Efficient Frontier Insights

Dayparting or Splitting Hairs?

In this month's Search Engine Land "Analyze This" column, I discuss whether dayparting or hour or day bidding is worth the time and effort. For my full analysis, please read http://searchengineland.com/dayparting-profitable-tactic-or-waste-of-time-30727 but here's the bottom line.

For most businesses, dayparting will at best give you a small incremental gain. It is best to look at all of your data, cost and revenue on a per click as well as aggregate basis before making any dayparting decisions.

Dr. Siddharth Shah

The Future of Biddable Media

Every day, Efficient Frontier's technology executes millions of bid changes on behalf of our clients. Dozens of servers contact dozens of other servers at Google, Yahoo, Microsoft and Baidu to adapt campaigns depending on changing market conditions and business goals. A constantly evolving set of APIs makes the communications efficient and seamless.

But for a moment, just imagine a world where this doesn't happen. Where there are no APIs, no automated setting of bids, and not even an interface to set those bids by hand. In fact, every bid needs to negotiated one-by-one, over the phone or in person. Sounds awful, doesn't it? Welcome to the world of online display advertising.
 
The banner is the grandfather of online advertising. It has spawned different sizes, formats, targeting over the years, but like many grandfathers, it still has an old-fashioned way of behaving: trading.

SEM has a dynamic ecosystem of biddable marketplaces that advertisers can value and buy media. Third party technology, such as Efficient Frontier, helps those advertisers evaluate market data to determine when and where to show their ads, and at what price. The time has come for this remarkable system of decision-making and trading to come to the display market.

For too long, display advertising has been hamstrung by an antiquated method of trading that delays decisions, creates inefficiencies and suppresses investment by advertisers. Ad exchanges, such as Doubleclick and Rightmedia, are creating marketplaces that will provide an efficient and dynamic environment for media owners and advertisers to do business.

All the trading benefits that we currently enjoy in SEM are being brought to display, for advertisers and publishers alike. At Efficient Frontier, we are rapidly immersing ourselves into this new world. As biddable market places become a bigger feature of the display world, we will be helping advertisers track, optimise and forecast - just as we do today in search. Performance marketing is about to get a lot more exciting.

Jonathan Beeston
Client Services Director, Europe

Follow the data...not the position

When we take onboard new clients, we find that some clients have a predetermined idea on which position on the Search Engine is the best. Some advertisers believe position 1-3 on Google is a must. Putting aside any branding or defensive PR reason for being placed at number one, one of the first things we try to educate new clients is to let the data dictate your Search Engine Results Page (SERP) position.  The following case study shows the importance of letting the data work its magic and give you a better ROI.
 
Recently, a German travel client used more than 3900 keyword constraints in order to influence its overall performance. A keyword constraint is the maximum/minimum CPC or maximum/minimum position rule for each individual keywords.  Soon, 90% of the daily budget was used to fulfill these constraint targets and only 10% of the budget was actually used to optimize keywords and increase real performance.
 

By taking away the majority of constraints, the complete daily budget was available to have the keyword market develop and to use the data generated from Efficient Frontier's portfolio optimization technology. Monitoring the performance very intensely, the following development was encountered.

When looking at Efficient Frontier's simulations this step became even more obvious. When the constraints were taken away, uplifts can be expected immediately. In this case, we saw an ROI increase of 96% (day to day) and 45% (week to week) just by taking away keyword limitations and letting the invisible hand of the optimizer take over. Since then, the free market environment has allowed the performance to improve continuously.

So if ROI is your key objective,  resist the need to seek the top SERPs positions and liberate your keywords from their constraints to improve performance and ROI.

Julian Stank
SMS Hamburg Germany

A New Challenge with a Familiar Feel

The Sunday NYTimes Business section featured an article by Stephanie Clifford on the evolution of display marketing called "Put Ad on Web. Count Clicks. Revise." It's worth a read. Clifford does a good job of covering how the ad exchanges brought an auction pricing model to display. Importantly, she covers how access to new targeting data from 3rd party sources like Blue Kai significantly alters the value of display inventory.

