This is the fifth and final excerpt from “Bid Testing Best Practices”, a white paper from OptiMine Software. In this post, Jason looks at two specific applications of value-based bid testing using the same data. You can read earlier excerpts about position-based bid testing and current bid-based bid testing, or visit optimine.com to download the whitepaper.

The best approach is value-based bid testing: basing test bids on the present value per click and making small changes up or down to see how they impact campaign goals. This strategy takes time due to the need to test a small bid change, observe the results, and repeat the process until you find the bid that ideally matches your campaign goals. However, it is time well spent because it avoids wild swings in click volume and maintains control over the budget. How much of a nudge to give bids depends on how much risk can be absorbed at any given time, balanced against whether the incremental cost incurred is outweighed by the incremental gain.

The question of whether to test up or down depends on the campaign goal. If the goal is to maximize conversions, test bids should be incrementally increased and then evaluated against your goal. If the goal is to maximize efficiency, test downward to see if the same results can be obtained at a lower cost. Testing downward is an often overlooked but extremely important bid test strategy. For example, if a bid of $0.85 meets the goal on average as well as a bid of $1 per click and the lower bid is applied across thousands of keywords, the cost savings quickly become substantial.

Below are two interpretations of the same hypothetical data, illustrating various outcomes of changing bid levels incrementally based on your goals.

Goal 1: Maximizing Conversions

If the goal is maximizing conversions, for example, bids should be increased to raise the ad position. In this example, bid testing shows the higher the bid, the higher the conversions. And even though the ad already occupies a high position, incrementally testing the bid upward might result in additional modest gains in conversions. Something to note is that profit falls as bids are increased, which might be an acceptable trade-off, given the goal of maximizing conversions. This is bid testing in its simplest form, but there is far more to it than this.

Goal 2: Maximize Profit

If we change to goal to maximizing profit, the ideal bid changes. In this case, testing shows that bidding lower accomplishes the objective. Fewer conversions are generated than with higher bids, and we are in a lower average position – but the cost per conversion is lower, and consequently the profit is higher. This example shows that, while bidding upward to achieve a higher position generates the greatest number of conversions, it comes at the cost of reducing profitability.

The Bottom Line on Bid Testing

Internal changes to financial goals combined with the constant changes of a dynamic marketplace make bid testing necessary to keeping a paid-search program competitive and profitable. Choosing the proper bid testing approach is as important to paid-search success as the choice of keyword bid optimization method. Of the three methods explored above, only value-based testing maximizes performance improvement while minimizing financial risk. In contrast to its bid-testing cousins, the goal of valuebased is to find the maximum value of a keyword, regardless of current bid or position.

There are several compelling advantages to testing small incremental changes and testing frequently. Small changes minimize risk because the potential impact on budgets is small and controllable. Moreover, because they represent relatively small potential risk to budgets and/or performance, small changes can be tested with greater frequency. Frequency is an important component of bid testing because it delivers much greater long-term benefits than sporadic testing. Frequent testing is also important for companies in highly competitive environments and companies whose products are highly seasonal. It also allows you to more quickly and proactively identify marketplace changes rather than simply react to drops in PPC performance with dramatic and often expensive bid changes.

In determining what to test, the simple answer is that every aspect of a PPC campaign should be tested to make consistent improvements in performance. But if you’re not testing now, a good place to start is determining which aspect of your campaign has the potential for the greatest and quickest returns – either in terms of improving important performance metrics or increasing the effectiveness of your ad spend. Once you’ve tested and optimized this low-hanging fruit, create additional and perhaps more difficult goals and start testing again.

Implementing such a testing regime can seem like a daunting prospect for companies that manage tens of thousands or millions of keywords. Fortunately, there are applications that can help automate the testing process. However, any tool you choose should allow you to control the frequency with which tests occur and the acceptable range in which you are willing to allow bids to be adjusted – either in terms of a fixed dollar increment or in terms of a percentage. The best tools allow advertisers to spread out the testing over a long period of time to gather a variety of performance observations at different bid levels, all while protecting budgets and profit margins to the maximum extent possible.

