In the old days of advertising, the name of the game was reach and frequency. Brands preferred mass media vehicles like television and radio, because they were the easiest means to reach large audiences and build brand awareness. Obviously, this meant the most effective advertising campaigns were dominated by the biggest brands with the largest marketing budgets.
If you’ve been reading our blog then you don’t need to be sold on the ways retargeting can help your business. However, putting everything together – building audiences, managing campaigns, optimizing performance, etc. – can sometimes feel overwhelming. This is especially true when retargeting is just one of the many marketing strategies that you focus on.
To help you out, we’ve teamed up with HubSpot, the world’s leading inbound and sales marketing platform, to bring you a free eBook, titled The Beginner’s Guide to Retargeting. In addition to providing context on the types of retargeting and the different ways it can help your business, we’ve collected some of our favorite tips and best practices for getting started, running your campaigns, creating good ads, and measuring and optimizing your performance.
Download the free eBook now and start learning how to use retargeting to increase leads and traffic today.
This is a guest post from Dionte Pounds, Account Manager at
Businesses kick their marketing efforts into high gear during the holiday season – which is technically from Thanksgiving until the New Year, even though I’ve seen people hanging Christmas lights from their windows before others start carving pumpkins. Many times, businesses depend on strong sales during the holidays to take them from the red to the black. As such, there’s extra pressure on the online marketer with e-commerce clients to drive the strongest performances of the year during this time.
Without strategic planning and execution, delivering on these expectations can be next to impossible. But by following these five outlined tips, you’ll be primed for success.
This should be a no-brainer. Use the performance history of the account as well as current trends to determine what a realistic budget for the holiday season should be. Work with your client to come up with a total budget and stick to that number. If you think the budget will be insufficient, try to create a plan to move spend from one or more low-performing campaigns into a high-performing campaign.
Imagine it’s January 2016 and you’re looking back at Q4. How will you determine success? Of course it’s important to hit established goals, but if there’s an opportunity to make a push for greater revenue and sales, would a possible increase in CPA be acceptable? Speak with your client before the season kicks off to figure out where you can be most flexible and what targets can’t be sacrificed.
Way in advance. Seriously.
The fewer last-minute adjustments that need to be made to accommodate promotional messaging in search ads, sitelinks, or Merchant Center Promotions, the better. Request a promotional calendar from your clients. Review all promotion details about a week or so in advance with your client if possible, just to iron out the details. When it comes to launching promotional creatives, use automated rules whenever possible to schedule future actions and remove any chance for human error.
Because the last thing you want to see before the start of a big seasonal push is a high percentage of disapproved Shopping products, do a quick review of your Merchant Center account and make sure all feeds are in excellent condition. Review your feed schedule. And, make sure your Shopping campaigns are structured in a way that makes sense for your business.
Remember: An item placed in the High, Medium, and Low Priority campaigns will automatically revert to the bid set at the High Priority Level. This is true regardless of whether the bids set in the Medium or Low Priority campaigns are higher.
Auction Insights won’t tell you how much a competitor may be bidding for a select term. But frequently examining Auction Insights will tell you if any competitors are creeping up on you (or beating you) in Google’s auctions. One of the more overlooked features is being able to segment Auction Insights by device type. This provides a useful look at who the key players are in your auctions and where you could be getting the most pressure – on desktop, mobile devices, or tablets.
Because this can’t hurt and you may come away with some real learnings to report to your client, try adding in new targeting criteria, such as average household income, to your campaigns with no set bid adjustment before the holiday season kicks off. As time progresses, periodically check in on these new targets and see how they perform. At worst, you’ll have no real actionable data and can simply remove the new targets if performance merits. But at best, you’ll have a better understanding of a new target audience and the ability to increase or decrease marketing efforts to that audience by applying bid modifiers.
Programmatic is hot right now. eMarketer predicts that by 2016, programmatic spending will top $20 billion, making up 63% of all US display ad spending. As quickly as it’s growing, though, programmatic has some serious terminology and conventions you have to learn if you want to consider yourself an expert. And once you get started, you may feel like you’re drowning in a sea of programmatic jargon, lingo, and acronyms.
The programmatic ecosystem is large and wide – but not impassable. A good way to start the journey is getting to know the 8 major players in the ecosystem, as well as their main functions.
