by Denae Luna | Jun 3, 2024 | Digital Marketing, Programmatic
At this point it isn’t a secret that the programmatic ecosystem has done an abysmal job with brand safety and supply quality. It also is pretty clear that The Trade Desk is doing whatever it can to distance themselves from the DSP pack. While The Trade Desk is clearly a Tier 1 DSP it’s hard to take market share away from their competitors who all own and operate premium inventory and data.
The Trade Desk has invested a lot into Universal ID2 to put themselves at the forefront of the post-cookie audience targeting solutions. While it’s too soon to write off UID2 it seems pretty clear that it will not achieve the scale needed to make them the “go to” for post-cookie identity. Now, it appears they are taking another shot at differentiating themselves from their other Tier 1 DSP competitors.
The new PR push is pretty straightforward. They want to brand themselves as the arbiters of “the premium open web.” The timing makes sense because brands and agencies are scrambling to figure out ways to ensure brand safety and supply quality in the wake of numerous reports highlighting how DV, IAS, and the like have been asleep at the wheeling certifying quality. The Trade Desk has released SP500+ (which seems to be an index of top, premium publishers) and more recently the Top 100 publishers.
These lists are not any kind of innovation in themselves. In fact, many on adtech Twitter (or X) chided the move as a SLAAP (site list as a service) and I essentially agree. Any programmatic media buyer with a few years of experience probably could have put a nearly identical list together. That said, something bigger is likely going on. It appears the Top 100 publisher list is full of UID2 adopters. The Trade Desk could be trying to bully the open web into their ecosystem of UID2 or else be branded “non-premium” inventory.
If this is the case I think it’s a dangerous path for The Trade Desk to take. Publishers are tired of being pushed around by monopolistic players on the buy side. Further, The Trade Desk has spent a lot of effort creating goodwill in the programmatic ecosystem around not being their competition. Attempting to use their clout in the industry to start pushing their view of the world on publishers and the rest of the programmatic ecosystem players could ultimately backfire. I don’t think the industry as a whole wants or needs a DSP to declare what is and is not the premium open internet.
No matter what The Trade Desks true intentions are with these publisher lists one thing is certain. We will be very interested to see where they go with all of this.
by Denae Luna | Jun 3, 2024 | Digital Marketing, Programmatic
As the hopes and dreams of a truly open internet come crashing down around the adtech industry, is there any chance that a truly independent ecosystem can not only survive, but thrive in an era of privacy, walled gardens, and domination by a handful of key players? I believe there is.
To be successful we as an industry need to beat the walled gardens at their own game. It will entail leveraging the interconnected ecosystem of agencies/buyers, platforms, and publishers to scale a walled garden experience in an open, programmatic environment. While it sounds challenging, the foundation for achieving this is already in place. We need all of the key players from the buy and sell side to collaborate on curation.
Here are three ways this can happen:
- The walled gardens need to understand the value of programmatic media buying. As Amazon continues to garner more market share and players like Yahoo and The Trade Desk create more premium, exclusive deals around O&O (or 3rd party O&O) the stranglehold that the duopoly of Google and Meta is slowly being chipped away. Advertisers understand there is a vast network of high quality inventory to be bought across multiple channels outside of
- The supply side (i.e. SSPs) needs to focus their efforts not on creating competing DSPs, but rather partnering with buy side players (agencies, in-house teams, data providers, and other solutions) to curate customized networks that aggregate premium data that can prove top of funnel value by starting customer journeys that end with conversions. Basically, the SSP of the future is the curated ad network of the past. However, instead of competing directly for advertiser dollars the opportunity to even better collaborate with DSPs that already have the advertiser budgets will grow immensely as SSPs create more value for every niche on the buy side.
- The adtech industry as a whole needs to stop focusing on scale and more on value. For every advertiser and every tactic there is a point where incremental spend provides a negative ROI. Adopting a focus on value alone will go a long way in eliminating MFA and other types of fraud from the ecosystem and raise CPMs on the quality inventory that is out there. Everybody wins!
