Successfully launching or scaling an ad platform includes taking into consideration a number of questions as you think through your ad strategy. Answering these questions will help better orient yourself in what it takes to plan a successful ad program.

Who are your advertisers?

The type of advertisers a platform works with and their specific advertising goals can significantly influence the buying experience and the advertising services offered. Let's explore the different types of advertisers and their potential impact on the buying experience:

1. Peer-to-Peer Marketplace Sellers: If the platform operates as a peer-to-peer marketplace, the advertisers are typically sellers within the marketplace who want to promote their listings or products to a broader audience. These sellers may include individual users or small businesses looking to increase visibility and attract more buyers. The advertising focus here is likely on promoting specific listings or products within the existing marketplace ecosystem. The buying experience may involve options for sellers to boost their listings, bid on ad placements, or set a budget for advertising their products to potential buyers.

2. Direct-to-Consumer (DTC) Brands: DTC brands are typically online businesses that sell their products or services directly to consumers. These advertisers are focused on increasing brand awareness, driving website traffic, and generating leads or sales. The buying experience for DTC brands may include options for self-serve ad creation and management, allowing them to target specific audience segments, set budgets, and track performance metrics to achieve their campaign objectives.

3. National Brands with Full Funnel Campaigns: National brands often run full-funnel campaigns, targeting users at different stages of the customer journey, from awareness to conversion. These advertisers seek comprehensive advertising solutions to reach a broad audience across various channels. The buying experience for national brands may require a combination of managed services and programmatic capabilities to execute large-scale, multi-channel campaigns effectively.

4. Third-Party Demand Partners: Allowing third-party demand partners, such as advertisers from external agencies or ad networks, to buy standardized inventory can create additional revenue streams. This approach may involve programmatic advertising, where advertisers bid on available ad impressions in real-time auctions. The buying experience for third-party demand partners would likely involve programmatic access to the ad inventory, enabling them to target their audiences programmatically.

Buying Experience Considerations:

1. Managed Direct Services: For high-touch advertisers or those seeking more personalized support, offering managed direct services where a dedicated team helps plan, execute, and optimize campaigns can be valuable.
2. Advertiser Self-Serve: Providing a self-serve platform empowers advertisers to manage their own campaigns, giving them control over ad creatives, targeting, budgets, and performance tracking.
3. Programmatic: Integrating programmatic capabilities enables advertisers to access inventory through real-time bidding and automate ad buying processes.
4. Hybrid Approach: Depending on the diversity of advertisers and their needs, a combination of managed direct services, self-serve options, and programmatic capabilities may be employed to offer a comprehensive and flexible buying experience.

To determine the most suitable buying experience, the platform needs to align its offerings with the specific needs and preferences of its advertisers, while also considering factors like budget constraints, target audience, and campaign objectives. Offering a tailored buying experience can enhance advertiser satisfaction and retention, ultimately leading to the platform's success in the competitive advertising landscape.

What ad formats are you considering and how will they be used?

When considering ad formats, it's essential to think about the goals and objectives of your advertisers. Different ad formats serve various purposes, and understanding the distinction between branding and performance ads can help in making the right choices.

1. Branding Ads are designed to create brand awareness, build brand recognition, and establish a positive brand image. The primary focus of branding ads is not necessarily to drive immediate conversions but to foster a long-term relationship with consumers. Common ad formats used for branding purposes include:
   1. Display Ads: These are visual ads displayed on websites, often in the form of banners or rich media, to increase brand visibility.
   2. Video Ads: Video content, whether on social media or streaming platforms, allows for compelling storytelling and engaging visual experiences.
   3. Digital Out-of-Home (DOOH) Ads: These ads can effectively increase brand exposure in high-traffic areas.
      The success of branding ads is often measured through brand recall, brand recognition surveys, and sentiment analysis rather than direct sales or conversions.
2. Performance Ads are focused on driving specific actions or conversions from the target audience. These ads are usually used in a more direct response-oriented marketing strategy and aim to measure their success through tangible metrics, such as click-through rates (CTR), conversion rates, cost per acquisition (CPA), and return on ad spend (ROAS). Common ad formats used for performance marketing include:
   1. Search Ads: Paid search ads appear on search results pages when users search for specific keywords, targeting users with high intent.
   2. Email : Targeted email campaigns can be used to promote products, services, or special offers directly to subscribers.
   3. Sponsored Listings (Product Listing Ads): E-commerce platforms can utilize product listing ads to showcase products and entice potential customers.
      Performance ads are usually more trackable and can provide immediate insights into their effectiveness in generating conversions and sales.

