It’s no secret that mastering retail media search advertising empowers brands to drive highly qualified traffic, optimize ad spend and stay competitive in a highly saturated digital marketplace. But when it comes to maximizing advertising budgets — especially on retail media platforms like Amazon, Walmart and Target — understanding and strategizing how cost-per-click (CPC) is calculated can help brands focus their dollars on high-intent, high-converting shoppers to drive long-term growth.
While CPC represents the average cost-per-click for a specific keyword or target, it’s important to recognize that this metric is influenced by much more than just a brand’s initial bid. Think of a keyword bid as the tip of the cost-per-click iceberg; beneath the surface, 90% of a brand’s CPC success is driven by factors like:
- Competition: What keywords are your biggest competitors bidding on, and how are those bids driving up your cost-per-click?
- Ad history: How have your retail media ads and bids performed in the past?
- Ad sales velocity: At what speed do your products sell based on retail media ad placements and keyword bids?
To pull ahead on the digital shelf, brands need data-driven insights and strategies to address both the obvious and hidden factors shaping their CPC performance. Let’s dive in.
Navigating the Second-Price Ad Auction
Most retail media platforms operate on a second-price auction for keywords, where the highest bidder wins but pays only the second-highest bid, plus one cent. For example, if Brand A bids $1.75 on a search term and Buyer B bids $4.00, Buyer B would win the auction for that keyword but pay only $1.76.
This model benefits brand advertisers, giving them the freedom to bid the maximum amount they’re willing to pay for a specific search term, but ensuring they only end up paying slightly above the true market value.
This means that when you bid on a keyword, the auction will consider various elements (like those outlined above) to determine who “wins” that search term — including your bid, the performance of your ad and real-time competition from other brands. As more brands compete for the same keywords, the dynamics of the auction change, resulting in fluctuating CPC rates.
For example, if a pet food brand wanted to bid $5 per click on a popular keyword like “dog food,” Amazon would determine the actual CPC based on deeper factors like competition and keyword performance. If competitors also were bidding to win visibility on “dog food” searches, a brand’s CPC could increase significantly. Now multiply that cost by the brand’s number of retailers, marketplaces, products and keywords. Your average CPC can get very expensive, very quickly.
On an endless digital shelf with more saturated aisles than ever before, the ad auction bidding war creates a challenging (and often expensive) environment for brands to win and convert shoppers across retail media platforms.
Enter: The Bidding War Dilemma
As omnichannel competition heats up, many brands escalate their keyword bids to secure top placements, which often leads to a vicious cycle that results in higher and higher CPC costs. Brands often find themselves in bidding wars, especially when large players with deep pockets enter the competition for popular search terms. This not only continuously drives up CPC but also can result in increased ad spend without a corresponding boost in total sales.
You may want to have your product appear at the top of search results, but chasing vanity metrics and getting caught up in the competition can be costly. Instead of pouring money into high CPC bids, brands should consider targeting longer-tail keywords to improve ad efficiency and lower overall spend while still maintaining (or even growing) total sales levels.
Plus, high bids on high search volume keywords will drain your budget quickly, which means you could miss out on high-converting times of the day once dollars are spent. To avoid this, brands need to make sure they’re being realistic within the confines of their total ad budgets — striking a balance between remaining competitive in the ad auction while not expending their ad budgets too quickly each day.
Great News for Brands: The Answer Isn’t Always ‘Spend More Money’
So how can brands navigate these challenges effectively without just throwing money at the problem? Automating a bidding strategy with artificial intelligence (AI) is a great place to start. By setting specific incremental return on ad spend (iROAS) goals and guardrails for keyword budgets, brands can intelligently and automatically adjust bids across the ad auction in near-real time.
AI-powered automations can raise bids for keywords where a product isn’t visible, while capping bids for keywords where products already have strong organic ranking. That means ad dollars go toward capturing incremental sales, while organic traffic keeps a brand’s bread-and-butter customers converting on products they already know and love.
This approach allows brands to optimize ad spend and maximize visibility without getting caught in the bidding war trap. While it may be tempting to chase top placements for terms like “dog food,” it’s more important that your retail media dollars actually create profitable, incremental sales from competitive keywords. Owning these desirable placements may drive a high sponsored share of voice, but your retail media strategy should also ensure you’re driving incrementality.
Finding Balance in Your Bid Strategy
Ultimately, winning on retail media is less about simply lowering CPC and more about developing a robust bid strategy. At CommerceIQ, we believe a successful bid strategy involves:
- Automating omnichannel bidding with AI-powered technologies that take every factor of your CPC into account, optimizing for growth, profitability and incremental sales across channels;
- Bidding more on keywords that have higher incrementality (those keywords where you want to improve visibility but lack organic presence); and
- Lowering bids on keywords where you already rank well organically, as it’s more cost-effective to focus ad dollars on finding and converting net-new customers.
By focusing on CPC trends, competition within brand categories and driving incremental sales, brands can achieve better ad efficiency and spend their budgets more effectively. The outcome — your cost-per-click — will naturally reflect the success of a well-planned and executed bid strategy.
To learn more about how CommerceIQ helps the world’s leading brands optimize omnichannel CPC, request a demo now.
Himanshu Jain is the SVP of Product at CommerceIQ. He is an experienced business leader with 12+ years of experience across product management, customer success, business development, statistical modeling, building enterprise software and services. He leads product management for the CommerceIQ Advertising platform. Prior to CommerceIQ, Jain advised Fortune 100 companies at Kearney and started his career building machine learning models at Capital One. He has a B.Tech. in Mechanical Engineering from the Indian Institute of Technology, New Delhi and an MBA from the Ross School of Business, University of Michigan.