Tag Archives: attribution

Move beyond last click attribution in AdWords

People often see many ads across different devices before making a purchase, booking a flight, or signing up for an account. Because of this, advertisers know that last click attribution may not always tell the full story. In 2014, we released the Attribution Modeling Tool in AdWords to share insights about how users interact with your ads. Later this month, you’ll be able to integrate the attribution model of your choice with your conversion data and bidding.

For each conversion type, use a simple drop­down menu in Conversion settings to select one of six different attribution models ­­ last click, first click, linear, time decay, position­based, or data driven. When you pick a new model, credit will be reassigned across the conversion path for all search or shopping ad clicks on Google.com, and your conversion stats will change moving forward. You can adjust bids based on your new way of counting conversions, and if you’re using automated bidding for search ads, your bids will be optimized automatically to reflect your new model. To learn more, visit our Help Center.
For the first time, AdWords advertisers with sufficient data will also be able to select the new data driven attribution model as a public beta, which is also available in Analytics 360, Attribution 360, and DoubleClick. Unlike rules­based models, data driven attribution uses machine learning to evaluate all the converting and non­converting paths across your account and identifies the proper credit for each interaction. The model considers the number of ad interactions, order of exposure, ad creative, and many other factors to determine which keywords and clicks are the most effective at driving results.

To help advertisers succeed with attribution, we’ve created a new best practices guide: “Beyond Last­Click Attribution.” The guide will show you how to:
  • Determine how important moving beyond last­click attribution is to your business 
  • Choose a model that best fits your needs 
  • Value early influencer keywords appropriately 
  • Act on attribution 
  • Evolve your approach to attribution as measurement gets better 

We hope the new functionality and guide will help you optimize your marketing campaigns and drive stronger results, and our goal is to expand beyond search soon.  

Posted by:
Joan Arensman, Product Manager
Wilfred Yeung, Product Manager

The New PR Reporting Landscape: How To Show Value and Drive Decisions

By Rajagopal Sathyamurthi (CTO & Co-Founder) and Leta Soza (Director of PR Engineering & Ops) at AirPR

Public Relations constantly grapples with the ability to report meaningful results in a manner that resonates with executives and members of the C-Suite.

Until the emergence of “PRTech” began to enable dot-connecting between PR activities and business goals, the PR industry generally used output driven metrics (impressions, number of press hits, AVEs, etc.) to communicate its value; but these barometers rarely tie back to business goals and don’t do much to inform future decision-making.

All of this is changing as PR shifts its focus from reporting on outputs to data-driven outcomes. Metrics such as visitors to site, engagement, and message “pull-through” are quickly gaining ground as the new gold standards for PR measurement. A widespread adoption of these metrics, however, is predicated on a reporting mechanism that can neatly and efficiently package this data.

To help solve this widespread challenge, AirPR recently launched a Reporting Suite that uses aggregated PR activity output data from our Analyst product to generate automated, actionable reports based on the customized success metrics of any company.

One of the key components to leveraging the power of the Reporting Suite is our solution’s unique integration with Google Analytics. This integration allows us to analyze and visualize specific subsets of Google Analytics data.

The Google Analytics Core Reporting API exposes a few key metrics which have great utility for PR professionals: users and goal/event conversions. Pre-processing and ingesting this metric data into our Reporting Suite allows PR pros to see trends over time as it relates to traffic and engagement driven by PR content.

When PR can quickly survey this data, the question isn’t, “do spikes in coverage volume correspond to spikes in traffic?” Rather it is, “which narratives, outlets or topics drive the most traffic, engagement, or amplification?” Also, “how can successes be replicated?” 


These key metrics combined with AirPR’s data, classification features, and proprietary algorithms also provide a simple way to slice, dice, and visualize complex data in seconds.

Dimensions such as full referrer (content sources) and date (subset of time) are crucial to PR pros understanding which media outlets and specific pieces of content are more impactful for their business over different time ranges. 

