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Leaders in the ad tech space are constantly searching for a win-win-win innovation—something that’s great for clients, employers, and employees alike. Many tech companies turn to their engineers to make these wide-scale improvements. However, data shows that innovating within a company’s employee benefits package is an easy way to bring large-scale, positive change to an organization and its stakeholders.
According to Forbes, the workplace policy employees value above all else is paid family leave. Employees want the option to start a family more than student loan reimbursement, paid time off, or lunch stipends.
Centro agency lead and new Mom, Kristina Boyer, exemplifies the talent a great parental leave policy can attract. When asked whether Centro’s 16-week paid leave policy contributed to her decision to work here, Kristina stated, “It actually very much did. Knowing that Centro has such an amazing maternity leave policy was a big reason why I came, because it fit into the larger family plan that we had.”
Once she got to experience maternal leave at Centro, Kristina reported, “The fourth month was hands-down the most enjoyable, and the most relaxing—it was pretty magical.”
Not surprisingly, data shows that offering paid family leave to both women and men improves a laundry list of employer headaches, including employee retention, productivity, morale, and loyalty. If you think these issues are trivial, think again: Finding and maintaining talent was listed as one of the top challenges facing a majority of tech companies in 2019.
Even more, we’ve all heard the statistic about how millennial workers are expected to job hop up to 20 times in their career. That means that finding and maintaining talent is more expensive than ever! Turnover is estimated at 50% of salary for an entry-level position, 125% of salary for a mid-level position, and for senior executives, rates can rise upwards of 200%.
Since there isn’t a federal law in the U.S. that mandates paid leave, some companies miss out on top talent by offering little, if any, relief for parents. Kristina shared that a previous company she worked for had only offered two weeks to a Mom who requested leave.
In addition to the leave itself, Centro offers a free membership to Sittercity and counseling sessions for the transition into and out of leave. Employees interested in adoption can submit an application for adoption assistance. And, Centro offers four weeks flexible paid leave for Dads as well.
Matt Klaers, Centro’s director of financial reporting, agrees that Centro’s attitude towards new parents is extraordinary. Having returned from his leave in March of this year, he encourages all Centro Dads to take the full 4 weeks: “Having eight hours, 10 hours a day to just stare at your baby is so great. They change so fast.”
Paul Troia, Centro’s director of analytical operations, took advantage of the flexibility of Centro’s parental leave: “I really liked the ability to break [the four weeks] out into different pieces.” Paul was able to split up his four weeks of leave throughout the first year of his baby’s life, so that he could be there when it made the most sense for his family.
Of course, for some companies, it simply isn’t possible to offer this many weeks of paid leave. But leave isn't the only benefit a company can provide to show its new mothers and fathers that it has their back. For instance, Claire Keating, director of client development at Centro, emphasized the impact Centro’s Nursing Mothers Room has had on her life:
“All of my friends have asked, ‘How are you still nursing at 10 months?’ Honestly, I think it’s because of Centro. The Mothers Room is such an easy place to take a 15-minute break and pump in. Being a nursing mother, I feel so supported here at Centro.”
Ultimately, it isn’t just about the benefits package a company offers parents. Rather, it's about parents feeling supported and cared for in and out of the office. As Matt said, “Just knowing that Centro is behind you is such a stress reliever.”
Learn more about Centro’s unique culture and benefit offerings here!
Let’s cut right to the chase: there are various PPC bidding optimization techniques and practices floating around, but portfolio bidding is probably the right one to use, provided you have a large program.
I sold it to you that quickly? Terrific.
But just in case, we’ll go on...
Portfolios are groups of assets, and in search engine marketing, these assets are the keywords and “publisher objects” that you can apply bids and bid strategies to. The power of a portfolio strategy is twofold.
One, it allows similar keywords to share goals and data, and be pointed in the same general direction. Two, it executes in a way that optimizes toward (and hopefully achieves) your goal in aggregate across the group. Results are more controllable because decisions are made based on shared information within the portfolio.
But what really is portfolio bidding? And how do you start using it? We’re about to find out.
If you ask Google Support, you may read a definition for portfolio bid strategy that sounds like this: “An automated, goal-driven bid strategy that groups together multiple campaigns, ad groups, and keywords. Portfolio bid strategies automatically set bids to help you reach your performance goals.” Thanks Google!
