Paid search marketing, with its complex bid management techniques and daily campaign management challenges, is difficult enough. And it doesn’t help that the industry’s thousands of vendors and consultants each think they have the inside secrets on how to optimize campaigns—and aren’t afraid to share their “advice” with you at every turn. This constant barrage of input combined with the need to test everything, understand a dizzying amount of data and build a workable strategy for bid management can make many search marketers nervous they’re not maximizing ROI from their paid search programs. There are three myths that seem to still be circulating in the industry about the complexity and difficulty of paid search optimization. It’s time these myths got busted so you can focus on the real optimization techniques that matter.

Myth #1: Google will pick the best creative for you

Most marketers think if they develop a campaign on Google, the search engine will automatically determine and serve the best-performing ad copy from the available set. Many marketers believe this means they should continually add creative, since the engine will take care of testing for you. But all that testing may not be helping as much as you think. Google determines which ad copy to serve based on which version has the highest click-through rate, but your highest CTR ads aren’t necessarily your best-performing ones. To get around this problem, you need to do two things: set the creative rotation in Google to “show evenly” to perform an accurate test, and then do your own tracking and measuring of ad copy to see which ones are performing the best.

Start by determining what you want to test, and defining a start and end date for your test. Once you implement the ad copy, ensure you are tracking conversion at the creative level using the dynamic insertion parameters provided by the engines. Also, be sure to choose a relevant metric like conversions-per-impression, instead of just click-through rate. Compare each creative in an ad group vs. the average of the ad group without that creative. By doing this, you find out which creatives are driving the most conversions, and once you know this, you can jettison poor-performing creatives and manually rotate higher-performing ones into rotation.

The bottom line: Pause creatives that come in below the average; continue to monitor those that are near average for any changes; and keep running creatives that are out-performing the others using a metric such as conversions-per-impression rather than the relatively meaningless click-through rate metric.

mythsgraphic

Myth #2: You have to look at all prior clicks for accurate bidding

Most marketers bend over backwards trying to attribute conversions back to every click in the visitors’ path to come up with accurate bid prices. It’s understandable you’d want to accurately attribute conversion to each keyword by looking at past clicks, but multi-click attribution can be difficult to track and even more difficult to understand and make actionable. Many marketers avoid tackling the attribution problem head on by simply over-investing in early-consideration terms, even if the ROI isn’t there, because they believe these terms influence purchases down the line.

The truth is, you’ll get a reasonably accurate picture of conversion and ROI for campaigns by attributing value only to the last click, because the majority of people do not click on multiple search terms before making a purchase. In fact, research into a leading client of ours spanning hundreds of brand-name and product-name keywords found that only 26% of paid search conversions had more than one prior click on a paid search term. That means three-quarters of all paid search conversions happened after just one click—so if you measure back just one click, you’ll get a pretty accurate measure of ROI. What’s more, we found that almost half of these multiple-click conversions had the same term for all prior clicks—making last click attribution accurate in more than 85% of all cases.

The bottom line: Evaluating and implementing a complex scheme for attributing conversion across multiple clicks can be valuable, but the impact from a measurement standpoint is likely small. Instead, you may be able to get a lot more value from focusing on other low hanging fruit for optimization such as keyword expansion, adding negatives or creative testing.

Myth #3: “Portfolio management” is really, really hard

Many marketers get stuck believing that optimizing their keyword portfolio to increase profit is inordinately complex. As a result, they turn to outside help, and in many cases will simply hand over bidding to a third party. The truth is, at a basic level, portfolio optimization doesn’t have to be hard, and in many cases, it’s downright easy.

When thinking about portfolio management, it’s crucial to calculate a “headroom” metric—or the bid price minus the cost-per-click. For example, if you bid $2 on a keyword and your CPC ends up being $1.40 after the auction is complete, you have what is known as “60 cents of headroom.” You could pay 60 cents more for this keyword and still meet your pre-defined ROI targets.

Using this metric, you can look at all of your keywords in your portfolio that have substantial headroom. If these keywords are in position #1 in the auction, don’t change anything, as your bid is already working to place you at the top of the heap. These keywords are maximizing your profit, and generating excess returns for you. However, if you have keywords with headroom where you are in a competitive position in the auction—maybe 2nd, 3rd, or 4th place—it might pay to raise your bid on these keywords to move up in the rankings. You’re already getting several top position keywords for lower than you’re willing to pay, so it’s OK to pay a bit more for some other terms.