Do I think all three of these things will happen overnight? No. In fact, I think it will take a long time for #1 to happen. If the adtech industry can actually come together, focus on #2 and #3, and stop fighting useless turf wars we can force the walled gardens back into the programmatic ecosystem. It’s time to call a ceasefire and admit that it will take all of us (agencies, in-house teams, DSPs, SSPs, data providers, publishers, and other solutions), working together, with SSPs as the new ad networks, to create a better, curated ecosystem that provides value to every advertiser.
by Denae Luna | Feb 15, 2024 | Digital Marketing, Programmatic
Transparency that comes via in-housing programmatic media buys plays a pivotal role in reducing costs and increasing the efficiency of digital advertising campaigns. This transparency pertains to the visibility into the entire process of buying and selling media, including fees, the performance of ad placements, and the authenticity of traffic. Here’s how increased transparency can lead to cost reductions:
Elimination of Hidden Fees
One of the most immediate ways transparency reduces costs is by revealing all fees associated with programmatic buying. With so many moving pieces in programmatic media buys, the amount of unnecessary fees/markups that advertisers don’t even know about is pretty immense. These can include technology fees, agency fees, 3rd party service fees/markups, and additional charges that might not be evident without a clear view of the transaction process. When advertisers have a detailed understanding of where their budget is going, they can identify and eliminate unnecessary expenses, negotiate better terms, and allocate more of their budget to actual media buying rather than to intermediary services.
Improved Inventory Quality
Transparency allows advertisers to see exactly where their ads are being placed and the quality of the inventory they are purchasing. This visibility helps advertisers avoid spending on low-quality sites that do not contribute to their campaign objectives or, worse, on fraudulent traffic. By directing their spend toward high-quality, relevant inventory, advertisers can improve the effectiveness of their campaigns and achieve better ROI, thus reducing wasted spend. It is a common practice for outsourced programmatic media buys via agencies or DSP managed services to only show you the best performing media while omitting the long-tail media that is largely low quality, unattributed media, or potentially outright fraud.
Optimized Supply Path
Supply path optimization (SPO) is the process of analyzing and choosing the most efficient and cost-effective way to purchase media. Transparency in the programmatic supply chain reveals the path an ad buy takes from the advertiser to the publisher. With this information, advertisers can identify and eliminate redundant or non-value-adding intermediaries, reducing the overall cost of the buy. This direct path ensures that a larger portion of the advertising budget is spent on actual media rather than on middlemen.
Data-Driven Decisions
Transparency provides advertisers with detailed data on campaign performance, including metrics such as viewability, engagement, and conversion rates. Armed with this information, advertisers can make informed decisions about where to allocate their budgets, focusing on strategies and channels that offer the best return. This data-driven approach to campaign management allows for the continuous optimization of campaigns, ensuring that budgets are not wasted on underperforming ads or strategies.
Enhanced Negotiation Leverage
Having a transparent view of the programmatic ecosystem gives advertisers leverage in negotiations with suppliers, including publishers, platforms, and technology providers. With detailed insights into costs, performance, and the supply chain, advertisers can push for better rates, more favorable terms, and higher-quality inventory, further reducing their costs.
Trust and Long-Term Relationships
Transparency fosters trust between advertisers and their partners, including agencies, platforms, and publishers. When all parties have visibility into the process and outcomes, it builds confidence and facilitates the development of long-term relationships. These relationships can lead to more favorable terms over time, including volume discounts and access to premium inventory at competitive prices.
Conclusion
In summary, more transparency in programmatic media buys can significantly reduce costs by eliminating hidden fees, improving inventory quality, optimizing the supply path, enabling data-driven decisions, providing negotiation leverage, and building trust. As the digital advertising landscape continues to evolve, the demand for transparency will likely increase, driven by advertisers’ desire to maximize the efficiency and effectiveness of their digital ad spend.
by Denae Luna | Feb 15, 2024 | Digital Marketing, Programmatic
In the ever-evolving digital advertising landscape, the shift towards in-housing programmatic media buying is becoming increasingly popular among brands seeking greater control, transparency, and efficiency in their advertising efforts. This move not only signifies a shift in operational strategy but also underscores a deeper understanding of the benefits that come with direct management of programmatic buying. Here, we explore the myriad advantages that businesses stand to gain by bringing programmatic media buying in-house.
