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Showing posts with label Attribution. Show all posts
Showing posts with label Attribution. Show all posts

Affiliate Attribution: Putting the Pieces Together

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

Introducing Search Response and Airings Data in TV Attribution

Introducing Search Response and Airings Data in TV Attribution

The following is a cross post from Adometry by Google, a Marketing Analytics and Attribution product. 

Mass media drives people to interact with brands in compelling ways. When a TV or radio ad creates an I-want-to-know, I-want-to-go, or an I-want-to-buy moment in the mind of a consumer, many pursue it online. Immediately - and on whatever screen they have handy.

Last year, we announced Adometry TV Attribution, which measures the digital impact of offline channels such as television and radio. Now, we’re moving TV Attribution forward by integrating Google Search query data and Rentrak airings data to help marketers better understand the important moments their broadcast investments create.

New Search Behavior, New Search Analysis
Broadcast media doesn’t just drive consumers directly to websites — it drives searches. Now, TV attribution lets you analyze minute-by-minute aggregated Google Search query data against spot-related keywords to detect and attribute search “micro-conversions” to specific TV airings. 

With insights on the entire digital customer journey — including search behaviors — brands can better evaluate broadcast network and daypart, specific ad creative, and keyword performance. As a result, brands can:
  • Assess Immediate Influence: See which messages are sticking in the minds of consumers to both maximize TV interest and choose ideal keywords for SEO and paid search strategies.
  • Evaluate Awareness Goals: Optimize against a digital signal even when a site visit isn’t the primary goal, such as in brand awareness or sponsorship campaigns.
  • Analyze Competitive Category: Glean which generic keywords drive category interest for the industry — a type of insights not possible through site traffic analysis alone. 

Rentrak Partnership Speeds TV Attribution Insights
Knowing when your spots aired and collecting that data for timely TV attribution analysis can be a challenge. Marketers who buy broadcast media through agencies often don’t have direct access to this data. And once data is obtained — after coordinating with multiple agencies, partners, and TV measurement companies — the time lag makes for outdated analysis. 

TV Attribution now solves these challenges a new partnership with Rentrak, the leading and trusted source for TV airings information. 

What Rentrak Integration Delivers
Integrating directly with Rentrak TV Essentials, TV Attribution now overcomes some of the biggest hurdles in TV measurement, with increases in: 
  • Actionability: TV Attribution can more quickly and easily obtain TV data for analysis without time-consuming coordination from you or your agencies.  
  • Accuracy: Rentrak provides a comprehensive data set with aggregated viewership information from more than 30 million televisions across the country, and from more than 230 networks.
  • Frequency: A direct relationship means more frequent reporting since there is no longer a manual find-and-transfer of data required from TV buying partners.
“What makes this partnership so exciting is it removes the biggest barrier to truly measuring TV effectiveness, timely access to spot airings data including impressions,” said Tony Pecora, CMO for SelectQuote. “Rather than hunting and gathering data, we are now able to spend our time evaluating insights and optimizing our marketing investments across both TV and digital. As a CMO, this is a really big win for our business.”

Want to Get Moving?

The gap between offline and digital measurement continues to close. Learn more about how Adometry TV Attribution, now with Google Search query data and integrated Rentrak airings data, can help you gain more actionable cross-channel insights.

Posted by Dave Barney, Product Manager

Refreshing “The Customer Journey to Online Purchase” - New Insights into Marketing Channels

Refreshing “The Customer Journey to Online Purchase” - New Insights into Marketing Channels

Last year we introduced “The Customer Journey to Online Purchase” -- a tool that helped marketers visualize the roles played by marketing channels like paid search, email and display ads in their customers' journeys.

The goal was to help marketers learn more about the customer journeys for their industries. If social makes your customers aware, and email makes them convert -- or vice versa -- you can make sure you're in both places with the right kind of message.

Today we're happy to introduce a new improved version of the Customer Journey to Online Purchase, with a few key enhancements.  We’ve refreshed the data based on millions of consumer interactions, updated the industry classifications, and we’ve split out paid search so you can see the influence of brand and generic search terms on the purchase decision.

In each industry you can now see journeys for small, medium and large companies, which can often be quite different.
Click to enlarge image
For instance, the above image shows the journey for customers of small businesses in the shopping industry. Note that organic search is very often an "assist" interaction for these customers.
Click to enlarge image
Now here's the same journey for large shopping businesses. Note that display clicks and social are strongly assisting interactions -- while display didn’t even appear for the small businesses above. For both small and large businesses, a direct website visit is most likely to be the last interaction. Across industries, the differences from small to large businesses illustrate how different marketing strategies and customer profiles may lead to different buying behavior.

And there's more! Now you can drill down into each marketing channel for a closer look at the role it plays based on its position in the purchase path. Channels that occur more frequently in the beginning of the path are more likely to help generate awareness for your product, while the end of the path is closer to the customer’s purchase decision.
Click to enlarge image
In these charts, for example, we see the different roles that different channels play in the Shopping industry. One interesting insight is that all channels -- even those traditionally thought of as “upper funnel” or “lower funnel” -- occur throughout the purchase path, but a given channel may be more common at particular stages depending on its role (and depending on the industry).

