Commentary

In Search Of The Golden Metric

"We know our digital advertising works," a client recently said, "because when we stop running it, our site traffic and revenue drop."   His company spends over $100 million each year on digital advertising; they are sophisticated marketers who want to use data to improve results.  If you ask him what the stacks of reports on site traffic, ad impressions, etc. he gets actually tell him, he'll tell you, "not much."  Why?  Because he and most digital marketers are accountable for getting results, they want specific, actionable information -- what to run with and what to change -- about creative, site and page placements, position, size, frequency, and other factors they can control.

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Measuring web sites and online marketing campaigns has kept marketers, agencies, and others busy for years.  Web analytics report visits, page views, visits and other counts of site activity.  Ad server analytics report impressions served, clickthroughs and other silo-specific measures.   Once upon a time, each delivered the "hot metric."  But, as soon as we begin to understand what each "hot metric" tells us, we begin to understand where it falls short, and we begin again to search for the "Golden Metric" that we can confidently use.

The latest Golden Metric candidate is attribution.  Attribution recognizes that people are touched by advertising and content in many ways as they move from first impression to action.  It brings together ad serving, site and other data to identify sequences that represent the full multi-channel path-to-action and enables you to assign credit to the ads, search words, content and other factors that influence people to take action.  Because it can help you understand what contributes to online success, attribution is gaining acceptance even as it evolves.           

Attribution's promise is that it is moving us closer to the Golden Metric that will tell us which actions will improve performance.  Its focus on paths, enables you to see which sequences result in the most conversions, assign economic value to sequences, discover where viewers derail, determine how to shorten the path, and more.  And, perhaps most importantly, it enables you to know how to shift marketing resources to generate more of the most effective ones. 

Today some attribution providers offer "U" attribution, which gives weight to first, last, and intermediate views and clicks along the path.  "U" attribution is a significant step forward, but it isn't the final stage in attribution's evolution, especially when the weights are assigned "intuitively" rather than from patterns in the data.  If we knew before we started what the "right" weights were, then there'd be no reason to do any analytic work.  But, marketing analytics repeatedly reveal that our intuition for which campaigns, creative, placements, etc. will work best is often wrong when we see the data.

The rigor of determining the model weights from the data gives us more confidence in our ability to act on the results.  The best modeling approaches use campaign goals as input to model, recognizing that information gathering and buying processes differ for different products, services and ideas.  Our tactics and measures of success vary based on whether we looking to increase awareness or targeting highly qualified prospects, so our model should vary as well. And, they provide analysis of all the factors we can act on-breaking results down by placements, page position, creative, size, etc. 

It's not enough to know that our digital ads help drive business.  We want to know exactly what to do to improve results.  Getting reports by the ton doesn't help.  Moving beyond simplistic measures that don't accurately reflect complex interactions online is hard work.  Doing it right is far tougher than most consultants and analytics vendors are willing to admit.  It's only when we recognize the failings of our current approaches that we are willing to do that.  But, if we want a Golden Metric, we must demand data-driven, actionable information, not just the next convenient measure.

3 comments about "In Search Of The Golden Metric".
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  1. Mark Hughes from C3 Metrics, June 24, 2011 at 5:34 p.m.

    Right on Dave.

    Attribution is a big gaping hole in online media. The more awareness we can bring to this issue, the more ROI the industry will experience.

    Mark Hughes
    CEO, C3 Metrics
    http://C3Metrics.com

  2. Steve Latham from Encore Media Metrics, June 27, 2011 at 7:17 p.m.

    I agree with Mark - the more awareness of the gaps in "traditional" metrics (namely CTR, CPC and direct CPA) the better... for everyone. And while I agree with the logic behind your 'science-is-best' approach to weighting, it's been our experience that the focus on the micro-details is causing some to miss the forest through the trees. Here are two quick data points:

    1. Seasonality and external events will skew results for any given day, week or month. If you're going to trust the data to tell you how to weight impressions and clicks, you need several months' worth to get normalized results. In the mean time, you need to know some insight into performance of your campaigns...

    2. Tweaking the weightings (e.g. impressions vs. clicks, or 1st click vs. last click) is not going to have a material impact on the final results. Case in point: if you cut the weighting of display impressions by 50% (e.g. use 9 impressions = 1 click, rather than 6 impressions) the net change in attributable leads will fall by only 15-25%. The impact of adjusting for 1st vs. last is even less significant.

    While data-wonks won't like to hear this, expert opinions

  3. Steve Latham from Encore Media Metrics, June 27, 2011 at 7:35 p.m.

    (continued from post below)

    ... assuming they are conservative and defensible, on how to weigh impressions vs. clicks should yield 80-90% of the insights needed to know what is clearly working, and what is not.

    Given a sufficient time range (see point #1 above) we can do some modeling of the data to validate and/or fine-tune the assumptions behind the attribution model. But it's been our experience that the 80/20 rule applies here as well. While we'd all like to have the perfect attribution solution (if it existed), the absence of one is not a sufficient excuse to sit back and continue to use antiquated metrics.

    Dave - thanks for shining a light on this issue. We all agree that advertisers should take a pragmatic approach when doing attribution. And when advertisers measure media correctly, everyone wins.

    @stevelatham
    Encore Media Metrics

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