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2022 Digital Advertising Benchmarks and How to Beat them_cr_Postclick

Why is it important to measure landing page conversion rates?

Marketers have historically turned to ad clicks as the measure of success for their digital campaigns. But ad clicks don’t accurately reflect the results, because the click is only one step of the campaign. The real measure of success is on the landing page, where customers take action and convert.

Conversions signify success with customers. They measure how well marketers reach and connect with audiences. Clicks are only half of the equation, ultimately meaningless without successful follow-through. Therefore, conversions need to be the primary metric for measuring campaign results.

The significance of industry insights

When evaluating how your results measure up, keep an eye on direct competitors. Looking up overall landing page conversion rate benchmarks can lead you down a rabbit hole and distract you from your analysis. To truly understand how well your campaigns are performing, you need to look at standards for your specific industry.

Benchmarks differ by industry for many reasons. For example, various conversion goals—like subscriptions, downloads, and purchases—use different strategies and target distinct audiences. Your niche and targets significantly impact how you measure success. Consider that the conversion funnel for a new car is vastly different from that of a grocery delivery service.

With that in mind, let’s take a closer look at landing page conversion rates from a few different industries.

Here’s a breakdown of benchmarks across 11 industries for Google Search Ads and Facebook, compared with results for Postclick landing pages.

The average conversion rate across Google Ads is 4.45%. The automotive industry has the highest average landing page conversion rate at 7.98%, while computing products and CE come in last, with 3.16%.

On Facebook, the average rate is 7.44%. Interestingly enough, the education industry has the highest conversion rate on Facebook ads, at 13.58%. Computing products and CE still come at the lowest position, with only 2.31%.

Conversion success is unique to each industry. Consider the auto industry. A conversion at a dealership can mean a sale of a vehicle worth thousands of dollars. Conversely, an auto dealership might be willing to invest more in their advertising if it means driving sales of this magnitude. The same is true for the education industry, where enrollments can be worth up to six figures.

On the other hand, conversions like that aren’t always as simple as “Click here to buy now.” The strategies used to achieve conversions for higher-priced items like cars or mortgages are more elaborate than the strategies of a consumer goods business. Separating conversion metrics by industry is the best way to define a true measure of success. Looking at results for industries with similar conversion goals and products or price points can shed light on how your results measure up.

Benchmarks are an excellent indicator for the standards you should aim to achieve with your results. But that doesn’t mean you have to settle for an industry average as your measure of success.

Postclick’s decade of experience in landing page optimization has helped us define new and more efficient ways to push the fold on conversion rate success. We used this expertise and our proven strategies to engineer the world’s first Advertising Conversion CloudTM—a platform that gives marketers greater control over their return on ad spend, optimization capabilities, and scale of their marketing goals.

Across all 11 industries, Postclick averages a conversion rate of 12.97%, 292% higher than Google and 174% higher than Facebook on average. The highest conversion average goes to the CPG and consumer products industry, with a rate of 18%. The lowest benchmark belongs to the computing and CE industry, with an average rate of 9.6%.

We created the Advertising Conversion Cloud to help marketers scale their initiatives. By deploying optimized landing pages with personalized narratives through automation and machine learning, marketers can propel their results beyond industry averages.

It’s not enough to take these numbers at face value. To measure up to industry standards, you must stay on top
of the strategies, best practices, and any new technology advancements your competitors are using to get ahead. This report will give you insights into how Postclick partners are pushing beyond industry standards, along with actionable strategies for exceeding yours.

Build your audience segments by filtering through each of these data points

You can start with wider criteria like demographics and geographics to curate larger target segments and subsequently, higher reach and lower costs.

From there, you can focus on the quality of your audience by narrowing in on more precise data points like psychographics and behavior.

Youngadultswhofrequentthebeach and enjoy paddle boarding Adults in with leadership roles in corporate industries with an interest in technical tools and new software. Students new to big city areas who need an affordable way for commuting between school and work.

Once you define the unique traits and backgrounds of individual audience segments, you need to align your campaign and landing page narratives to each audience.

Instacart put this into practice with one of their recent outdoor advertising campaigns. Each ad spoke to a pain point for a different audience segment.

This first ad targets the struggle of navigating confusing grocery store layouts and customers’ growing desire for a quick e-commerce solution rather than in-person shopping. Using a digital buzzword familiar to Gen Z audiences, this ad targets shoppers who value convenience over in-person experiences.

This second ad addresses the challenges of commuting to the grocery store. This ad might be more suited for busy shoppers who work from home or customers in densely populated areas.

These ads create a narrative that speaks to their audiences’ unique values and pain points. Find the angle for each segment and target your campaigns for each one. Understanding your potential customers’ motivators and purchase intent enables you to craft an authentic and persuasive experience.

Align the narrative from ad to landing page

Ad-to-page relevancy is vital to maximizing your ROAS. It significantly impacts your Google Quality Score and cost per bid. Plus, as we saw in the previous section, aligning the narrative across all campaign touchpoints lowers bounce rates once you get a potential customer onto your landing page.