1. The Advertiser
If you’re reading this, this is probably you. The advertising world wouldn’t exist without the companies that buy the ads.
2. The Publisher
Publishers are all the publications, web sites, and mobile apps that create and deliver the real value – the content – as well as the ad space that advertisers buy.
3. Ad Exchanges
Ad exchanges are the backbone of programmatic ad buying, and a major driving force for the display advertising renaissance over the past few years. Ad exchanges are essentially marketplaces where advertisers and publishers buy and sell ad space programmatically. Publishers make their inventory available and advertisers then bid for those ads, often in real-time, based on how much a particular visitor is worth to them.
4. Ad Networks
Ad networks are like the older, less capable big brother of the ad exchange. Like ad exchanges, ad networks aggregate inventory across multiple publishers and package it up, helping advertisers buy ads at scale more efficiently. Because they can still be a simple, efficient way to scale your media buy across a large number of publishers, they’re still relevant in this age of programmatic. Still, ad networks don’t offer the same targeting sophistication that ad exchanges do.
5. Data Management Platforms (DMPs)
Advertisers use DMPs to collect, store, and leverage their first-party audience data. DMPs also aggregate data from third parties and make it available to clients to use in their advertising.
6. Demand-Side Platforms (DSPs)
A demand-side platform is a tool that enables marketers to bid on and buy ads from ad exchanges. There are some big differences between the different platforms out there, so be sure to determine what’s most important to your business before investing in one – for example, access to data, quality of reach, transparency, etc.
7. Supply-Side Platforms (SSPs)
Advertisers use DSPs to buy ads on ad exchanges. Publishers use SSPs to sell their ads on ad exchanges. It’s basically the mirror opposite.
8. Agency Trading Desk
Agency Trading Desks (ATDs) are essentially the media buying and reselling arms of major advertising agency holding companies like WPP, Publicis, and Interpublic. ATDs reflect a mix of people and technology. While media is often bought programmatically using technology like DSPs and DMPs, it’s then resold to advertisers as a managed service.
These eight players are just one piece of the programmatic puzzle. For a more complete discussion – including how data, targeting, and retargeting figure in – download our full white paper, The ABCs of Programmatic.
Let’s suppose you’re a B2B marketer using the Marin platform. Hopefully, you’re using the more sophisticated “Revenue by Conversion Type” revenue model, and you’ve associated relative values to each conversion type in your website. If you’ve done all this…congrats! You can use Marin to bid to a lifetime value/cost ratio that’s most appropriate to your business.
However, by refining your strategies even more, you can increase the likelihood of boosting your lead generation.
During my first Marin onboarding, I received some pretty sage advice. My Marin rep told me I should allocate a small portion (10%, he told me) of the lifetime value from each conversion to a point earlier in the funnel. This serves as a vehicle for increasing relevant traffic diversity, which ultimately leads to more sales. If I were to assign 100% of lifetime value only to terms that converted at the bottom of the funnel, I would hinder my ability to grow the account.
What’s a good lifetime value reallocation strategy? It’s easy! Are there intermediary downloads on your site that lead people down the conversion funnel? Create a conversion type for each and assign each a value. Are there high-intent pages on your website that represent the penultimate step before conversion? Create a conversion type and assign people who land on that page some lifetime value. Are you doing email marketing with unique click-through pages? Create a conversion type for people who click on the email link and land on the site, and assign those folks a value. There are plenty more ways you can get creative with micro-conversions.
With a multi-layered micro-conversion strategy, it’s easy to either over-assign or under-assign value. You should have an understanding of how many micro-conversions each visitor typically completes, and set your values so that the “average” visitor will get assigned an “average” pre-sale value. Engaged visitors who trigger an above-average number of micro-conversions should be more likely to convert; by counting each, Marin’s bidding algorithm will favor the keywords that tend to generate hyper-engaged visitors.
Also, you can use micro-conversions as a traffic lever. If you decide a certain download has become a more valuable part of the sales process, raise its value. Marin will favor traffic more likely to download that item, and you’ll generate more downloads of that document. Whereas Marin’s Boost function will raise the bids allocated to an entire bidding folder, raising the bids on a conversion type is a hyper-specific way to impact your entire traffic flow – either within one bidding folder or throughout the whole campaign.
Marin is a wonderful platform to increase the value of your paid search efforts. And, with a little extra insight into the value of each step of your sales funnel, you can use Marin’s functionality to optimize your campaign’s performance to an even higher level.
