Experimenting with “No-Conversion” Targets and Manual Bids: Surprising CPC and Quality Gains
In the world of Google Ads, testing unconventional strategies can sometimes yield unexpected—and even counterintuitive—results. Recent experiments suggest that by employing a so-called “no-conversion” target coupled with manual bidding, it’s possible to dramatically increase click volume at the same cost, and in some cases even improve lead quality. While not a guaranteed recipe for success, these findings warrant further investigation for advertisers who are curious about pushing the boundaries of Google’s ad algorithms.
The Experiment in a Nutshell
Traditionally, Google Ads’ smart bidding models lean on conversion data to optimize campaigns. When you rely on well-defined goals—such as lead form completions or e-commerce sales—Google’s machine learning works to improve performance over time. However, what if you feed it a conversion action that never actually converts?
In these experiments, campaigns are:
- Switching to Manual CPC Bidding:
Instead of using automated bidding like Target CPA or Max Conversions, the campaigns revert to manual CPC without enhanced CPC enabled. This change removes some algorithmic constraints, allowing advertisers to set deliberately lower bids. - Selecting a “No-Conversion” Goal:
The chosen primary conversion action might be an old, inactive event—such as a chat feature that no longer exists on the site—or a YouTube engagement that the traffic source (search or shopping) will never realistically achieve. This means the algorithm, while trying to hit a leads- or sales-focused objective, never sees a “success” event. - Aligning Campaign Objectives with Leads or Sales:
Even though the selected conversion action never fires, the campaign’s objective is still set to “Leads” or “Sales.” With the conversion action offering no actual wins, the system’s predictive models don’t “relearn” in the traditional sense. Instead, they continue delivering traffic—potentially at lower CPCs—because there’s no conversion pattern to optimize towards.
The Unexpected Outcomes
1. More Clicks for the Same Cost:
One of the most striking results observed was a significant surge in click volume at the same total spend. For instance, where a campaign once generated 100 clicks for a given budget, it might now produce 400 clicks for that same budget. This indicates that, with the algorithm freed from tight conversion-optimization constraints, it may source cheaper traffic opportunities—some of which could still be quite relevant.
2. Stable or Even Improved Lead Quality:
An initial concern was that cheaper clicks would inevitably lead to lower-quality leads. Surprisingly, in some tests, lead quality remained stable or even improved. Predictive metrics—like internal lead scoring or “predicted ROAS” models—suggested that the traffic was still reasonably qualified, despite the absence of a defined conversion signal.
3. No Need for Algorithmic “Relearning”:
Usually, changing a core metric or conversion action prompts the campaign’s algorithm to relearn patterns, often leading to a temporary dip in performance. In these experiments, choosing a stable (but never-triggered) conversion action from the start avoided that retraining period. The campaign kept humming along, delivering high volumes of traffic without the normal fluctuation associated with shifting conversion data.
The Caveats and Mixed Results
This is not a universal silver bullet. While some accounts experienced dramatic improvements in cost efficiency and click volume, others “completely tanked” under similar conditions. There’s no guarantee that every account can exploit this quirk successfully.
Additionally, internal or external factors—such as website downtime, form builders malfunctioning, or seasonal shifts—can muddy the data. One test faced a site-builder issue that skewed lead numbers, complicating the interpretation of results.
For consistent success, advertisers need to:
- Test Cautiously: Try the approach in a controlled environment or on a smaller subset of campaigns.
- Monitor Lead Quality: Use internal scoring methods or qualitative checks to ensure that the incoming leads remain valuable.
- Stay Agile: Be prepared to revert to standard strategies if performance deteriorates.
Why Does This Happen?
The hypothesis is that when you remove the “pressure” of hitting a known conversion goal, Google’s auction models still aim to satisfy the campaign objective setting (like “Leads” or “Sales”) but without the guiding beacon of actual conversions. This lack of actionable conversion feedback may encourage the algorithm to source lower-cost clicks broadly.
By choosing a legacy or unreachable conversion action, the campaign objective still signals to Google that it should look for valuable traffic, but it can’t confirm success the usual way. The outcome: More clicks flood in as Google tries to find that elusive conversion event, driving down CPCs and potentially uncovering overlooked, less-expensive traffic pools.
Key Takeaways
- Manual Bidding Can Outperform Expectations:
Even as automated strategies dominate the conversation, manual CPC bidding—set thoughtfully—can still uncover efficiencies. - Non-Converting Conversion Actions Are a Strange Lever:
By choosing an inactive or irrelevant conversion action, you might “trick” the system into delivering cheaper clicks. This isn’t a conventional best practice, but the experiment shows it can happen. - Lead Quality Isn’t Necessarily Sacrificed:
Contrary to expectations, lead quality may remain stable or improve, though this won’t be true for every account. - Not a One-Size-Fits-All Solution:
This technique may fail in certain scenarios. Advertisers should approach with caution and be ready to pivot if performance sours.
Final Thoughts
It’s too early to declare this an industry-wide tactic. For now, these experiments serve as a fascinating reminder that ad platforms are complex ecosystems, and their black-box algorithms can occasionally be nudged into unexpected behaviors.
For advertisers constantly seeking a competitive edge—especially those willing to experiment—this “no-conversion” approach to manual bidding might open doors to higher volumes of affordable traffic. Just proceed carefully, keep a watchful eye on quality, and remember that what works in one campaign may not work in another.