Okay, so it’s this thing that automatically sets bids on groups of publisher objects, based on your goals…
But what is it really? How does it work? And why? Is this thing Google is talking about the same thing you’d expect for the core methodology for PPC bid optimization?
Let’s dig in a bit.
Modern Portfolio Theory was an economics concept originally introduced in 1952 and describes the technique for limiting risk and optimizing outcomes by sacrificing individual components to benefit the larger whole. It was first discussed in terms of stock market investment strategy (diversifying investments so some will win and some will lose, but the whole investment portfolio comes out on top). Presently, it helps to describe this SEM bidding optimization technique.
The solution involves bidding on a group (or portfolio) of keywords towards a target goal, while also maintaining an efficiency metric. With this methodology, the goals of the group outweigh any specific keyword-level goal: some keywords will perform worse to maintain the efficiency metric of the group, while other keywords will be bid up to drive the target goal. As a whole, the group is optimized based on the context of the entire portfolio.
The relationship between spend and return is non-linear, and that is true across keywords. Portfolio methodology models this relationship granularly at the keyword level, but adjusts for the findings collectively–across the portfolio.
So by way of example, let’s say you want your keyword group to maintain 220% ROAS while maximizing revenue. The portfolio bidding algorithms would use data from clicks and conversions to bid up the more valuable keywords that drive revenue while simultaneously bidding down other keywords to stay within the ROAS limit. The shared goals and data allows the bidding algorithms to execute towards a multi-faceted goal accurately by sharing the context of all the keywords in the group with each other.
To put it simply, one does not simply “do” portfolio bidding without utilizing an optimization tool.
As a very simple “two-keyword example”, an exercise can be run to look at the volume/efficiency curve and select the values (based on some data exports) where you’ll bid so that a target goal for efficiency is maintained while otherwise maximizing for the revenue metric… however, it’s simply too much to do manually for any real program.
Obviously, Google allows portfolio bid strategies to be applied to groups of keywords you define by using some of the goals available in Google Ads: Target CPA, Target ROAS, and Enhanced CPC, plus some others. How do you apply this to your programs? If you’re using Smart Bidding, you can effectively just follow the on-screen instructions.
But Google’s method is limited in the same way any other bidding method is limited with Google: it’s subject to the same requirements for volume and conversions; it doesn’t utilize any customer journey data outside of what Google tracks; and it’s built as a one-size-fits-all solution, to help small businesses, mid-sized spenders, and big programs all try to accomplish their individual business goals.
Any third-party PPC bid optimization tool (well, any modern one worth using) will utilize portfolio bidding in one way or another. Remember, it is a conceptual approach to solving a problem. However, there is certainly a great deal of variability between different solutions: between the best practices and most robust models, versus standard approaches.
To get started, you’ll want to ensure your conversion data is being tracked and is cleanly integrated into your optimization tool. Data integration is key to making smart decisions.
Next, you’ll determine which keywords should be grouped together in the same portfolios, or ideally utilize a tool that helps to automate this. Whether it’s a handful of keywords, ad groups, or campaigns, you select the best group of objects that share sufficiently similar attributes and goals to put under one portfolio.
Select which goals and strategy you want applied to each group and define the target metrics for each: goals for maximization, and goals for maintaining efficiency across the portfolio. However, be aware that setting goals too extreme up front can cause issues with volume or spend, and lead to disappointment.
Here’s what we see: even with the technology available to automate and optimize with something as complex as portfolio bidding, it still requires human decision-making and touchpoints to thoughtfully structure the program, define goals, and strategize.
Portfolio bidding is a technique that is here to stay. Why? First, because it is conceptual - not some specific tool. Second, it is a concept that aims at what we digital marketers are after: ensuring the aggregate performance across a group of keywords is hitting the target.
However, we must not forget that this technique, like many facets of life, fits in with that old adage from Drake’s song Preach: “Doing is one thing. Doing it right is a whole different story.”
Many PPC automation tools will use a portfolio bidding mindset to optimize SEM performance, but more is involved for great outcomes and peak performance: machine learning involved at every step; infrastructure built for accuracy and speed; data ingestion of customer journey data and other relevant context; and so on.
