acquisio building an_attribution_model_that_works

Building anAttribution Model

That Works

A Search Marketing Now E-Book

© 2011 Third Door Media, Inc. http://searchmarketingnow.com • Email: [email protected] • (203) 664-13502

Building an Attribution Model That Works

IntroductionThe use of attribution modeling to improve PPC efficiency has quickly grown in both popularity and sophistication. In many cases, a PPC conversion is the first in a string of interactions that together comprise a long and profitable customer relationship. Viewing these transactions within the broader context of lifetime customer engagement and attributing this information to bid rates and ROI calculations, is crucial to your company’s bottom line.

Yet, creating an accurate attribution model is still one of the most difficult parts of any agency’s or marketer’s job, whether you are working with online or offline channels – or both. Every marketer wants to find the most effective, profitable marketing mix for its products and services across all channels, including paid search. What you struggle with is how to monetize paid search, in terms of accurately measuring its impact on sales and customer engagement. While this is not a difficult concept to grasp, it is difficult to break down the problem into actionable tactics that can be readily applied to your PPC programs.

There are so many important variables to consider when building an attribution model and there are still no clear-cut answers to questions such as the following:

• Should ad impressions be weighted the same as clicks?

• Are clicks from search worth the same as clicks from Facebook and other social media?

• How does recency effect attribution? Is a click that happened 12 days ago still worth anything? How much more than a click that happened 25 days ago?

• What tools are currently available to help decide?

This E-Book discusses why attribution modeling has become so important to PPC marketers and agencies and presents numerous tips and techniques to help you build attribution models that will more accurately measure and value your online marketing campaigns.

Our thanks go to the following industry experts and Search Engine Land columnists, who provided valuable insight for this E-Book: Josh Dreller, director of media technology, Fuor Digital; Andrew Goodman, founder and principal, and Mona Elesseily, director of marketing strategy, Page Zero Media; Cindy Krum, CEO, Rank-Mobile, LLC; Eric Peterson, CEO and founder, Web Analytics Demystified; David Roth, director of SEM, Yahoo!; Danielle Smith, head of strategy and client development, Range Online Media; and Michelle Stern, client services director, iProspect.

Thanks also to Karen Burka for preparing this E-Book. n



Why Use Attribution Models? Paid search is rapidly becoming the most important driver of online sales. According to The 2010 State of Retailing Online report, co-produced by Forrester Research and Shop.org, online retailers estimate that 35 percent of their sales are motivated by Internet search. Attribution modeling can help quantify the symbiotic relationship that exists between PPC and online display advertising.

At the same time, research shows that a growing number of consumers use multiple channels when making purchase decisions. According to The Multi-Channel Retail Report, co-sponsored by J.C. Williams Group, bizrate.com and shop.org, 26% of consumers that visit a store looking for a product subsequently buy that item from a catalog; another 25% of consumers that visit a store subsequently purchase the product online. In addition, more than two-thirds of catalog shoppers ultimately purchase a product online, while 39% of website browsers purchase a product from a print catalog.

Another study of more than 1,000 consumers by Art Technology Group (ATG) found that 78% use two or more channels to shop; 30% said they spread their spending across three channels.

As a result, measuring the bidding process in relation only to online transactions significantly underestimates PPC’s overall contribution to company revenue. Attribution modeling enables agencies and marketers to more accurately analyze and measure PPC’s contribution to offline conversions. The key is understanding the full sales cycle by incorporating data from marketing events that happen further up the funnel, but which still play an important role in leading to the final sale, including top-of-funnel influencers such as newsletter subscriptions and store locator searches. By following the sales cycle all the way through to downstream, bottom-of-funnel influencers such as call center conversions and returns, marketers can develop a more accurate picture of future revenue and conversion rates, creating smarter keyword bidding strategies and uncovering new opportunities and take advantage of current CPMs and CPCs before the competition does.

The Complexity of Proper AttributionAlthough search marketing and technology platforms have become increasingly sophisticated over the past two years, it is still very difficult to track multiple clicks or the purchase path that online consumers take, especially when they begin with one type of search but end up in another. In 2010, the IAB (Internet Advertising Bureau) reported $26 billion spent on online advertising led by search (46%) and display (24%). The challenge is that

measurement technology makes attribution very complicated and difficult, particularly when trying to understand how online search affects offline channels.

Currently there appear to be two basic types of approaches, neither of which is perfect. The first requires marketers or their agencies to enter percentages into boxes on a screen and assign portions of the conversion value to different online

marketing channels (i.e., 25% for SEM, 35% for display, 15% for email). The second approach relies on the use of black-box math and is more likely to be done in-house by large marketers using statistical and predictive modeling to simulate different attribution models and map their outcomes to business metrics like profit, revenue or ROI.

