In April 2012 I presented a case study on Full-Funnel Attribution at the granddaddy of all industry conferences: Ad-Tech in San Francisco.

I was honored to share the stage with Young-Bean Song, a pre-eminent thought leaders in digital media measurement and analytics (and a very nice guy).  After years of applying to speak at Ad-Tech, I was finally selected; not because I’m the world’s most pre-eminent speaker but because the case study we developed is so effective at presenting how advanced analytics and full-funnel, cross-channel Attribution can be utilized to maximize performance and boost Return On Spend.

Among the highlights of the case study, we demonstrated:

• How converters who were exposed to display ads followed a range of conversion paths before taking the desired action(s).
• How attributing fractional credit for assist impressions and clicks (beyond just the last click) yielded much deeper insights into the performance of each channel, vendor, placement and keyword.
• How recency, or the time lag between the first impression, last impression, visit and conversion) impacted performance.
• How frequency is still a big issue that needs to be addressed – especially when buying exchange-traded media.

For those who didn’t make the show, I’m happy to share the case study in two formats (both are hosted on slideshare):

• View the Presentation: Ad-Tech Attribution Case Study
• View the detailed writeup: Encore Attribution Case Study

If you’d like to learn more about Attribution or discuss the case study, please drop me a line (see Contact link below).  Also please feel free to comment, tweet, like, post, share, etc. as you see fit.  Thanks for your time and interest!

- @stevelatham

Latham to present Beyond the Last Ad: Better Decisions Through Better Attribution

Conversion reporting has become an everyday part of how campaigns are optimized.  As digital budgets grow in size and complexity, collective skepticism continues to build against the current “Last Ad” reporting standard.  The demand for more advanced attribution methods has spawned a host of new analytics and technology capabilities, yet going beyond the Last Ad has yet to “cross the chasm.”  Spiritually – advertisers, agencies and publishers are on board – but their reporting and optimization methods have yet to budge.  Led by Young-Bean Song, an expert in digital advertising effectiveness research, this session will reveal how current standards bias our view of the digital marketing world, and our spending as a result. We’ll also feature the latest data and case studies that quantify the impact of new attribution models.

Key takeaways:

• Learn how leading brands are tying display ads directly to purchases
• Discover pre- and post-campaign testing methods that are cost-effective and easy to execute
• Get insight into some of the most cutting-edge attribution research

Session Leader: Young-Bean Song, Principal and Founder – AnalyticsDNA

Presenter: Steve Latham, Founder and CEO – Encore Media Metrics

Session:

ad:tech San Francisco
Tuesday, April 3 at 3:45pm
http://na.ad-tech.com/sf/sessions/i-love-data-attribution-and-online-display-advertising-beyond-the-last-click/

Today a colleague sent me a link to a new article on Attribution and media measurement with a request to share my thoughts. Written by a statistician, it was the latest in a series of published perspectives on how Attribution should be done. When I read it, several things occurred to me (and prompted me to blog about it):

1. Are we still at a point where we have to argue against last-click attribution?  If so, who is actually arguing for it?  And are we already at a point where we can start criticizing those few pioneers who are testing attribution methodologies?
2. Would a media planner (usually the person tasked with optimizing campaigns) understand what the author meant in his critique: “the problem with this approach is that it can’t properly handle the complex non-linear interactions of the real world, and therefore will never result in a completely optimal set of recommendations”?  It may be a technical audience, but we’re still marketers… right?
3. The article discusses “problems” that only a few of the largest, most advanced advertisers have even thought about.  When it comes to analytics and media measurement, 95% of advertisers are still in first grade, using CTRs and direct-conversions as the primary metric for online marketing success. They have a lot of ground to cover before they are even at a point where they can make the mistakes the author is pointing out.

In reading the comments below the article, my mind drifted back to business school (or was it my brief stint in management consulting?) and the theoretical discussions that took place among pontificating strategists.   And then it hit me… even in one of the most innovative, entrepreneurial and growth-oriented industries, an Ivory Tower mindset somehow still persists in some corners of agencies, corporations, media shops and solution providers.  Not afraid to share my views, I responded to the article in what I hope was a polite and direct way of saying “stop theorizing and focus on the real problem.” Here is my post:

“…We all agree that you need a statistically validated attribution model to assign weightings and re-allocate credit to assist impressions and clicks (is anyone taking the other side of this argument?).  And we all agree that online is not the only channel that shapes brand preferences and drive intent to purchase.