Influencers have become a lasting fixture of the social media marketing world—but in a loosely regulated space, marketers are wary of jumping into a pool of unknowns.
Catapulting into the spotlight in the 2010s, influencers have become a valuable component of the social media marketing world. Once a niche space targeting younger audiences, influencer marketing is now on pace to reach ad spend levels between $5 and $10 billion by 2022.
These social-first spokespeople market products and services to targeted followings that range from a few thousand to tens of millions. The potential for influencers to reach a variety of ever-expanding audiences remains strong. However, since influencer marketing is a loosely regulated space, agencies may hesitate to jump into a pool of unknowns.
To bring clarity to the haze, we chat with Dalyn Ward, the Director of Product at influencer marketing platform Popular Pays. Dalyn speaks to how marketers should be approaching the influencer space—from measurement options to bots and AI, to the infamous Fyre Festival.
In this post, we’ll be delving into why you should always be segmenting and evaluating your data as often as possible. We’ll share a few examples and common errors in the process.
Most decisions pertaining to PPC are based on data relating to different metrics. For example: if devices are showing contrasting performance, you’ll want to use Mobile and Desktop device modifiers.
Normally, you can rely on Google Enhanced bidding and Google Smart bidding to make most of these decisions, but there are many scenarios where this may not be an option for you. If you have a SEM bidding optimization tool, you can use the segmentation in your favor, but if that’s not the case, then it will always be useful to know some basic rules about how to understand your data.
With the amount of data flying around marketing campaigns in the modern age, it can be difficult to know where to start. Here are a few ideas about how to break up your data in order to be able to make sense of it. Whether you’re evaluating a significant change, troubleshooting underperforming segments, or simply doing an A/B test, be sure to keep these two frameworks in mind:
1) Always check the trend
For any performance evaluation, it’s clear that data will vary over time depending on recent changes and trends. Below we have two data sets with vastly different behavior.
First, let’s take a look at this chart. We’re plotting the profits of a campaign over time and analyzing its evolution. There appears to be a healthy growth at a steady rate over the entire 16-week period:
If we break this down into months and do a comparison of the profit realized in the first two months versus the last two, we would report that profit throughout the campaign grew 136% period over period:
Now, let’s assume this campaign had a different result. After having two solid months, the campaign started to suffer some changes. Around week 10, what seems to be a dramatic increase in profit preceded a drastic collapse:
If we evaluate the high-level picture of this data set and we repeat the same report, we will see the following comparison:
The campaign once again shows a rise in profit period over period. It further reports a 1% lift—137%—compared to the previous example.
In both cases, then, profit grew by more than 35%. The period versus period charts show identical performance. If we dive into trends and behaviors, though, we see two very different scenarios. The first showed solid and steady growth, while the second indicates that performance worsened severely and there is an underlying issue that requires immediate attention. Remember to always look at trends when assessing performance evolution.
2) Always Check the Relationship Between Metrics
There are times where you would evaluate a variable against another variable. A typical SEM case for this is plotting the relationship between volume and efficiency—for example, by comparing Revenue (in dollars) and ROAS (in percentage). These analyses are very useful when looking to verify a correlation or when we want to understand how two metrics are connected.
Below, we will plot four different data sets, each of them containing the same number of observations:
A quick scan of them reveals that these four charts have no connection at all. Data Set 1 has a simple linear relationship between metrics; Data Set 2 has a non-linear correlation between metrics; Data Set 3 is an almost perfect linear correlation; and Data Set 4 appears not to have any identifiable relationship.
These four charts probably describe four different metrics and behaviors. However, if we pull out the main KPIs for these data sets, we will always get the following for all four cases:
This example shows the importance of always looking at the data graphically before jumping into performance conclusions, metrics, and interpretations. This exercise was developed in 1973 by the statistician Francis Anscombe and is called the ‘Anscombe’s quartet’ (and yes, this could well be the name of a folk band).
Understanding your data can be challenging, and adopting the right approach to it will save you time and will help your decision-making process. We can always trust KPIs and metrics, as long as this is reinforced by a thorough process of data interpretation. Segmenting your data graphically is a key tool that will help you in the process.
How is your latest campaign doing?