Both of these approaches take a very generic view of attribution rather than consider the unique needs of each marketer’s business. They also assume that there is enough in-house analytical expertise to intelligently decipher marketing data.

In 2010, the IAB (Internet Advertising Bureau)

reported $26 billion spent on online advertising

led by search (46%) and display (24%).



Multi-Touch vs. Last-Clicked Attribution ModelsThere has been much search industry debate on the merits of last-click vs. multi-touch attribution models. Increasingly, PPC conversions are influenced by more than just the last click; many times a conversion happens a few hours, days or weeks after a series of clicks and searches.

However, multi-touch attribution models are difficult to develop and make effective primarily because there are so many variables involved. For example, you’ll need to decide what percentage of the conversion value to give to the first interaction vs. the last…or whether display view-throughs are worth as much as a search click. Timing and recency need to be examined as well. Did a consumer interact with your ad last week…or last month? These are all questions search marketers and their agencies must consider and discuss before assigning attribution values.

For these reasons, some search marketers believe that the “last-ad clicked” model is the most beneficial because search occurs deep into the purchase funnel, close to the conversion. But last-click attribution models have their drawbacks, as well. Namely, they don’t follow consumers over extended time periods, or consider the variety of online influencers such as email, direct navigation, display ads or even organic search (SEO). As a result, a significant portion of the inaccuracies and oversimplifications now involved in crediting online media sources for conversions comes from only counting the last click.

Effective PPC marketing requires you to stay ahead of real-time bid markets and the evolving complexity associated with search engines. Setting up search accounts on a new search engine can be challenging and expensive while the cost of keywords continues to increase. In addition, it is difficult to measure the relationship between search marketing and other

marketing programs, including SEO, online display and offline advertising without a complete view of the conversion funnel from top to bottom.

According to Microsoft’s Atlas Institute, between 93-95% of audience engagements with online advertising typically receive no credit at all when marketers review campaign ROI. That means that most marketers are only looking at five percent to seven percent of consumer media interactions when optimizing conversions. Without tracking and analyzing multiple touch points,

you can’t get the true ROI of your marketing dollars. As a result, you might not be fully optimizing your marketing initiatives.

A multi-touch attribution model allows you to track all user touch points and capture more complete information about their interactions with yours or your clients’ brands. The key is to track all of your online media in one system, allowing you to see

The Simplest Attribution May Be the Most MisleadingLast-click attribution is simple and most platform application defaults are set to last-touch attribution (as well as showing one model at a time). But this simplistic approach misses most, if not all of the value in the consumer interaction pathway. At a minimum, you need to look at first- and last-click attribution equally. To gauge how close – or how far – you are from proper attribution, ask yourself the following:

• Do you rely on last-touch attribution?

• Do you make ad buying decisions based on data you know is misleading or incorrect?

• Does your attribution platform support multiple attribution models?

• Does your attribution platform make multiple attribution data easily available?

• Do you have a plan to improve your view of marketing attribution?

Source: Web Analytics Demystified, SearchEngineLand



all of the pathways users took to ultimately convert. For example, Consumer #1 might have seen a display ad on Monday, clicked a sponsorship on Tuesday, received an email from your client on Wednesday, and came back on Friday via a paid search ad and converted. Multi-touch attribution assigns credit to the entire conversion pathway, not just the last ad clicked.

Building an Attribution Model That WorksSo how do you decide to attribute the revenue that results from a sale? And how do you decide where to allocate your ad spend based on that attribution? Developing attribution models that integrate multiple online channels requires having your internal data management house in order. As you begin the process, here are eight key questions to ask…and answer before you begin.

1. Do you have adequate technical resources? The availability (or lack thereof) of technical resources will help you determine how many channels to initially consider in your attribution modeling efforts. Start simply with just two channels to create a case study. Then leverage it to get the additional resources you need for modeling across more channels.

2. Is there an attribution plan for multiple products? Once you’ve decided which channels to include in your model you should consider attribution between different products as well, for example if a consumer clicks on an ad for Product A and then later converts on Product B. In addition, if your company markets several brands, the same scenario would be applicable to multiple brands.

3. Do you have a single tracking system? For each channel you’re measuring you’ll need to have the same tracking system. Keep in mind that if one of your channels is display advertising, you’ll want a tracking system that can track view-based conversions and not just click-based conversions. Should you decide to change tracking providers, don’t forget to keep a record of the historical data.

