MediaMind and Encore Partner to Deliver Integrated Attribution

March 7th, 2012 by Encore Media Metrics Team No comments »

MediaMind announced today its partnership with Encore Media Metrics to help marketers understand Attribution credit across digital campaigns. The integration between the MediaMind platform and Encore will give marketers immediate access to attribution reports that show what worked and what didn’t, in order to easily implement budget allocation to the best performing ads. Below is the first in a series of articles on Attribution written by Steve Latham, Founder and CEO, Encore Media Metrics.

Read the Press Release

Read CEO Steve Latham’s Guest Post on MediaMind’s CreativeZone!

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It’s Hard to Solve Problems from an Ivory Tower

March 2nd, 2012 by Steve Latham No comments »

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

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Conversion Paths vs. Full Attribution

February 24th, 2012 by Encore Media Metrics Team 1 comment »

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

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FAQ: Can you tell me about a success story you’ve had with a particular engagement?

February 16th, 2012 by Encore Media Metrics Team 2 comments »

In a recent campaign we measured for a leading media agency and their client (national retailer), we not only identified the top performers from a CPA standpoint, but we also found that 60% of impressions were wasted.  In fact, 82% of impressions seen by visitors were served to 6% of visitors with an average Frequency of 515 impressions over 45 days (average frequency for remaining visitors was 9).  We then determined that only 4.2 impressions were needed to drive a conversion, indicating a significant opportunity to optimize the campaign by limiting frequency and re-allocating budget to the top performing media vendors.

As always, feel free to comment and share!

The Encore Team

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FAQ: What is the Process for Doing “Attribution”

February 6th, 2012 by Encore Media Metrics Team No comments »

Encore’s approach to Attribution starts with aggregating and syncing impression data with site visitor data to create a comprehensive record of served impressions, visits, actions and page views for every visitor (paid and organic).  This user-based data is then analyzed to produce actionable insights into campaign performance.  Analyses include:

1) Conversion Path Analysis:

Encore aggregates and groups media conversion paths into natural clusters using statistical models that quantify the contribution of each channel in the engagement process.

2) Vendor Analysis:

Encore uses cluster sequencing algorithms and Markov probability analyses to measure performance of each vendor and placement.  We attributed credit for each vendor based on it’s statistically derived contributions (assists) and compute an Attributed CPV and CPA for each vendor.  We then group vendors as a “Winner,” “Laggard” or “Bubble” based on where they rank in the distribution.

 

 

 

 

 

 

3) Sequence-Based Impression Weighting: We calculate the relative value of each impression based on its sequence in reverse chronological order (starting with most recent) to help advertisers understand how recency and sequence impacts performance.

 

 

 

 

 

 

 

 

 

 

 

4) Lastly, we quantify wasted spend by calculating how many impressions are inefficiently served. We use the statistical modeling above to calculate how many impressions were required to drive a visit and a conversion, then calculate how much budget the Advertiser could have redeployed by reducing frequency and increasing reach.

 

 

 

 

 

 

 

 

 

 

 

As always, feel free to comment and share!

The Encore Team

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FAQ: What Types of Marketers Should be Investing in Attribution?

January 26th, 2012 by Encore Media Metrics Team No comments »

While e-commerce companies have led the adoption of advanced analytics, consumer brands (CPG, manufacturers, retailers, ecommerce, auto, travel, finance, health, etc.) are now actively adopting.  We’re also seeing more B2B advertisers extend their interest in measuring ROI by adopting Attribution solutions.

Ideally advertisers are using multiple digital channels: display, search, email, affiliate, etc.

Seeking to drive traffic to a web site to take some type of action: view or submit content, visit a goal page, join a list, complete a form, submit a lead or make a purchase.

As always, feel free to comment and share!

The Encore Team

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FAQ: What Questions Does Attribution Seek to Answer?

January 16th, 2012 by Encore Media Metrics Team No comments »

We’re all about capturing, analyzing and presenting data in the form of intuitive, actionable insights. In short, we provide answers to our clients’ questions, including:

  • 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?
  • 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

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Encore Media Metrics Shortlisted for Econsultancy’s Innovation Awards 2012

January 13th, 2012 by Encore Media Metrics Team No comments »

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

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FAQ: What is Attribution?

January 6th, 2012 by Encore Media Metrics Team No comments »

Attribution solves the “last-click” problem by allocating partial credit to each impression, click and interaction that influence conversions. Through Encore’s statistically validated attribution model, marketers can see the true performance of each channel, vendor, placement and keyword. Encore also measures the optimal frequency for converters while quantifying opportunities to expand reach and increase ad efficiency.  Armed with these insights, marketers can optimize campaigns effectively and efficiently while gleaning a deeper understanding of customer engagement cycles.

As always, feel free to comment and share!

The Encore Team

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The Online Media Paradox: Steve Latham’s Guest Post on iMediaConnection

November 15th, 2011 by Encore Media Metrics Team No comments »

Steve Latham offers his view of the gap that exists between how data is being used to find audiences and measure performance. He provides 3 reasons for the gap, a roadmap for addressing them, and a glimpse at what better metrics will do for the industry. Read the full post at iMediaConnection today!

Key topics of discussion and questions answered:

  • What are the key reasons for the slow adoption of new metrics in online advertising?
  • How can marketers close the gap and remove roadblocks to growth in online advertising?

Read More:
OMMA Metrics Interview: Multichannel Attribution and Insights

The Five Forces Driving Attribution: Media Measurement Comes of Age

Attribution 101: Full Funnel Media Measurement

Media Attribution Demystified

As always, feel free to comment and share!

The Encore Team

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