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Data from media buying doesn’t always translate easily to financial systems—with dynamic CPMs and fluctuating contracts, campaign data typically has to be pulled from multiple siloed systems, making monthly and quarterly reconciliation a major pain point for agencies. Finance teams are under even more scrutiny to perform with accuracy and speed.
Basis Technologies and FreeWheel partnered to build a robust API-level integration between their platforms, Basis and Strata, which connects digital media planning and execution with client billing and vendor payments. Together, the platforms present an automated solution to reduce financial risk, streamline billing and reconciliation, and generate trustworthy data.
Basis and Strata offload additional pressure by reducing manual labor - which decreases errors and accelerates processes that have undermined the capacity of accounts payable teams for decades. Review the benefits of this exciting partnership below!
Our two-way API connection protects margins by routinely sharing information between platforms, with accelerated billing and reconciliation processes to help improve cash flow. Collect payments faster by getting accurate invoices out on time and pay vendors right away.
Once an estimate ID is entered in Basis, information flows between the two platforms daily, liberating employees from manual-entry duties and allowing them to focus on more strategic assignments.
This integration eliminates the anxiety of a missed, revised, or updated media plan. The ongoing dialogue between Basis and Strata is designed to provide a single source of truth, so users can feel confident about the data in front of them.
It's as easy as...
Link—enable Strata Buying Management Software (SBMS) in Basis.
Plan—create campaigns in Basis and match them to estimates in SBMS.
Buy—execute omni-channel digital media buys in Basis.
Bill—data flows automatically from Basis to SBMS.
Are you ready to redefine your digital media business from planning to payment? Increase your operational efficiencies today! Basis’ integration with SBMS makes automated billing and financial reconciliation easy. For more information on Basis Technologies' partnership with FreeWheel, read the full press release.
When it comes to promotion and advertising, you’d be amazed just how many companies throw themselves into marketing campaigns without the faintest idea about the demographic make-up of their target audience. Now more than ever, at a time when competition online is fierce, garnering an understanding of your desired market and tailoring your messaging accordingly is essential in successfully engaging with and persuading consumers to purchase what you’re offering. While it may be tempting to dive straight into a campaign and start constructing creative content, it’s vitally important that you first take a step back and consider who exactly you’re building it for.
How you define this will inevitably come from your data. Whether you’re working at a start-up or at a company in the Fortune 100, I’m sure by now you’ve embraced the importance of collecting vast swathes of statistical information and leveraging it efficiently to meet your business goals. The problem facing marketers of today, though, is the sheer quantity of data people are generating and how meaningful insights can be surfaced from amongst all the noise.
Thankfully, with this data explosion has come the invention of technologies and strategies designed solely to manage it all effectively. One of the most powerful tactics is dedicated audience targeting based on user behavior. There are currently eight major audience types advertisers can use to target and drive peak performance, yet due to their large number, few marketing managers have a complete understanding of how to utilize them to their full potential. In this infographic, we take a look at them and explore how they can help ensure your brand is in the right place, at the right time, with the right message.
To download this infographic on how to improve the reach of your campaigns, click here. The full eBook is also available, offering a more thorough analysis of how you can leverage the power of audience targeting to drive better business outcomes and truly move the needle in your favor. Alternatively, if you’d like to talk to our team about how to solve paid advertising problems at deeper levels of granularity, get in touch.
Folks, winter is coming and I know it’s a scarily busy time for all marketers.
The aim of this article is to provide a source of information that you can use to help deal with the upcoming seasonal assault. I conveyed these insights at eTail: The eCommerce and Omnichannel Conference at Boston in August earlier this year and would like to share with you here as the eTail audience found it incredibly helpful.
I’ll begin with the much-discussed topic of data.
Data is a big investment for all companies nowadays. CMOs are spending a significant portion of their budget on market research, analytics vendors, software, and technologies, as shown in recent research by Gartner.
This investment has increased YoY and a majority of the decisions coming from business leaders are data-driven based on analytics.
