Posts Tagged ‘purchase path’

Understanding Attribution: All Reports Are Not Created Equally

Thursday, May 13th, 2010

Attribution is a new concept to many marketers.  And a natural reaction to seeing new information, especially information (or data) that is different, is to question the accuracy of the reports (data).  The way that seems most logical to confirm that the new numbers are correct is to compare one report to another.   In my last post I introduced this series of blogs hoping to alleviate frustration that many marketers experience when they try to compare two reports and the numbers don’t match.

All reports are not created equally nor are they calculated the same way.  In an attribution world, there are two types of reports, ones that factor in attribution and ones that don’t.

The two types of reports have two different purposes:

  • Operational Reports
  • Performance Reports

Operational Reports

Operational reports don’t factor in attribution.  Operational reports are reports used to measure how your business is doing.  Operational reports are used to ensure there is nothing ‘broken.’  Operational reports include reports run from your ecommerce system, most traditional web analytics reports and reports that are compiled from several different sources.

Performance Reports

Attribution is crucial for performance reports.  Performance reports are used to judge how well your advertising is performing.  Performance reports also take into consideration latency and latent conversions described in my last post.

Both reports are extremely useful.  The problem arises when you try to compare an operational report to a performance report.  One common example of this  that I see is when a new ClearSaleing customer attempts to compare a report from their web database, an order report or a booking report, to the ‘All Sources’ screen of the Performance tab or any other report that factors in attribution.

These two reports will never ‘match,’ nor should they.  Operations reports give 100% of credit to the last click, 100% credit to the date and source of conversion (no attribution).  Performance reports divide up the credit and attributes it to each date and source that led up to the conversion (attribution).

So before you try to compare two reports, take a step back.  Think about the report that you are trying to compare to a performance (attribution) report.  Does the report factor in attribution?  If the report is coming from your ecommerce database or booking engine, or even your traditional web analytics, it probably does not use attribution.

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Understanding Attribution: 5 Reasons Why the Numbers Won’t Match

Monday, May 3rd, 2010

Almost daily I field questions from marketers who are trying to compare two different reports.  They are confused because the numbers don’t match.

There are many, many, many reasons why, when comparing two reports, even from the same system, the numbers will not match.

The reasons are (and each week, I will cover one reason in detail):

1. Attribution Reporting

Attribution reports’ calculations update daily and divide credit (orders, revenue and profit) over all of the contributing ads, impressions and clicks that led to a sale or other conversion.  Attribution is a newer concept for many marketers.   The fact that there is now the idea of a fraction of an order is definitely a different way of thinking.

2. Non-Attribution

Most marketers are very comfortable with non-attribution reporting.  Common examples of non-attribution reports are reports that are used for operational decisions, for example a Daily Order Report from a shopping cart.  Problems arise when trying to compare an attribution report to a non-attribution report (comparing apples to oranges).

3. Multiple Data Source – Over Counting/Over Crediting

If web analytics have not been configured to track all of the different sources of traffic to a conversion level, marketers are left to rely on reports provided by the source itself (e.g. Google AdWords Reports, Yahoo Search Marketing Reports, as well as other vendors like Display, Affiliates and Email).  Because none of these sources are ‘aware’ of the other sources, conversions and revenue can be over counted, and therefore, over credited.

4. Under Counting – Under Crediting

This is a by-product of the limitations of last click.  If you are using traditional web analytics, this is likely a problem.  Because the referrer only pays attention to the last place where a visitor came from, you wind up under crediting certain sources.

5. Accuracy – Data Quality of Web Reports

Here is the big elephant in the room that no one wants to talk about.  It is possible that the data that you are relying to make important spending decisions is wrong.  The number one cause, in my experience, is a problem with the implementation.  Examples I have seen of implementation problems are code not being on every page, conversion code not being on the page or not being correct, and profiles or other settings that have not been configured properly.  It is definitely worth auditing your implementation, even if you are using a free solution.