AirPR Analyst enhances the direct attribution data from Google Analytics with additional sources of PR data to track and display the performance of content that contain links back to company websites, as well as the impact of articles that do not contain links or those with links that do not get clicked. 

Last but not least, our Reporting Suite aims to impact how PR success is defined. Not only will PR have a clearer picture of what delivers for their brand or client, they can quickly and succinctly speak to business leaders in key data points, which highlight success stories.

No matter what technology or methods you are using, here are a few simple tips for communicating success like a PR boss, and ensuring that the executive (to which you report) can clearly see the value of your hard work and effort:

Top-line and bottom-line it.
 • The best of the month in terms of X metric was Y content and what this means is Z.


Use numbers to tell the story. 
 • We saw an X% change in Y month over month, and what that does for us is Z.


Speak to business wins.
 • This is what X activity did for business goal Y.


Share what’s next. 
• With X data, we are going to focus on Y.


The remaining hurdle for PR pros is to begin thinking differently about what metrics matter in terms of future decision making. While impressions and press hits are certainly important in terms of “activity-based metrics”, they don’t necessarily tell the whole story. Our information-rich environment implores us to continually evaluate which pieces of media or content properly convey key messages, reach our desired audiences, generate top-of-funnel business leads, and ladder up to business goals.

Posted by Google Analytics technology partner AirPR

Enable better decisions with Data-Driven Attribution

The following was originally posted on the DoubleClick Advertiser Blog.
Consumers see a lot of different ads as they make buying decisions. Some ads have a huge impact on the final purchase, others help the process along, and still others contribute absolutely zero. The trick, of course, is knowing which ad does what.
Today we’re introducing Data-Driven Attribution to all DoubleClick accounts. It's a new tool that helps you give the right credit to each and every advertising touch point ― and shows you the optimal combination for your marketing.
Powered by Adometry, Data-Driven Attribution uses a modeling methodology developed by Google engineers and grounded in advanced statistics and economic principles. It assigns credit accurately and automatically to all your digital media ads served through DoubleClick.
Click image for full-size version

Turbocharge your campaigns
DoubleClick Digital Marketing already has a strong attribution foundation with Multi-Channel Funnels and the Attribution Modeling Tool. Now it's even easier to make decisions about how to best allocate your digital media budget. Data-Driven Attribution is:
  • Actionable: The contribution made by each marketing channel is clear (in both converting and non-converting paths), so you can make better data-driven marketing decisions.
  • Accessible: Just choose your goals (such as e-commerce transaction or email signups) and Data-Driven Attribution will show you the contribution made by each of your digital campaigns.
  • Comprehensive: No need for new tags, just turn on the feature and you’ll see data for your campaigns.

There’s no room for guesswork in attribution ― and when you’re not guessing, you’ll see greater ROIs and better performances.

“Mindshare helps brands get the most of their digital marketing. To do that we need meaningful insights on the consumer path to purchase across both display and search. We have been testing Data Driven Attribution in DoubleClick and we have seen tailored recommendations that allow us to take fast action for greater impact and better ROI. In some campaigns we have been able to improve budget allocation and have seen CPA improve by 25%.”
-Karen Nayler, CEO, Mindshare Canada

How to get started
You'll find the Attribution interface in the Reporting and Attribution section of your DoubleClick account. You can activate Data-Driven Attribution for all your floodlight tags and once you start collecting data, you'll see a new recommended model appear after seven days.
Learn more about Data-Driven Attribution.
Posted by Luke Hedrick, Product Manager, DoubleClick


Data-Driven CMOs: Leaving the Information Age

Originally Posted on the Adometry M2R Blog

Remember the so-called “Information Age”? Once a catch all for all things technological, over time the term came to refer to the transition to a society in which individuals had access to a wealth of information to aid in decision-making – a global democratization of knowledge. From a marketing perspective, the Information Age also came to represent a fundamental shift for data-driven CMOs away from simple push tactics to a dynamic, real-time ebb and flow of information between brands and customers.