However, and many of you can relate to this fact, marketers are mostly stuck in data collection and queries. Data analysts and scientists are spending their time in the management, integration, and formatting of data or even mundane tasks like creating dashboards and reporting. Only 29% of their time is spent on data advanced modelling.
If we look at the current state of publisher data, there are obvious challenges ahead of us. Namely;
If you look at all of the customer-level data that you’re processing currently, you’ll no doubt have some powerful data on repeat purchase value, call surge and capacity, and lifetime value or average order value. To beat out your competition, you’ll want to be smart about your advertising strategies with all of this data.
If you look at contextual data, there are so many signals available out there regarding how your prospects are finding you - think about device, location, time of day, day of week, weather, etc.
The real question, then, is how do you integrate all of this rich data coming from various sources and channels to enhance your advertising and marketing efforts. Many of you may say a “Customer Data Platform” is the solution! And many of you may have been working with a CDP vendor. Raise your hand if you have one or are talking to a CDP vendor currently?
Well, I can’t see a show of hands here but just having all of this data in silos doesn’t make it usable. Smart advertising is all about integrating this data and modelling it to get the best results from your advertising efforts, and that’s what QuanticMind has been helping customers with.
We’ve been integrating all of this data even before the term CDP was born 🙂
But how do we use all of that unified, integrated data for optimization?
This flow chart simply captures how we apply all of your rich data to achieve a potential use case or business application. I call it smarter advertising.
Our platform processes all of these online and offline data signals and calculates the revenue for each of your keywords. It then optimizes bids based on said revenue. We call it revenue-per-click optimization. The result is peak performance. And I am borrowing this line from our co-founder Brian Bird: “Peak Performance is a beautiful thing”
My father used to work at a Radio station. Growing up, I used to hate the holiday season. While all my friends were with their fathers, mine was busy as it was the time everyone would tune-in to listen to him on the Radio (He was a popular host and had a fan following back then).
I couldn’t automate his busy work but maybe I could help you automate your busy work so you can enjoy more time with your family this holiday season.
I can go on and on as I’ve been doing all of this manually at some point in a very restricted way before using QuanticMind. I joined this company founded by data scientists and digital marketers to provide my fellow marketers with a better way to achieve superior results. Please cut down on the busy work and focus on business strategy and results.
We would love to tell you all about the beauty of our platform and smarter advertising. Request a free consultation now.
At Centro, we know that keeping up with the trade pubs and latest trends can be tough and time-consuming. To make that easier, we’ve compiled all the articles, reports, and other bits of awesomeness you may have missed, but should definitely read. Enjoy our latest list below!
RTB RIP? The Writing Could Be On The Wall For Real-Time Bidding In Europe [:05]
RTB is in the center of debate for the future of programmatic advertising. With GDPR and companies having to update how they collect consent for data processing, the industry is facing a crisis on how to incorporate it into RTB while still being within regulations. Some believe that if you take data out of the equation, RTB is still possible, while others believe that the two go hand in hand.
How Ad Tech Is Adapting To The Pivot To Privacy [:04]
Programmatic advertising is changing with the threats from regulators, platforms and browsers impacting the way user data is collected. Amongst some of the predicted changes include the demise of the third-party cookie, dominant players converging like SSPs and DSPs, and a future in an authenticated web.
How We Can Restore Trust in Advertising [:03]
Marketing Land interviews the CEO of French ‘drive-to-store’ marketing platform Teemo about how transparency can thread the digital needle between irrelevance and creepiness.
YouTube Taps Machine Learning to Serve the Best Contextual Ads for Each User [:03]
YouTube is introducing a new way for marketers to upload and manage their various video campaigns, leveraging machine learning to automatically serve “the most efficient combination” of ad formats at the individual user level.
