Optimizing Paid Search Bids for Seasonality & Cyclical Trends

By Kye Mou May 16th, 2013

Anticipated changes in paid search performance, such as increases in RPC or decreases in conversion rate, create a common challenge that all bidding strategies must address—seasonality. To account for seasonal changes in performance, like the holiday shopping season, search marketers must constantly analyze year-over-year performance and adjust bids according to identifiable trends. Whether you’re driving clicks, increasing conversions, or maximizing revenue, accounting for these types of fluctuations in performance is critical to success in highly dynamic and competitive bidding environments. By deploying boost schedules, where bids are increased or decreased over specified time periods, search marketers can optimize their campaigns ahead of expected fluctuations in RPC or conversion rate. For example, a marketer might bid aggressively or dampen bids for in-season and off-season products, respectively. A bidding strategy that doesn’t adjust bids for seasonality will fail to capitalize on critical revenue opportunities throughout the year, enabling competitors to capitalize instead.

For more information on how to determine an optimal boost during seasonal periods, please see our tutorial on adjusting bids for seasonality.

Cyclical Trends

Cyclical, as opposed to seasonal, shifts in RPC or conversion rate can last for time periods shorter or longer than a calendar year. In paid search, these trends are typically observed as day-of-week or time-of-day fluctuations in performance. For example, an increase in mobile conversion rate during afternoons and evenings, or a decrease in desktop RPC during weekends. To account for cyclical trends, search marketers must analyze campaign performance across multiple weeks, identifying day-to-day changes in RPC or conversion rate; and in more sophisticated bidding strategies, analyze hourly changes in performance. Once these trends have been identifying, search marketers can implement dayparting strategies unique to each campaign, where keyword bids are boosted or dampened by day or by hour to maximize paid search performance.

Addressing Seasonal and Cyclical Data

Accounting for shifts in consumer behavior, whether it’s seasonal or cyclical is critical to a sound paid search bidding strategy. However, increases and decreases in RPC and conversion rate often results in periods of irregular performance. Consequently, bidding solutions and tools that don’t exclude this data may calculate suboptimal bids. So how do search marketers account for periods of incomplete or irregular data? Next week, we’ll take a closer look at addressing conversion latency and the importance of excluding abnormal search data from bid calculations.

Google Is Listening: Enhancing the Enhanced Campaign

By Kye Mou April 11th, 2013

On Tuesday Google announced that advertisers will soon be able to set mobile bid adjustments at the ad group level, in addition to the campaign level, for enhanced campaigns. This comes on the heels of Google’s release of two new ValueTrack parameters: {ifmobile:[value]} and {ifnotmobile:[value]}. Google also indicated July 22, 2013 as the start of the migration deadline, when AdWords will begin automatically upgrading legacy campaigns to enhanced campaigns.

These recent announcements shouldn’t come as a surprise to search marketers. Google has historically made adjustments to new AdWords features as market demands became more evident. (A recent example is last year’s update to the campaign ad rotation settings.) Sophisticated search marketers have been asking for additional enhanced campaign features to provide additional control and transparency for optimizing their paid search programs. Today, we’ll review the two recently announced enhancements to enhanced campaigns and discuss their importance to search marketers who operate in a multi-device world.

Ad Group Mobile Bid Adjustment

Before this Announcement: A mobile bid adjustment could only be set at the campaign level, which allows advertisers to boost desktop keyword bids for searches on mobile devices by -100% to 300% across the entire campaign.

The Ask from Marketers: Search marketers are used to granularity. From management to reporting to optimization, sophisticated marketers often desire to operate at the most granular levels possible, which often means making decisions down at the keyword level. The reason is that clicks, cost, conversions, and revenue data are all attributed at the keyword level; and in order to optimize bids and maximize performance, keyword-level bids needed to be calculated and applied individually.