I sympathize with Mr. X – it’s not easy (or economically feasible) for most advertisers to understand every brand interaction (offline and online) that influences a sale. The more you learn about this problem, the more you realize how hard it is to solve.  So I agree with Mr. Y’s comment that we should focus on what we can measure, and use statistical analyses (coupled with common sense) to reach the best conclusions we can. And we need to do it efficiently and cost-effectively.

While we’d all love to have a 99.9% answer to every question re: attribution and causation, there will always be some margin of error and/or room for disagreement. There are many practitioners (solution providers and in-house data science teams) that have studied the problem and developed statistical approaches to attributing credit in a way that is more than sufficient for most marketers.  Our problem is not that the perfect solution doesn’t exist. It’s that most marketers are still hesitant to change the way they measure media (even when they know better).

The roadblocks to industry adoption are not the lack of smart solutions or questionable efficacy, but rather the cost and level of effort required to deploy and manage a solution.  The challenge is exacerbated by a widespread lack of resources within the organizations that have to implement and manage them: the agencies who are being paid less to do more every year.  Until we address these issues and make it easy for agencies and brands to realize meaningful insights, we’ll continue to struggle in our battle against inertia. For more on this, see “Ph.D Targeting & First Grade Metrics…”

I then emailed one of the smartest guys I know (data scientist for a top ad-tech company) with a link to the article and thought his reply was worth sharing:

“I think people are entirely unrealistic, and it seems they say no to progress unless you can offer Nirvana.”

This brings me to the title of this post: It’s hard to solve problems from an Ivory tower.  Note that this is not directed at the author of the article, but rather a mindset that persists in every industry.  My point is that arm-chair quarterbacks do not solve problems. We need practical solutions that make economic sense.  Unless you are blessed with abundant time, energy and resources, you have to strike a balance between “good enough” and the opportunity cost of allocating any more time to the problem.   This is not to say shoddy work is acceptable; as stated above, statistical analysis and validation is the best practice we preach and practice.  But even so-called “arbitrary” allocation of credit to interactions that precede conversions is better than last-click attribution.  It all depends on your budget, resources and the value of advanced insights.  Each marketer needs to determine what is good enough, and how to allocate their resources accordingly.

Most of us learned this tradeoff when studying for finals in college: if you can study 3 hours and make a 90, or invest another 3 hours to make a 97 (recognizing that 100 is impossible), which path would you choose?  In my book, an A is an A, and with those 3 additional hours you could have prepared for another test, sold your text books or drank beer with your friends.  Either way, you would extract more value from your limited time and energy.

To sum up, we need to focus our energies away from theoretical debates on analytics and media measurement, and address the issues that prohibit progress.  The absence of a perfect solution is not an excuse to do nothing. And more often than not, the perfect solution is not worth the incremental cost and effort.

As always, feel free to comment, tweet, like, post, share, or whatever it is you do in your own social sphere.  Thanks for stopping by!

@stevelatham

Attribution is a hot topic!  As marketers are shifting their focus to measurement and optimization, Attribution is rising to the top of the priority list for 2012.  However, like many things, Attribution has many flavors and often means different things to different people.  In this and future posts, I will shed some needed light on this topic and help marketers make sense of this complicated and ever-evolving discipline.

For starters, let’s define Attribution is simply the process of attributing credit to each interaction in a user’s path to conversion.  These interactions may include display ads, paid searches, natural searches, emails, social and other media.  To truly optimize your online marketing efforts, we must measure each channel, vendor, placement and keyword’s contribution, and give appropriate credit in the final analysis.  While the industry generally agrees on the problem (last-click measurement is woefully insufficient) and the objectives (give credit where it’s due), there are many divergent opinions on which approach is best for solving this problem.  With the goal of illuminating and educating (vs. selling) here is my perspective.