What the Taboola-Outbrain Combination Means For Publishers [:03]
What does $250 million cash plus 30% of equity in a combined company get you? Well that’s what Taboola is paying to acquire Outbrain in what may be one of the longest discussed M&A events in adtech history to create a content recommendation monster. The promise of the two content recommendation companies’ platforms is more efficiency for advertisers looking to buy sponsored links across the web, though some publishers are concerned around the quality of the recommendations.
Google Ad Manager will be rolling out first-price auctions by the end of September and since then, publishers have seen CPM increases between 9% - 50% as a direct result. Any type of transition of this size will initially see a price fluctuation, however, with bid shading, this is thought to even out over time.
Google Play Pass Launches With 350+ Premium Apps And Games [:03]
Google is launching its own take on subscription-based access to premium mobile games and apps. This will be $1.99 for the first 12 months and then will be $4.99 after the first year. It is unclear what advertising opportunities will be, however, the potential is huge with subscriber data.
Experiential Retail Encourages Greater In-Store Shopping for Consumers This Holiday Season [:04]
In-store shopping is seeing a resurgence as retailers continue to provide consumers with convenient and exciting purchase experiences. And with the holidays approaching, it’s important for retailers to evolve their in-store strategies to encourage repeat shopping.
Pinterest’s Lens Can Now Recognize 2.5 Billion Home and Fashion Objects [:03]
In the 2 years since it’s launch, Pinterest’s AI-powered computer vision discovery tool has been enhanced to more easily perform searches from photos. And now users will begin seeing shoppable Pins—Pins with products, pricing information, and a direct link to checkout—directly into visual search results. The 2.5 billion objects that Lens can recognize range across home and fashion Pins, including tattoos, nails, sunglasses, cats, wedding dresses, plants, quilts, brownies, natural hairstyles, home decor, art, food, and more.
There are a multitude of ways a paid search campaign can be improved, and the avenue one should choose depends entirely on the desired business outcomes. However, the one metric that I have found to be most powerful is efficiency - knowing who to advertise to and when to do it. This “efficiency” can be significantly improved through the bid adjustment tools, which can effectively help target a key demographic to better meet the goals of a given campaign. It can help granularize one’s audience, advertise specifically to each segment, and ultimately eliminate waste by excluding audience members who are unlikely to convert or contribute towards the overall campaign goal.
Before getting into the technicalities of what bid adjustments are and what types are commonly used, I’ll first build some intuition. Everybody is familiar with TV ads - they can be a great building block to understand bid adjustments and how they are beneficial. As a basic example, think about when companies choose to air their ads. Children’s toy companies like Toys ‘R Us (R.I.P) will likely choose to air their ads on Saturday afternoons between cartoons. This is because they know their key demographic - young children - will be engaged and receptive at this time. You would never see a Toys ‘R Us ad at 3:00 am. Companies that primarily target men, like Gillette, will try to air their ads during sporting events. This is because the primary consumers of sports content are males - the demographic these brands are trying to reach. Conceptually, bid adjustments do the same thing in the SEM space.
Per Google Ads Help, a bid adjustment is a percentage increase or decrease in your bids that allows you to show your ads more or less frequently based on where, when, and how people search. A bid adjustment simply means raising or lowering your bid based on when you think it would be more or less valuable for your ad to be seen. There are a few metrics that this “value” is based on which coincide with the different types of bid adjustments.
Location bid adjustments
This does exactly what one would expect - it adjusts bids based on the relative value of a location to a campaign. The location adjustments can be based on country, state within the United States, and, at the most granular level, DMAs (Designated Market Areas). DMAs are regions of the United States used to define television and radio markets. DMAs are centered on large, metropolitan cities and are named as such. They also encompass suburbs and smaller towns further out of the cities.
Let us consider the New England Patriots as another example. The Pats would want to show their ads in New England since someone in that area is more likely to buy a jersey or tickets to a game. To accomplish this goal, they should have a location bid adjustment to bid up searches in this area. Everybody else hates the Patriots with a burning passion and would be unlikely to convert on their ads in any form whatsoever. The Patriots would thus want to bid their ads down in the other 49 states in order to prevent money being wasted on ads that do not generate revenue. All the money that they save from bidding down ads can be used to pump up their footballs. While this example is basic, and a bit extreme, it explains why location bid adjustments can be helpful.