Enhanced Control and Transparency
One of the primary benefits of in-housing programmatic media buying is the increased control and transparency it offers brands over their advertising operations. By managing programmatic buying internally, companies can directly oversee their ad spend, campaign targeting, and optimization strategies without relying on third-party agencies. This direct oversight allows for real-time adjustments, ensuring that campaigns are aligned with the brand’s goals and market dynamics. Furthermore, in-housing reduces the layers between advertisers and their data, providing clearer insights into spending efficiencies and campaign performance.
Cost Efficiency
In-housing programmatic media buying can lead to significant cost savings. By eliminating the middlemen – typically agencies or managed service providers – brands can reduce the fees that were previously paid for campaign management and strategy. Additionally, with direct access to ad exchanges and supply-side platforms, companies can negotiate better rates and enjoy the cost efficiencies of buying media at market price without added agency markups.
Data Ownership and Privacy
With data privacy becoming a paramount concern for consumers and regulators alike, having direct control over data is critical. In-housing programmatic buying allows brands to maintain strict oversight of their data usage and storage, ensuring compliance with data protection regulations. Moreover, owning the data generated from programmatic campaigns enables brands to build and refine their customer insights, leading to more personalized and effective advertising strategies.
Agility and Speed to Market
The digital market is characterized by its fast pace and constant evolution. Brands that manage programmatic buying in-house benefit from increased agility and speed to market, enabling them to launch campaigns quickly in response to emerging trends or competitive pressures. This responsiveness is a significant competitive advantage, allowing brands to capitalize on opportunities as they arise and adjust strategies swiftly to optimize campaign performance.
Tailored Strategies and Creative Control
In-housing programmatic media buying empowers brands to develop and implement advertising strategies that are precisely tailored to their business objectives and target audiences. With direct control over the creative aspects of campaigns, companies can ensure that their messaging is consistent, on-brand, and adapted to the specificities of each channel and audience segment. This customization extends to the optimization of creative assets, where in-house teams can test, learn, and iterate in real time to improve engagement and conversion rates.
Building In-House Expertise
Finally, in-housing programmatic media buying cultivates a deep reservoir of digital advertising expertise within the organization. As in-house teams grow more proficient in managing programmatic campaigns, they develop a nuanced understanding of the digital advertising ecosystem, enabling more strategic decision-making and innovation. This expertise becomes a valuable asset, informing not just advertising strategy but broader marketing and business strategies as well.
Conclusion
In-housing programmatic media buying offers a range of strategic benefits that can significantly enhance the effectiveness and efficiency of digital advertising efforts. From increased control and transparency to cost savings, data privacy, agility, tailored strategies, and the development of in-house expertise, the advantages are compelling. As more brands recognize these benefits, the shift towards in-housing programmatic media buying is likely to accelerate, reshaping the digital advertising landscape in the process.
by Denae Luna | Nov 17, 2023 | Digital Marketing, Programmatic
Running ads efficiently on more than one Demand Side Platform (DSP) requires a strategic approach that optimizes time, resources, and budget while maximizing reach and performance. Here are several best practices to consider when running in multiple demand side platforms:
Use a Data Management Platform (DMP)
Integrating a DMP can help you centralize and manage your data across different DSPs. This allows for consistent audience segmentation and targeting, and helps in making data-driven decisions across platforms.
Establish Clear Objectives and KPIs
Define what you’re trying to achieve with your campaigns and the metrics you’ll use to measure success. Why are you using multiple DSPs to achieve your goals? It’s likely you are cherry picking best of breed in channel partnerships or you need access to owned and operated (O&O) inventory available on only one platform. For example, an ecommerce brand may need Amazon DSP to access premium data and inventory within the Amazon ecosystem, but also needs a best of breed solution to reach their target audience across a variety of top connected TV apps outside of the Amazon ecosystem. Consistent KPIs across DSPs will help you compare performance effectively. For more information on implementing a DSP, check out this article: https://populationscience.com/how-to-implement-a-demand-side-platform-dsp/
Standardize Creative Assets
Prepare a set of creative assets that can be used across all platforms. This includes ad copy, images, videos, and interactive elements that are in line with the specifications of each DSP. If you deviate too far from the standard it can be difficult to understand if the DSP or the creative that is used is the issue if you experience poor performance.
Automate Where Possible
Use automation tools within the DSPs for bidding, optimization, and reporting. Many DSPs offer automated rules and machine learning algorithms to adjust campaigns in real-time based on performance.
