Last month I had the pleasure of moderating the Display Ecosystem panel (View the Video) at Rapleaf’s 2012 Personalization Summit.  On my panel were experts from leading companies that represented numerous categories within the display landscape.  Panelists included:

• Arjun Dev Arora – CEO/Founder, ReTargeter @arjundarora
• Key Compton – SVP Corporate Development, Clearspring @keycompton
• Tod Sacerdoti – CEO & Founder, BrightRoll @todsacerdoti
• Mark Zagorski – CEO, eXelate @markzexelate

Our discussion addressed many of the issues that we are grappling with in the Ad-Tech industry, including:

• Complexity: The challenges of planning, executing, measuring and optimizing display media are exacerbated by the complexity in our space.  How can we reduce the cost and level of effort required via integration, prioritization, standards, etc.?
• Consolidation: What will the landscape look like in 2 years?  Will there be more or fewer players?  Where will consolidation take place?  Who will be acquired and by whom?
• Effectiveness: What can the industry do to improve performance and effectiveness of advertising? How will better targeting, data-driven personalization, frequency management and 360 customer-centric approaches improve efficacy of online marketing?
• Accountability: Where are the gaps today, and how should we be measuring results, performance, ROI, etc?• Outlook for publishers, ad networks, DSPs and agencies.  What must each do to survive / thrive in this hyper-competitive marketplace?
• Other issues: privacy, legislation, new platforms, etc.  In order to fully realize the potential of display advertising (i.e. Google’s $200bn forecast) these will need to be addressed.

After our discussion, I thought about the implications for the Display Ad ecosystem, and for the Ad-Tech industry as a whole.  Here are a few of my thoughts…

• No other industry is as innovative, adaptive and hyper-competitive as ad-tech. Where else can new niches evolve to multi-million dollar categories overnight with hundreds of startups raising billions in financing every year?  We’ve all seen industries where startups disrupted an established ecosystem for a period of time.  But where else does this happen over and over and over again?  Our industry is all about disruption and it doesn’t take long for the challenger startups to become the established incumbents or targets.
• No other industry creates wealth like ad-tech.  Where else can companies launch, raise capital and exit for hundreds of millions (or more) in less than 18 months?  Where else are so many successful entrepreneurs (and their benevolent VC backers) rewarded with lifetime wealth for 1-3 years of work?  It’s pretty amazing if you think about it… our modern day decade-long gold rush.
• Success in our industry requires mastery of several disciplines: marketing, technology and data science.  You can’t be a world-class ad-tech company without expertise and experience in all 3 of these categories.
• While we are making progress as an industry, we still have so far to go.  Despite the advances in targeting, real-time bidding dynamic creative optimization, analytics and optimization techniques, most media buying is still done the same way it was 5 years ago.
• There is still much confusion about how real-time exchanges work, and how they can be utilized by agencies and advertisers.  When you overlay that with efforts to aggregate 1st party data, creating proprietary cookie pools and using that data to find new audiences, many marketers become quickly overwhelmed.
• We still have a scale problem that must be addressed.  While there is a huge supply of impressions available for real time bidding, there are only so many unique audiences in the warehouses operated by the data providers.  The more granular you get from  a targeting standpoint, the smaller your reach wil be.  Frequency capping is challenging, so you end up with hundreds or event thousands of impressions being served to a small pool of unique users.
• We still have a people problem.  All the technology in the world won’t save us if we don’t have people trained to leverage these capabilities.  We also need a deeper pool of managers and leaders who can bring operational excellence to a fledgling, always-evolving industry.

The wall mural below sums up the discussion – and made for a nice graphic snack for attendees.

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

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

Encore Selected in Two Categories for Innovation Awards

Encore Media Metrics was selected from over 450 competitors in more than 19 categories as a nominee for Econsultancy’s 2012 Innovation Awards! The annual list highlights cutting edge ideas in digital marketing. Encore is proud to be selected in two categories: “Innovation in Online Advertising,” and “Innovation in Web Analytics.”

We congratulate our strong, creative competitors and wish everyone a very happy and prosperous 2012!

For more information about Econsultancy’s Innovation Awards, visit: http://econsultancy.com/uk/awards

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

In early June I was fortunate to be one of 350 ad tech CEOs who attended LUMA Partners’ Digital Media Summit in NYC, featuring the best and brightest in the industry.  I’ve been to some great networking events before (IAB, 4A’s, etc.) but this was tough to beat.

In addition to meeting some amazing people, one of the highlights was the release of the latest display ad landscape or “LUMAscape” aka “the slide” that was originally produced by Terence Kawaja in 2010.  For those who are new to display advertising (or have been out of the market for the last 3 years), buying display media is like buying a house: you also need phone service, internet, cable, gas, electricity, dog-walking, etc.  In this case, Media is the house; ancillary services include ad verification, OBA compliance, data/tag management, audience measurement, ad serving, and our favorite: attribution.