The Updated Approach: Google will now allow advertisers to set a mobile bid adjustment at the ad group level. Once implemented, the same boost range, from -100% to 300%, can be applied to all desktop keyword bids within a given ad group for searches made on mobile devices. The campaign level mobile bid adjustment will be ignored if an ad group level bid adjustment has been set.

What It Means: The enhancement to allow group-level mobile bid adjustments provides search marketers with additional control over their enhanced campaigns and mobile performance. For advertisers that follow account best practices, where ad groups contain a small set of like or similar performing keywords, this enhancement should meet the requirements for most paid search programs. Although some search marketers may long for keyword-level mobile bid adjustments, keep in mind that the goal of enhanced campaigns is to simplify the way advertisers manage their paid search campaigns across device, location, and time of day. Group-level adjustments appear to be a reasonable and effective compromise.

{ifmobile} and {ifnotmobile} ValueTrack Parameter

Before this Announcement: Search marketers could only leverage one landing page across all devices rather than have the ability to direct users to optimized landing pages based on device. The other option was to remove keyword level destination URLs in favor of creative level URLs.

The Ask from Marketers: Screen sizes and user behavior varies significantly between desktop and mobile devices. Presenting users with a device-specific landing page is critical to improving the user experience and maximizing paid search performance. Consequently, advertisers wanted the ability to define two destination URLs at the keyword level in order to present the most relevant content and optimal experience based on the device the user is searching on.

The Updated Approach: The {ifmobile} and {ifnotmobile} ValueTrack parameters will enable search marketers to direct users to device-specific landing pages at the keyword level. Additionally, these new parameters enable the measurement of the effectiveness of campaigns by device for advertisers who are unable to leverage the {device} ValueTrack parameter.

What It Means: The ability to assign a device-specific landing page falls directly in line with Google’s approach to a multi-device world—helping advertisers reach consumers with the right ad experience based on device, location, and time of day. As users move across device, this enhancement will enable search marketers to remain relevant and engaging.

Google Is Listening

Clearly, Google is open to enhancing enhanced campaigns based on industry feedback. However, I wouldn’t expect any further changes to be announced ahead of the migration deadline as advertisers nail down their migration plans and establish revised best practices before heading into the holiday season. In order for enhanced campaigns to be a win-win-win solution (for Google, the consumer, and the advertiser), Google will need to continue collecting and applying market feedback, especially once all advertisers have migrated over to enhanced campaigns.

The Truth about Real-Time Bidding in Paid Search

By Rebecca Momberg April 1st, 2013

Calculating and pushing keyword bids in real time is one of the most talked about paid search bidding strategies. However, this approach is easier said than done. Accounting for consumer behavior and collecting enough performance data minute-to-minute or hour-to-hour is difficult and often results in sub-optimal bids. Today we’ll discuss the challenges that online marketers face when attempting to calculate bids in real time and the requirements that need to be in place to execute a successful bidding strategy.

Consumer Behavior

Consumers often click on multiple ads before converting. In many cases, they conduct research using several different search queries over the course of days, weeks, or in some cases months. Often times a consumer will validate their decision with one final burst of research just before converting. This delay between the initial ad click and subsequent conversion is known as conversion latency. To measure this latency, advertisers rely on tracking solutions that identify each unique user and follows them through the conversion process. The conversion and any associated revenue can then be attributed across each touch point; for example, the three paid search clicks that occurred prior to a purchase. Achieving this level of visibility enables automated bidding solutions to calculate accurate and optimal bids for all keywords that contributed to the conversion.

Display Retargeting vs. Search

Real-time bidding was born in the world of display retargeting, where advertisers bid to deliver ads to specific users based on information collected about them, such as which products or pages they’ve previously viewed on a company’s website. In this scenario, an automated bid, calculated and pushed out in real time, enables advertisers to target their spend and impressions towards consumers who are more likely to convert. The likelihood of a conversion is estimated using large datasets; the behavior of thousands, if not hundreds of thousands of visitors to a website is analyzed before implementing an optimal bidding strategy. This is a fundamental difference when approaching real-time bidding in display versus search, where the amount of data collected for display retargeting is significant enough to inform bidding decisions in real time.