Analyzing Conversion Paths

Conversion path analysis is quite popular these days and is usually at the top of marketers’ wish lists.  Not to be confused with site-specific conversion analysis, media-centric “conversion path analysis” looks at the digital channels that influence customers throughout the conversion cycle.  In short, marketers want to a macro-view of all the touch points (we call them “assists”) that drive a conversion.

To capture the data needed to view conversion paths, you need to match impression cookies (set by your ad server when a user is exposed to display ads) and your site visitor cookies (set by your site analytics software).  You’ll also need to maintain all the details for each impression or visit as time-stamped, individual records are a key requirement for conversion path analysis and more advanced attribution.

Once you have the detailed history of impressions, clicks, visits and actions for each visitor, you can query the data to visualize the conversion paths for those who converted.

The table below shows the “average” path for all visitors, as well as the common paths for 4 unique groups of converters (segmented into natural clusters by a machine-learning algorithm).  As noted, the “average” converter saw 6.8 display ads and visited the site 2.9 times before converting, with natural search accounting for 0.4 visits, paid search 0.4 visits and display ads 0.9 visits.

Most marketers are content with channel-specific conversion paths, but we’re seeing more and more interest in vendor and placement specific paths and expect this will become more common over time.

Conversion path analysis is a good start towards cross-channel / full-funnel Attribution and should provide a foundation for more advanced (and necessary) analysis.  That said, there are a few limitations that marketers should be aware of when looking at conversion paths.

First, it’s important to note that Averages can be misleading and there is usually a broad distribution of paths that are not represented by the mean. While the average number of impressions was 6.8 in the case above, the number varied between 1.5 and 20 for each group (that’s a big range).  Likewise, while Display accounted for 70% (on average) of interactions that led to a conversion, it ranged between 38% and 88% among the four clusters.

Second, while conversion path analysis is insightful (and may help justify your display buys), you’ll need more information to truly understand campaign performance and determine how to optimize your media plan.  This is where Attribution comes into the picture.

Moving Beyond Conversion Paths to Full Attribution

If you have detailed conversion paths for each visitor, you have the data you need for advanced analysis.  Now you need a model that allocates credit for every impression and click assist in a way that makes sense.

And now we move into the realm of debate and disagreement that is characterized by “my math is better than your math.”  Truth is, Attribution models come in all shapes and sizes; some are proprietary and some are based on well-known statistical methodologies.  While there is no universally-accepted algorithm that constitutes the gold standard in Attribution modeling, there are numerous approaches that are more than sufficient.  The good news is that you don’t need a 99.9% solution to be successful.  In most cases, a 90% solution is sufficient and more cost-effective.

So without getting too deep into Attribution modeling, let’s talk about the Questions your attribution model should answer, such as:

• What is the relative contribution of each channel, vendor, placement or keyword (i.e. how many conversions should each get credit for)?
• What is the attributable cost per action (or return on spend) for each channel, vendor, placement or keyword? (see sample report below)
• How many impressions are required to influence a visit and/or a conversion?  (i.e. what is the optimal frequency?)
• How does the optimal frequency vary by vendor or placement?
• What was the actual frequency (and how many impressions were wasted)?
• What is the appropriate look-back period (how far back should we give credit for assist impressions and clicks)?

As always, feel free to comment and share!

The Encore Team

Steve Latham is interviewed by Russ Capper, host of The BusinessMakers Radio Show.

Key topics of discussion and questions answered:

• What is the history of Spur Interactive & Spur Digital as it relates to Encore Media Metrics?
• How did Encore Media Metrics evolve out of Spur and what challenges did you encounter during the transition?
• What needs did you identify in the industry and how did you did you learn of those needs?
• How did you plan for and initiate the buyout of Spur Interactive?
• Challenges of turning the platform into a product (Packaging, pricing, marketing, positioning, supporting)
• Location challenges and the digital advertising hub of New York City
• Nuts and bolts of how Encore Media Metrics helps clients measure and optimize media through better analytics and metrics
• Display vs. Search and other advertising types and their impact/value depending on a user’s position in the funnel

As always, feel free to comment and share!

The Encore Team

• What is attribution?
• What does Encore Media Metrics do?
• How do “last-click” models compare to attribution analysis?
• How can media spend be optimized by using attribution analysis?

As always, feel free to comment and share!