With this transition has come all sorts of complexity. An argument can be made that demands on marketers have never been higher; yet, in some respects the evolution towards data-driven marketing has simplified or even solved some of the profession’s biggest pain points, such as:
  • Gaining an ability to track performance at a granular level
  • Understanding consumer behaviors within the marketing funnel
  • Gleaning insights about how marketing impacts consumers’ inclination to make a purchase decision
In short, the Information Age now has less to do with access to information as it does with the ability to utilize it effectively.

Moving from Information to Insights

In a previous interview with CMO.com, I was asked what I now know that I wish I had known earlier in my marketing career. My response?
“Today’s marketing leaders are a combination of creative, technologist, analyst and strategist. Success in modern marketing is predicated on being agile, having great vision and being able to effectively manage change across the organization. To be clear, the advice would not be to blindly chase shiny new objects. Rather, it would be to proactively set aside the time and resources to foresee, evaluate and test opportunities on the horizon.”
So how do marketers manage change across their organizations? It starts identifying where marketing can offer unique value by transforming raw information into insights.

“Big data really isn't the end unto itself. It’s actually big insights from big data. It’s throwing away 99.999% of that data to find things that are actionable.”

The comment above was made previously by Bob Borchers, Chief Marketing Officer for Dolby Laboratories, at a Fortune Brainstorm Tech conference. It should go without saying...but to reiterate; data isn't the same as knowledge. Data without context is no more useful than knowing your current driving speed without understanding which direction the car is headed.

Another way to think about this is to consider the difference between building a data-driven marketing culture and a truly data-driven organization. We’re already witnessing this maturation happening within organizations that were early adopters of “big data”. Led by marketers who invested in foundational elements – attribution measurement and analytics, cross-channel allocation and alignment, etc. – these organizations are now taking the next step to integrate marketing with other disciplines, such as finance. In doing so, discussions about marketing performance start to sound less like functional assessments of campaign efficacy and more like part of a strategic, holistic business plan. Now impression and click-stream data can be discussed through the lens of media costs (online and offline) and supplier value, linked directly to sales.

Using a data-driven attribution measurement solution offers additional clarity by showing exactly how individual channels, publishers and creatives contributed to revenues. By looking beyond simple metrics and getting a more complete view of performance across channels, marketers suddenly have a sense for how to proactively manage towards overarching business objective (e.g. top-line growth) while also maintaining a sense for costs and ROI.

So is this still the Information Age or something else? What’s clear is that simply gathering and organizing information is no longer the endgame, it’s only the beginning.

Posted by Casey Carey, Google Analytics team

Integrating Marketing Mix Modeling with Data-driven Attribution for Holistic Insights


Today’s marketers have more opportunities than ever to drive business success. They also face increasing pressure to prove, manage, and optimize marketing performance. 

A relentless push towards accountability has driven the adoption of ever-more-sophisticated measurement tools. Many marketers use marketing mix modeling (MMM), some use data-driven attribution, while others consult a separate solution for each. 

Tools continue to evolve. Now, solutions that merge and substantively improve both of these measurement best practices promise faster, more efficient, more holistic insights. To find out more, we commissioned Forrester Consulting to survey 150 companies in order to explore how marketers are evaluating, adopting, and using these emerging tools. Key learnings will be presented in our Dec 8th webinar hosted by Google and featuring Tina Moffett, Senior Analyst at Forrester along with Dave Barney, Product Manager, Adometry at Google. Sign up here.

Why consider a merger?
While separate MMM and data-driven attribution tools offer cross-channel measurement, each has limitations:
  • Speed and Granularity. Traditional MMM offers high-level analysis on a quarterly or yearly basis, which can limit more granular, or on-the-fly optimization
  • Data Limitations. Data-driven attribution requires a wealth of granular, user-level  data, which can limit offline channel visibility
When the two measurement practices are combined, however, they improve the outputs from each. Data-driven attribution informs MMM models. MMM data feeds attribution analysis. Resulting insights allow marketers to see the impact of each marketing element in near real-time.