Device bid adjustments
Again, the name gives it away - this type of adjustment modifies bids based on the device that is being used to interact with the ad. Device bid adjustments can be split by device type and not between device types. For example, iPhones and Android phones don’t have separate device mods, they both come under “Mobile devices with full browsers”. Macs and PCs would both go under the same category: “Computers”. For the sake of rounding out the examples, I’ll also say that all tablets, such as iPads and… it’ll come to me… I got nothing sorry. iPads will go under the device category of “Tablets with full browsers”. This is what I meant when I said that device adjustments cannot be implemented for different subsets of the same device.
“So, when should I use device bid adjustments?”. Great question. The short answer is to use your data and figure it out. Does your business get a lot of traffic on mobile? This can be the case with low price, high volume items or quick local services. A simple example is that of a restaurant - perhaps the restaurant’s primary source of traffic is mobile impressions that come from people searching on the go, or conversions in the form of a phone call. This restaurant would want to bid up mobile searches in order to get more traffic. Another example could be a car dealership. People might be unlikely to buy an expensive item like a car on their phone or tablet which is why one might consider bidding down mobile ads. However, here it is important to note that mobile ads might drive impressions that result in conversions on computers. This example illustrates that device adjustments can often work in conjunction with one another, and one must be careful when integrating them into the overall campaign.
Time of day bid adjustments
Fairly intuitively – these adjustments allow you to change your bids based on the subjective value of a particular time of day to your business. However, this has limitations. One cannot simply adjust a bid for every minute or every hour of the day. Google lets you make six bid adjustments per day. That’s 42 a week, 180 a month, 2190 a year, and for all you extra curious folks 173,010 over the average human lifespan. This is important because it means that hours need to be grouped, or “bucketed”. Grouping hours in a way that optimizes performance can be very tricky. At a high level, one would want to use time of day adjustments to bid up hours that historically have higher intent-based traffic, which can be measured as conversions. One would also want to bid down hours with low intent-based traffic.
A good example of this would be retail. Retail businesses would want to bid up their ads late in the morning and early in the afternoon because this is a prime time for conversions. Customers searching for retail stores at this time would be the most likely to actually visit the store and convert. Retail locations would want to bid down hours later in the day since the ad spend would not result in conversions since the store would be closed. The impression might be important in acquiring a conversion for the next day which is why the business should not bid their ads down too far, but they should prioritize peak hours. This is a simple example of time of day modifiers in action.
Remarketing adjustments
If a potential customer has already visited the website of a business but did not convert, they get placed on a remarketing list. Remarketing adjustments are most often used to bid up ads for people who did not convert on a previous visit to the website. This is applicable to almost any business and I don’t think it needs an example to illustrate what it represents.
There are simpler bid modifiers to account for age, gender, and other demographic information, but rather than going into detail on those, let’s discuss why bid adjustments are useful. First and foremost, they help increase cost efficiency and performance. By cutting costs in lesser-performing conditions and driving conversions in more efficient conditions, the overall performance of campaigns will improve. Bid adjustments help businesses market to their desired audience at a more granular level and prioritize audience members more likely to convert. They can increase efficiency by dictating when and where the ads are seen and by whom. Overall, bid modifiers, if implemented correctly, will greatly improve the performance of an SEM campaign.
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To learn more about how you can become more efficient with bid modifiers, connect with our digital media experts today.
‘Ask the Expert’ is a series that breaks down the tools, tech, and trends you’ve been hearing about in the trade pubs and around the office. We ask our in-house experts the tough questions and write up the answers in bite-sized pieces for your reading pleasure.
This month’s topic? Customer Data Platforms (CDPs) and Data Management Platforms (DMPs). We brought in Centro’s VP of Performance Analytics and Ad Operations, Zach Moore, to give us the breakdown.