The Encore Team

Encore founder and CEO Steve Latham recently participated in an OMMA Metrics Panel discussion in San Francisco on July 15, 2011.

While many people talk a lot about “predictive analytics,” few actually successful deliver business value by telling business people about their fat tailed, stochastic, and autoregressive conditional heteroskedastic volatility model for online advertising in ad exchanges. Yet, high-order mathematics and statistics exist in many companies.

In this video, you’ll hear from experts who create and use verifiable and statistically-valid quantitative methods. You will learn from professionals who have successfully crossed the academic chasm of mathematical research ideals to the other side: using statistics and modeling to generate quantifiable profit.

Moderator:
Jason Harper, VP, Analytics & Marketing Intelligence, Organic, Inc.

Panelists:
Matt Butner, VP and Director, Brand & Media Research, InsightExpress
Andy Fisher, EVP, Global Data & Analytics Director, Starcom MediaVest Group
Steve Latham, Founder and CEO, Encore Media Metrics
Tim McAtee, Research Director, IPG Emerging Media Lab
Leon Zemel, Chief Analytics Officer, [x+1]

A video of the panel is embedded for viewing above.  You may also view it on ustream.

As always, feel free to comment and share!

The Encore Team

Encore founder and ceo Steve Latham recently moderated the “Measuring Social ROI” discussion at the OMMA Metrics NYC Conference in March 2011.  The big questions addressed were:

1. Social Media: Shiny Object or ROI Producer?
2. What are brands doing to measure the impact of social ROI?
3. What works and how do you know?

These questions were discussed by industry thought leaders and expert practitioners from across the country including:

- Adam Cahill, EVP Media Director, Hill Holliday
- Ben Straley, CEO & CO-Founder, Meteor Solutions                                                                  \
- Jonathan Mendez, Founder & CEO, Yieldbot
- John Lovett, Senior Partner & Principal Consultant, Web Analytics Demystified, Inc.
- Jascha Kaykas-Wolff, VP of Marketing, Involver
- Moderator: Steve Latham, Founder and CEO, Encore Media Metrics

A video of the panel is embedded for viewing below.  You may also view it on ustream.

As always, feel free to comment and share!

The Encore Team

Advertisers are (finally) looking beyond the last click.  Here is an overview of the Five Forces that are driving adoption (also published by MediaPost in May 2011)

It’s been 3 years since measurement buzzwords “attribution” and “engagement mapping” emerged with great anticipation and excitement in online advertising.  The idea of looking across digital channels and beyond the last click to measure media throughout the funnel was thought to be the holy grail in online marketing.  Recognizing that “last-click wins” is insufficient for measuring the brand-building attributes of display media, brands, agencies and media vendors saw Attribution as the next big thing in digital advertising.

Yet as we entered 2011, very few marketers were using Attribution to measure and optimize online media spend.  Despite the universal desire for better measurement, most were still using old metrics (click-through rates, cost per click and direct cost per action) to analyze paid media.  Greg Papaleoni, who develops Analytics and Insights for Yahoo! Advertising Solutions, sums it up well: “While Full Funnel Attribution is the future of the ever-evolving digital media measurement landscape – it should be the present.  Those advertisers who embrace and implement this logic, methodology and technology sooner rather than later will enjoy a massive advantage over their competition.”

While adoption has been slow to date, this is changing quickly due to the convergence of numerous factors.  Borrowing on Michael Porter’s “Five Forces” model for analyzing industries, here is my take on the Five Forces that are driving digital media attribution (author note – I received permission from Professor Porter to adopt his model to this category):

1. The continuing shift of media budgets from traditional to digital.

While total U.S. media spend will grow only 3% in 2011, digital spend will grow 14%, surpassing Newspaper as the #2 medium.  Accounting for almost 30% of daily media consumption, Digital spend will continue to outpace all other channels for the foreseeable future.