The newest version of the slide is getting ever closer to accurately depicting all the segments and sub-segments that comprise the digital advertising landscape.  It also marked the debut of Encore Media Metrics as a recognized leader in the Attribution and Measurement category.

“The Slide”may also viewed on slideshare or you can download the LUMA Display Landscape here.

The industry is extremely fragmented, and is likely to stay that way for a while.  So if you want to play in the display advertising space (either as a buyer, seller or manager) you need to understand the difference between a DSP, DMP and SSP without yelling “WTF!”  Yes, it’s easier said than done but this map should help you get started.

Steve Latham (@stevelatham)

Encore’s CEO was recently interviewed by AdExchanger, a leading online marketing  news publisher, about the launch of Encore, the problems we solve and how we’re positioned.  You can read the article on AdExchanger or see the transcript below.  Enjoy and feel free free to share!

Encore Media Metrics Incorporating Attribution For Paid, Owned And Earned Media

Steve Latham is CEO of Encore Media Metrics, an attribution technology company.

So, what problem are you solving with Encore?

We solve 2 problems for agencies and brands alike.  First, we provide advanced attribution and measurement, enabling them to see across channels and beyond the last click to measure performance of paid, owned and earned media.  While most marketers are aware of the need for attribution, very few are doing it.  Second, we allow them to offload the tedious, manual work of reporting and measurement, which is a loss-leader for most agencies.  They need good metrics, but it’s hard to justify the cost of large teams needed to manage all aspects of reporting.  We offer a cost-effective way to produce the insights they need to optimize budgets and maximize campaign ROI.  So to sum it up, we provide better reports and deeper insights in a way that saves them time and money.

I believe we’re hitting the market at a great time and that this will be the year Attribution goes mainstream for a few reasons.  First, paid search is maturing and expanding digital budgets will have to be deployed elsewhere (display, social, mobile, etc).  There are only so many searches every day and most companies have optimized their ppc campaigns.  The low hanging fruit in search has been picked; further gains will be in much smaller increments and will require buying short-tail terms that start conversations rather close them (hence the need for keyword attribution).  This is supported by the fact that Display will grow faster than search in 2011 and is expected to outpace it for coming years. Search is still the big dog, but display and other brand-building media are nipping at its heels.  If you believe Eric Schmidt’s prediction of a $200 billion global display market, we’re still very early in this game. Other factors driving Attribution are the increasing focus on accountability, the upgrading of web architecture (e.g. adoption of universal tags) and the emergence of affordable attribution solutions – such as ours.  These factors are converging to make 2011 a very exciting year for those of us in the attribution space.

What’s your view on the competitive set and where you’ve been and how would you say you differentiate?

To understand how we’re positioned, you must first understand how the Attribution marketplace is segmented. For starters, there are two different approaches to attribution: operational attribution and statistical or algorithmic modeling. Each approach has its place and I believe they are more complementary than competitive. Statistical modeling analyzes vast amounts of data to look for correlations that indicate how media channels (display, search, email, affiliate, etc.) work together to drive results. Modeling allows you to see which channels feed each other, and which mix should yield the best overall ROI.

In contrast, operational attribution creates detailed records for each visitor that enable you to see which ads were seen and clicked on, how the visitor found your site, what pages they viewed and what actions they took. You can then query the data to analyze engagement paths and assess the performance of each channel, vendor, keyword and placement. We believe operational attribution is the foundation for advanced analytics as it’s based on actual visitor data (vs. a black box) and provides much more granular insights into performance of all types of media. Once you have operational attribution, you can then do advanced modeling of that data to glean additional insights. But, operational attribution will provide 80-90% of the insight you need to optimize your spend.

Within the Operational segment, you then have to look at the extent of attribution: lower-funnel (click-based) vs. full-funnel (clicks and impressions). While click-based attribution is better than nothing, it doesn’t answer the question: “which media buys are creating demand?” The lower-funnel approach relies on clicks, which may be great for search, but insufficient for measuring the impact of display media. If you want a true picture of which ads are creating demand and which placements are satisfying demand, you need a full-funnel solution.

Now to the original question: how are we positioned vs. our competitors? While I can’t speak for our competitors, I can say we differentiate in a few ways: 1) we incorporate attribution from social media (even in the absence of referring clicks), allowing us to provide attribution for paid, owned and earned media, 2) we have a flexible approach that is designed to accommodate varying needs of agencies and brands (no long-term commitments, pay for what you use, etc.), and 3) we are affordable for most marketers. If a client spends between $50,000 and $5 million per month in online media, they can afford our solution.

Is scale of ad spend critical to Encore’s services – attribution, media mix modeling?