Pending or trending?
Today, many marketers get the optimization benefit from separate MMM and data-driven attribution tools. Will merged tools become a new marketing performance measurement standard?

While it may be too early to tell, there is a growing desire for tools that help marketers move beyond channel-based optimization to larger strategic cross-channel planning. Forrester reports that many respondents have already moved, or plan to move, on the merged measurement trend and the most common approach has been to purchase a solution from a vendor, and to make use of the vendor’s implementation support. 

“There will be a paradigm shift in understanding for the marketing channels. I think it gives them an opportunity to think holistically rather than in a silo, like, ‘this is my world, this is my budget, as long as I get this much traffic in my channel, I am ok.’ It’s no longer the case. Getting that understanding is going to be key. It gives us better understanding of how our customers navigate through different touch-points.”

— Director of Marketing And Automation Systems at a major global retailer

Benefits and challenges
Integrated MMM and data-driven attribution tools are enabling marketers to make strategic planning decisions and precisely measure individual-level interactions in near real-time. Satisfaction with integrated tools is high among those who have implemented them.

Faster access to insights has more companies looping in more stakeholders from marketing execs and analysts to customer insights or analytics, brand managers, and eCommerce professionals. 

At the same time, early adopters report challenges. Integrating tools and data sources is a big ask, learning when to make changes based on new insights takes time, and setting expectations about timelines and results is paramount. 

Ensuring that the entire organization is on board with using a merged measurement platform is critical, as is supporting stakeholders in changing business practices as a result.

Proceed with insight
As merged tools come on strong, the experiences of early adopters may be instructive to those moving to embrace a merged solution. Recommendations on best practices, processes, and supports, are examined in the full whitepaper. 

Making the right move
While companies cite common barriers to adoption, respondents suggest that a number of challenges that are stopping them today would be resolved in the near future including, skills, understanding of benefits and technology blockers.  

As merged tools mature and become more commonplace, technology concerns will abate. More marketers will know about these solutions, and about how to use them to drive marketing optimization and strategy. Staying informed is the key to making the right call on whether, when, and how to adopt merged measurement tools for your business.


To learn more, sign up for our upcoming webinar with Forrester Research on December 8th.

Posted by Natasha Moonka, Product Marketing Manager, Google Analytics team

Introducing the Definitive Guide to Data-Driven Attribution

Originally Posted on the Adometry M2R Blog
For as many dollars organizations invest in marketing, it never ceases to amaze me how many of those organizations are willing to make guesses about how effectively those dollars are being used. Even when those guesses are educated, they can be way off. We live in a world where data-driven attribution can take the guesswork out of your marketing program to gain a clear and comprehensive view into the customer journey.

It can be intimidating to get started with data-driven attribution. Many marketers are already inundated with data from marketing mix modeling, real-time bidding, website analytics, CRM and more. But the genius of data-driven attribution is that it makes all that other data better, more relevant and actionable to improve the bottom line.

With our Definitive Guide to Data-Driven Attribution, we’ve laid out just how your organization can approach marketing attribution. We’ve made it easy to understand what data-driven attribution does, how it fits in with what you’re already doing and how to get started.

What Is Attribution and What Are the Benefits?

Let’s start with the basics. There are a number of basic models such as first touch, last touch, even and custom attribution. Those models offer general answers across a basic marketing mix, but they fail to provide the true value of each marketing asset as the marketing campaigns get more complex. Today’s cross-channel marketers need a more scientific approach.

Data-driven attribution models use sophisticated algorithms to determine which touch points are the most influential. That means marketers can see the benefits of each touch point and adjust future spending to maximize results.

How Does Data-Driven Attribution Fit into my Analytics Toolset?

Odds are you’re already collecting a ton of marketing and advertising data. That’s great! Data-driven attribution doesn't replace that information. It greatly enhances it.

