Introduction
Programmatic buying is much more than a simple automated process for acquiring advertising inventory; it is a discipline that demands strategy, constant analysis, and proactive optimization to achieve maximum return on investment. For advertisers, programmatic offers the opportunity to target their audiences with unprecedented precision and adjust campaigns in real-time, but to capitalize on these advantages, it is essential to understand the key strategies and how to implement them effectively. This article explores the essential tactics for programmatic buying, from initial planning and objective setting to advanced optimization based on data and performance metrics.
Planning a Programmatic Campaign
Before launching a programmatic campaign, thorough planning is crucial. It is not enough to set the basic parameters in a DSP; it is necessary to analyze a series of internal and external factors that will influence performance and results.
Prior considerations for planning include a deep understanding of the target audience, the brand’s status and recognition in the market, competitor activity, the available budget, internet penetration in the target region, and how users in that region interact with technology and digital media. It is vital to analyze the current situation of the advertiser and the product or service offered in the digital market to establish a solid foundation for the buying strategy.
One of the most important aspects of this stage is managing results expectations. Based on the analysis of external factors and the likelihood of achieving objectives, realistic goals can be set, and the campaign budget and duration can be allocated appropriately. Understanding the external factors affecting performance, such as brand positioning and authority, the product’s digital competition level, the volume of potential buyers (audience size), how attractive the product or offer is, the length of the sales funnel, and the conversion capability of the landing page, is fundamental for anticipating potential challenges and adjusting the strategy proactively.
Objectives and KPIs in Programmatic
The beauty of programmatic advertising lies in its versatility to adapt to a wide range of marketing objectives. Advertisers can use programmatic to gain awareness, drive quality traffic, generate leads, or boost sales. Clearly defining campaign objectives will guide the selection of strategies, formats, and performance metrics (KPIs).
- Branding: If the main objective is to increase brand awareness and place it in the consumer’s mind (top of mind), programmatic allows using advertising formats with high visual and auditory impact. Recommended formats for branding are usually large banners (e.g., Megabanner, Billboard), in-stream or out-stream video, and audio ads. KPIs that measure success in branding include unique impressions per user (to measure reach), banner viewability percentage, video view percentage (25%, 50%, 75%, 100%), and the percentage of audio ads played to completion.
- Traffic Acquisition: If the goal is to drive quality traffic to the advertiser’s website or a specific landing page, the buying strategy will focus on reaching users with high affinity for the brand or product. The main KPIs will be click volume and click-through rate (CTR). To measure traffic quality, metrics such as landing page/website visit volume, time spent on page, and visit depth will be considered.
- Performance: Performance campaigns are aimed at achieving specific actions by the user, such as lead generation, account creation, or making purchases. These campaigns work with more complex funnels, from initial attraction to final conversion. It is especially useful to incorporate advertiser CRM data to target existing customers or look-alike audiences and work on loyalty, upselling, or cross-selling. The use of dynamic creatives, which adapt the message to the individual user, significantly increases the conversion rate. Key KPIs in performance are lead or sales volume, cost per lead (CPL), and cost per acquisition (CPA).
Key Metrics in Programmatic
In programmatic, a metric is a numerical value that helps measure campaign performance. Understanding and monitoring the correct metrics is essential for optimization.
Some of the most common metrics include:
- Impressions: The number of times an ad is displayed.
- Clicks: The number of times users click on the ad.
- Conversions: The number of times users complete a desired action (e.g., purchase, registration) after interacting with the ad.
- Reach: The total number of unique users who saw the ad.
- Click-Through Rate (CTR): The percentage of impressions that result in a click (Clicks / Impressions * 100).
- Cost Per Mille (CPM): The cost paid for every thousand impressions of the ad.
- Cost Per Click (CPC): The average cost paid for each click on the ad.
- Cost Per Action / Acquisition (CPA): The average cost paid for each conversion.
- Conversion Rate (CVR): The percentage of clicks or interactions that result in a conversion (Conversions / Clicks or Interactions * 100).
- Cost (Investment): The total amount of money invested in the campaign.
- Revenue: The total value generated by conversions attributed to the campaign.
- Viewability: The percentage of impressions that meet the viewability criteria (e.g., 50% of the ad on screen for at least 1 second for display, 2 seconds for video).
- Other metrics: Depending on the format, may include specific metrics like video view percentage (25%, 50%, 75%, 100%).
Optimization in Buying
The true advantage of programmatic lies in its ability for continuous optimization. Optimization in programmatic buying involves adjusting the campaign in real-time to improve performance based on the set objectives. To achieve this, programmatic traders constantly ask questions about the target, budget, and desired results.
The campaign setup in the DSP must be aligned with the defined objectives and KPIs. DSPs allow for automatic optimization of bids and ad delivery based on metrics like CPM, CPC, or CPA. A key functionality is budget capping, which controls total investment, and compartmentalization by strategic line, which allows allocating budgets and optimizing independently for different audience segments or tactics.
Targeting is the heart of optimization in programmatic, allowing ads to be directed to the right users. There are common targeting options (demographics, geography, web/app environment, device type, language, frequency) and other more advanced or less common ones (time of day, internet provider, specific exchanges, private deals, browsers, internet connection type, minimum viewability, creative position on the page, brand safety, audiences). Choosing the right DSP is important, as available targeting options can vary.
The use of data is what truly differentiates programmatic optimization from other media. Segmentations can be based on sociodemographic data, interests, purchase intent, or behavior (e.g., products purchased, places visited – geofencing). Combining first-party data with second and third-party data in a DMP or CDP greatly enriches segmentation possibilities.
Creatives also play a fundamental role in optimization. The ad message and design must be relevant to the audience and context. Using different types of creatives (display, video, audio) adapted to campaign objectives and different audience segments can significantly improve performance. Programmatic allows for on-demand creativity and rich media formats.
Targeting strategies can be refined using whitelists (lists of sites where we do want to appear), contextual targeting (based on keywords to appear on sites with relevant content), audience targeting (users who visited our site, similar users), and blacklists (lists of sites where we do not want our ad to be displayed for brand safety or irrelevance reasons).
An indispensable element for conversion-based optimization is the correct implementation of the advertiser’s pixel or SDK on their website or application. These allow tracking user actions after seeing or clicking on an ad and sending that information to the DSP, which uses it to optimize delivery towards users most likely to convert.
Although many DSPs have automatic optimization algorithms, manual supervision and adjustment by an experienced trader are still crucial. The trader can interpret data, identify opportunities that the algorithm doesn’t detect, and make strategic adjustments beyond simple algorithmic optimization. Sufficient data volume is required for both algorithms and traders to make informed decisions.
The campaign structure in a DSP varies but generally follows a hierarchy that allows for organizing the strategy (e.g., Campaign > Insertion Order > Line Item). Each level allows configuring different parameters for targeting, budget, creatives, etc. Campaign duration and investment influence the algorithms’ ability to optimize, as the more data available, the better the algorithm learns.
Obtaining segmented reports at different levels (campaign, line item, creative, targeting) is essential for analyzing performance and making informed optimization decisions.
Conclusion
Optimization in programmatic buying is a dynamic and continuous process that combines the power of technology and algorithms with strategic intelligence and human analysis. From detailed initial planning and clear definition of objectives and KPIs, to precise data-based segmentation from various sources and constant adjustment of creatives and targeting tactics, every step is crucial to maximize efficiency and return on investment. Advertisers who master these strategies and make the most of the capabilities of DSPs, the richness of data, and the experience of traders will be better positioned to succeed in the competitive landscape of programmatic digital advertising. Optimization is not a destination, but a constant journey in pursuit of the best possible performance.