Until recently, targeting data has been controlled by large publishers and ad networks to drive higher CPMs and margins. As Clifford rightly notes, "this combination — real-time [targeting] data and ad exchanges — has monetized what was once considered throwaway space online." The key point is that access to both real-time targeting data and ad exchanges have shifted price control to the marketer and away from the publishers and networks. The result is that while demand builds in the exchange and data auctions, early-to-move marketers stand to benefit from the low prices and good volume available in-part because of the lack of competition. The early mover opportunity in the exchanges is reminiscent of the early days of search marketing with Overture and Google.

One point omitted from the NY Times story was the link between search marketing and the developments in exchanges. Search marketers and their agency and technology partners have been using data to drive bid and copy decisions for many years. In fact, the data-driven, Wall Street-like approach to marketing now being applied to display is core to any successful search engine marketing effort. Efficient Frontier's founder and CTO, Dr. Anil Kamath, brought the quantitative modeling techniques he built for programmatic trading in the hedge fund industry to search marketing in 2002. To those companies like ours immersed in search engine marketing, ad and data exchanges are an exciting development that fit well with our competencies and technology. This "new era" of display advertising is very search-like at its core.

We're actively working on our display and exchange management capabilities. Early testing has shown clearly the opportunity that the exchanges present in delivering efficient results at significant scale to our performance-oriented clients. The opportunity is still evolving as the exchanges develop and improve their APIs, a necessary step for us to automate optimization. We’re thrilled to be a primary participant as the new era of display unfolds, presenting us with a new challenge with a familiar feel.

by Justin Merickel
Vice President of Marketing and New Product Development

It isn't obvious

Consider the following keywords
You would like to bid each keyword so that you maximize orders subject to the constraint that the overall Cost Per Order (CPO) is less than $20. A lot of us would simply look at each keyword and bid them to a CPO at or higher than the average CPO. So we bid keyword 1 to position 1 (CPO of $20) and keyword 2 to position 2 (CPO of $20). In this scenario we would get 15 orders from keyword 1, 10 orders from keyword 2 for a total of 25 orders at a cost of $500 ($300+$200). The overall CPO is $500/25=$20. So it's good.

But what if we did the exact opposite? Here we would get 10 orders from keyword 1 at a CPO of $10 and 20 orders from keyword 2 at a CPO of $25 for a total of 30 orders at a cost of $600 ($100+$500). What is the CPO now? Its $600/30=$20. We got more orders for the same CPO despite exceeding the CPO target for keyword 2! Welcome to the portfolio theory of SEM. Like we said... It isn't obvious.

Learn more about the portfolio theory of SEM and several other cutting edge SEM concepts in our latest paper: Algorithms and Optimization

Visualization of Data through Motion Charts

One of the key advantages of SEM is that data can be measured at several points in the sales funnel. For example: Impressions measure the degree of user intent, Click Through Rates (CTR) measure the effectiveness of your ads in capturing that intent, Cost Per Click (CPC) measures the price you are paying to capture intent and finally the ROI measures the rate of return on investment in this marketplace. While this multi-dimensional measurability of data is a key asset to the search advertiser, the complex interactions of the metrics can be daunting to analyze without the right mathematical and analytical tools. Visualization techniques such as treemaps, which was discussed in a recent post, can help capture several dimensions of data successfully and make the data meaningful. In this post, we present another very powerful tool called Motion Charts that can capture 5 dimensions of data in an extremely effective manner. Whats more these charts are fun ! Before, delving into these charts, a bit of history. Motion Charts were first presented to a large audience by Dr Hans Rosling in a famous TED talk where he discussed global health in an extremely engaging manner. The tool he used was called the Trendalyzer developed by a non-profit Gapminder.org . Google later acquired the Trendalyzer and developed this technology into the Motion Charts. It is now part of the Google Docs suite of visualization tools . As an example, we will analyze the performance of a hypothetical SEM campaign with this chart.