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The following is the fourth in a series of excerpts from “Bid Testing Best Practices”, a white paper from OptiMine. In it author Jason Mulvey explores the three primary methods for conducting bid testing in paid search.  In earlier posts we covered position-based bid testing and current bid-based bid testing. In this post, Jason looks at value-based bid testing and how it differs from its two cousins. Visit optimine.com to download the whitepaper.

Value-Based Bid Testing

Value-based bid testing differs significantly from its two cousins. Whereas position-based and current bid-based approaches each test around a point that has no relation to actual keyword performance, value-based bid testing uses keyword performance as its guide. Regardless of position or bid, value-based testing seeks to test around the observed value of a keyword.

Properly implemented, value-based bid testing reduces the risk of loss while maximizing the probability of improved performance. In practice, value-based testing works by moving up and down around a bid that matches the keyword’s average value per click. For example: If a keyword receives 100 clicks and returns $100 in revenue, the average value per click is $1. Value-based bid testing will use that average value as a starting point, testing up and down in a reasonable range and monitoring keyword performance.

Where value-based testing becomes difficult is in estimating the value per click for every keyword. Not every keyword receives a click and, of those that do, there is always a percentage that does not experience a conversion event. In cases where there is no conversion or value data, predictive modeling is required to estimate the value. While difficult, estimating the value per click can provide immediate improvements to performance, especially in face of changing goals and external conditions.

By nature, the appropriate predictive models used for bid testing are exploratory. Traditional predictive models do not provide estimates outside the range of values that have been seen in the past. Therefore, if a keyword has never had a bid as high as $2, a predictive model should not predict a $2 bid. Exploratory models have that restriction removed, allowing them to test in new ranges of bids that have not been tried before. The disadvantage to this exploration, however, is that the predictive accuracy of the performance is greatly decreased because there is no keyword performance data for the bids being tested.

Next up, Jason will look at value-based bid testing in practice and how the same data can result is very different results depending on the goal. If you don’t want to wait, you can have the white paper in its entirety by downloading it today.

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The following is an excerpt from “Bid Testing Best Practices”, a white paper from OptiMine. In it author Jason Mulvey explores the three primary methods for conducting bid testing in paid search.  In the previous post, Jason looked at position-based bid testing. Today he covers the pros and cons of current bid-based bid testing. Visit optimine.com to download the whitepaper.

Current Bid-Based Bid Testing

As the method states, the baseline used for testing is the current bid, whatever that happens to be. This is the most conservative of the three strategies and is executed by varying bids a small amount above and below the current bid. In contrast to position-based bid testing, the risk of loss is greatly diminished through current bid-based testing. However, where the conservative approach reduces risk it also decreases the probability of driving dramatic financial performance improvements. If the current bid is $0.50 and the sweet spot is $2.00, even doubling the current bid will leave the keyword well short of its optimal bid, missing potential revenue.

In the next post, Jason will look at the value-based bid testing. In the meantime, you can have the white paper in its entirety by downloading it today. 

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If you’re not bid testing as part of your regular paid-search maintenance, you’re giving your competitors the upper hand.

Bid testing has a reputation for being a risky activity where one can spend a whole lot of money and, in the end, learn little of value. High-risk bid testing certainly exists and many digital advertisers have been burned by the practice in the past, but, when done correctly, bid testing will deliver relevant and actionable insights without breaking paid-search bank.

OptiMine’s Jason Mulvey recently authored a white paper that compares the three primary methods of bid testing, their risks and rewards.  Position-based, current bid-based and value-based are three very different approaches to what is a necessary part of paid-search maintenance.

Reading “Bid Testing Best Practices” will give you what you need to assess your own bid testing program and help you understand how it impacts the performance of your paid-search campaigns.

@OptiMineInc

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