6. Bonus:  One web vendor report to another

Even armed with the knowledge that both implementations are correct and complete, it is most often an exercise in futility comparing one vendor report to another.  The reason for this:  each company has a different idea of how metrics should be defined and calculated.  And each company has settings both internal and external that define how metrics are calculated (e.g if someone is on your site for 60 minutes are they one visit or two).

This week – Attribution

Attribution is a difficult concept.  Take pay-per-click as an example.  In order to fairly and accurately measure an ad, you have to think about latency.  On the day an ad runs, some of the conversions will take place.  But some people will come to your Web site from the ad and not be quite ready to purchase.  They may decide to return to your site a few days later and purchase.

To be ‘fair’ to your ads, you have to be able to count these conversions and credit them to the original ad (or multiple ads if several were seen along the way).

For example, say someone clicks on a Google ad on April 27th.  They get to your site but are not convinced to purchase.  Instead they continue their research.  The next day, April 28th, they go to Yahoo, click on an ad and purchase.

If you are attributing credit, here is what your reports look like:

April 28, 2010 – Yesterday’s Report

Date Source Visits Conversions Ad Spend Revenue
4/27/10 AdWords 100 4 $231.00 $512.00

Here’s the tricky thing – the numbers change.  In order to give credit for latent conversions, the historic performance will then change.

April 29, 2010 – Custom Report Range 4/27/2010

Date Source Visits Conversions Ad Spend Revenue
4/27/10 AdWords 100 4.5 $231.00 $655.00

There is no additional ad spend, but the .5 order is now credited to the correct day.

And this impacts all of the calculated metrics.

April 28, 2010 – Yesterday’s Report

Date Source Conv. Rate Cost/Order Rev/Order Rev/Visit
4/27/10 AdWords 4% $57.75 $128.00 $5.12

Here’s the tricky thing – the numbers change.  In order to give credit for latent conversions, the historic performance will then change.

April 29, 2010 – Custom Report Range 4/27/2010

Date Source Conv. Rate Cost/Order Rev/Order Rev/Visit
4/27/10 AdWords 4.5% $51.33 $145.56 $6.55

And even a step further, this impacts the ROI for each day.

The best thing about solutions that provide attribution reporting is that they supply this information already pre-calculated, so you don’t have to think about these types of calculations or even consider the fact that there are now fractions of orders.

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Understanding Attribution

Monday, April 5th, 2010

Understanding Attribution

Conceptually, attribution is easy to understand.  Metrics are calculated based on allocation rules.  At its simplest, attribution is based on even allocation.

But taking a look ‘under the hood’ shows that even this basic attribution model can be quite complicated.   To do this, let’s isolate one order:

One product sold to Google Affiliate Network:


Two clicks in the path:

Exclusions (‘All But First’, meaning we exclude giving credit to that source unless it’s the first click in a path, so the first click (Direct) will get ½ the credit):

Correct Calculation: ($224.00 * .50) = $112.00 (Revenue)

Then, back out 50% of the total cost of goods sold and 100 % of Ad Spend to get to the total net profit, which in this case is negative.

It may seem confusing that the calculation shows ½ the revenue, then backs out ½ the cost of goods sold, yet backs out 100% of Ad Spend.  However, this is the only way to accurately value each advertising source.  Traditional web analytics tend to under-credit some sources and over-credit the last click sources.  Search engine reports can over-credit ads, especially when people cross search engines in their research.

In the example below, both Yahoo and Google would take credit for the sale:

Taking complete Ad Spend into consideration when calculating profit is crucial to accurately value each paid media source, but there is one other consideration.  What about the clicks that don’t cost anything?  That is where Exclusions come in to play.

If you exclude clicks that don’t cost anything, the story changes. If the exclusions had been set to exclude all non-cost clicks, the earlier example would tell a different story.

Correct Calculation: ($224.00 * .100) = $224.00 (Revenue)

Then, back out 100% of the total cost of goods sold and 100 % of Ad Spend to get to the total net profit.  In this case, the conversion would have been profitable.

Excluding giving credit to the clicks that do not cost you anything gives you the ability to analyze and optimize your total marketing budget.  It answers the questions, ‘Where is money being spent making the most money?’, and ‘Where is it losing money?’