Real-Time Bidding in Paid Search

In paid search, the data collected for a keyword in real time is minimal. Calculating keyword bids based on such a small dataset is extremely risky as these bids often leverage an insignificant amount of data that doesn’t account for consumer behavior.

To address this challenge, Marin developed a patented bidding algorithm that utilizes Bayesian Estimation to minimize the risk of bidding on low volume keywords. Additionally, to account for consumer behavior, Marin allows online marketers to exclude performance data from bid calculations across a custom rolling date range. For businesses that experience high conversion latency or a large proportion of latent conversions, this means optimal bids based on accurate and complete performance data. Finally, Marin analyzes time of day paid search performance across multiple weeks in order to identify significant trends. These trends are used to inform daily and hourly dayparting recommendations, which can be implemented with just a few clicks.

Execute a Sound Strategy

When making bidding decisions, online marketers must ensure that they have a complete picture of performance. For paid search campaigns that are subject to conversion latency, this means sacrificing real-time bids in favor of implementing rolling date exclusions across a significant amount of performance data. Search marketers that execute their bidding strategy with this in mind are positioned to calculated optimal bids that maximize keyword performance.

For more information on Marin’s bidding solution, please contact info@marinsoftware.com.

Marin’s Enhanced Bidding Capabilities Maximize Revenue Outcomes

By Jason Young November 5th, 2012

As online advertising budgets rise, marketers find it increasingly difficult to calculate bids across large-scale campaigns, account for conflicting business goals, and respond to seasonal and market shifts. To address these, Marin has made some significant enhancements to our patented bidding technology.

Through advanced execution techniques that include predictive analytics, KPI maximization subject to constraints, and adaptive learning methods, advertisers and agencies alike can now realize even more significant financial lift via Marin bid optimization. Specifically, our enhanced bid optimization capabilities enable marketers to maximize revenue outcomes such as clicks, revenues or profit while accounting for multiple business constraints such as spend targets and performance.

By design, Marin bidding preserves visibility and control for the marketer. Advertisers are able to define their own portfolios, set business goals and constraints, and build a forecast of bid outcomes. Using an interactive interface, marketers can now perform a “what-if” analysis to understand trade-offs between volume, cost, and profit associated with varying bid scenarios.

The enhancements to Marin bidding are available immediately for all Marin Enterprise users, enabling online marketers to maximize financial lift. Initial results have been very promising: 77% of users who have deployed the solution have seen financial lift above and beyond their previous results, with an average lift (measured by increase in clicks, conversions, revenue or profit) of 20% or more. As an example, Symantec, one of the world’s largest software companies, keys on revenue maximization and utilized Marin’s new bidding enhancements to increase ROAS by 67%.

Adjusting Bids for Seasonality [Video]

By Sam Wilcke June 11th, 2012

If your paid search program experiences an increase in volume over a seasonal period, how much should you increase your bids by to maximize performance? Sam Wilcke, PhD and Director of Analytics at Marin, talks through how to do this and dispels a common misconception.

2 Ways to Decrease Your First Page Minimum Bid

By Kye Mou June 6th, 2012

If you’ve ever browsed through your AdWords account, you’ve most likely encountered Google’s pesky keyword status, “Below first page bid”. This estimate is based on your keyword’s Quality Score and competition, and is the bid you’ll likely need to set in order for your creative to show on the first page of search results. Though these keywords are active, they’re most likely missing out on a large chunk of impressions, and potential clicks and conversions. Since this first page bid is directly linked to Quality Score, marketers that regularly experience high first page bid estimates will likely benefit from improvements to their keyword’s Quality Score. Today we’ll review two strategies for decreasing your first page minimum bid.