While algorithmic bidding certainly helps advertisers meet their goals for individual keywords, it may not necessarily result in maximizing profit for the overall collection of keywords. In order to achieve maximum profit, advertisers should consider utilizing a volume-based optimization strategy that has all keywords working together. What this means is that rather than managing keywords individually, volume-based optimization has all a marketer’s keywords working together. This way, instead of depending on one keyword to help a marketer reach their ROI target, all the keywords in a set are working together to reach that target. The volume-based optimization approach is particularly geared toward driving gross profit. When there is an extra dollar to spend, volume-based optimization will determine which keyword(s) will provide the highest revenue in return.
Volume-based optimization is most effective when applied to the head terms of a given set of keywords. The large amount of historical data associated with head terms means that volume-based optimization can more accurately assess how much to invest in each keyword.
Here are some best practices for utilizing volume-based bidding strategies:
While head terms are generally more visible, tail terms make up the majority of searches. Unfortunately, tail terms generally don’t have much historical data available. To overcome this obstacle, leverage Bayesian Estimation to predict performance and estimate bids for tail terms. In combination with volume-based optimization, this is the most comprehensive and insight-driven approach for maximizing overall profit.
Unexpected factors, such as website downtime, can have a huge impact on performance. Utilize a bidding tool that allows you to exclude any outliers from the historical data used to calculate bids, such as Marin’s excluded dates feature.
Bidding tools can also be helpful when it comes to planning for seasonality, including sales and promotions. Using a feature like Marin’s Dynamic Actions, advertisers can automatically apply a percentage boost to any campaigns or groups that fit their pre-designated criteria. This automated handling of user-specified criteria ensures that advertisers never miss a chance to increase visibility during crucial seasonal events.
Knowledge is power, and the old adage is especially true when it comes to bid management. Using sophisticated tools, advertisers can harness the power of their data warehouses and third-party data feeds to build flexible rules that adjust bids based on trends in contextual data. For example, an advertiser using Marin could bring inventory data into the platform and use it to automatically boost bids for keywords with high inventory. Other use cases include setting bid overrides, bid caps, and bid floors based on fluctuations in the data. By leveraging external and contextual data, it is possible to make smarter and more informed bids.
In addition to these foundational elements of bid management and optimization, advertisers should also consider a host of newer factors. In particular, budget forecasting, audiences, and mobile have become critical components of successful search advertising programs. To learn more, check out our latest white paper, Bidding and Optimization Strategies for the Modern Search Marketer.
Additional thoughts? Leave them in the comments section below.
You put a lot of time and effort into your Paid Search advertising. You leverage Marin’s bidding algorithm to efficiently and effectively automate your bidding process based on individual ROI/CPA goals.
Your competition probably follows a similar process. So how is it that your competitor keeps showing in the first spot, even when you try to loosen the reins on your ROI/CPA targets? You enviously theorize about their amazing site conversion rates or a giant SEM budget that permits them to outbid anyone just for the sake of being number one.
In all likelihood, their reasoning is probably more scientific than you think; it’s just a different science than you are used to.
Let’s consider two competing advertisers with identical site conversion rates and AOV, both selling and bidding on the term “Acme Widgets.” Advertiser 1 is on an ROI-based model and will value that click based on what they expect to make from any orders that occurred that day. Advertiser 2 knows that on average, when a customer makes a purchase of Acme Widgets, the value extends much further. They get looped into the CRM system, email, SMS, and direct mail cycles, and tend to stay with them for about 3 years, placing several orders per year throughout that time.
Who do you think will be willing to pay more for that bid, and will constantly win the auction for that top position?
The majority of digital advertisers’ budgets fall into two categories:
When asked what the main goal of their digital marketing program is, however, a common response from the executive team is “grow the business” and/or “acquire new customers.” Deep down inside, they know that there is value that extends beyond that initial purchase, but can’t wrap their heads around the short-term cost vs. the long-term gain.
This creates a challenge for marketers who try to manage to a fixed ROI. When they optimize for growth and new customers, the CPA rises. When they optimize for ROI, the growth stops. This results in targets that are constantly moving back and forth.
To truly compete and acquire new customers in the digital landscape requires a mindset that values the entire customer lifecycle and stresses growth and profit over all else.