Are you driving traffic to your site? Are you increasing conversions? Are your social shares increasing your presence on the web? If proper metrics aren’t established in advance, you won’t be able to answer these questions. Numbers are needed to gauge success but know that numbers alone aren’t going to tell you everything.
Establish a baseline for the metrics you’re looking to measure and interpret the analytics that represent the various elements of your campaign. There a lot of elements that can be measured—but how do you know which metrics are most important to track for your business?
Review important metric considerations for ad campaigns below:
How are you being found on the web? If you’re mindlessly putting ads out into the universe in hope of gaining clicks—chances are, you're spending too much time and effort in places that aren't driving your bottom line. Regardless of the industry—knowing how consumers are finding you will enable you to optimize your outreach and focus on the channels that are actually driving traffic.
Programmatic technology was created for this very reason; robots track consumer behavior and learn where your traffic is coming from. Basically, it allows you to monitor performance easily so you can see which channels are most productive for your messages.
Are people leaving as soon as they arrive on your site? If so, that’s probably costing customers. Your bounce rate is indicative of the percentage of people who navigate away from your site after they look at the first page on which they land. There are many things that can cause your bounce rate to hit alarming figures but knowing what's causing people to leave will give you the power to remedy the situation.
The following are a few common reasons companies experience high bounce rates:
This metric tells you how many people have actually clicked on your ads, versus the number of people it was put in front of. In an ideal world, you’re putting ads directly in front of the consumers who are most likely to be interested in your products or services. A low CTR may indicate that you're bidding on the wrong keywords, or that your messages are in the wrong places.
Page value tells you where you’re making money in terms of transactions. For example, are people purchasing your products from the homepage or via individual pages? Knowing which pages are most valuable to consumers will help engage your audiences in more meaningful ways.
At Centro, data and analytics are what we do best. If you're ready to automate and optimize your campaigns in a brand new way, let's talk! Request a demo today.
As a mom of two young kids, I am very passionate about providing them with great experiences. I take them for hikes, biking trips, long drives, multiple vacations, and, of course, to any new food joint that opens up in downtown Palo Alto or Menlo Park.
My kids, like every other kid (and many adults too!), love ice-cream. But when it comes to flavors, their choice is simple: chocolate for my boy, strawberry for my daughter and between my husband and I (occasionally we try something new) we end up with vanilla. If you look at ice cream flavors, I bet these three outperform sales of all others.
In the summer of 2017 when we were in Portland, Oregon for a vacation (yeah, weird Portland), we tried Salt and Straw and for some reason, that Ice Cream experience stuck with my kids. So when we heard that they opened up a storefront in downtown Palo Alto, we just had to go back.
So now at Salt and Straw, our new favorite flavors of ice cream are “Strawberry Tres Leches”, “Freckled Mint TCHO-colate Chip” and “Double Fold Vanilla”. Ah well, you would think we didn’t go too far from our regular, favorite flavors. That got me thinking creatively about how we manage our keywords.
If you are a performance marketer (like me) you would agree that we often pay too much attention to our set of top keywords. We are ready to bid and pay Google, Bing, and Amazon any amount to get our ads in the top positions for that keyword or set of keywords. Why? Because we spend a lot of time trying to understand the full funnel view of those keywords to know how they are converting from prospects to customers. We know that those queries/keywords, i.e. chocolate ice cream and strawberry ice cream, have topped our sales charts over and over again.
However, many marketers are still relying on the bid optimization tools that Google and Bing provide, even those with decent SEM budgets (~$50k). These publisher optimization tools and best practices like “Estimated first-page bid recommendations” and “Smart bidding” end up increasing our CPA and thinning our margins on those top keywords.
The good news, though, is that marketers have options now. This eBook - SEM Optimization Techniques: Are You Overpaying Google? - touches on how using revenue-based bidding can help us achieve our goals without overpaying for certain keywords.
We all have thousands of keywords in our SEM PPC accounts. Although these keywords are grouped together per product or common theme in each folder or campaign, many of them suffer from a “low-quality score”. Quality score is a black box and many of us have been working day and night on the prescribed recipe to get the best quality score for our top keywords. Think about it for a second! If the keyword doesn’t have an appropriate bid, it won’t appear in top searches and won’t get clicked. And if it doesn’t get clicked, Google’s algorithm will mark it as “bad quality”. It’s a chicken and an egg problem that we’re all dealing with.
