Your paid advertising isn’t working hard enough – The Push-Pull Strategy

When was the last time you shocked your Google Ads account by drastically reducing the budget on a well performing campaign?

Sounds insane? But so does pumping an increasing amount of money into an ad system designed to draw more money out of you. Every algorithm has a sweet spot between blindly throwing money in and getting something out and being made to “work harder”. Too afraid to touch anything in case it breaks is a typical agency approach on this one (just check out this facebook ad article as an example).

Google’s machine learning algorithms are built to optimise for specific goals, like clicks, conversions, or ROAS (Return on Ad Spend). However, they often work more efficiently under constraints that force them to prioritise high-quality traffic and convert at a higher rate. This is the core of the Brand Ambition Push-Pull Audience-Centric Funnel Strategy. (BAP-PACs for short) It’s about strategically manipulating Google’s algorithm to maximise ROI and improve lead generation, particularly in highly competitive markets and the results we get at comparatively tiny budgets are explosive.

The Mechanics of the Push-Pull Strategy

The Push-Pull Strategy leverages Google’s learning algorithm by first allowing a broad learning phase (“push”) and then compressing the budget to focus on high-performance keywords and ads (“pull”). This method ensures that your campaign is continuously optimised, reducing wasteful spend and driving better ROI.

1. Broad Learning Phase (“Push”)

Start by using broad match keywords and a diversified ad set to gather comprehensive data. This phase allows Google’s machine learning algorithms to explore a wide range of search queries and user behaviours, identifying which combinations perform best. The goal is to cast a wide net, gathering as much data as possible to feed into Google’s algorithms ​(Read more about this at Cobiro).

There is nothing more of putting than these messages from Google about Broad Match. They feel like a dishonest way of making you spend more money, but over the last couple of years, we have seen significant improvement over the relevancy of Broad Match adverts as the Google algorithm and language models as a whole has got smarter.

2. Budget Compression and Focused Targeting (“Pull”):

Once Google thinks it has got away with catching you into a broad match approach, and after sufficient data collection, reduce the budget and narrow the focus to high-performing keywords and audience segments.

This forces Google’s algorithm to prioritise quality over quantity, targeting the most relevant and high-intent searches, effectively making the algorithm “work harder” under tighter budget constraints ​(Marin Software discuss this and the reasons why here).

You can add more keywords, and more broad match phrases throughout a growth phrase and then repeat this process, continually pushing and pulling your marketing budget back for staged growth rather than just increasing the budget endlessly and not seeing the expected results.

3. Integrate Display and Remarketing Ads:

Use display ads to maintain brand visibility and attract new visitors. Then, deploy remarketing campaigns to re-engage users who have shown interest but haven’t converted. This approach helps refine your audience targeting and increases the likelihood of conversion by focusing on already-engaged users.

This article by ​Search Engine Land demonstrats how Global brands are thriving despite budget cuts as a result of the use of audience expansion and an insight led approach.

Why This Strategy Works: Evidence and Insights

You don’t need to be a Global Brand to take advantage of audience insights and algorithmic adaption. The tools Google provides are there to be manipulated and set-up regardless of the budget, but the trial and testing of the process, is the most important aspect. For brands that are spending £2k+ on Adwords every month, this strategy works and here are just some of the examples of clients we’ve worked with.

Algorithm Adaptation and Budget Compression:

Experiments and data from 2024 have shown that budget manipulation can significantly impact Google’s algorithm performance. By compressing the budget after an initial learning period, advertisers have observed improved performance metrics like CTR (Click-Through Rate) and CPA (Cost Per Acquisition). The algorithm, having gathered enough data, focuses more narrowly on high-converting opportunities, making each ad pound work harder​.

Leveraging Data for Dynamic Optimisation:

Google’s machine learning thrives on data diversity. The initial “push” phase provides a wide dataset from which the algorithm learns and predicts future behaviours. Once this data is available, refining the strategy with a “pull” approach ensures that only the most effective keywords and ad copies are retained. This continuous optimisation aligns with the principles of audience-centric funnel strategies, focusing on user intent and journey​. Read more about the Google Learning Phrase.

Enhanced Audience Engagement with Display and Remarketing:

By integrating display ads with remarketing efforts, the strategy capitalises on audience engagement across multiple touchpoints. Display ads help build awareness and attract broad audiences, while remarketing re-engages those who have interacted with your ads but have not yet converted. This multi-touchpoint strategy is particularly effective in maintaining engagement and driving conversions in both B2C and B2B contexts​.

Remember the goal for these type of campaigns is typically lead generation, so your display ads need to have a campaign approach. You should have a clear mix of Brand engagement and service level offering to vary the ads.

Applying the Strategy to Different Markets

B2C Example – Solar Energy Companies:

Start with broad keywords like “best solar panels” or “solar energy benefits.” Use display ads with attention-grabbing, billboard-style messaging to attract a wide audience. Once enough data is collected, compress the budget to focus on high-intent keywords and deploy remarketing ads targeting users who have visited pricing or FAQ pages but didn’t convert.

B2B Example – Professional Services:

Target keywords that reflect different stages of the buying process, such as “consulting firms in London” or “engineering solutions provider.” Use display ads on industry-specific websites to increase visibility among decision-makers. Implement remarketing campaigns to re-engage users who downloaded a whitepaper or attended a webinar but didn’t schedule a consultation.

The Trade-Off: Better Results Take More Time

You can start an exact match text campaign tomorrow and get the results you expect. Your only focus is on the quality & relevancy of the ads because you’re bidding on all the same keywords as your competitor. The limitations mean your cost per conversion is typically 25%-30% higher as a result of the CPC (cost per click) being more competitive and higher, but the results are initially more likely. This short-term view is often used for those looking for a quick fix or those not looking to squeeze every penny out of a pound, but we’re a Yorkshire company, so every penny counts.

Conclusion: Maximising Your Google Ads Potential

The Brand Ambition Push-Pull Audience-Centric Funnel Strategy (BAP-PACs) is a powerful method to optimise Google Ads performance by dynamically manipulating budgets and focusing on high-value audience segments. This approach leverages both Google’s machine learning capabilities and strategic ad placement to drive higher engagement and conversions. By making Google’s algorithm work “harder,” you can maximise ROI and achieve more effective lead generation, whether in B2C or B2B markets.

Comparison against alternative approaches