It seems obvious, but most advertisers are not thinking like this. The truth is that it is difficult to change models that have been in place for a long time and require sign-off from several stakeholders.
Understanding the lifetime value of a customer will significantly shift how you view digital media investment and should become an element of your measurement and optimization. You can streamline this process by leveraging Marin’s Custom Column feature to bring LTV calculations into your dashboards or bidding logic. If you aren’t sure how to get started, an excellent 4-part series recently wrapped up with a wealth of information on building LTV models.
Next, once you find a CPA that works better to maximize your customer growth and profits, don’t hold all digital marketing channels to that same CPA. Tactics work very differently, but work well together to help your reach your overall growth goals.
Finally, give it time – You already know that it takes a long time for a customer’s value to build within its lifecycle, so give your new model time to grow, too. You can still monitor daily or weekly like you’re used to, but don’t panic when efficiency suffers initially, because it will. Test often, but adopt a monthly or even quarterly mindset when it comes to significant trimming and optimizations. Without growth there would be nothing to trim at all.
Dane Manning is a Paid Media Manager at Rosetta, a full-service customer engagement agency. He joined Rosetta in 2008, and has successfully led the digital marketing strategy (paid search, online display, paid social) for his clients across the B2B, Retail, and Financial Services verticals. Dane graduated from Cleveland State University with a BBA in Marketing.
Bidding can be one of the most challenging aspects of Facebook advertising. However, by making good use of proper testing and tracking methods, it doesn’t have to be. Marin Software’s new white paper provides a breakdown of Facebook’s bidding models and offers advanced tactics to make your campaigns a success.
Advertisers can buy Facebook ads on a CPM, CPC, or “OCPM” model. The majority of advertisers opt for a CPC model, taking advantage of the opportunity to pay only for clicks, rather than impressions. Under this model, Facebook provides a suggested bid range. If your bids are too low, you may not achieve optimal audience reach. If your bids are too high, you’ll likely end up eating away at your ROI. As a best practice, pick a mid-point in the recommended bid range and adjust from there based on performance.
When it comes to bidding, automated solutions put sophisticated advertisers at a significant advantage. Third-party bidding solutions enable marketers to create custom groups of ads based on business goals, then algorithmically leverage data from other ads to calculate optimal bids that maximize performance. Automated solutions also excel for tracking purposes. The ability to weight on- and off-Facebook conversions independently enables you to use more of your budget to drive higher-value clicks.
Top Industry Tips:
Final Thoughts: As we wrap up our series on Facebook tips and best practices, here are a few key takeaways to keep in mind. First, don’t be afraid to experiment with new targeting options and ad formats. Second, remember that Facebook advertising is often about measuring long-term engagement rather than short-term sales. And finally, consider Facebook alongside the rest of your online and offline activity for a complete picture of ROI.
For additional best practices, download our full Facebook white paper, “The Marketers’ Guide to Driving ROI from Facebook Advertising”.
Do you find yourself wishing there were more hours in the day? Are you faced with a neverending to-do list? Then take five minutes out of your hectic day to read our latest blog post which highlights 5 ways Marin can help you streamline your day.
Web Query Reports
Wouldn’t it be great if you could wave a magic wand and your Excel report completed itself? Well, waving a magic wand is optional but with Marin’s Web Query reporting you can embed a link in Excel which will automatically pull in the latest data from your Marin account and update any graphs or charts you have built in Excel!
Average time saved per week – 4 hours
Manually calculating keyword bids, even with the help of Excel, can take hours and many marketers find themselves calculating bids once or twice a week because they simply don’t have time to do it daily. However, because the search auction is so dynamic, if bids are not being calculated daily then you’re not maximizing revenue. Other keywords you may run on a position target strategy which, again, requires bids be calculated daily in order to maximize revenue and avoid unnecessary spend. Marin caters to all bid strategies and calculates bids daily using only the most recent, most relevant data to give you the confidence to put your mind to more strategic tasks.
Average time saved per week – 10 hours
Many marketers we talk to say that adding to their keyword (and negative keywords) lists is something that regularly gets dropped from their things-to-do list due to more pressing tasks like reporting and bid optimisation. However, expanding your keyword (and negative keyword) lists to ensure maximum exact match coverage can significantly reduce CPCs as you no longer have to rely on more expensive broad match terms. With reduced cost comes increased ROI, and who doesn’t want that? Marin will automatically add new keywords (and negatives) to your account based on the number of clicks and conversions they have generated (or not generated when it comes to negative keywords).
