Top 3 Lead Generation Experiments

The world is changing at a pace faster than ever.

Humans’ ability to adapt to technological change is increasing, but it is not keeping pace with the speed of scientific & technological innovation.

 

As Thomas Friedman notes in his book Thank You for Being Late: An Optimist’s Guide to Thriving in the Age of Accelerations the market is shifting from knowledge stock, where one person completes a university degree with the mindset: Great, no more studying!, to I am going to continue learning.

Digital marketing is one of the fastest-changing environments and in order to adapt at this fast pace marketers must develop additional skills. These include faster learning, quicker iterations and above all, experimentation. What works today is almost certainly not going to work tomorrow.

Our clients are very advanced in their approach to performance optimisation as they made the move away from last-click attribution. In this post, we’re showing some of their lessons learned in the very recent past.

 

Bidding strategies on paid search

Automated bidding strategies such as Target CPA and Target ROAS have become the default in Google Ads. In most accounts, using them saves time on manual bid management and performs at least as well as bidding manually.

It’s worth noting that Google deprecated Enhanced CPC (ECPC) for Search and Display campaigns entirely, effective the week of March 31, 2025. Campaigns that hadn’t been migrated to another bid strategy were automatically switched to plain Manual CPC as a fallback. If you’re still running manual or eCPC-style bidding today, that’s no longer a deliberate strategy choice you can make in Google Ads, it’s what happens when you don’t pick one of the automated strategies.

For accounts with enough conversion volume, the practical question now is less “manual vs automated” and more “which automated strategy.” It’s still worth running structured experiments to compare Target CPA against Target ROAS or Maximize Conversions rather than assuming any single strategy performs best by default. More information here.

 

Multi-step landing pages

This experiment is not directly linked to the media side of itself and more about where you send the traffic. Millions of dollars are spent on driving traffic to non-converting landing pages.

When you use a multi-step form vs. a single-step form, especially complex products, the conversion rate in most cases is higher.

When the forms start with a set of questions which are very simple to answer using dropdowns (e.g. Where do you live? or What type of car are you interested in?) and only on the second page you start asking for details of the person, the sunk cost fallacy kicks in and the person filling the form is more likely to complete it.

The best is to use any A/B testing tool out there and then send 50% of traffic to a multi-step form.

CRM data-based performance optimizations

Combining your analytics and sales data is crucial for understanding where your media investments are unprofitable.

Ecommerce is relatively simple: If you are an eCommerce store you will have two data sets you look at: Google Analytics e-commerce and your CRM system. If you connect Google Analytics Data to your CRM data you will be able to understand which campaigns attracted the users which cancelled the orders or returned the goods. With these insights, you can easily find patterns and start improving.

For lead-gen optimisations, it can be a bit trickier, especially when scaling AI lead generation campaigns across multiple channels. It’s likely that you have your Google Analytics conversion data and your CRM (Salesforce, MS Dynamics, Marketo, …) data.

 

Here the key to bringing the data together is to create a unique identifier which you can store in your Analytics data and submit to your CRM with the use of a hidden field.
Once you know which lead or opportunity came from which channel, you can start actioning the insights.

More on this topic specifically for Salesforce can be found here: Connecting Salesforce CRM to Google Analytics.

 

Conclusion

While there is no silver bullet to magically bring down your cost per revenue, the experiments above should help you to save money. If you are able to test these experiments within your organisation quickly, you are part of a culture of fast learning, quick iterations and experimentation.