The two bubbles represent 2 portfolios of campaigns managed by Efficient Frontier. One bubble represents Google campaign and other represents the Yahoo campaign. If one moves her mouse over the right most bubble, 4 dimensions readily become apparent. The horizontal axis captures weekly spend, the vertical axis captures weekly account signups, the size of the bubble is proportional to average conversion rate (free registration to paid subscription rate) for the Google portfolio and the color of the bubble is proportional to the CPA of this portfolio (note the color specturm on the right side of the chart). The paramters to be tracked can be interactively changed by selecting the drop downs on the axes and on the right side of the chart. Finally, note the date on the right side of the chart. This is the fifth dimension. So, to interpret: on Week starting May 1 the Google portfolio generated 800 registrations at $1000 spend with a conversion rate of 9.4% at a Cost Per Registration (CPR) of $1.25. Moving the slider, will change the time and will display the locations of the 3 portfolios on that week. Hitting the play button will play the "movie" of your quarterly performance. Trails are a very powerful feature in the motion chart. To enable trails, check the trails box on the screen (it defaults as already checked), change the size parameter of the bubbles (in the drop down) to "same size", and click on the Google portfolio bubble again. You would now see a name tag pop up next to it. On pressing play again, the Google portfolio is "tracked" over the quarter and one can clearly see the change in performance over time. In this example, the Google portfolio is seen to be 25% more efficient from week 2 i.e. the weekly account signups have increased by about 25% at close to the spend on week 1. Also note that since week 2, the portfolio has clustered at its "sweet spot" i.e. while there are week to week fluctations in performance, i is always better than the performance on week 1. An analysis of several accounts managed by EF reveals a similar pattern i.e. while performance fluctuates on a weekly basis, the portfolios cluster around a region of higher efficiency due to optimization.

Managing Risk in SEM: Using Histograms

Today Siddharth Shah, PhD and Senior Business Analyst at Efficient Frontier will speak on the topic of "Managing Risk in SEM" at SMX Advanced in Seattle. This post will introduce the concept of managing risk in SEM that he will present, and show how you can use histograms to help you assess and manage risk.

Firstly, what does risk mean in relation to your PPC campaign? You have hundreds, thousands, tens of thousands, or in the case of some Efficient Frontier clients, millions of keywords on multiple search engines, with multiple ad copies, landing campaigns, and possibly targeted to various regions. Every day you are expecting a certain amount of clicks to drive traffic and conversions to your site. There can be high levels of variability in impression volume, user behavior, and competitive activity, but the success of your business depends on this traffic. Therefore gaining some level of predictability to what can be a highly volatile marketplace is imperative.

A histogram is a statistical visualization tool that shows the proportion of cases that fall into certain ranges. Unlike a bar chart, it is the area of the bar that defines the values, rather than just the vertical scale. To make a histogram in Microsoft Excel, you need to download the Analysis ToolPak. You then have to define the bins, or ranges, that your data groupings should fall into. For example, the histogram below shows that for this particular head keyword, there were 27 days out of 80 that the keyword received between 60 and 69 conversions. The bins used here were multiples of 10, but as you will see on the Wikipedia entry, the bins do note have to be equal values.

So how can a histogram help you manage risk? Siddharth created histograms of many keywords by number of days that the keywords received certain amounts of revenue (or conversions), and found that head term histograms, like the one above, followed a certain pattern that resembles the normal distribution. In contrast, tail term keywords followed no visible pattern of revenue generation, suggesting that head and tail keywords should be treated differently in your portfolios.

Why is the normal distribution important? The normal distribution, or Gaussian distribution, or bell curve, as some call it, has many important properties, the most important of which in this case is its predictability. The blue line on top of the histogram above represents the normal distribution for the same values in the histogram. The central limit theorem, a fundamental theory of probability, states that a large number of random variables will follow a normal distribution. Thus we can predict, with a reasonable amount of certainty, the range in amount of revenue or number of conversions we should expect from a head keyword.