The other set of keywords (a.k.a. long-tail keywords like Freckled Mint TCHO-colate Chip and Strawberry Tres Leches) are like many flavors in the ice cream shop that have not turned around (i.e. optimized) for months. They are often ignored because they don’t sell well or it takes too much time to optimize them. After all, we’re all humans and have limited time in our day to improve our SEM performance. But we often ignore the fact that there could be a strong following of these long tail keywords, i.e. if someone searches for Freckled Mint TCHO-colate Chip, they have a strong intent to buy and eat it. You don’t want to miss this opportunity.
With developments in data science, it’s possible to work on both sets of keywords (top converting and long tail keywords) and achieve the best performance for SEM PPC campaigns.
In this eBook, we touch upon the power of machine learning algorithms and how they can empower optimal bids across your entire portfolio. The QuanticMind algorithm integrates multiple sources of data (CRM, Business Intelligence, Revenue Intelligence, Inventory, Weather, and Publisher data like keywords, clicks, impressions, audience, etc.) and churns out the best possible bid for “ALL” keywords at that point in time to achieve a goal of conversion. Kind of a no-brainer and it works.
QuanticMind’s technology was previously only made available to a handful of premium customers, until now. Since many enterprises like 1-800-Dentist, Windstar Cruises, Moz and Hot Topic have seen great success with this technology, we’re now making it available to other performance marketers too. You could save time and focus on more strategic planning rather than manually changing bids and engaging in “busy” work.
And, of course, don’t forget to visit Salt and Straw Ice cream with your entire family. Now, my monthly ritual is to try their new and seasonal flavors 🙂
Accurate attribution is likely more important for search advertising than any other marketing initiative. PPC managers target hundreds or thousands of keywords to reach their audience on search engines. Paid search attribution helps them understand the role each keyword plays in driving key performance indicators (KPIs).
Other marketing initiatives simply don’t have the same volume of attributable data points to work with. As a result, even slight changes in your paid search attribution strategy can have a huge impact on the return on investment (ROI). Industry research and the personal experiences of PPC practitioners are more than enough to prove this. Here’s an overview of the different tools and models marketers can use to maximize insights, performance, and marketing ROI from paid search attribution.
Google Ads offers several different attribution models as features advertisers can implement for conversion tracking and bidding insights. Right now, attribution modeling is available for Search Network and Shopping ads, but not Display ads. It can be used for website, Google Analytics, phone call, and import conversion actions (but not for app and in-store conversions).
Google Ads attribution models include:
Last Click - All credit for the conversion goes to the last-clicked ad and corresponding keyword.
First Click - All credit for the conversion goes to the first-clicked ad and corresponding keyword.
Linear - Distributes the credit for the conversion equally across all clicks on the path.
Time Decay - Gives more credit to the clicks that happen closer in time to the conversion.
Position-based - 40% credit to the first and last-clicked ads; 20% spread across other clicks.
Data-driven Attribution - Assigns credit for the conversion based on past data for the conversion action.
You might like to think that any attribution model you use is “data-driven.” But data-driven attribution is actually the name Google gives to a special model reserved for accounts with sufficient data. This model calculates the contribution of each keyword across your conversion path based on previous data, then distributes credit for the conversion action.
If your account has enough data, then the data-driven model is definitely the best choice for paid search attribution. It’s more likely than any other model to reflect the real value of different touchpoints in your funnel. It considers all clicks from your account (both converting and non-converting) in order to assign value to an ad or keyword.
When using Google Ads to build a paid search attribution strategy, it’s important to compare the different modeling options to determine which one is best for you. Google allows you to easily do this from your AdWords account:
1. Click the “Tools” button from the top menu
2. From the drop-down menu, click Measurement, then Search attribution
3. On the side menu of the next page, click Attribution Modeling
4. From the dropdown menu, select the dimension you want to view attribution models for
5. Then use the other dropdown menus to select which attribution models you want to see and compare
Google Ads attribution models are a great free resource you can use to build your paid search strategy, but it has some limitations compared to more advanced tools out there.
Search Ads 360 is a paid alternative to Google Ads. It has a lot of features that empower improved paid search performance and track your overall marketing efforts. Their advanced attribution models are just one of many reasons you might consider investing in it.