The good news is that you can still see how the impact of the non-cost clicks affects the value of each ad source by switching the display option.

Tip of the Month:  Exclude your non-cost clicks to optimize your budget to your Ad Spend.  Then use the complete Purchase Path to see the impact of the non-cost clicks on the value of the different ad sources.  It is the best of both worlds.

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Attribution Management Buyers Guide Part 8,9,10 – Basic Attribution Models, Mathematical Attribution & Data Warehousing

Monday, November 23rd, 2009

Given the critical nature of attribution management to advertising analytics, we have created the Attribution Management Buyer’s Guide for marketers to use when selecting an advertising analytics and optimization platform.  The Guide is intended to highlight key attribution management features and functionality that should be available in any advertising analytics solution you select.

This is the eighth blog in a 10-part blog series for the Attribution Management Buyers Guide. This eighth section focuses on Basic Attribution Models.

When engaging with a new attribution management technology, you should be able to start performing attribution on day one out of the box. Though attribution can be a very complex exercise, there are also some simple attribution models that can greatly improve the performance of your online campaigns. To ensure the solution you decide to go with offers attribution models that you can use on day one, ask the following questions:

1. What kind of basic attribution models does your platform offer?

2. Can you verify that using these base attribution models will improve my accuracy and performance?

A robust attribution platform should be able to offer basic attribution models out of the box, such as:

  • Even - where conversion credit is spread equally across all participating ads in the Purchase Path
  • Even with Exclusions - the even model with the additional ability to exclude specific ads, such as Branded terms, at the end of the Purchase Path
  • Path Length – the ability to assign specific percentages to participating ads based on the number of steps in the path
  • Rules Based - the ability to assign specific percentages based on the types of ads and the number of steps that are used in each step along the path

An experienced attribution management provider should be able to provide you with case studies or examples of how these basic models were able to increase the accuracy of conversion valuation and, ultimately, how that improved performance, as measured by increased profit and/or ROI.

Of course, the best indicator of an attribution management models success is its ability to grow your own bottom line profit. You’ll need to have a benchmark in place before you start attribution to make sure these models truly are having the desired impact.

Part 9 – Mathematical Attribution

This is the ninth blog in a 10-part blog series for the Attribution Management Buyers Guide. This ninth section focuses on Mathematical Attribution.

After you find success using basic attribution models, you may want to move to more advanced attribution that allows you to set specific weights for different activities that occur during the purchase path. When selecting an attribution management vendor, it is imperative they offer not only basic attribution models but also provide you the ability to build more sophisticated models either through the use of their technology and/or with their consultative services.

Asking the following questions will ensure you have the ability to be more sophisticated in the future:

1. What kind of customization options do you offer?

2. Do you offer any consultative services that can build custom attribution models?

Moving beyond an Even attribution or an Even with Exclusions model requires an understanding of some complex mathematics. Setting custom attribution rules should not be a subjective exercise and should only be taken on by attribution management vendors with solid statistical and mathematical knowledge. Custom models should be able to include variables like the decay rate of different types of ads, the influence potential of different types of ads, additional time variables, types of products sold, type of customer, impact of social media, etc.

Part 10 – Data Warehousing

This is the tenth blog in a 10-part blog series for the Attribution Management Buyers Guide. This tenth section focuses on Data Warehousing.

When you make the move to attribution management, you’re going to then be collecting a wealth of information you did not have access to before.  For example, you’re now going to have information for all the ads involved in the sale(s) versus just the last ad. If you are tracking true profit that means you are also going to have individual product information. You also know a lot more about your customers buying behavior since you are able to see all the ads your customer uses versus the last one. To harness this information and to make it actionable, it will require the use of a data warehouse, which can be a powerful marketing intelligence asset for your company.

Ask the following questions to determine how your attribution vendor will allow you to get even more value out of the data being captured:

1. Does your technology reside on a data warehouse?

2. Do you offer a data warehouse as an option?

3. Can the warehoused data be queried to create custom reports?

Attribution management systems that are built upon a data warehouse will provide you with much greater flexibility in building custom models and custom reports. Additionally, it will be able to provide further analytics around things, such as product trends, customer buying behavior and lifetime value, for example.