Let’s look at an example from The Farmer’s Dog, a healthy dog food delivery service.

This ad positions its narrative around the idea that traditional kibble is bad for dogs’ teeth and fresh food is healthier for dogs “from tooth to tail.” The ad includes a 50% offer for your first order, enticing viewers to click and learn more.

Automate Page Creation

Landing page personalization is no easy task. The problem with effective personalization is that it usually requires a lot of manual effort from internal teams or agencies. But handcrafting unique, thoughtful pages for every audience isn’t feasible—even for well-established brands with robust budgets.

Implementing a solution that uses automation and machine learning to support your team’s human insight enables you to quickly and continually optimize your landing pages.

Many brands have started using online landing page builders with template libraries to speed up manual page creation. Taking this a step further, the Advertising Conversion Cloud uses machine learning and AI to experiment, track performance in real time, allocate ad spend to the best- performing landing pages, and automatically make ongoing improvements for you.

Frequent testing

The core of CRO is constant testing. Traditionally, this has required costly and time-consuming A/B testing. When you need to conduct and analyze frequent tests to generate as many insights as possible in a short period, traditional tools don’t get it done. Advances in AI and machine learning allow marketers to move past this historical challenge.

Using a Multi-Armed Bandit (MAB) methodology for testing prioritizes conversions and speeds up testing periods with the help of machine learning. A MAB experiment automatically directs more traffic to testing variations that perform well. With this system, you won’t waste conversion opportunities by sending traffic to a page with low conversions, as is the case in most A/B tests.

By automatically adapting to the data and insights of the test, the MAB approach increases conversion performance at an accelerated pace.

Test for multiple conversion factors

Frequent testing is vital for creating and refining better- performing experiences. You need the ability to test multiple elements on your landing pages—from copy to imagery
to layout to button color— to optimize the experience for each audience.

Some customers will care more about social proof, while others will feel inspired to convert based on product shots showing how your brand will enhance their daily lives.

Think about your purchase process. What content do you need to see before you feel comfortable making a purchase? Pricing? Dimensions? Durability? Customer testimonials? The list goes on, and it’s clear that a one-size-fits-all approach doesn’t work for people at different points in the marketing funnel or across industries with different price points or conversion goals.

Continual optimization

Frequent, robust testing creates continual optimization opportunities, helping businesses increase conversions and improve ROAS. The challenge for implementing continual optimization is similar to that of personalization and CRO: You need the resources for scale and speed, which is challenging to achieve manually.

If you have to wait weeks for statistical significance before making any optimizations, you’ll find yourself constantly behind your goals. Each campaign requires multiple opportunities to be truly effective. You need a way to reach your optimization objectives at a pace that fits your audience goals. To start, make sure you have a solid framework in place for your optimization efforts.

As you increase scale in testing and personalization, you need a way to track every insight for every audience and use case. Insights and experiments need to build on each other, ensuring you’re continually pushing page performance, not plateauing.

If you can’t clearly track and adjust for these insights, you’ll waste your current progressions and have to start from scratch each time. Find a platform that can track data insights and progress, and show how each experience is performing at a granular level. This will make it simple to monitor and adjust any campaign, landing page experience, or audience, without having to backtrack.

Optimize your pages for mobile

Mobile is quickly shifting to the dominant channel for e-commerce experiences—and a lackluster or frustrating mobile experience can be costly. Don’t only create responsive landing pages. Build optimized landing pages for mobile audiences. Consider a mobile-first design. It can be a lot easier to scale up to desktop than it can be to scale down to mobile. Make sure your file sizes aren’t increasing load times and your page content isn’t too dense for small screens.

Optimize unique pathways

Conversion journeys are unique to each audience and sales channel. You need to optimize each pathway to provide a cohesive and aligned journey throughout. When maximizing your marketing channels, consider customer intent. A customer browsing your social media posts on their phone is in a vastly different state of mind than someone sitting at their desk reading search ads for a particular product. Consider how funnel location and attention span impact each channel—and build a journey targeted to that specific experience.

Machine-driven Insight

Conversion rate optimization is a long-term strategy that requires consistency to achieve success. As mentioned, the scale required to frequently test and optimize your personalized campaigns can generate a heavy demand of oversight and manual effort. Machine learning lets you leap over these pitfalls.

Machine learning is a system of AI that tracks data, identifies patterns, and makes calculated predictions based on these insights. Machine learning records every insight and tracks it back to its original pathway. Automating insights ensures the best possible outcome by making it unlikely you’ll miss any details.

When implemented properly, machine learning can eliminate guesswork from the equation. Find a system that allows you to set parameters, establish a hypothesis, and automatically track your results toward those goals. With the correct technology, you can generate insights at a faster pace, automate the optimization process, and constantly refresh your experiences to better resonate with new and returning customers.

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