What’s a CDP? What’s a DMP? What do they do?
A CDP, or Customer Data Platform, and a DMP, or Data Management Platform, can be complimentary to each other—but ultimately exist to accomplish different objectives for marketers.
A CDP contains data attributes for known and unknown customers: Names, addresses, purchase histories, product preferences, etc. These data points are aggregated from multiple systems, matched to profiles, and ultimately, used to create personalized touchpoints.
A DMP, on the other hand, operates anonymously and utilizes browser cookies. DMPs exist to segment audiences, gain insights into specific actions, and facilitate targeting these users anonymously.
What’s the primary difference between the two platforms?
A CDP typically contains PII (personally identifiable information), whereas a DMP is not usually permitted to store this type of information.
What’s an example of how a marketer would use a CDP or a DMP?
Let’s say a brand wanted to launch a targeted email campaign to their e-commerce customers. Using a CDP, they can utilize different messages and offers based on their customers’ predicted lifetime value (LTV).
They can target their high LTV customers, who are more likely to keep spending, with an e-mail that contains a discount or special offer on a big ticket item. Low LTV customers, who are less likely to spend a significant amount of money, can be targeted with an email that features moderately priced accessories or an alert about an upcoming sale.
Let’s say the same brand is attempting to get prospective customers down the purchase funnel, but they experience a drop-off right before conversion. By utilizing a DMP, the brand can map out the prospects’ journey throughout their website and build rules to collect and segment the prospects—to target them more efficiently and gain better insight into their path.
These user segments can be activated within ad buying platforms. For example, the brand can target those users with an ad to remind them that they still have items in their cart, or retarget them with variations of similar products that they’ve already viewed.
What should a brand keep in mind when considering either a CDP or a DMP?
Both are major investments for any marketer and should be carefully considered. The marketer should have a firm use case for each platform, as well as solid buy-in across the organization early on in the process. It’s likely that various teams will need to play a part at some point. Everyone in the organization should be aligned around the business use case, and metrics should be established up front to gauge success.
For CDPs in particular, organizations need to input “clean” data in order to receive actionable data as an output. There should be a large emphasis on data hygiene in order to start the process correctly. If this is a new concept and your data is a bit of a mess, stakeholders will need to be realistic about short- and long-term goals.
Along these lines, it’s important to ask yourself: When was the last time you audited your CRM data? Are these customers still active? Have they moved? Be honest with how fresh your data is.
For both CDPs and DMPs, create a plan for how to use your data and a clear path to customer segment activation. In the case of media activation, ensure your partners can ingest what you’re sending them.
When it comes to DMPs specifically, stay in lock step with your dev and/or IT teams, to make sure that the necessary data points are surfaced in your website’s data layer, or available through the existing tag management solution. If they are not readily available, extra development will be needed to bring them to the forefront.
How does Centro work with clients who currently have, or are looking to obtain, either solution?
Our clients can bring Basis in-house or utilize our managed services option to easily activate segments programmatically. In situations where neither of these options are a perfect fit, Centro meets clients where they are to create custom solutions.
Not sure where you stand? Connect with us to learn more!
Social media platforms like Facebook, Instagram, and LinkedIn rely on audience data to help businesses target their aids. But it’s equally relevant for the search ad landscape. Many search advertisers continue to largely ignore audience targeting options, rather than focusing on keyword bid optimization alone. Using audience targeting for PPC makes it possible to focus on users who are part of your potential customer base. Here’s how.
Keywords have long been the most important tool advertisers use for paid search ad targeting. It was once in the name. “Google Adwords” referred specifically to the role keyword-targeting played in advertising success. That said, audiences have always been an important aspect of what kind of keywords businesses add to their lists. To choose the most valuable keywords to target, you must understand the people (audiences) that use them as search queries.