Conclusion

Sophisticated marketers are keenly aware of the importance of Attribution Management in accurately measuring and improving the performance of their cross‐media advertising campaigns. The challenge for these marketers is to find a robust advertising analytics platform that is built on a foundation of attribution management. Hopefully, this Guide will help you assess whether the solution you’re considering measures up to the robust requirements of an effective attribution management platform.

Want to get more involved in attribution management? We invite you to become a member of the Attribution Management Forum, an online group that represents more than 300 leading marketers from a diverse range of companies across nearly every industry segment. For more information on joining, or for additional information on Attribution Management, visit us online at AttributionManagement.com or ClearSaleing.com.

Check out the remaining blogs in the Attribution Management Buyers Guide series:

Part 1 – Attribution Variables

Part 2 & 3 – Products and Ad Sources Tracked

Part 4 & 5 – Display Advertising and Exclusions

Part 6 & 7 – Purchase Path Stages and Time

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Attribution Management Buyers Guide Part 6 & 7 – Purchase Path Stages and Time

Friday, October 30th, 2009

Given the critical nature of attribution management to advertising analytics, we have created the Attribution Management Buyer’s Guide for marketers to use when selecting an advertising analytics and optimization platform.  The Guide is intended to highlight key attribution management features and functionality that should be available in any advertising analytics solution you select.

This is the sixth blog in a 10-part blog series for the Attribution Management Buyers Guide. This sixth section focuses on Purchase Path Stages.

Purchase path stages represent specific consideration steps in the overall buying process that a consumer goes through en route to a purchase.

Now that you are valuing ads based on where they occur in the customer buying cycle, it will be important for you to be able to identify and differentiate which specific ads introduce your brand to the customer, which ads influence their buying decision, and which ads close the sale. This information helps you pinpoint how certain ads are having a positive influence on customers in the beginning or middle of the buying cycle versus those at the end that close deals.

One question to ask vendors is, ‘How does your system report on which ads do a great job of introducing people to my business, closing deals, or being an ad that sits in between the two and influences the buying behavior? ‘

An additional benefit of working with a vendor that determines the effectiveness of all relevant ads along the purchase path is that, like most companies starting out in attribution, you will find you have many ads that close deals, but very few that wields influence during the early part of the buying cycle. This type of information highlights opportunities to invest in ads that are effective influencers in the early or middle parts of the buying cycle.

Attribution Management Buyers Guide Part 7 – Time

Time is one of the most impactful variables when performing attribution. Therefore, it is important that the attribution technology utilized provides you a lot of flexibility to apply different time variables and provides a lot of insight about the time it takes consumers to purchase and to navigate through the Purchase Path.

Here are some questions that you should ask of attribution management vendors to ensure that you’ll have the flexibility needed to handle this important variable:

  • – How is time factored in your tool’s attribution models?
  • – What kind of flexibility do I have?
  • – Can you tell me the time from first ad to conversion? Last ad to conversion?
  • – Can you tell me the time between ad clicks, ad impressions, direct visits, and organic visits in the Purchase Path?
  • – How long do your cookies last?
  • – How do I know the appropriate window of time to give credit back to an ad?

The ideal attribution management solution should be flexible with leveraging time as one of the key attribution attributes. Specifically, the solution should allow you to tell the time from first and last click to conversion. It should also be able to measure intervals between all clicks in the Purchase Path. This data, coupled with the ability to set an appropriate time window to apply attribution, will allow you to more accurately attribute proper credit back to the ads that contributed to the sale. In addition, the cookie that the vendor provides should optionally be configurable to last for much greater than 30 days, and it should renew each time that person visits the website.

The ideal attribution management vendor should allow you to easily see the time from first ad to conversion, last ad to conversion, and the time between each ad. The cookie that the vendor provides should last for much greater than 30 days and should renew each time that person visits the website.