This is where the mean and the standard deviation (SD) come in, as have been shown on the chart. The mean, or average, number of conversions that occurred from this keyword on any of the 80 days analyzed was 60.55.  But if you expect 61 conversions every day from this keyword, you will be sorely disappointed, as the histogram shows that there were only 34 days (27/80) in which there were between 60 and 69 conversions. Even if you expect 60 or greater conversions, your goal will only be satisfied 79% of the time (63/80), which leaves 17 days that you will be wondering what went wrong.

In a normal distribution, a standard deviation of 1 standard unit above or below the average indicates 68% probability, and a deviation of 2 standard units indicates 95% probability. The standard deviation (a convenient formula in Excel: STDEV) for this group of data is 13.21. Thus there is a 68% chance that on any given day this keyword will bring in between 47 and 74 conversions (60.55 +/- 13.21). There is a 95% chance that the keyword will bring in between 34 and 87 conversions (60.55 +/- 2*13.21).

You can use this method to define a range of expected performance for your head keywords. If you are 95% confident that the keyword will bring in a specified range of conversions, you only have to worry about the days that performance fell outside of that range. Since you don't have to worry about the days where performance exceeded expectations (unless you want to investigate if there is a positive change in the marketplace), you now only need to worry about the days where performance did not meet expectations. In this case, there was only one day where the keyword received fewer than 34 conversions, which is far less taxing than worrying about performance not meeting expectations on say 17 days if you were holding this keyword to a 60 conversions per day goal.

This kind of management of the head keywords allows you to approach the tail with a different mindset. Siddharth did another analysis and found that in one month there were 16,105 keywords in a campaign that generated revenue, while in the following month there were 17,238 revenue generating keywords in the same campaign. Closer analysis showed that there were only 2,937 keywords, or 15% of total, that generated revenue in both months. Tail terms should closely monitored and actively bid on as their behavior is very dynamic and sparse data does not allow the same level of predictability found with head terms. This unpredictable behavior also means that tail terms should not be held to a daily revenue target if you want to extract the most value out of the tail.

Efficient Frontier's algorithmic optimization technology reduces risk by proactively monitoring and acting upon this dynamic keyword behavior in both the head and the tail, in a way that rules-based systems cannot. By modeling every keyword every day at every position for clicks, revenue and CPC, risk is reduced as the bids continually reflect activity in the dynamically changing marketplace.

 

Increase returns by tracking and optimizing the right web metrics

Metrics are important, both in online and traditional marketing but it's the trackability which makes online marketing so exciting. What's even more exciting is that the technological advancement in online marketing has enabled maximization of multiple success metrics simultaneously.

Track right metrics

Tracking provides visibility on business relevant metrics like return on investment (ROI), cost per order (CPO), return on ad spend (ROAS) and user lifetime value (LTV). You should try to track as many metrics as possible, even if they are not needed at the time the campaign is set up. It's frustrating not to have the data you need at a later time.

Conversion data on various steps in the process can provide useful insights on visitor bounce rates, page views, links clicked and actions taken. Having this information can help understand how users navigate through the site and the pages where users drop off.

Optimize to success metrics

If the conversion is a single step process, it's easy to choose the optimization metric. However, often the conversion cycle involves multiple steps. Marketers are faced with the challenge of selecting the best optimization metric in such situations.

For example, for an online dating advertiser it could be confusing whether the optimization metric should be registrations or subscriptions. By trying to maximize only subscriptions, the advertiser runs the risk of ignoring registrations which could potentially bring subscriptions. On the other hand, by trying to maximize only registrations, the advertiser might end up with too many registrations which may never turn into subscriptions.

These metrics are interdependent and for optimization purposes one can not be chosen over the other. This is when multi-metric or "blended" optimization is necessary.