As an example, let’s look at marketing mix modeling. At the end of a campaign, you look back and assess performance. With data-driven attribution, you can accurately see how each tactic performed so you can plan better for the next campaign. Extending that to the next step, accurate attribution gives you insight that your real-time bidding partners can use to buy top performing ad placements.

Another example is your CRM. As you gain customers, your CRM captures transaction, contact and segment data, but CRMs tend to focus more on customer service and support, not marketing. And although CRMs track multiple channels, they look at lower-funnel activities and offer limited visibility into acquisition and cross-channel marketing in non-direct channels. CRM data is an input that can feed your data-driven attribution solution to yield a more complete picture of customer behavior.


As the graphic above shows (and details more within the guide), data-driven attribution ties all of your other marketing analytics together and improves what you’ve been getting from each one.

Getting Started

Data-driven solutions vary. To get the benefits, you’ll need to ask the right questions about your organization, solidify the right budgets and motivate the right people. In the guide we outline five key steps to getting started.

  1. Define Goals: Consider your current pain points and business goals. Determine the value that all of your marketing activities must deliver for the business and take a holistic view of the data-driven changes you’ll make to meet those goals. That will help determine marketing’s impact on revenue so you can formulate budgets that will yield the highest returns.

  2. Justify Budget: The right solution will pay for itself by creating cross-department efficiencies and increasing the return on each marketing investment, but change can be difficult. Check out the full Definitive Guide for a real-world budgeting exercise to help you promote the benefits of data-driven attribution to key stakeholders.

  3. Be Selective: There are a number of attribution providers. Evaluate them by asking the right questions about their ease of implementation, breadth of services, methodology, capabilities and technology roadmap. Can they handle your data? How will they work with your existing partners, including your ad agency? Do they provide a consultative partnership? Is their model data-driven or rules-based? Are they media agnostic? How is their model validated? Can they measure online and offline activities? How do they account for multi-screen customer journeys? How often do they upgrade their solution?

  4. Get Prepared: Picking a provider is a good start, but you also must get ready for integration. Prepare both human and data resources to hit the ground running. Evaluating data readiness and preparing stakeholders ahead of time will help you determine how much support you’ll need during implementation.

  5. Evaluate Success: Your stakeholders will be more invested in driving success with data-driven attribution if they can envision what success looks like, and concretely evaluate whether goals are being achieved. Show them the way. Leverage your goals to evaluate your provider’s performance on marketing performance, enterprise ability, ease and flexibility, quality of output, total cost of ownership and an innovative roadmap.
There’s no doubt that today’s marketers need better performance measures to know whether they are producing the best results for the organization. Data-driven attribution requires investment on the front end, but it pays big rewards that will have you asking why you didn’t take the plunge sooner.

We encourage you to dive deeper to help your organization understand the true benefits and implications of data driven attribution through our definitive guide.