4. Is your cookie expiration set right? Set your cookie expiration according to what your company accepts as an appropriate length of time for the sales cycle. If you’re unsure, it’s best to err on the higher end because you can always filter the data based on the time from the initial impression or click to the conversion.

5. Is your data clean? Set up business rules ahead of time for data that’s not appropriate to analyze. For example, if 97% of your data reveals that there are between one and 12 touch points during the life of the cookie, you’re going to have some cut off point above 12 touch points where it makes sense to scrub that data.

6. Can you integrate CRM data? After cleaning your data, it will be useful to marry your internal CRM data with your engine and conversion data. This will allow you to determine which purchase paths lead to the least and most desirable customers and guide your optimization strategy.

7. Is your data weighted properly? There are several ways to allocate success across different online

marketing channels. The easiest method is to weight each channel equally, leaving yourself the option of taking the frequency of each channel’s exposure into account, as well as the placement of each in the purchase path (first, last or middle touch point). For example, if someone has been exposed to a display ad five times in a seven-touchpoint path, then the credit given to display can be weighted higher. Or if display was the first touchpoint, you could make the case that this channel introduced someone to the brand and should be given more credit than the other channels. In addition, it would make sense to weight the data points

based on whether they result in new customers or existing customers.

8. Do you have the right reports? Several reports are critical in attribution modeling. You need to be able to see the purchase path (marketing channel, engine or site, and keyword, if applicable) by custom date range. In addition, you need to be able to see which channels introduce new customers to the brand, which channels influence and which channels net the transaction. Viewing this data by customer type will paint a more complete picture when attempting to improve overall results.

Start simply with just two channels to create a case study. Then leverage it to get the additional

resources you need for modeling across

more channels.



Step Two: Developing a StrategyTo build an attribution model that works for yours or your clients’ business goals, begin with a three-pronged approach involving people, statistical analysis and actionable information that combines elements of your existing practices and expands upon them to provide a more complete, appropriate solution for each advertiser.

The first phase should focus on human resources. Data can only be as smart as the people interpreting it. Employing an attribution specialist to lead the effort is ideal, though not always doable. In any case, you will need to conduct a fairly exhaustive analysis of the marketer’s business and online marketing programs. Start with business goals and product adoption cycles, move on to conversion window analysis and end with a channel-by-channel audit of both online and offline marketing.

Armed with the proper inputs as they relate to a marketer’s business and its metrics or KPIs, the next step is statistical modeling to predict all possible outcomes and understand which model will best support your business goals. This is where an honest evaluation of the company’s data quality and accuracy is vitally important. Analytics and measurement must be standardized on a single platform to be able to compare “apples to apples.”

Acquisio’s performance media platform, for example, has an integrated third-party ad server that allows agencies and marketers to track multiple online channels – search, display and social media – with the same technology. One server powers display ad views and clicks, as well as Facebook and PPC clicks giving business users the ability to more accurately weight an ad view vs. an ad click. There are multiple models to choose from and cycle through to see how any given model will impact campaign results or ROI.

Finally, the third step makes all of this information actionable by using the model outputs to apply directly to actual online channels. Ideally this process should be

automated to easily implement the recommendations into the media buys themselves.

Step Three: A Practical Approach to Appropriate Attribution The next step is to assign attribution within any given campaign through an approach called appropriate attribution. To begin, walk back through each click and decide how to assign the revenue collected to the first touch and divide that by the revenue collected if you were to assign or associate it with the last touch.

Revenue from First Touch/Revenue from Last Touch = Appropriate Attribution Ratio

In essence, you are creating a ratio that will allow you to evaluate or interpret the value of any online campaign toward your marketing goals. For example, the closer your resulting number is to zero the more skewed toward the last click your revenue is and the campaign can be viewed as a true conversion campaign that results in sales. The further the resulting number is from zero, the more likely you are running an acquisition or top-of-funnel campaign, because the value will be skewed toward the first click. If your attribution ratio is balanced between the two ends of the click pathway, then the value of that marketing campaign is as a persuasion campaign because it is not actively acquiring or converting customers.

• Closer to 0.00 = Conversion Campaign• Closer to 1.00 = Persuasion Campaign• Closer to 10.00 = Acquisition Campaign

Using this type of appropriate attribution ratio for any online marketing channel will allow you to more efficiently bid and allocate resources to specific keywords or campaigns based on your business goals. Summarizing each of your marketing channels will also enable you to see where you need to drive more sales (and perhaps spend more) or see where your campaigns are working and spend more there.