Audience intent is the driving force behind what kind of phrases users put into the search engines. Yet there can be significant variation in why different people type the same keywords into a search engine. That’s where audience targeting helps a great deal.
Say, for example, someone types “Law offices Seattle” into a search engine. The assumption might be that the person is looking for a lawyer. But what if they’re actually looking to open their own law office in Seattle? Using behavioral and other audience data to separate these users is a valuable way to ensure your ads only appear for the most relevant audiences (as well as queries).
In 2018, Google rebranded its PPC advertising platform from Google Adwords to Google Ads to de-emphasize the role of keyword targeting. However, that doesn’t mean advertisers today shouldn’t be concerned with keywords. Keywords still play a very valuable role in reaching target audiences. Now it’s also important to consider the true value of audience data to improve ad reach and performance.
Audience targeting on its own comes with certain challenges. When using platforms like Facebook or Instagram that rely solely on audience attributes for targeting, there’s no way to know if all the people who see your ads are truly part of your target customer group. Just because someone is in a certain age group, has certain interests, or is near a certain location doesn’t mean they want to buy your products right now.
Paid search advertising is able to avoid this issue by using keywords and audience targeting in unison. The types of phrases people type into a search engine can indicate an intent to purchase. And their demographic profile can help you understand why they’re using those specific search phrases in the first place. Using audience and keyword targeting in combination ensures you prioritize the most relevant audiences at a time when they’re likely ready to make a purchase decision.
Today Google Ads offers more audience targeting options than most marketers are prepared to keep up with. They include:
Here are some of the different ways search advertisers can use audiences to better reach leads and improve campaign performance:
Behavioral-Based Audiences
Many of the aforementioned audience types are based on different kinds of behavior. Certain actions people take can indicate their interests and point in the sales funnel, which you can then use to segment and prioritize different users.
With Google’s remarketing lists, you target users based on actions they made on your website, such as visiting certain pages, filling out a contact form on your site, browsing your site for a certain length of time, etc. With YouTube users, you can target audiences that have watched your videos. And with App users, you can target people who’ve downloaded your apps.
Targeting audiences based on behaviors helps ensure you use the right marketing message to match their point in the sales funnel. Say, for example, you're targeting users that have already filled out a contact form on your site but haven’t converted into paying customers yet. Your PPC ad could then focus on setting your business apart from the competition (middle-of-the-funnel) instead of illustrating what your product is about (top-of-the-funnel).
In-market Audiences
In-market audiences is a targeting feature that reaches potential customers while they’re actively browsing content related to your product/services. It’s incredibly valuable to reach people who are actively browsing, researching, or comparing different products online. Most people turn to search engines to get quick information so they can make purchase decisions. Targeting audiences after they’ve gone through this critical search phase often leads to your ads reaching them after they’ve already bought.
Using in-market audiences is also particularly valuable because they rely on third-party data to categorize prospects into interest groups. There’s a variety of options to choose from, so you can usually find an audience group that perfectly matches your audience. Some of the available in-market audiences include:
Google’s in-market audiences for search have been around for a few years. Bing launched their own version of in-market audiences in 2018. Yet few advertisers take advantage of this targeting option to reach audiences that are ready to buy. Because it’s such an underutilized audience targeting category, it’s also possible to get significant returns when you use it.
Remarketing Audiences from Prior Ad Campaigns
There are many ways to build remarketing audiences for your advertising campaigns. One option is to use UTM tracking codes. UTM tagging allows you to effectively market to your audiences across channels like Facebook, LinkedIn, and Google. Prospects are much more likely to convert if they are exposed to your brand on more than one advertising platform. And it’s possible to use UTM tagging from social media advertising to target audiences on Google search.
Say, for example, you want to target people on Google search who previously converted through your Facebook ads. You can tag URLs from your best Facebook ads with UTM tracking parameters then create a corresponding remarketing list in Google Analytics. You can now use this as a remarketing list for search ads (RLSA) to target these users more aggressively. This increases your chances of reaching high-quality leads in the process.