By default, Search Ads 360 uses a last click attribution model. You can, alternatively, import a different attribution model from Campaign Manager or Google Analytics. Search Ads 360 also offers data-driven attribution modeling that can include several different interactions. This is valuable since a great many conversions are driven by a series of clicks on display ads, paid search, shopping campaigns, generic or brand keywords, and other biddable items.
Data-driven attribution can help identify frequent conversion paths within a campaign, then compare these paths with other interaction patterns to accurately assign credit. You can also compare the difference between a model built on data-driven attribution calculations and the traditional last click model
Unlike Google Ads, Search Ads 360 can analyze clicks from a variety of channels, including:
This data integration is able to paint a more accurate picture of the path to purchase so you can successfully attribute credit to different touch points across paid search and other advertising initiatives.
If your priority is building a cross-channel attribution model, then Google Analytics 360 is a powerful option for PPC attribution. It’s designed to work together with Search Ads 360 to help you track, optimize, and automate your marketing efforts across varying channels.
Key features of Google Analytics 360 include:
You can use performance data from Analytics 360 to drive search campaigns, bid strategies, and rules in Search Ads 360. Analytics 360 gives you a full picture of marketing performance, while Search Ads 360 can help you act on these insights through automated bidding.
Investing in third party attribution technology is a good idea for businesses looking to get more accurate and nuanced results from their attribution strategy. There’s no denying that using a tool like Google Ads for cross-channel attribution could have an inherent bias issue. Marketers who have explored third party attribution tools and compared their results to Google Ads often find Google Analytics shows a larger number of conversions from Google channels than the third party tool.
Third party attribution technologies should (in theory) eliminate this bias and offer more opportunities to customize your attribution model. Some examples of notable third party attribution tools include:
Facebook Attribution is a relatively new option and not one that most paid search advertisers consider. It is, though, a compelling option because it integrates with a lot of other tools, including Google Ads, Campaign Manager, and Search Ads 360. It further assigns credit where it’s due for conversions across marketing channels:
VisualIQ is another alternative that offers multi-touch attribution across channels, collecting audience and attribute data to created customized attribution models. Professionals use it to learn which publishers, campaigns, placements, keywords and other tactics drive their KPIs.
Marketers wishing to build a strong paid search attribution strategy should consider the features of third-party tools based on their unique needs. Make sure they have the right integrations as well as sophisticated reporting needed to make bidding decisions. Understanding the role PPC plays in driving conversions only matters if you can also see which dimensions are driving performance (campaigns, ad groups, keywords, etc.).
Marketers today dedicate a great deal of time and energy to finding the most accurate PPC attribution model to understand the value of different touchpoints for driving conversions. Attribution is supposed to provide performance insights you can use to further optimize your marketing efforts. In paid search, that means adjusting investment in different keywords, ads, and ad groups based on their conversion value.
So, while it’s important to choose the perfect attribution model, it’s equally imperative to ensure that you use it quickly and efficiently to optimize your campaigns. Google Ads offers a solution for this, helping advertisers automate bidding decisions based on paid search attribution performance. But their solution comes with some inherent limitations that only advanced bid optimization technology can help with.
Unifying Data Sources
The customer journey is complex but largely trackable, thanks to the growth of MarTech. Today, there is an overwhelming amount of relevant data about audience behavior and the factors that impact their purchase decisions. Most marketers are in no position to harness it all to drive performance-enhancing insights. And the popular attribution tools Google offers only paint a partial picture, focusing heavily on data from Google properties.
The solution is a platform flexible enough to capture all relevant brand interactions. Advanced bidding technology does this, factoring in important data types such as:
The more data your attribution technology uses to understand the path to purchase, the more accurately it can attribute conversion value to different marketing assets.
Taking the Guesswork Out of Bidding
Third-party paid search attribution technologies have more data integration options than Google Ads or Google Analytics. They can help you build a more accurate attribution strategy, but lack the features to implement changes to your PPC campaigns based on these insights.
Automated bidding technology uses historical performance data, statistical modeling and artificial intelligence (AI) to accurately estimate the value of each keyword in your campaigns. It’s then able to make necessary changes to your max cost-per-click (CPC) and bid adjustments. By using all relevant performance data and adjusting bids in real time, automated bidding technology can improve campaign efficiency and performance, freeing up marketing managers to explore new growth initiatives.