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Independent Research Firm Names ClearSaleing A Leader in Attribution Management

Monday, October 26th, 2009

ClearSaleing Earns Highest Score in Both Current Offering and Strategy Categories among Interactive Attribution Vendors

Columbus, Ohio (PRWEB) October 26, 2009 — ClearSaleing, a technology and thought leader in attribution management, today announced that the company has been recognized by Forrester Research, Inc. as an Interactive Attribution “Leader” in an independent report: “The Forrester WaveTM: Interactive Attribution, Q4 2009″ (October 2009)”. ClearSaleing received the highest scores in both the “Current Offering” and “Strategy” categories. It also garnered a 5.0 out of a possible 5.0 score for its strength of management team.

Forrester described ClearSaleing’s attribution offering as “a standalone attribution tool with rich modeling,” saying it “comes closest to offering a complete solution…” The report also says ClearSaleing’s technology is “easy to use, sophisticated, and relevant for a wide variety of interactive marketers” and notes that “ClearSaleing is an easy-to-install standalone product rather than a feature of a larger offering, but it is still relatively affordable and scalable for a range of clients…. Through a partnership with Vetra Analytics, ClearSaleing offers the best of both rich custom modeling and easy-to-use reporting.”

“ClearSaleing is delighted to be recognized by Forrester,” says ClearSaleing co-founder and Chief Innovation Officer, Adam Goldberg. “Since we began, ClearSaleing has been working steadily to develop and deliver technology that marketers can put to use immediately to optimize campaigns and realize the greatest ROI. We believe attribution management is the linchpin of any successful marketing strategy, combining customer insight with smart campaign management.”

The Forrester report also stated that “All of the clients we spoke with were fiercely loyal to ClearSaleing, citing its high level of service and its commitment to high-quality insights.”

Based on the increasing recognition among marketing executives as to the importance of attribution management and ClearSaleing’s position as a leader in advertising analytics technology, the Company has also been successful in forming partnerships with large interactive agencies to offer its attribution management platform to their customers.

“We did an exhaustive search and review of a wide range of attribution management solutions that we could use to optimize the performance of complex, cross-media campaigns that we manage for our customers,” said Dustin Engel, Vice President, Strategy and Media, Range Online Media. “And we found that ClearSaleing had by far the most robust advertising analytics platform, built from the mindset of attribution management,” Engel said. “The ClearSaleing Attribution Management platform has received enormous interest from our customer base and has already been implemented for a few of our clients, with many other customers lining up to implement our attribution strategies utilizing the platform.”

“We knew from the beginning that to optimize the ROI of a company’s online advertising portfolio required the ability to do cross-media profit tracking and true attribution management,” said ClearSaleing President and co-founder, Randy Smith. “We have built our advertising analytics platform from the beginning on these cornerstones and our customers and our agency partners all recognize our position as a leader.”

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About ClearSaleing

Named “Technology Platform Search Marketers Can’t Live Without” at the SES Awards, ClearSaleing’s advertising portfolio management platform helps marketers identify ways to more effectively and profitably allocate ad spend across a complex mix of online advertising investments.

ClearSaleing is a thought leader in the growing scientific field of attribution management and publishes www.AttributionManagement.com that provides a rich repository of ClearSaleing and externally published articles, white papers and other material focused exclusively on attribution management.

ClearSaleing’s unique ability to give marketers telescopic insight into their online ad investment is attracting major brand customers such as American Greetings and Nationwide Insurance. The company was founded in 2006 and is headquartered in Columbus, Ohio. For more information, please visit www.ClearSaleing.com.

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Ecommerce Know How: Avoid The Last Click Effect

Monday, October 5th, 2009

In recent months, many more online marketers have realized that the “last click effect” can be hazardous to the success of their online marketing campaigns.

This article from Practice Ecommerce details the problems surrounding the last click effect along with ways to avoid it. Some of the solutions include using the latest attribution management tools and technology.