The bottom line: By increasing your bids on competitive keywords with headroom, you can wring more margin out your overall portfolio while still meeting your ROI goals.

Opinions expressed in the article are those of the guest author and not necessarily Search Engine Land.

Related Topics: Channel: SEO | Google: AdWords | Industrial Strength | Search Ads: General

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About The Author: is a product manager at Marin Software in San Francisco, CA.

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  • http://www.clickequations.com Craig Danuloff

    Niraj – Hope you don’t mind some push back on these ideas.

    Your first point seems to be that manual management of text-ad-testing is better than letting Google shift traffic toward ads with a higher CTR. Certainly the idea of considering conversion rate as well as click-through-rate is important (although how often they really diverge is another question). But CTR drives Quality Score so it certainly can’t be dismissed as a core determinant of ‘best’ performing ad. And deciding which to pause based on comparison to an average of the others is certainly a slightly more advanced way to make that decision. But fundamentally the AdWords algo will reduce impressions of low performing ads (CTR measured) and increase impressions of high performing, so when a person isn’t carefully monitoring a test leaving campaigns set on ‘rotate evenly’ can be quite damaging. Everyone has seen campaigns were one low performing CTR ad lingers forever wasting returns while set on ‘even’ distribution.

    The second point against considering revenue attribution is curious. Two things are true, 1) if attribution doesn’t shift revenue for any keyword, then it won’t harm any bid calculations, 2) in a small minority of cases using attribution radically shifts the revenue and therefore the appropriate bid calculation. Suggesting that attribution isn’t important because it doesn’t impact all keywords all the time is like saying someone shouldn’t wear a seat belt because the usually don’t have a car accident. And applying attribution isn’t (or shouldn’t be) a lot of work – either your software supports it or it doesn’t. If it doesn’t I would agree with you that hand-calculation isn’t worth the trouble…

    Finally, the third point seems itself based on three other myths – that hitting your ROI target is the optimal bid (isn’t the real goal to pay the least for the most) and that moving up in position creates higher ROI (sometimes yes, sometimes no), and that raising bid price raises position (will for some queries matched to the keyword while introducing others at lower position, possibly lowering overall KW ave Pos). Really the whole idea of ‘headroom’ as an indicator of potential bid increase seems strange – again because the goal isn’t to give the engine as much money as possible and the bid itself didn’t assure that it was the optimal spend in terms of return. Maybe I’m missing something you’re saying with this point because I really don’t get it – admitting that. this is a hugely complicated subject to fit into a few paragraphs. Also confused as to how the word ‘portfolio’ applies to any of this.

    I think the idea of myth busting in PPC is a great one. Hope this discussion can further that goal.

    - Craig / ClickEquations

  • http://www.efrontier.com Efficient Frontier

    Since it is our specialty, we are compelled to oppose myth 3 in which Niraj suggests portfolio management is easy to implement.

    Portfolio Theory was developed by a Nobel Prize winning economist and uses mathematical models to weight risk and return across numerous variables. In the same way, true portfolio management for search is founded upon keyword modeling and is about making bidding decisions on all keywords at the same time. Looking at keywords individually will almost always return a less than optimal solution.

    There are three main factors that determine the quality of a model:

    • Availability of historical data – It is about looking at overall impact on performance while accounting for bidding effects one keyword might have on the other. There is an exponential relationship between clicks and position – using simple rules may cause you to bid too high and burn budget for a poor return.

    • Capability to properly model tail terms – 30-40% of spend comes from the long tail. You could not use a simple ROI rule to bid these up or down. A much better solution is to use finite mixture models.

    • Adaptability of the model – Campaigns are influenced by factors such as competitors, news and search engine algorithm changes. Our models ensure keyword trends are identified and responded to immediately. It is impossible to do this at scale using the approach suggested in the article.

    The bottom line: using a simple heuristic on a complex problem will result in suboptimal returns. If estimates of CPCs et al are not accurate, then the method to optimize for performance will not be successful.

    For more details see our whitepaper (copy and paste) http://bit.ly/4rZqDB

    Justin Merickel
    Vice President, Marketing and New Product Development
    Efficient Frontier

 

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