2. The resurgence of display advertising

Per eMarketer, Display media spend will grow 14% in 2011, outpacing 10.5% growth in paid search.  While there are many reasons behind the growth (consumption of social, video and mobile content, better targeting capabilities, real-time bidding, richer formats, etc.) I believe the resurgence of display is driven by two primary factors:

• The maturing of search: There are only so many searches every day, and most marketers have optimized their paid search efforts.  For the big advertisers, there are no more keywords to buy.  As one search exec was recently quoted “paid search inventory is maxed out.” Incremental dollars will have to go elsewhere.  Display is the obvious choice.
• The return of branding:  As the economy recovers, marketers are re-investing in their brands.  During lean times, online dollars focused on harvesting existing demand (via search).  But with the improving economy, brand-building is once again a strategic priority.  In the digital realm, display media offers the most efficient, effective and scalable way to create awareness, consideration and preference for brands, products and services.

3. Increasing focus on accountability

While marketing budgets may have loosened, the focus on results has not.  As a result, marketers are keeping a very close eye on ROI from “brand-building” media.  With the ever-increasing need to show ROI, brands now want branding plus performance.  To properly measure brand-building media, we need to measure engagement, not clicks.

4. Evolution of web architecture

Recent forays by IBM and Oracle into the marketing arena signal a new wave in convergence of IT and Marketing.  As the IT behemoths push technology-based marketing solutions, CIOs are becoming more attentive to the needs of the marketing department.  The deployment of Data Management and Universal Tagging Platforms enable advanced analytics and media measurement that were off-limits to marketers in the past.  With this roadblock removed, the stage is set for new measurement tools to be deployed across their digital infrastructure.

5. The emergence of better Attribution solutions.

While early Attribution solutions were expensive and limited in capabilities (e.g. couldn’t attribute credit for organic conversions), a new breed of point-solution vendors (including my company Encore Media Metrics), are now offering more effective, flexible and affordable solutions.  For a very modest investment (as low as 1-2% of media spend), advertisers can now have a much more holistic and accurate view into the performance of each channel, vendor, format, placement and keyword.  These insights are enabling advertisers to optimize media budgets, yielding 20-40% gains in revenue.  The immediate return on investment in Attribution solutions may exceed 1-20x (100%-2,000%).

The Five Forces Driving Attribution are illustrated below:

As our business objectives change, so must the manner in which we measure results.  As dollars continue to flow into digital, brands and their agencies must use more efficient, accurate and effective metrics for measuring media throughout the funnel.  The emergence of more advanced and affordable Attribution solutions, supported by growing support from IT departments is paving the way for Attribution to become a foundational component within the digital marketing ecosystem.

Matt Miller, SVP of Strategy & Analytics at Performics, agrees, stating “Attribution is one of the top priorities for us and our advertisers.  Focus on attribution will only increase as advertisers build and implement strategies to maximize ROI across all digital channels.”

As always, comments are encouraged. And please feel free to share!

Steve Latham (@stevelatham)

The What, Why and How of Online Media Attribution
[if you like presentations, view "Attribution 101" on slideshare]

Anyone who has ever bought (or sold) display ads is painfully aware of the need for new metrics for online media.  While “last-click wins” may work for paid search, it fails miserably in measuring the impact of display and other media at the top of the funnel.  Hence, the need for full-funnel Attribution, which allocates credit for “assists” in the customer engagement cycle.

By attributing credit to contributing impressions and clicks that precede subsequent visits and conversions, marketers can have a much more accurate and holistic view into the performance of each channel and vendor.  While most interactive marketers are familiar with Attribution, many are still trying to understand what it is and how it works.

The Need for New Metrics

While digital is the most measurable medium, the “one-size fits all” approach to online media measurement needs to be re-evaluated.  While click-through rates (CTRs), cost per click (CPC), direct conversion rates and cost per action (CPA) may be applicable for search and other “bottom-of-the-funnel” media, these metrics are not appropriate or insightful for measuring performance at the top of the funnel, where demand is created.

Display ads can be very effective in achieving their objectives (driving awareness) without any clicks or direct conversions.  A recent Media Math study showed that 80% of post-impression conversions are the result of viewing display ads without clicking and only 20% of conversions are the result of a click.  In other words, for every conversion that follows a click on a display ad, there are four (4) post-impression conversions without clicks.  The upshot: we need better tools and methodologies for measuring the performance of media at the top of the funnel.  This is where attribution comes into the picture.