     AdWords

     Marin Enterprise

When adding a new keyword, you’ll notice that Google automatically assigns an initial Quality Score. Whether that score is high or low, it’s determined by the keyword’s historical performance for other advertisers who have targeted that same keyword. As a result of this assigned Quality Score, your initial keyword bid might be below the first page bid estimate. As a best practice, be sure to check the status of all your newly added keywords and ensure that you’ve set appropriate bids that are above the first page minimum. It’s critical that marketers do this, since a keyword’s initial performance will dictate whether or not its Quality Scores move above or below the assigned score. Give your keyword bids an initial boost to help facilitate a higher ad position. A higher ad position promotes a higher click-through-rate (CTR), which remains one of the most significant factors in improving Quality Score. Once your keywords have established their own Quality Score, hopefully better than what was inherited, reassess your bids. With higher Quality Scores, your first page bid estimates will have dropped, allowing you to bid less for the same ad position.

For keywords that have an established Quality Score, decreasing the first page minimum bid can be a long and difficult task. In addition to setting an appropriate bid above the first page minimum, marketers must take the necessary steps to increase keyword relevance to promote higher CTRs. Create an organized campaign structure that promotes granular groups containing a highly focused set of keywords. In addition, generate relevant and engaging creative to support your keyword set. Finally, assign appropriate landing pages that focus on providing the best customer experience. These tried and true best practices not only ensure that relevancy is maintained from impression to conversion, but will result in Quality Score improvements and decreases to first page minimum bids.

For additional best practices on improving Quality Score, click here.

Stop Paying for Unwanted Clicks with Our Negative Keyword Strategies

By Matt Lawson February 22nd, 2012

Whether you’re just starting out in paid search or have fully built out search campaigns, in order to be successful, you’ll want to know how to implement negative-keywords within your campaigns. Why? Actively managing negatives is possibly the single most impactful tool marketers have to increase revenues and lower costs. The virtuous circle of lowering costs while simultaneously increasing quality and position results in a win-win for the advertiser: increased revenue and ROI. Given the benefits, negative keywords should always be a top consideration for advertisers looking to optimize paid search.

In a recent white paper, Marin Software reviews the benefits of successful negatives strategies and presents a variety of best practices for deploying and managing negatives. Some of these best practices include:

• Strategies for Identifying Negatives: Where does one start when identifying negative keywords? Learn 5 tactics for sourcing negatives, as well as tips and tricks for implementing these methods efficiently.
• Using Negatives to Shape Traffic: One of the most common methods for shaping traffic with negatives is by creating match-type silos. Discover how match-type silos force search engines to trigger the correct keyword-match-type combination for each query and how to implement them in your campaigns.
• Negative-Keyword Strategies for Yahoo! & Bing: Marketers should not assume that negatives in adCenter act the same way as negatives in AdWords. Find out the important differences in the treatment of negatives between the two search engines.

Gain a complete understanding of how to leverage negatives to maximize revenue and performance for online advertising programs. More importantly, become equipped with the techniques necessary to make a strategic implementation of negatives a reality.

Download the free white paper here.

And, join our free webcast on Thursday, March 15 at 10am PST (1pm EST).

Cascade Bidding For Bing’s Match Types

By Mickey Nguyen December 7th, 2011

It is widely known that in Bing, the three separate match types are in fact the same entity, forcing advertisers to use the {matchtype} parameter to properly track. What causes confusion is the fact that Bing recommends something called ‘cascade bidding’ which allows users to analyze performance more easily and prevents the wrongful inheriting of bids across match types.

In Bing, match types can inherit the less specific match type bid. It is not uncommon for a user to set a bid for broad match, failing to set an explicit bid for the phrase and exact, thus causing all match types to have the same exact bid. For example, if an advertiser is bidding on the keyword “shoe” with a $1 bid on broad match and a bid isn’t specified for phrase and exact match types, they will both inherit the broad match bid. This results in Bing serving phrase and exact match queries as if they had been bid at $1 as well.

