Increase Conversions With Post-Click Optimization

June 9, 2020
 
Post-click optimization

With separate budgets, separate plans, and often different design teams and agencies, advertising that is designed to entice clicks often leaves potential customers hanging when they arrive on a page that feels generic and impersonal. Or worse, it has little to do with the messaging from the paid advertisement that brought them to your site. For retailers looking to capture more demand, building a better bridge between the click and the post-click is an important and profitable step to improvement. Post-click optimization uses testing and personalization to continually improve conversion rates for new and returning visitors to your sites.

Improve the Post-Click Experience 

Neil Patel notes that a well targeted retail site should expect bounce rates of 20% to 40%. That’s a wide range because there are a lot of factors that can contribute to your level of success. If your site is not well targeted, it’s likely your bounce rate will be much higher. Or, it’s possible your site has low bounce rates for returning customers, but high bounce rates for new visitors. It’s also possible that visitors from a particular channel like social or display advertising have high bounce rates.

Optimizing the post-click experience for any of these cases can dramatically reduce bounce rates and drive higher conversion rates, and it doesn’t have to take a lot of work with the right approach. 

There are many tactical best practices that can immediately improve the post-click experience. For any visitor that has just clicked on an ad, optimizing a page to eliminate friction in the transition to the site is key. For example, ad-based or ad channel-based optimization would use landing pages that are optimized to share the same headline or tagline, use the same fonts and colors, use similar imagery, and repeat the same offer or call to action.

Post-click optimization

There are several factors to consider when improving the post-click experience:

Content and Messaging

Retailers need to have access to a library of images and content that can be associated to the “pre-click” experience. For example, if there is a series of UGC-based social media posts, the post-click landing page should be able to draw from these same creative assets. Or if there is a banner ad that pulls from the product catalogue, the post-click landing page should pull from those same product assets.

Personalization and Data

Post-click optimization works best when retailers can test certain segments (such as people that searched for a particular product) and can use data to personalize messaging for individuals (such as someone that is a loyalty member that just clicked through on a special offer in an email.) These experiences can only be created if you can access the same customer data from a CRM system, from channel partners, or from third-party data partners.

Automation and Scale

Retailers certainly can’t create every version of a post-click landing page by hand, and even if they could, they couldn’t match these pages to individual advertisements or search terms at scale. In order to expand post-click optimization to work across a large audience, retailers need a solution that’s automated based on rules and algorithms, and can execute at scale with ease.

Easy to Get Started, Easy to Grow

Just a few small optimization tests will quickly show retailers just how valuable it is to focus on this important customer experience.

With Monetate personalization from Kibo, retailers can use both majority fit experiences (MFEs) and individual fit experiences (IFEs) to test and personalize landing pages for segments and individual visitors for dramatic improvement. MFEs, sometimes referred to as dynamic tests, leverage machine learning to dictate the amount of traffic exposed to each variant based on the chosen goal metric. IFEs leverage AI to decide which content to show to each visitor based on everything known about them—the goal here is to maximize performance against a given metric.

  • Use MFEs to optimize messaging to a large audience: With MFEs, retailers can test elements like hero images for overall optimization improvement, and can segment and test specific audiences. For example, by segmenting audiences by origination channel, such as search or social, or by what ad or message they were exposed to, brands can optimize the customer experience even for people that haven’t visited the site before.
  • Use IFEs to deliver unique personalization: UK clothing retailer JoJo Maman Bébé worked with Monetate to improve home page engagement by 124% and conversion on their site by 25%. By using AI to test a wide variety of creatives at scale, the retailer was even able to predict and optimize for new visitors as well.