Strategies for Overcoming Bias in PPC to Enhance Ad Performance
Pay-per-click (PPC) marketing is a challenging field that requires constant adaptation and flexibility. There are no one-size-fits-all solutions in PPC, which can make it difficult for marketers to overcome their biases and tailor their approach to each client’s unique needs. In this article, we will explore some major biases that PPC strategists may have, when these biases are justified, and how to test assumptions without compromising a client’s profitability.
One major bias in PPC is the debate between smart bidding and manual bidding. Some marketers believe that manual bidding is outdated and that all bidding should be automatic or smart based on conversions. On the other hand, there are those who distrust ad platforms and prefer to have full control over their bidding strategy. Both methods have their pros and cons, and the right approach depends on the context.
For low-volume accounts, manual bidding may be necessary due to insufficient data to support smart bidding. However, bidding strategies like max clicks with a bid cap can help unlock volume. According to Optmyzr data, max clicks with and without a bid cap outperformed manual bidding on CPC, conversion rate, and CPA. On the other hand, for high-volume accounts, smart bidding tends to outperform manual bidding when there are at least 60 conversions in a 30-day period. Optmyzr data showed that Max Conversion Value beat Manual bidding by 400% across 25,000 accounts.
To test these bidding strategies, marketers need to be able to control variables and have a risk-tolerant campaign. They can target different locations or choose a part of the market where some fluctuation is acceptable. It’s important to remember that automatic or smart bidding requires a learning period of at least five days, so significant changes should be avoided during this time. Marketers can adjust bid floors and caps without triggering a new learning period.
Another bias in PPC is the perception of Performance Max campaigns as branded cannibals. Performance Max campaigns have faced mixed reactions due to their focus on visual content and initial lack of control over certain elements. However, Performance Max has evolved and now offers tools for better control and optimization. When testing Performance Max, marketers should consider factors such as conversion volume, account structure, and objective alignment.
Keywords also play a role in PPC biases, with debates around single keyword ad groups (SKAGs), dynamic search ads (DSA), and theme-oriented structures. SKAGs can be powerful when used moderately and supported by sufficient budgets and aggressive negative keywords. However, they may struggle with low volumes and data threshold issues. The choice between broad match keywords and match-type specific campaigns depends on the goals of the campaign, whether it’s transactional or focused on data acquisition.
Lastly, there is a bias against advice and updates from ad platforms themselves. This mistrust can stem from the differences in rules and mechanics between different networks. However, it’s important to remember that humans work on the product teams at ad networks and they appreciate constructive feedback. When testing a new network, marketers should budget enough time and money for a realistic test and communicate expectations with stakeholders.
In conclusion, biases are a natural part of human nature, but they can be counteracted through objective testing. PPC marketers should embrace the flexibility of both smart and manual bidding, understand the potential of Performance Max campaigns, and structure their keywords to maximize relevance and performance. By doing so, they can keep their PPC campaigns adaptable and effective, helping clients achieve their business goals.