Why You Should Care About Attribution

Originally Posted on the Adometry M2R Blog
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This is a guest post by Brian Sim, Product Marketing Manager, Marin Software
Attribution is sometimes perceived as being too complex, too technical, and too cold. However, when you look beyond the advanced-level math that goes into attribution algorithms and consider consumer behavior and buying tendencies, the importance of attributing revenue across the customer purchase path becomes very apparent.
Consider your own purchase behavior. How many steps did it take to get you from awareness to purchase the last time you bought something? Chances are it took you at least a few steps to get from “I think I could use a new lawn mower” to deciding “This 200cc self-driving, side-discharge robot lawnmower is the exact one that I need, and I’m going to purchase it this weekend because there’s going to be a seasonal sale.”
With that in mind, the next logical question is, based on your customer journey, do you think it makes sense for the last advertisement you saw prior to buying to get 100% of the credit for your purchase? If your answer is “no, that doesn’t make sense,” then you’ve uncovered the problem that attribution is trying to address.
On the analysis end, attribution modeling platforms like Adometry are tackling one of the most grounded-in-reality problems marketers face: “Is my multi-channel marketing budget being spent on the right channels?” On the execution end, revenue management platforms like Marin Software enable marketers to optimize their campaigns based on their advanced attribution data and answer the question, “How can I take that attribution data and improve my future ROI?”
Three Reasons Why You Should Care About  Attribution
Reason 1: It helps you understand your customer’s path from discovery to purchase.
As a recent Google study showed, consumer purchase paths are rarely straightforward; 60% of purchases take multiple steps, and depending on the industry you’re in, up to 84% of total revenue can come from purchases that required multiple steps across several days. Advanced attribution models can quantify each step of the customer purchase pathway. Armed with this knowledge, marketers can begin to associate ROI with specific marketing channels, understand the time lag for customer decision-making, and optimize spending across different marketing channels.
Reason 2: It allows you to understand and quantify performance across channels.
The multi-step customer purchase path may not be an issue if every step occurred within a single channel, but alas that’s not the case. The path from discovery to purchase typically involves multiple disparate marketing channels, each playing a slightly different role.
In order to optimize your marketing spend, you first need to understand the interplay amongst the various channels. Data-driven attribution allows marketers to assign proper credit to each touch point along the buyer journey. This allows the marketer to understand the proper valuation of channel and budget, and bid and tailor creative more effectively.
For example, within the travel vertical, Social acts as an assistive interaction and is many steps displaced from the actual purchase decision. In contrast, Display is almost as close to the customer’s purchase decision as the paid Search channel. In this case, direct marketers may optimize their campaigns to weigh the Display and Search channels more significantly. In many other cases, Display plays much more of an assistive role, and direct marketers may optimize their campaigns towards Search or another channel that is closer to the customer’s purchase decision.
Reason 3: It gives you the insight you need to make smarter decisions.
As the saying goes, “knowing is half the battle.” But knowing is only half the battle. The value of attribution is only realized once marketers can act upon their data. Adometry’s Programmatic Connector enables marketers to seamlessly incorporate attribution data into day-to-day decision-making workflows. Additionally, this is where an open stack execution partner like Marin Software helps complete the circle. Marin’s Revenue Connect is an open, flexible platform that enables advertisers to integrate data from any of their sources, including advanced attribution data, to improve campaign performance.
Activating your attribution data can help achieve real results. MoneySuperMarket, the UK’s leading price comparison site, partnered with Marin Software and Adometry to activate their attribution data in their marketing campaigns. By marrying their search intent and first-party audience data and then applying an algorithmic multi-click attribution model, MoneySuperMarket increased CTR by 12% and reduced CPC 7% across their motor insurance campaign, and increased profit margins 14% across all insurance campaigns.
Yes, attribution can be complex. But the value in unlocking that data can provide sustainable, competitive advantages across all of your marketing decisions.

Top 5 ways to amplify the impact of TV dollars with digital

Today’s consumers hop from screen to screen according to their needs-of-the-moment. They don’t give a thought to what “channel” they are using to interact with your brand — they simply expect brands to keep up. 

In last week’s post, we discussed the advent of TV Attribution and the new opportunity marketers have to drive more ROI in a multi-screen world. This week, we’ll discuss 5 key ways that TV Attribution can help you get more from mass media investments with digital insights. 

If you want more details on any of our top tips, take a look at our recent white paper or register for our upcoming webinar. 


1. Align creative across channels. If a friend was always chummy on the phone, but cold in person, wouldn’t you be confused? Don’t let a choppy brand presentation put off interested consumers who experience TV ads, search online, and visit your sites and apps. Use consistency between your online and offline presence for a clear message. 

2. Empower mobile search. Knowing that TV ads inspire mobile searches, make sure digital copy aligns with verbal and on-screen messages in TV ads to ensure consumers find you online. Use mobile context — include click-to-call, highlight nearby stores, show relevant hours — to move consumers from search to purchase.

3. Connect the data. Connecting TV airings data with digital signals like search query and site traffic offers a new level of granularity and immediacy of reporting. With better insights, you can fine-tune your next TV campaign and align digital strategies to capture incremental opportunity.