Each marketing campaign and channel may have a different impact on customers depending on when they interact with it. Using what you learn from this tool, you can help adapt your marketing messaging to be more relevant and useful for your customers.

Try the Customer Journey to Online Purchase today. And for more helpful marketing insights, check out Measure What Matters Most: our new guide chock-full of suggestions on how to measure the impact of your marketing -- across channels -- to complement what you learn from the Customer Journey tool and take action to improve your marketing.

Happy analyzing!


Learning what moves the needle most with Data-Driven Attribution

"Tremendously useful."  That's what Chris Bawden of the TechSmith Corporation says about Data-Driven Attribution.

What is Data-Driven Attribution? Well, in August we launched a new leap in technology that uses algorithmic models and reports to help take the guesswork out of attribution. And it's available now to Google Analytics Premium customers around the world.

Data-Driven Attribution uses statistical probabilities and economic algorithms to analyze each customer's journey in a new way. You define the results that count — sales, sign-ups, or whatever matters to you— and the model assigns value to marketing touchpoints automatically, comparing actions and probabilities to show you which digital channels and keywords move the needle most. 

The bottom line: better returns on your marketing and ad spend. 

We checked in with companies using DDA and results have been strong:
  • "Data Driven Attribution really showed us where we were driving conversions," says Will Lin, Senior Director of Global eMarketing for HomeAway. They saw a 23% increase in attributed conversions for their test keywords after making changes suggested by Data Driven Attribution. Download case study.
  • TechSmith Corporation saw a 19% increase in attributed conversions under the Data Driven Attribution model. "It uncovered growth potential we would have not seen otherwise," reports Nicole Remington, their Search Marketing Manager. Download case study.
  • And the digital analytics firm MaassMedia saw display leads increase 10% while costs per lead remained flat. "We now have a much more accurate measure of how display impacts our business," one of their clients told them. Download case study.
In short, the early returns for DDA users have been strong. Some of the key advantages of this model:

Algorithmic and automatic: The model distributes credit across marketing channels scientifically, based on success metrics you define. 

Transparent: Our unique Model Explorer gives you full insight into how marketing touch points are valued — no “black box” methodology.

Actionable: Detailed insights into both converting and non-converting paths offer clear guidance for your marketing decisions.

Cross-platform: DDA is deeply integrated with other Google products like AdWords, the Google Display Network, and YouTube, and you can pull in data from most any digital channel.

You'll learn much more about the benefits of Data-Driven Attribution when you download our cheat sheet. Or to learn more about Google Analytics Premium, contact your Google Account Manager or visit google.com/analytics/premium.

Posted by Bill Kee, Product Manager for Attribution, and Jody Shapiro, Product Manager for Google Analytics Premium

Using a permanent URL to share Custom Attribution Models & Custom Channel Groupings

Using a permanent URL to share Custom Attribution Models & Custom Channel Groupings

The need to customize and fine-tune your marketing measurement solutions becomes a key discriminator in unlocking additional value which might have been missed when applying out-of-the-box views on your data. For this reason, the Multi-Channel Funnel Analysis within Google Analytics Attribution provides the ability to configure content based channel groupings, as well as customized attribution models. This allows you to better reflect how partial credit is assigned to the marketing efforts driving your conversions. Having the ability to develop these customized assets is great, and now you are able to easily share them with your organization, your customers, or your audience. Here is how sharing a custom channel grouping, or custom attribution model works: 

Step 1 - Build a Custom Attribution Model
Building a custom model is easy. Just go to the Model Comparison Tool report in the Attribution Section of Conversions. In the model picker you can select ‘Create new custom model’, which opens the dialog to specify rules which can better reflect the value of marketing serving your specific business model. As an example, we can develop a model to value impressions preceding a site visit higher within a 24 hour time window. We also set the relevant lookback window to 60 days, as we know our most valuable users have longer decision and decide cycles:

Click image for full-sized version
Ensure you opt-in the Impression Integration, enabling Google Display Network Impressions and Rich-Media interactions to be automatically added to your path data through the AdWords linking. Don’t forget to also check out the recorded webinar from Bill Kee, Product Management Lead for Attribution, providing more details on how to create a custom model.

Step 2 - Access the Model in Personal Tools & Assets Section
In the admin section you can now look at your personal tools & assets. The newly created model will show up in the ‘Attribution Models’ section. You can find custom channel groupings you created under Channel Groupings.


The table shows all assets available, and a drop-down allows you to ‘share’ these assets through a link.


Step 3 - Share the Link - Done!
From the drop-down Actions menu select ‘Share’, and a permanent link to the configuration of this object is generated. This link will point to the configuration of the shared asset, allowing anyone with a GA implementation and the link to make a copy of the asset config, and save it into their instance of GA. You maintain complete control over who you share your assets with. 


Include the link to your brand-new attribution model asset in an email, IM message, or even a Blog Post, such as this one.

Happy Customizing!

Posted by Stefan F. Schnabl, Product Manager, Google Analytics