If you’re asking is Attribution is only suited for the biggest advertisers, the answer is no. It really doesn’t matter how much you spend; you still need to look across channels and beyond the last click to optimize your mix. Even if you’re only spending $50,000 a month, a small incremental investment can yield a dramatic improvement in Return on Spend. Any advertiser who is buying more than just search is going to benefit from Attribution.

What’s your view on the “view‑through conversion”?

View-throughs are good for ad networks seeking to optimize their media placement, but they are limited in what they offer advertisers.  If you are buying display media from 5-6 vendors, you’re likely to get some view-throughs from each buy.  While view-throughs tell you if an ad was seen they don’t tell you which ads were the most effective (and cost-effective) in creating demand, or how each media buy influenced results from paid or natural search.  You can’t analyze recency or frequency and you can’t tell the order in which ads were viewed.  You need more details to truly understand which placements created demand, the role they played in the engagement path, and how to attribute credit within the channel.  Yes, you need a full-funnel attribution solution.

What’s the difference between attribution modeling and media‑mix modeling?

In the context of measuring the impact of digital media, they’re effectively the same thing.  But for most marketers, media‑mix modeling encompasses all channels, including TV, print, radio and other traditional media.  Within that context, operational attribution should play an important role in providing the inputs that go into such a model.  We can provide a much more accurate and richer set of data inputs that will enable the global media mix model to produce more relevant and insightful outputs.  As mentioned earlier, it shouldn’t be “either / or” when evaluating operational vs. algorithmic attribution.  They can work in concert quite well.

What do you see out there as the most difficult channel to provide the sort of service you’re providing today?

Within digital media, Social is definitely the hardest to measure.  First, referring clicks are not good indicators as very few actually click-through from social sites to the brand’s web site (see “Connecting the Dots”).  But beyond clicks, how do you attribute credit back to people who are watching your You Tube channel, viewing comments on your Facebook page or reading a blog about you?  It’s hard because you can’t cookie browsers on 3^rd party social media sites.  While Facebook now allows marketers to set cookies via iframes on company pages, very few are doing it.

Some try to do social attribution via correlation or looking at directional trends, where a social mentions drove a spike in traffic and a lift in conversions.  But this approach is, in technical terms, “squishy.”  For most, social attribution is a future goal more than a near term objective.

But since you asked, I should mention that we offer a unique solution to the social media attribution problem. We use a patent-pending tool that allows us to identify which visitors or purchasers have engaged with the brand in social media, regardless of whether or not they clicked through to the site.   Through this, we can draw a direct line between online conversions and the social interactions that preceded them.  We think it’s pretty cool and we’re seeing a lot of interest from brands, agencies and media vendors.

Do you see social media attribution as an opportunity?

It’s definitely something we see as a differentiator but it should be viewed as part of our solution for two reasons: 1) social should be integrated with other channels from a measurement perspective, and 2) it’s hard to make a ton of money on social media measurement.  A brand may spend $500-$1,000 to measure social interaction, but they’re not likely to spend more on the tool than they do on their social media marketing efforts.  You also don’t want to be a one-trick pony in the digital landscape.  Things move too quickly and one player (e.g. Google) can make render your product obsolete overnight.  So we see it as a differentiator and a conversation starter more than a standalone offering.

What is Encore’s target market?

We serve brands and agencies who are seeking to create demand and/or drive sales through paid, owned and earned digital media.  While we can accommodate budgets as low as $50k per month, our sweet spot is campaigns with budgets of $100,000 to $2 million per month.

In general, Attribution tends to be more appropriate for considered purchases, e.g. financial, auto, travel, health care, luxury goods and anything B-to-B.  The longer the sales cycle and the bigger the ticket, the more you need Attribution.

We work with brands, agencies and trading desks of all sizes, even those with internal ad ops teams.  Even if they have a bench, they still need better tools to produce the insights their planners and customers demand.

How does pricing work? Do you charge on according to media spend or is it a per seat?

We price our solution as a technology (vs. a flat % of media spend) that is tiered based on the scope and scale of the campaign.  In general, we charge a fixed fee that covers the planning, production and client services, along with a cpm-based fee that covers the cost of data capture, storage and analysis.  The fee as a percentage of the media budget will vary significantly.  If you’re buying premium placement media at $10cpm, our fees are tiny.  If on the other hand you’re going for scale (e.g. $2cpm), the fee will be slightly higher as a percentage of spend.  But in either scenario, we’re very affordable and the ROI is hard to beat.

What sort of milestones would you like the company to have accomplished?

My primary goal for 2011 is for Encore to become widely known as a leading provider of measurement, attribution and reporting services.  If there is a discussion about Attribution, I want us to be one of the solutions that are always mentioned.  Our value proposition (better reports, deeper insights, affordable and adaptable) is hard to beat, and we look forward to proving it to leading brands and agencies.

Follow Steve Latham (@stevelatham), Encore Media Metrics (@EncoreMetrics) and AdExchanger.com (@adexchanger) on Twitter.

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