by verifying with analytics the degree of confidence in the measured results. That provides an unbiased view of property selection in media decisions. In that specific formula, and most core formulas, cost is almost always a crucial component. If media costs twice as much, performance of creative must be doubled to generate the same CPMS. However, because of the high reliance on cost, there is a danger that programs would skew to consumers that may not be providing the best long-term value.
For this reason, I suggest an additional secondary metric should be developed as a barometer against such erosion. For this example:
SPMI (searches per thousand impressions) = (searches/impressions) * 1,000.
The SPMI metric is all about consideration impact and quality, whereas the CPM metric is about volume and efficiency. SPMI removes the pricing methodology from the optimization and concentrates on the consideration impact of the advertising, and the quality of the user it attracts. A roadblock placement, although cost-inefficient, generates a higher SMPI than a simple banner. It is a monitoring metric in that it is not optimized on, as with CPM. But SPMI does monitor the impact of the advertising and assess whether certain placements or sites warrant additional spend.
By using the two metrics your goal is to reduce CPM while maintaining or increasing SPMI.
Any business can implement this dual metric optimization and monitoring tactic. You just need to look at your business and find the one thing that will drive the business the most. Develop a cost-based metric for optimization and an impression or income-based value metric for monitoring. It could easily be CPMR (cost per thousand registrations) and IPMI (income per thousand impressions). Your IMPI becomes your monitoring metric that you should increase, while your CPMR is the optimization metric you should decrease. You can track all this at a gross level, but also down to the site level for media decisions. Some sites may have a higher referral quotient (which you can layer in), in that they may have a higher CPMR but funnel additional registrations into the system downstream. Sites can then be scored for such values, adjusting the optimization metric.
This may all sound a bit complicated, but if you work through the logic, all the little gems are there to get you on the right path to using a formulaic approach to your online advertising.
How will this help you escape being pigeonholed into direct response and elevate you online programs to branding? The easiest way is to set targets with management for your metrics. As long as you are hitting those numbers, you can use the deltas of any efficiency gains to work your way into more communicative messaging programs. Those programs will naturally be less efficient when you start, but as long as the overall programs are hitting your numbers it will allow you to start the process of expanding out of a pure click/view metric world, and into demonstrating long-term value of your programs through ongoing tracking and monitoring of those key performance indicators that drive your business. Demonstrate how online contributes to them, without ignoring the hard data metrics, and you'll be a superstar in no time. Well, either that or your entire program will implode and you'll be looking for your next job. But at least you'll be a strategic marketer and not a click-monkey. I know, you feel better already.
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Sean X Cummings runs SXC Marketing, an advertising and marketing consultancy specializing in helping brands, agencies and vendors connect with their consumers more effectively.
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