What type of targeting are you considering?

1. Contextual Targeting involves showing ads to users based on the content they are currently consuming or the context of the webpage/app they are visiting. The primary focus here is to match the ad's content with the surrounding content. Contextual targeting ensures that ads are displayed in relevant environments, increasing the chances of capturing the attention of users interested in related content. However, it may not necessarily target users based on their specific interests or behaviors.
2. Behavioral Targeting involves showing ads to users based on their past behaviors and actions online. This targeting method uses data collected from users' browsing history, search queries, and interactions with websites to build user profiles and deliver relevant ads. Examples of behavioral targeting include:
   1. Retargeting/Remarketing: Displaying ads to users who have previously visited your website or shown interest in your products but didn't convert.
   2. Interest-Based Targeting: Targeting users with ads based on their demonstrated interests, such as people who frequently visit fitness websites being shown ads for workout gear or supplements.
      Behavioral targeting allows advertisers to show personalized ads to users likely to be interested in their offerings, increasing the chances of conversion. However, it requires the collection of user data, which may raise privacy concerns.
3. Machine Learning Audience Segments has revolutionized the way advertisers target audiences by leveraging data-driven insights and predictive algorithms. With machine learning, publishers can create dynamic and highly precise audience segments, allowing for more effective ad targeting. Examples of machine learning powered audience segments include:
   1. Predictive Segmentation: Machine learning algorithms analyze vast amounts of data to identify patterns and behaviors. This enables publishers to create predictive segments, showing ads to users who are likely to be interested in specific products or services based on their historical behaviors.
   2. Lookalike Audiences: Machine learning algorithms can identify users similar to an existing customer base. Publishers can then sell these "lookalike" audiences with relevant ads, expanding their reach to potential customers who share characteristics with their most valuable customers.
   3. Behavioral Clustering: By using machine learning algorithms, publishers can cluster users based on similar behaviors, preferences, and interests. This allows for the creation of more nuanced and specific segments, enabling tailored ad relevancy.
   4. Real-Time Personalization: Machine learning can process real-time data about user interactions and adjust ad targeting on the fly. This enables personalized ad content to be delivered to users in the moment, increasing the likelihood of engagement and conversions.

How will ads be sold?

1. Are you selling guaranteed placements at a flat rate or a CPM/CPC/CPA?
   1. With flat rate guaranteed placements, advertisers and publishers agree on a fixed price for a specific ad placement. The price remains constant regardless of the number of impressions or clicks the ad receives. This approach offers advertisers predictability and control over their ad placements, ensuring their ads appear in chosen positions on the publisher's website. Guaranteed placements are commonly used for premium ad inventory or during direct sales negotiations with publishers.
   2. Guaranteed placements sold on a CPM model is where advertisers pay for every one thousand ad impressions delivered. Advertisers agree on a fixed cost for every set of a thousand ad views, regardless of how many clicks or interactions the ad generates. Selling on a CPC or CPA model follows the same idea, but sold on clicks or conversions/acquisitions rather than impressions.
2. Are you looking at offering non-guaranteed placements using auctions as a way to potentiate higher revenue through competition?
   1. Some publishers adopt auctions to sell their ad inventory in real-time. In this setup, advertisers bid for available ad impressions, and the highest bidder's ad is displayed to the user. Auctions facilitate fair market competition, allowing advertisers to value ad impressions based on their perceived worth and targeting preferences. This dynamic pricing model can lead to higher revenue for publishers, especially when there is strong demand for their ad inventory.
      1. Demand and Auction Types: There are two main auction types: first price auctions and second price auctions.
         1. First Price Auctions: In first price auctions, the highest bidder pays the exact amount they bid. It's straightforward and transparent for advertisers because the winning bid is the price they pay. However, this simplicity may lead to aggressive bidding and overpaying for impressions.
            Second Price Auctions: In second price auctions, the highest bidder wins the ad placement but pays $0.01 more than the second highest bid. Second price auctions encourage advertisers to bid their true valuation, knowing they won't overpay if they win. However, it can be more challenging for advertisers to predict their optimal bid strategy due to the black box nature of the auction.

How much inventory will you have versus demand? Depending on your ratio, how you scale can be impacted.