Average time saved per week – 3 hours
Marketers often struggle to identify and prioritize the most impactful activities that will provide incremental performance improvements for their online marketing programs. Marin Next is an intelligent recommendation engine that leverages Marin’s proprietary optimization methodology—based on experience with hundreds of leading brands—to uncover new revenue opportunities and help marketers address them with best practice workflows. Average time saved per week – 8 hours Saved Views You want to pause under-performing keywords, but they come in several flavours – how do you find the time to run all the data analysis required to find them all? Simple, Marin’s saved views allow you to apply the filters you want to your data and save the view; you can even share the view with other users. Then each day you just login and select your views, Marin does all the hard work for you, all you have to do is take action, which you do on the same screen. It doesn’t get much simpler than that!
Average time saved per week – 5 hours
You want to pause under-performing keywords, but they come in several flavours – how do you find the time to run all the data analysis required to find them all? Simple, Marin’s saved views allow you to apply the filters you want to your data and save the view; you can even share the view with other users. Then each day you just login and select your views, Marin does all the hard work for you, all you have to do is take action, which you do on the same screen. It doesn’t get much simpler than that!
Average time saved per week – 5 hours
We think that’s pretty impressive and hope you do too! Let us know what you do with the extra 30 hours a week.
In a previous post, we explored the effects of seasonality and cyclical trends on revenue-per-click (RPC) and conversion rate. Today, we’ll take a look at how identifying and excluding irregular or outlying data, and accounting for conversion latency, are critical to calculating optimal bids and maintaining control over revenue outcomes.
Seasonality and Outlying Performance
During the holiday shopping season, RPC and conversion rates can double in the months leading up to mid-December, and drop dramatically thereafter. Leveraging data during these periods of irregular paid search performance can result in suboptimal bid calculations. In order to factor these types of performance shifts into their bidding strategy, search marketers must first identify outlying and irregular data and subsequently exclude those dates or date ranges from bid calculations. Using advanced filters and alerts, search marketers can manage their data by exception and quickly identify the extent to which seasonality or cyclical behavior has impacted paid search performance.
For example, you might create an alert to notify you when RPC or conversion rate has increased by more than 50% of the average over the last three days. It’s possible that a new promotion or period of seasonality is causing a significant shift in performance. Excluding dates with outlying RPC or conversion rates will prevent calculations from inflating bids even as performance returns to normal.
Looking past seasonality and cyclical trends, date exclusions are also critical in accounting for conversion latency—the time between an initial ad click and an eventual conversion or revenue. Conversion latency varies across industries and product lines, ranging from same session to several months. For certain businesses with high consideration products or services, conversions and revenue can go unattributed to click and cost data for extended periods of time. As a result, bid calculations that leverage these periods of incomplete data fail to maximize performance. To address conversion latency, search marketers need the ability to exclude the most recent days from bid calculations.
For instance, if it typically takes two days for a customer to complete a purchase after clicking on a paid search ad, a sound bidding strategy would exclude the last two days from bid calculations. This would ensure that bids aren’t being calculated using click and cost data that would otherwise have revenue attributed to it after two days. Dynamically extending or shortening a rolling exclusion window (in the example above, it would be a two day rolling date exclusion), depending on business needs, enables search marketers to calculate optimal bids based on a complete picture of paid search performance.
Informed vs. Reactive Bidding
For some businesses, high conversion latency can often warrant leveraging a lengthy rolling date exclusion. However, to remain competitive and respond quickly to shifts in the bidding landscape, carefully consider how long of an exclusion window is used. For example, let’s pretend that a business needs to wait sixty days until 98% of their revenue is attributed back to their paid search clicks. With a sixty day rolling date exclusion, it would require them to wait nearly two months before making informed bid calculations. Due to this length of time, they would undoubtedly fail to capitalize on immediate revenue opportunities. On the other hand, let’s assume that the same business can attribute 80% of their revenue after seven days. Using a seven day rolling date exclusion, they could still calculate informed bids while remaining reactive to the current bidding landscape.
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, 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 time, we’ll take a closer look at addressing conversion latency and the importance of excluding abnormal search data from bid calculations.