Unlike with in-market audiences, these are people who were exposed to your brand on social media before expressing purchase intent. But once they turn to search engines to learn more about and compare products, your ads will show up. This ensures you target these micro-moments when users switch from passive browsing to actively searching for information on products and services.
First-Party Data with Customer Match
Customer Match is a valuable advertising tool because it has its own unique features. In-market audience targeting relies on third-party data to help businesses broaden their reach to new customers. Customer match instead relies on first-party data from your own business to help you identify and target audiences with Google Ads.
Customer Match allows you to utilize your own data to engage current customers on Search, YouTube, Display, and other verticals. It also uses the information that your current customers have shared with you to help you discover and target new customers like them.
For example, you can use data from your customer relationship management (CRM) platform to target previous customers with upsell opportunities on search. Using Similar Audience targeting based on your Customer Match audiences, you can also target audiences similar to your remarketing lists on YouTube, Gmail, or Display.
Location and Demographic Targeting
Location targeting has been around for a long time before Google started even pushing towards more audience targeting. Adjusting your bids based on performance in certain locations or with certain demographic groups can significantly improve ad performance and help you better allocate spend.
Say you run a chain business with locations in five different metropolitan areas. You could distribute your ad spend evenly across them with a constant cost per click. But looking closely at your performance data, you discover three locations drive more sales from ad clicks and conversions. Redistributing your ad spend to maximize the value of your most popular areas can make it easier to reach your revenue goals.
At the same time, you may find that targeting a specific age group, gender, or other demographic has a similar effect on performance. Leaving all other audience targeting options aside, simply increasing bids for specific locations and demographic factors leads to significant options to improve campaign performance. The challenge is discovering all these opportunities and making appropriate changes to maximize the value of audience data.
The above examples are just a few ways that audience targeting can be very valuable for PPC advertisers today. Once you start using audiences to their full extent, the positive impact on campaign efficiency and effectiveness continues to grow.
This is especially true when utilizing an advanced automated bidding technology like QuanticMind by Centro. Using artificial intelligence and machine learning, it’s possible to calculate the precise bids you need to target audience groups, based on their expected revenue-per-click (RPC).
Say, for example, a business has a number of remarketing audiences segmented based on specific behaviors, such as:
Even a modest business can come up with 10 or 20 relevant remarketing audiences to target based on behavior. But they often don’t have enough data and internal data analysis capabilities to assign CPC value to them all.
Automated bidding technology uses historical performance data and the current bid landscape to determine your CPC for each micro-audience. This not only improves campaign performance but also reduces wasted spend targeting less valuable audiences with broad bid adjustments.
The majority of businesses today aren’t taking advantage of the targeting potential that specific audiences bring because they don’t have enough internal processing power. Advanced audience targeting paired with automated bidding opens up significantly more opportunities to benefit from this.
It’s not enough to create a remarketing list or try out one of the many audience targeting options available on Google Ads. Performance marketers need to utilize nuanced audience characteristics to make changes and improve campaign performance.
In the long run, search advertising platforms like Google and Bing will continue to encourage advertisers to use more audience targeting options to optimize their campaigns. Forward-thinking businesses should use the wealth of audience data available to maximize campaign performance and stay ahead of the competition.
Real-time bidding has been a driving factor in the growth of the digital media ecosystem. As the industry continues to evolve, media buyers are expected to navigate not only guaranteed direct media buys, but biddable media as well.
Stop gambling with your media dollars and start winning with smarter bidding strategies.
Location-based advertising has entered a new era. For years, advertisers focused on leveraging the most granular location data, often ignorant of how it was obtained. Today, however, the landscape has changed.
Regulators expect certain standards to be met, requiring advertisers to uphold the latest policies on privacy and transparency.
Listen in, as we chat with Lawrence Chan, EVP of Data Ecosystems at mobile intelligence company, Cuebiq, who sheds light on how advertisers can use location data in impactful ways while still observing new standards of privacy compliance.