Defining Attribution

Attribution is the art and science of allocating credit to all interactions that play a supporting role in the customer engagement process.  In other words, it’s the act of giving credit for assists.  Rather than viewing results from each digital channel in its own silo (a la traditional web analytics platforms), Attribution requires you to take a holistic approach to analyzing how each touch-point contributes to the overall goal (visits, conversions, etc.).

With the resurgence of display advertising, Attribution is becoming increasingly important for optimizing media budgets.  As shown in the Google trends chart below show, searches for “online attribution” have increased 150% over the past 36 months.

Approaches to Attribution

Generally speaking, there are two types of Attribution: Operational and Algorithmic / Media Mix Modeling.

• Operational attribution consists of creating detailed records of every impression, click, visit and action for each visitor to your site, regardless of the source or channel (e.g. display, paid search, natural search, direct navigation, email, social, affiliate, etc.).  Data is then organized and reported in such a way that visitor paths and media placements can be effectively (and efficiently) analyzed.  By understanding which paid, owned and earned media placements are driving the most effective engagement, you can optimize spend and marketing efforts to boost ROI.
• Media-Mix / Algorithmic Modeling consists of analyzing impression data, search data, email data and web log files to statistically correlate patterns and trends to fine tune campaigns.  This “black box” approach is useful but it depends entirely on the hard-coded assumptions and calculations in the model.

We believe operational attribution is the foundation for advanced measurement and analysis of media.  The operational approach of giving credit for assists is intuitive, logical and easy to understand.  Once the operational attribution model is defined, algorithmic modeling can be used to further optimize the media mix.

Channel Level Attribution

Channel level attribution addresses the relative roles of each media channel in driving traffic and conversions.  Attribution requires an algorithm that attributes partial credit to display impressions and clicks that precede visits and conversions.  The weighting of impressions relative to clicks will vary based on the type of ad, format, placement and other issues.  For example, highly-targeted rich media placements should have higher weighting than Run-of-network animated .gifs.  Weightings should be customizable for each vendor and placement.

The channel attribution report below shows the relative impact (last click vs. attributed) of each channel: direct navigation, natural search, referring sites, email, paid search, display advertising and 3^rd party email.  As shown, attributable credit for display ads may be 50-400% higher than a last-click report would show. It should also be noted that paid search generally sees a net increase in attributable actions as short-tail keywords often play contributing roles in the customer engagement process.

After attributing credit for actions for each channel, spend data can be imported to show the adjusted cost per action for each channel, as shown below. As illustrated, we typically see a 30-80% decrease in attributable cost per action (CPA) for Display, and a slight drop in CPA for paid search (resulting from keyword assists)

Vendor Level Attribution

Looking beyond channel level, we use the same approach to assess the performance of each media buy.  Shown below is a sample report showing the cost per action for each media vendor, both last-click and attributable.  As shown, some media buys can appear to be very poor performers on a last-click basis, but are in fact very effective for creating demand that is subsequently satisfied through other channels.

Keyword Attribution

Short-tail keywords (category terms, product terms, etc.) often play “assist” roles in the customer engagement process.  Just as it’s important to know which display ads precede visits and conversions, assist keywords should also be identified.  In many cases, assist keywords may perform poorly on a last-click basis, but perform very well in an attribution report.

The Business Case for Attribution

Attribution is more than just a buzzword – it is an essential part of campaign measurement and a requirement for optimizing media spend.  As illustrated below, moving “loser” budgets to the “winning” vendors can produce a dramatic improvement in revenue and return on spend.

Beyond the improvement in media efficiency and ROS, the economic benefits also accrue to:

• Media planners: save wasted time and energy trying to replace ostensibly “bad” buys that are actually quite effective
• Ad Ops and analytics teams who are tasked with aggregating silos of data into massive .xls workbooks (attribution vendors will do this for you)
• Media vendors whose ads are actually engaging customers and creating demand that is satisfied through other channels.

As an industry, we have to do better.  We can’t use yesterday’s tools to measure tomorrow’s media. Attribution should no longer be an aspirational goal, but rather a key part of your 2011 digital marketing strategy.  The economic returns are compelling and there are numerous vendors (including us!) who would be happy to assist you in taking a more holistic approach to digital media measurement and optimization.

As always, comments are encouraged.  And please feel free to share!

@stevelatham