4. Find your best audiences. Take the guesswork out of demographic targeting with digital insights. Search and site data reveal who is really responding to TV messages by taking online actions — so you can confirm your best audiences by behavior.

5. Understand your consumer. Analyze digital signals to understand what parts of your message consumers are retaining — or not retaining. The keywords consumers search after being exposed to your TV ad offer insights that can drive faster campaign optimization, saving time and money over traditional surveys or studies.

More insight, more opportunity

TV Attribution not only offers a new, immediate, and granular view of mass media impact — it allows you to create more cross-channel synergy. Today’s consumers want immediate gratification and have high expectations for the brands they pursue. Join us for a webinar October 20th to discuss more tips and tricks for meeting new consumer expectations, and hear how top brands are leveraging minute-by-minute TV Attribution analysis to improve cross-channel marketing. If you’re ready to dive in, register here.

Posted by Natasha Moonka, Google Analytics team

How can you get more ROI in a multi-screen world?

We live in a world of instant gratification. Wherever we are, and whatever we may be doing, when we want to know, to do, to buy we pull out our phones and search for satisfaction.

For marketers, a multi-screen world offers new opportunities for ROI. While TV accounts for 42% of all ad spending, or $78.8 billion annually,  we also know that 90% of consumers engage with a second screen* — think tablets and mobile phones — while watching TV. 

This means that in a multi-screen world, executing separate television and digital campaigns is a strategic miss. If that’s the case, why are so many of us still doing it?

The old TV measurement problem
In the past, channel-centric thinking, competing objectives, and data silos often stopped marketers from true cross-channel measurement. Even with the advent of marketing measurement best practices like marketing mix modeling, we lived with a significant blind spot around the true impact of TV advertising. 

TV airings data was hard to come by, and traditional Marketing Mix Modeling reports are often too high-level — and too slow — to offer actionable insights. So, while we’ve known for a long time that TV drives consumers online, we had no way to accurately attribute digital activity to granular TV investments.

The new TV attribution solution
Now, TV attribution makes it possible to connect the dots between TV airings data and digital activity. The resulting insights from TV attribution enable marketers to improve campaign strategies across both mass media and digital channels. 

At a high level, TV attribution carefully analyzes typical search query and site activity to establish a baseline. Then, minute-by-minute TV airings data is correlated with search and site data to detect — and accurately attribute — traffic driven by each TV ad spot. 

We’ve seen great results for marketers that have embraced this new marketing measurement best practice. For example, Nest assessed and improved cross-channel campaigning with TV attribution, achieving a 2.5x lift in search volumes and 5x increase in search and website responses by acting on resulting insights. 

For more details, read our new infographic to learn:
  • How TV attribution reveals TV-to-digital behaviors
  • How TV attribution insights help marketers quantify TV’s business value, optimize media buys, and empower creative teams
  • How deeper understanding of consumers can lead to more effective cross-channel strategies


Time to improve your ROI?
Now that TV and digital data can be analyzed to reveal cross-channel behaviors, marketers have a new opportunity to improve both mass media and digital strategies. Next week, we’ll post our top 5 tips on amplifying TV dollars with digital. If you’re ready to get going on maximizing TV ROI, stay tuned.

Posted by:  Natasha Moonka, Google Analytics team

*Source: Neal Mohan, Google, “Video Ads and Moments That Matter,” Consumer Electronics Show 2015.


Affiliate Attribution: Putting the Pieces Together

Originally Posted on the Adometry M2R Blog
Recently I was reminded of an article from a little while back, titled, “2013: The Year of Affiliate Attribution?” It’s an interesting take and worthwhile read for those interested in affiliate marketing and the associated measurement challenges. Given that some time has passed, I thought it would be interesting to take a look at progress to date towards realizing a more holistic and accurate view of affiliate performance as part of a comprehensive cross-channel strategy.
Most affiliate managers have a similar goal to manage affiliate holistically, meaning investing in those that predominantly drive net-new customers independent of other paid marketing investments. Ultimately, this model allows them to optimize CPA by managing commissions, coupon discounts, and brand appropriateness based on true “incremental value” provided to business. Unfortunately, due to a lack of transparency and inadequate measurement, many marketers find themselves short of this goal. The result is the ongoing nagging question, “Is my affiliate strategy working and am I overpaying for what I’m getting?”