Central Reporting Dashboard
Consider using or building a central reporting dashboard that can pull in data from all the DSPs you are using. This allows for an aggregated view of performance and simplifies the analysis process.
Balance Overlapping and Unique Targeting
Be mindful of audience overlap across DSPs to avoid bidding against yourself. However, leverage the unique data or inventory sources of each DSP to reach different segments of your audience. If you have established clear objectives for why you are using multiple DSPs you should be able to avoid overlap in bidding on inventory.
Optimize Based on Performance
Regularly review campaign performance across all DSPs and shift budgets to the platforms and campaigns that are performing the best.
Work with a Media Aggregator
For smaller businesses or those without the capacity to manage multiple DSPs, consider working with a media aggregator or an agency that can manage this for you. They have the expertise and technology to run campaigns across multiple platforms efficiently.
Leverage Cross-DSP Strategies
Some strategies may be more effective on certain DSPs due to their specific strengths or inventory. Tailor your approach to each platform while maintaining a cohesive overall strategy.
By carefully planning and continuously optimizing, you can efficiently run ads across multiple DSPs and achieve better results from your advertising spend.
by Denae Luna | Nov 17, 2023 | Digital Marketing, Programmatic
A Demand Side Platform (DSP) determines what to bid for each ad impression using a complex process that takes into account several factors. Here’s a simplified breakdown of how this works:
Advertiser Input
– Campaign Objectives: The DSP considers the goals of the campaign, whether it’s brand awareness, lead generation, conversions, etc.
– Budget: The advertiser sets the campaign budget and bid limits.
– Bid: The advertiser sets the maximum CPM or CPC they are willing to pay.
– Targeting Criteria: The advertiser defines the audience segments, geolocations, devices, and other targeting parameters.
– KPIs: Key performance indicators are set, which can include click-through rate (CTR), conversion rate, cost per acquisition (CPA), etc.
If you’re looking to learn more on how to implement a DSP, check out this article here: https://populationscience.com/how-to-implement-a-demand-side-platform-dsp/
Data Analysis
– Audience Data: The DSP uses first-party data (from the advertiser), third-party data (from external providers), and its own data to identify the value of a potential impression.
– Historical Performance: Past performance data of similar ads and targeting criteria are used to predict future performance.
– Contextual Data: Information about the content surrounding the ad placement is considered to ensure relevance and brand safety.
Real-Time Bidding (RTB) Auction Mechanics
– Auction Type: The DSP evaluates whether the auction is a first-price (pay the price you bid) or second-price auction (pay one penny over the second place bidder), which impacts how much should be bid.
– Supply and Demand: The DSP assesses the supply of available impressions and the demand from other advertisers, which influences the market price.
– Bidstream Data: Each bid request contains data such as user demographics, behaviors, the site/app they’re on, and other key data points which the DSP uses to calculate the value of the impression and whether or not it meets your inputs. For more information about the bidstream click here (link to our other blog)
Machine Learning and Algorithms
– Predictive Modeling: DSPs employ machine learning algorithms to predict the likelihood of a user taking the desired action after seeing an ad.
– Bid Optimization Algorithms: These algorithms determine the optimal bid amount based on the likelihood of meeting the campaign’s objectives at the lowest possible cost. Note, some DSPs allow you to customize your own bidding algorithm.
Budget Optimization
– Pacing: The DSP ensures the budget is spent evenly over the campaign duration or adjusts spending based on performance peaks and lulls.
– ROI Considerations: The DSP will bid higher for impressions that are more likely to lead to a conversion or achieve the desired outcome, ensuring a better return on investment.
Real-Time Decisioning
– Latency Constraints: DSPs have milliseconds to make a bid decision once they receive a bid request.
– Dynamic Bidding: The actual bid is dynamically calculated in real-time for each impression, based on all the above factors.
Feedback Loop
– Performance Feedback: After the ad is served, the DSP collects performance data which is fed back into the system to refine future bidding strategies.
Conclusion
The DSP’s bidding process is a sophisticated, real-time system that combines advertiser-defined parameters with advanced data analytics and machine learning to calculate the most appropriate bid for each ad impression. It’s designed to maximize the chances of achieving the advertiser’s goals while optimizing the use of the campaign budget. The process is highly automated and occurs in the time it takes for a webpage or app to load.