More Precise Attribution
Top-of-the-line bid automation tools have features that ensure more precise attribution than what basic models and technologies can provide. Such technologies use multiple data sources to map locations with higher precision (zip codes, cities, metro areas, etc.). This allows the tool to better attribute cost and revenue data to the correct location, improving the efficacy of automated location bid adjustments.
The more sophisticated solutions also use decimal conversion values, attributing a single conversion to multiple clicks throughout the customer journey. This better illustrates the real impact of each keyword on the path to conversion. The algorithm can then use this more accurate data to calculate click value and bid more accurately.
Accurate paid search attribution is key for success in today’s competitive PCC world. There are a variety of free and paid tools with different modeling capabilities to choose from. No matter if you’re investing time, money or both in PPC attribution, you must ensure it brings positive ROI for your marketing efforts in the long run.
Advanced automated bidding technology is one solution that offers nuanced insights into what biddable factors drive conversions, and allows you to make changes to your campaigns efficiently and at scale.
Thought leaders, assemble! We recently hosted a roundtable discussion with the Centro Industry Advisory Group (CIAG). The CIAG is aimed at gathering valuable input from thought leaders to help shape the future of advertising technology and services. Read on for four key takeaways:
1. Expect unexpected staffing issues
Recruiting and retaining talent is an issue for agencies in all markets. In large markets, intense competition for talent leads to higher turnover, and in smaller markets, qualified candidates can be hard to come by.
On top of that, staffing needs are unpredictable. Team needs change day-to-day due to sick days or unexpected departures. Events such as an acquisition, a change in management, or a big account win or loss can have long-term impacts on staffing plans.
Whatever the reason, be proactive. Use platforms and implement processes that help you prepare for a staffing gap before there’s an issue. Make it easy for team members to pick up where others left off by preserving institutional knowledge during a departure. Use tools that retain campaign histories, log all relevant communications, and store critical documents where they can be accessed by the rest of the team.
Finally, when hiring, lean into your network to find great people. Be open-minded and resist the urge to make a checklist. Instead, focus on a candidate’s adaptability, culture fit, and capacity to learn.
2. When it comes to CPMs, you get what you pay for
In the media world, if something seems too good to be true, it probably is. Cheap CPMs may mean more impressions—but not all impressions are created equal. For the middle 70% of the CPM range, quality and rate are reasonably scalable.
On the other hand, low-end and high-end CPMs can be out-of-whack; for example, $50 CPMs rarely produce 10x the benefit of a $5 CPM. Conversely, winning inventory at $0.25 per thousand can be wasteful and damaging for brands if their ads are running on the wrong sites.
Be sure to monitor your campaigns to balance the quality and price equation. Viewability is a good place to start, but also look for reasonable frequency, comb through domain reporting for excessive impressions on unknown sites, and turn off exchanges with reputations for excessive non-human traffic.
Additionally, depending on your set KPIs, set up testing opportunities to compare different CPM ranges.
3. Strategic thinking makes a comeback
With so much focus on ad tech, data, and execution in the last few years, deep strategic planning has taken a back seat—but don’t lose sight of the fact that a solid strategy is critical to a campaign’s success!
Rather than channel-based planning, flexible categorical planning may help media professionals and brand managers freshen their approach. Planning categorically means that groupings are tailored to each specific initiative based on business goals and marketing positioning.
For example, digital planners traditionally use buckets like search, social, and programmatic. Instead, consider groupings that align with your business goals and build tactics to serve those goals. This could include simple buckets like “engage, close, retain” or more customized frameworks such as “buzz-building, event support, post-event reengagement.”
This kind of creative thinking can create a more unified experience for consumers, help brands break through the noise, ultimately, produce more effective campaigns.
4. Narratives are more valuable than numbers
We are currently in an era of ‘data bloat’ where whatever can be measured is measured. It’s easy to get lost with all the numbers flying around, but two elements need to remain at the forefront: KPIs and effective narratives.