1. More Demand Requires More Sophistication:
   1. Auctions As An Equalizer: When there is high demand for ad inventory, auctions can effectively allocate the available impressions to the highest bidders. Auctions create a competitive environment, ensuring that advertisers who value the inventory the most gets the opportunity to display their ads. This dynamic pricing model can maximize revenue for publishers when there is more demand than inventory.
   2. Additional Targeting Filters: To handle high demand and increase revenue, publishers can implement additional targeting filters. By adding sophisticated targeting options, publishers can segment out specific demand, enabling them to match ads with the most relevant audiences. With more refined targeting, advertisers are likely to be willing to pay higher floor rates for highly targeted placements, leading to increased revenue
2. More Inventory Requires Growing Demand:
   1. Working Directly With Brands And Agencies: If a publisher has a substantial amount of ad inventory, building direct relationships with advertisers and advertising agencies can be a strategic move. Direct partnerships allow publishers to negotiate rates and sell their inventory at fixed prices, providing stability and predictability for both parties. This approach is common for publishers with significant, valuable inventory who want to secure long-term partnerships with specific brands or advertisers.
   2. Programmatic Demand: If a publisher has a large volume of ad inventory and wants to grow demand, programmatic advertising can be an effective solution. Programmatic demand involves working with demand-side platforms (DSPs) and advertisers who use real-time bidding to purchase impressions through automated auctions. This approach can increase fill rates and revenue by tapping into a broader pool of advertisers and allowing for more efficient ad placements.
      1. High Inventory Levels Or Unique Inventory: To attract demand partners, publishers need to showcase either high inventory volumes or offer unique and valuable inventory. High inventory volumes indicate that the publisher can consistently deliver impressions to meet advertiser demand. On the other hand, unique inventory, such as niche targeting opportunities, can make the publisher's inventory more attractive to advertisers seeking specific high value audiences.

What performance metrics will your advertisers expect?

When advertisers invest in advertising campaigns, they expect to measure the effectiveness of their efforts and understand the return on their investment. The performance metrics advertisers expect can vary depending on their campaign goals and the specific advertising channels they are using.

1. Click-Through Rate (CTR):CTR measures the percentage of ad impressions that result in clicks. It helps advertisers gauge how engaging their ad creatives are to the target audience. A higher CTR indicates that the ad is resonating well with users and driving them to take action.
2. Conversion Rate:Conversion rate measures the percentage of users who complete a desired action after clicking on the ad, such as making a purchase, filling out a form, or signing up for a newsletter. A high conversion rate is essential for campaigns focused on driving specific actions and generating leads or sales.
3. Cost Per Conversion (CPC) or Cost Per Acquisition (CPA):CPC or CPA represents the average cost incurred by the advertiser to acquire a conversion (e.g., a sale or lead). Advertisers aim to optimize these metrics to ensure they are acquiring conversions efficiently and cost-effectively.
4. Return On Ad Spend (ROAS) Or Return On Investment (ROI):
   ROAS and ROI measure the revenue or profit generated for every dollar spent on advertising. Advertisers want to ensure that their advertising efforts are generating positive returns and providing a profitable outcome.

What does your current ads team look like and what will it look like as you scale?

As your ad platform grows and scales, the structure and roles within the ads team will naturally need to evolve as business expands. The requirements for campaign and workflow management will also transform as you transition from a lean ad team to a fully scaled ad team with specialized teams handling different aspects of the business.

For instance, when you are in the initial stages of starting an advertising operation, tasks typically handled by an Ad Operations Specialist might be handled within a hybrid Account Manager role. Alternatively, you might find that a single Campaign Manager is sufficient for a guaranteed tenancy-based ad program. However, as you explore additional selling tactics, your advertisers' expectations for optimization will likely increase, which would make it necessary to add more Campaign Managers to meet those demands.

What your team looks like now will influence how you get started, but as you look to scale, taking into consideration what a fully functional and streamlined ad team looks like for your ad platform should be a priority as you plan for growth.

What does scaling look like for you?

Once you have a general idea of what you're looking to do with Kevel, we recommended working with our Solutions Architects to help translate your strategy into Kevel. Although Kevel recommends starting with a simple version of your ad platform to get value out of Kevel as quickly as possible, having a long-term plan for scaling will help lay the right foundation to continue to build on top of.

Potential areas of scale to consider can include:

1. Increased ad inventory
2. Advanced targeting strategies
3. Automation
4. Integration of programmatic demand
5. Audience expansion
6. Dynamic creative optimization
7. Performance optimization
8. Adopting to new challenges in the ad tech industry

If you want to get a head start, see below for how to think about the above in the context of getting started with Kevel.