Start with business goals and product adoption cycles, move on to conversion window analysis and end with a channel-by-channel audit of

both online and offline marketing.



Bringing Margin and Cost into the EquationBecause revenue is only part of the equation for many marketers, you can create a more sophisticated, accurate attribution model by building costs and/or marginal contribution into your appropriate attribution ratio to evaluate campaigns.

Appropriate Attribution RatioNet = (Revenue from first touch - Campaign marketing cost) / (Revenue from last touch – Campaign marketing cost)

Appropriate Attribution RatioMargin = (Revenue from first touch – Campaign COGS/Revenue from last touch- Campaign COGS)

*Appropriate Attribution Ratios courtesy of Web Analytics Demystified and Coremetrics.

Seven Metrics to Measure the Impact of PPC on Offline ConversionLastly, attribution modeling can be a valuable tool for both agencies and marketers to prove the impact and value that PPC and other online channels have on offline sales. Here are seven key metrics to link online channels to offline conversions.

1. Online/offline orders and pick-ups. Tracking how many customers searched and purchased online, then picked up their purchases in your brick-and-mortar stores provides very precise online/offline data for retailers that offer this service.

2. Store locator pages. Customers who want to visit a particular store tend to seek information on store locator pages. For these pages to be most effective and trackable make sure you provide relevant information like “find a store near you,” store hours, directions and phone numbers in your online campaigns, and that it’s easy to find on your website.

3. Time spent on website. The more time someone spends on your website, the more likely they’re

interested in your product or service. We know if someone searches for camera information for more than 15 minutes on a consumer electronics website that they’re interested in cameras. Online marketers should try to close the loop definitively with an online sale to these types of visitors. Don’t get “too good” at driving online searchers to physical stores; improve your conversion marketing so the customer is spending more than just his or her time online.

4. Queries with geographic qualifiers. Some queries containing geographic qualifiers indicate offline purchase intent. For example, if someone is searching for the query “dentist in West Vancouver” they’re more than likely looking for a dental appointment in a particular geographic location. The type of insight you get will depend on your industry and may not be as relevant in other categories so use care when examining terms.

5. Local search. Many times local PPC campaigns are designed to drive offline purchases. Using the same example as above, if the term “dentist in West Vancouver” was targeted to West Vancouver and designed to drive traffic, it is probably driving a high proportion of your phone appointments or walk-in traffic. Some Yellow Pages advertisers use dedicated phone numbers for their campaigns. Try doing the same on the search side. If not, you’re not adequately tracking the campaign’s impact.

6. Promo codes. To track offline conversion, create a coupon or other online-specific promotion that’s only redeemable in the store (if appropriate). Customers can write down or print special codes that they can redeem in-store.

7. Focus groups and post-purchase surveys. Run a focus group to get a better idea of how your buyers shop. Also, after people make purchases online, ask for their feedback through a post-purchase survey to get more information on buying behavior and offline impact.



In SummaryAttribution modeling has become a critical marketing tool in today’s competitive media marketplace, where consumers are bombarded by multi-channel advertising messages and budget dollars are tight. With PPC becoming a key driver of online sales, and more marketers questioning its role in driving offline sales, it’s more important than ever before to view conversion within the broader context of lifetime customer engagement and attributing this information ROI calculations. Using a multi-touch attribution model allows marketers to track all customer touch points and capture more complete information about customer interactions with their brands.

Yet proper attribution still poses numerous challenges to marketers and agencies alike because there are so many variables involved. There are no shortcuts or clear-cut answers to questions about weighting each channel or the impact that recency has on the value of a conversion. And each business must make decisions based on their own unique business goals, KPIs and metrics -- there is no one-size-fits-all model.

These challenges will diminish as more and more analytics solutions and PPC reporting platforms develop the capacity to more accurately track and model multiple attributions. For example, Acquisio’s performance media platform has an integrated third-party ad server that allows agencies and advertisers to track multiple channels – search, display, social media – with the same technology. One server powers display ad views and clicks, as well as Facebook and PPC clicks making it easier to traffic existing ad buys. n



The world’s leading Performance Media Platform, Acquisio helps marketers buy, track, manage, optimize, and report on media across all channels. The platform was designed for search marketing, and it has evolved to include Facebook ads and all major RTB display networks. Acquisio provides the industry-leading technology for marketers buying ads on any online channel, allowing them to handle all tasks associated with performance advertising, from ad purchase through conversion tracking and beyond, within a single integrated platform. With more than $500MM in ad spend under its management, Acquisio is the multi-channel advertising solution preferred by advertising and marketing agencies around the world. For more information, visit www.acquisio.com.

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