First, before any performance data is gathered, establish a KPI that aligns with your strategy. Once data starts coming in, maintain focus on the KPI and make optimizations to improve that singular metric. Recommend actions to take based on the campaign data, anecdotes from non-competitive parallel brands, and industry trends. Actionable insights are more valuable than reporting.
Second, find the most effective way to tell the story. Every audience is different, and you may need to change your approach to communicate effectively. That may be via data visualization, digging through the data together in a working session, or creating a sample user journey to illustrate your theme. Every report should have a narrative and a next step.
At Centro, we can help you implement these insights to keep your business at the top of its game. Whether you’re ready to plan and buy on your own or if you need additional guidance—we have a solution. Learn more about Basis and Centro services today!
In paid search programs, the levers you can pull to improve results come in many forms: landing page optimization, ad copy testing, program structure efficiency, automated workflow, and reporting functionality. The most powerful tool, though, is unquestionably keyword bids.
SEM bidding optimization is the most significant way to achieve peak performance in paid search. A number of techniques and tools are available to help advertisers take on this challenge, but there are strengths and weaknesses among these. Over time, innovative transformations have sprouted up, but there is an apparent divergence between what benefits smaller versus larger search programs.
In this article (and more thoroughly in our new eBook) we explore some of the transitions, strengths, and weaknesses of different PPC bid optimization techniques - all to help performance marketers like you find success in improving paid search results.
Today’s landscape is varied, and many of the tools are provided by our beloved search engines - predominantly Google and Bing.
Manual bidding is a powerful technique that gives the advertiser control, but at the expense of effort. Like some of the other native tools, it can work well for smaller, local programs, yet any sizable program (in terms of budget or keywords) will quickly hit a problem of scale where true optimization, frankly, can no longer happen.
Google’s Smart Bidding options are the clear stand out for cheaply and easily applying real optimization tools to your PPC bids, but even these have limitations. Restrictions arise when it comes to the amount of your business data that can be used for optimization (outside of the Google tracking ecosystem), or when it comes to long-tail keywords without enough traffic or conversions to get any optimization.
Scripts on Google and Bing, or other “out of the box” tools, provide some functionality to optimize, but many of these are made for problems of simple logic, programs without many keywords, local businesses, or businesses that collect meaningful lower funnel data. Third-party tools are outperforming native tools in many instances due to differences like these between simple, small programs, and large, complex build-outs.
Methodologies have also transitioned over time. The old folder model was a great way to optimize PPC bids in the past, but it has since become outdated. A folder would optimize for a given goal in a simple and direct way: higher-performing keywords would be bid up, and lower-performing keywords in the folder would be bid down. This, unfortunately, resulted in some keywords becoming lost after being bid down so regularly - not the ideal outcome.
Aggregated bidding leads to inefficient bidding as it does not reveal or eliminate hidden waste at more particulate levels. In general, aggregating simplifies the task at hand (which is great in some ways!). However, when we’re talking about SEM programs that are core revenue producers in your business, this mindset promotes just-above-average results.
With the current data environment we live in, PPC marketing creates massive troves of click-level data that follows the customer through their journey to multiple purchases, sometimes offline sales. This data is the key and the fuel to unlock and boost SEM.
Granularity is of massive importance in the modern age of bidding optimization. Click-level information leads to click-level correlations, which result in the ability to optimize at very granular and specific levels for different audiences and keyword queries.
The tried-and-true SEM optimization technique known as portfolio bidding is actually still one of the best possible ways to make PPC bid decisions for programs that have revenue or conversion goals, but still need to stay within a cost efficiency limit. Most bid optimization tools utilize this technique, but there are some key differences that will separate the good performers from the greats. The three key aspects are:
SEM teams looking to optimize PPC bidding face a number of challenges and blockers. There are some obvious ones, such as insufficient budget or already averaging position one, but we discuss some of the blockers that are hidden at first glance, including:
Our new eBook, SEM Optimization Techniques: Are You Overpaying Google? looks at the landscape of bidding optimization techniques (from tools to methodologies), some blockers teams may face, and the variability between average versus great third party PPC optimization tools.
Why is portfolio bidding for PPC the best methodology for many large advertisers? Why - for others - is there an even better way than portfolio bidding? Is infrastructure that important for fully optimized PPC bidding? How does more granularity and more data create better results? Read the eBook to learn these answers and much more.
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