How do we get around this?

Bing recommends setting an implicit bid on all match types. The chart below will provide an example of AdCenter’s recommendation for dealing with this Bing intricacy. You’ll see that in the broad group, the other two match types are set to the group level minimum bid. The phrase will have exact bid set to $0.5 and so on.

Since AdCenter does not allow advertisers to pause just one instance of the keyword in a group, advertisers will need to implement this solution. If all keywords resided in the same ad group, pausing one match type will cause the others to follow suit. Due to this behavior, Bing recommends the above: cascade bidding.

Cascade bidding is particularly useful for advertisers who do not have the luxury of tracking dynamic parameters like {matchtype} mentioned above. Even without tracking the dynamic parameter, advertisers can now report more accurately on keyword performance.

This Year, Holiday Advertisers Got a Deal on Black Friday and Cyber Monday

By Matt Lawson November 30th, 2011

In the wake of another historical early holiday shopping weekend, we thought it interesting to take a look at how search marketers faired from Thanksgiving through Cyber Monday. Here’s what we found compared to 2010:

• 30% increase in paid search impressions
• 118% increase in paid search clicks
• 44% increase in paid search spend
• 68% increase in click-through rate (CTR)
• 34% decrease in cost-per-click (CPC)

So what’s it all mean?  The dramatic increase in clicks and click-through rate compared to the more moderate increases in impressions suggest a significant change in consumer behavior.  Either advertisers have managed to make their ads more relevant and appealing, or the search engines have come a long way in improving their matching algorithms.  Most likely, it’s a little bit of both.

In our Q3 benchmarking report, we detailed a trend of rising click-through rates for large-scale advertisers over the past couple of quarters.  This shift has occurred in large part as advertisers expand their use of phrase and exact match keywords – improving relevance and click-through.  This shift in match types would also explain why click volumes rose faster than spend, resulting in lower costs-per-click for search marketers.  If that trend continues throughout the remainder of the season, it will be a happy holiday indeed for advertisers and shoppers alike!

Clients running on Marin outperforming the typical Google advertiser

By Gagan Kanwar October 17th, 2011

Just last week, Google released their third quarter earnings. With almost $10 Billion in revenue for the quarter, the search giant continues to show strong and consistent top line growth. In their earnings report, Google noted a 5% increase in the average cost per click (CPC) on a year over year (YOY) basis.

In contrast, the typical Marin user running a Google paid search campaign during this time saw an 18% decline in CPC, coupled with higher click through rates (CTR). This combination of decreasing CPCs and increasing CTR resulted in a higher return on ad spend (ROAS) for Marin users. Assuming no changes in other factors, the following chart shows how reducing the CPC leads to a direct increase in the ROAS.

As ROAS is also affected by ad position and Quality Score, we normalized for the influence of these two factors by looking at CTR trends. The chart below shows how CTR actually increased across our user base during this time, implying that Quality Score and ad position did not have an adverse impact on ROAS.

While this trend doesn’t apply to every client, our data suggests that the average Marin user may have outperformed the average AdWords user. So, how did this happen?

We think that these performance gains can be attributed to the following three factors:

1)      Improved Keyword Matching – Marin users leveraged match types more effectively. More clicks were observed coming from exact and phrase match terms, which led to higher CTRs and lower average CPCs.

2)      Bidding Efficiencies – Marin’s bidding algorithm automates keyword bids based on user defined business goals (such as ROAS), leading to more efficient capital allocation across the keyword portfolio.

3)      Cross-Channel Visibility – Many conversions happen offline or in a call center. Because Marin incorporates conversion data from online and offline channels, users have complete visibility into their paid search performance and can make smarter, informed decisions about where and how they spend precious ad dollars.

Download the complete quarterly report behind this blog post and learn about the latest trends across verticals, devices and search engines.

(Note: You will be asked to fill out a short registration form to gain access to the full report)