Why ‘Affiliate Attribution’ Is Hard

Affiliate marketers’ challenges range from competing against affiliates in PPC ad programs to concerns about questionable business practices employed by some “opportunistic” affiliates offering marginal value, but still receiving credit for sales that likely would have happened regardless. Which brings us to the central question:
How do marketers determine how much credit an affiliate should receive?

As you may know, opinions about how much conversion credit affiliates deserve for any given transaction vary widely. While there are a number of factors that influence affiliate performance (e.g. where they appear in the sales funnel, industry/sector, time-to-purchase length, etc.) for most brands the attribution model that is utilized will have a significant impact on which affiliates are over- and under-valued.
For example, in a last-click world affiliates that enter the purchase path towards the bottom of the funnel often hold their own; yet, when brands begin measuring on a full-funnel basis incorporating impression data, many struggle to prove their incremental value as the consumer has many exposures to marketing long before they reach the affiliate site. Conversely, affiliates that act predominantly as top- or mid-funnel (content, loyalty, etc.) are usually undervalued using last-click but can garner more credit using a full-funnel, data-driven attribution methodology. I should also mention these are broad generalizations only meant as examples, and it’s not necessarily a zero-sum game.
Another challenge is that fractional, data-driven attribution is difficult to implement for some types of promotions. One instance of this is cash back, loyalty and reward sites that must know an exact commission amount they will receive for each transaction so that they can pass on discounts to members. Given the complexity of more sophisticated attribution models, this data isn’t readily available.
Lastly, there several organizational challenges that inhibit the use of data-driven attribution among affiliate marketers. Some industry experts have indicated that many publishers, as much as 70-80%, strip impression tracking code from affiliate URLs. Another measurement challenge we see frequently is brands managing affiliates at the channel level leaving little sub-channel categorization which is where significant optimization opportunities exist.
Affiliate Attribution and the Performance Marketing Goldmine
Of course, part of our work at Adometry is helping customers address these challenges (and more) to ensure they are measuring affiliate contributions accurately and able to take appropriate action based on fully-attributed results.
Some key advantages of using data-driven attribution to measure affiliate sales include:
  • The ability to create a unified framework to compare performance (clicks and Impressions) in which affiliates compete for budgets on equal footing,
  • Increased visibility into which publishers are truly driving net-new customers through specifying which are an integral part of a multi-touch path and which are expendable,
  • The knowledge required to implement a Publisher category taxonomy to allow more insights into how different types of publishers perform by funnel stage and areas to improve efficiency,
  • Insight into the true incremental value publishers are providing and the offering commission rates to reflect this actual value,
  • A better understanding of affiliate’s role in the overall mix, further informing marketers use of complementary tactics to maximize affiliate contributions in concert with other channels,
  • The ability to use actual performance data to counter myths and frustrations with affiliates (cookie stuffing, stealing conversions, etc.)
Taken separately, each of these represents a significant opportunity to both be more effective in how you identify and utilize affiliate attribution to drive new opportunities. Together, they represent a fundamental improvement in how you manage your overall marketing spending, strategic planning and optimization efforts.
Top-performing affiliates, particularly those at the top and middle of the funnel, also stand to benefit from more transparent, accurate and fair system for crediting conversions. In fact, several large-scale, forward-thinking affiliates are already investing in data-driven attribution to arm themselves with the data required to effectively compete and win business in the market as brands become more sophisticated and judicious with their affiliates budgets.
It’s an exciting time for performance marketing. Change is always hard, but in this case it’s absolutely change for the better.  And frankly, its time.  What are your thoughts and experiences with measuring affiliate performance and attribution?

Posted by Casey Carey, Google Analytics team