Blended optimization

At Efficient Frontier we use a blended optimization approach which allows our clients to optimize their ad campaigns concurrently to multiple business metrics. For example, the marketing objective for one of our banking clients is to maximize new customer sign ups. The sales process involves three steps: application form completion, approval and final sign up. The campaigns or keywords driving final sign ups are more valuable than the ones driving approvals and form completions. With Efficient Frontier's tracking technology, the client is able to track entire sales funnel and the user drop off at each stage in the funnel.

Efficient Frontier's optimization technology allows our clients to assign different weights to different stages in the sales funnel based on the value of each stage. Using this technology, the banking client is able to maximize customer sign ups while maintaining the constant inflow of the leads or application form completions.

Web metrics can tell the advertisers exactly where the marketing budget is being spent and what they are getting out of every marketing dollar. If implemented, tracked and optimized right, these strategies can certainly help increase the return on investment.

Google Becoming More Efficient: Improved CTR

The recently reported decline in Google paid clicks caused what may be an unnecessarily strong reaction in the investment community this past week. Efficient Frontier's US Client Index, which covers more than 20 million paid clicks each month, did indeed see a 5% drop in click volume on Google when comparing January 2008 to January 2007. But same advertiser spend was up on Google by 7% in the same period, and click through rates improved by 10%. CPCs were up by 13%. This data suggests, as Comscore posited, that Google is becoming more efficient at serving ads by delivering more relevant clicks to advertisers. Thus it is able to charge a higher premium for those ads, hence the increase in CPCs.

Our Search Engine Performance Report: Q4 2007 showed that ROI on Google was up 7.5% from Q4 2006 to Q4 07, which does not spell disaster in my mind. Next week we'll take a look at overall statistics for February on this blog. Stay tuned!

SEM Tools: Risks, Limitations & Best Practices - Part III: Demographic Targeting

In the previous two posts in this series, I discussed key elements to pay attention to in geo targeting and content targeting. In the final post in the series, I will discuss the risks, limitations and best practices in using demographic targeting.

Part III: Demographic Targeting

Demographic targeting is a relatively new tool currently offered by MSN AdCenter and Google Adwords (for limited site targeted content campaigns). Through demographic targeting you can target your audience based on gender, age, ethnicity, family income and even whether they have children at home or not. This would be one of the greatest tools for search engine marketing if completely accurate, since you will be able to show your ads to the preferred demographic. However, there is still room for improvement.

1. Inaccurate User Information

Search engines base demographic targeting on the information users enter at the time of signing up for any of their products. MSN AdCenter, for example gets this information from MSN Hotmail and Microsoft Windows signups. It’s a common knowledge that people give inaccurate information during signups and there is no shortage of fake Hotmail and Gmail profiles on the internet. Search engines base their trends on this information which is perhaps not entirely accurate.

For example, a 50 year old man in Canada can easily create a user profile of a 27 year old woman in San Diego, California. Thus a cosmetics ad intended for women in their 20s would not reach its intended audience in this case.

2. Again, know your business

Just like , demographic targeting would be applicable only for certain businesses and not for others. If your product is targeted towards a particular demographic, it may make sense to use this tool.

When I looked at the demographic report for the keywords "evening gown" and "tuxedo" from MSN AdCenter’s new MS Excel Add-in "Ad Intelligence", I could see very clear gender-based search trends. If you are a business which aims to sell evening gowns and tuxedos, you should keep two sets of keywords, one targeted towards men and the other towards women. 

Similarly, if you look at the demographics for the keyword "baby clothes," the majority of searches are from women between the ages of 18 and 50. 

On the other hand, if you look for demographic trending of electronics related keywords like "hdtv" and "digital camera," the search volume doesn't skew strongly towards one gender or age group. In this case demographic targeting would limit your reach more than necessary and is not recommended.   

All said, you should have enough data and proof to determine which demographic group is more likely to buy your product before you use this feature.

Unlike geo and content targeting, demographic targeting is relatively new. I am still not completely confident of its accuracy as many web users likely enter incorrect information. I am positive though, that the tool will become more robust in future. If you decide on using this tool, I would strongly recommend conducting research on demographic trends in your business from both internal and external sources.