Read the entire article from Practical Ecommerce…

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You Need More Than Simple Math to Solve Attribution

Wednesday, April 8th, 2009

If you’re reading this blog, there’s a good chance you’ve been in a situation like this: You and your marketing colleagues believe giving conversion credit to the last ad click is a flawed attribution method. Therefore, you have investigated or invested in technology that allows you to track beyond the last ad that is clicked so that you can perform attribution over the team of ads that lead to a conversion. With this new tracking in place, you then need to determine the correct attribution models, and it is at this point that if you are like most marketers, you get stuck.

Why do we get stuck? We quickly realize that the argument could be made for many different attribution models. For example, consider the following Purchase Path: a user clicks on an ad for ‘running shoes’, then clicks on an ad for ‘Nike Shox’, followed by clicking on an ad for ‘Nike turbo 7′ and making a purchase. One way to attribute in this scenario would be to give equal credit to all three ads. Another could be to give 20% of the credit to first ad, 30% to the second ad and the final 50% to the final ad. Or a third model could be the reverse, where 50% goes to the first ad then 30% to the second and 20% to the final ad. The point is that we can go on for a while with many different models. So which model is correct?

Marketers can find attribution very frustrating when observing the models above because there doesn’t seem to be a clear cut mathematical solution to what the right answer is. At this point, most marketers then begin to question if attribution is all that it’s cracked up to be given that there doesn’t seem to be any accurate way to solve the correct attribution models.

Attribution Models take some very complicated mathematics to develop. Recently, we conducted a webcast titled ‘Measuring the Immeasurable’ that featured our partner, Vetra Analytics. Vetra is a statistical consultancy made up of PHDs in Statistics and Mathematics that can utilize advanced mathematical modeling to create attribution models.

When solving for attribution, one needs to determine the ‘influence potential’ of each ad click, impression and site visit. In order to determine this potential, one needs to consider many factors, including but not limited to the timing of the ad, decay rate of the ad, if a conversion was made what products were sold, the amount spent of a first time buyer or repeat buyer, etc. In order to determine the influence potential, a model or models need to be built which will help to predict the consumer decisions as accurately as possible.

The statistical models account for one of the most difficult things for marketers to grasp – uncertainty. Uncertainty is all of the factors that may go into a buying decision that are not capable of being measured by your advanced technology. For example, did a friend recommend this product to the consumer? Did they see a billboard or TV commercial? Or did a sales person in the store influence their decision?

By accounting for the uncertainty and building a model that incorporates these factors, we can test the model on a go-forward basis. If the attribution in the model matches the actual results over a sufficient sample size and period, we then know the model that was built is mathematically sound. If the reality does not match the model, we then know the model is not optimal and can be recalibrated.

There are solutions to attribution management that will change the ways in which you manage campaigns. If you are serious about solving attribution because you recognize that accurately attributing credit to your ads will allow you to make more effective media buys, which ultimately lead to greater profits for you and your clients, then you will need to utilize a tool set that implements advanced modeling.

Always remember that a technology is only as good as the people behind it. When implementing an attribution solution, make sure you have the staff that understands how to calibrate it or that the vendor you choose offers services to assist you in building sound models. Your success with attribution is solely dependent on your ability to employ accurate models. If you are serious about solving attribution because you recognize that accurately attributing credit to your ads will allow you to make more effective media buys, which lead to greater profits for you and your clients, then you will need to engage with professionals that have the necessary mathematical skill sets, such as Vetra Analytics.

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Total Economic Impact: Attribution Webinar


Forrester Consulting recently examined the total economic impact and potential ROI that enterprises may realize by deploying ClearSaleing's advanced advertising analytics and attribution management platform. Register for the webinar to see the full analysis and the benefits from implementing an attribution management solution.

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Independent technology research firm Forrester Research, Inc. selected vendors for a 44-criteria evaluation to determine the leaders in the attribution management field.
ClearSaleing Takes "Top Honors"
ClearSaleing received the highest scores in both the “Current Offering” and “Strategy” categories.
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About Attribution Management

In the world of online marketing, Attribution Management is the process of properly identifying and valuing the chain of marketing initiatives and advertisements that lead to a sale or conversion.

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