Over 100 years ago, John Wanamaker famously said, “Half the money I spend on advertising is wasted; the trouble is I don’t know which half.”
Despite all our advancements, this statement still holds true. In 2021, big brands like P&G, Chase, and Uber demonstrated this paradox by cutting millions in digital ad spend without seeing a hit to sales. P&G paused $200 million in digital marketing, Chase cut website ad reach by 99%, and Uber scaled back $120 million. Does that mean digital marketing is ineffective? Not necessarily. These companies didn’t abandon digital, they re-evaluated how they used it.
“Blame It on the Algorithms”
An ad strategy that worked last quarter suddenly underperforms, and it’s tempting to point fingers at new algorithms on platforms like Google or LinkedIn. But algorithms only tell part of the story.
For example, LinkedIn results shifted while using similar strategies over three months. A closer look revealed LinkedIn had rolled out new ad types, started defaulting to Expanded Audiences, and now defaults to advertising across affiliate networks. This forced us to reconsider the type of ads we ran and how we defined conversions:
- Did we really want to target people who are prone to clicking on links and visiting websites?
- Do we want to target people who are more likely to engage with content?
- Do we want to reach people who are more likely to convert?
- Which behavior is less likely to represent bots?
Through experiments with Expanded Audiences, affiliate sites, and unfamiliar campaign types, we started rethinking what success looked like at each stage of the buyer’s journey. Early indicators like cost per click and landing page conversion rates still held value for awareness and early consideration. Yet, our focus shifted to north star metrics- like pipeline influence– that better reflect meaningful engagement, while we kept close tabs on intent signals that lead to conversions.
Ultimately, identifying where ad spending truly matters requires constant adaptation, as we can’t always wait for the full pipeline picture before optimizing.
Measure What Matters
In many of the early-stage companies I’ve worked with, there was a tendency to obsess about vanity metrics:
- Website visitors
- Page sessions
- Social followers
- Shares
- Likes
An executive’s insistence on reviewing these metrics was inversely proportional to the pipeline generated by the sales team. If pipeline and revenue were healthy, they didn’t worry about topline metrics. Because we only worry about vanity metrics when we aren’t getting the answers we want elsewhere, it’s hard to know whether or not these topline results are good or bad benchmarks for a company.
As someone who watches metrics every season, I can tell you with 100% confidence that the metrics listed above don’t matter nearly as much as conversions and pipeline influence. Bot traffic can drastically increase your visits while your conversion rate flatlines.
For content marketing or website copy performance, visit volume is influenced by how often you link the content on higher-traffic pages and social media. How you use the content in paid advertising will also influence page visits. More meaningful content metrics are:
- Bounce Rate
- Time on page
- Form fill/conversion rate
If a post’s bounce rate is low and people are spending a long time on the page, it signals that people are getting more out of that piece of content. This makes the piece a good candidate for advertising and social shares, provided the people consuming the content are in your target audience. Useful early metrics for paid social and paid search are:
- Cost per click
- Ad conversion rate
- Landing page bounce rate
- Landing page conversion rate
Who cares if thousands of people see your ad if no one clicks on it? Who cares if people click on your ad if 96% of them bounce from your landing page?
High bounce rates indicate a misalignment between your ad content and your target page content. Low landing page conversion with low bounce rates may indicate a misalignment between the value you’re offering and the call to action (in other words, you may want to try updating your content).
Useful later-stage metrics to use in the weeks after launching a campaign include opportunity and pipeline influence. We also like to use marketing-qualified accounts or engagement generated as a success measure.
Make sure you are using multi-touch models to calculate whether an opportunity is opened or a pipeline is added after someone interacts with your content or ad. If you’re relying on a last-touch model, you’re missing a lot of important information!
Industry Benchmarks
Before we dive in, here’s a quick codex for the following acronyms:
- CTR: Click-Through Rate: people who click over all people who view
- CPC: Cost Per Click: total spend divided by the number of clicks
- CVR: Conversion: The number of “goal” actions taken divided by the total impressions. This doesn’t necessarily mean “leads created”
- CPA: Cost Per Action: the total spend divided by actions taken
- CPM: Cost Per Mille: the total spend divided by the number of thousands of impressions
July 2020 statistics (for B2B) published by Wordstream for Google and Bing:
Google search ads averages:
- 4.6% CTR
- $3.35 CPC
- 4.76% CVR
- $87.23 CPA
Bing search averages:
- 2.82% CTR
- $0.86 CPC
- 3.1% CVR
- $80.49 CPA
Google display ad averages:
- 0.46% CTR
- $0.34 CPC
- 1.07% CVR
- $58.86 CPA
Landing Pages:
- Bounce Rate: 60-90%
- 2.35% Conversion Rate (Top 25% convert at 5.31% or higher)
Blogs:
- Bounce Rate: 65-95%
- Time on page: 2 minutes 17 seconds
LinkedIn (from The B2B House):
- 0.45-0.6% CTR
- $5.58 CPC globally (varies by department and rank)
- $33.80/1,000 Impressions CPM
- $15-$350 CPL
Facebook (from Wordstream):
- 0.78% CTR
- $2.52 CPC
- $23.77 CPA
Opportunity creation and pipeline influence are highly variable from business to business because of different product price points and sales cycles. We recommend you compare campaign influence data across similar campaigns to develop an internal benchmark by channel.
A Real-World Example
In 2019, we created a gated content piece on a new kind of multi-touch attribution that leverages machine learning. What makes it so exciting is that it can be used to optimize the buyer journey. The piece was, “The Guide to Chain-Based Attribution.”
The LinkedIn CTR was 1%, and the CPC was about $8 per click. The ad type was “Website Visits.” Where things get crazy (in a good way) is that the ads resulted in a 23% conversion rate on the landing page. That’s almost 10X better than average and over 4X better than the top 25%. The bounce rate was 71.59%.
In 2020, we tried to repeat the success we had in 2019 using the same LinkedIn ad and creating new, related content on how cutting-edge marketers are using chain-based algorithms to do everything from mapping out the next best step in the buyer journey to flagging at-risk deals.
Using the same ad type and target audiences, we saw a CTR of 0.43% and a CPC of $3.49. The CTR drop was worrying, but the CPC was very reasonable. We knew we had to change something when it came to our attention that the landing page conversion rate was 4.3% and the bounce rate was 87.64%.
Sure, the conversion rate was higher than average, but compared to 23%? We were able to exceed a 5% landing page conversion rate and bounce rates dipped below 80% when we changed the ad type to Conversion and aligned the ad text with the landing page copy. The CPC jumped up to $11!
Despite improvements in landing page conversions, the CaliberMind engagement score didn’t continue to climb for the accounts that were engaged with the campaign after they consumed the piece. We didn’t see form fills leading to deeper interest in the product that we expected.
Using that information, we pivoted again and changed the content to focus on a more foundational marketing concept. We challenged the usefulness of the MQL measurement and encouraged people to aggregate qualification at the account level, using our MQA vs. Traditional Lead Scoring guide.
Our CTR was 0.68%, the CPC was $4.11, and the landing page conversion rate was 5.2%. More importantly, we increased our opportunities sourced by 33% and our pipeline influenced by 30% with content that resonated more with our target audience.
Meet People Where They Are, With the Right Tools
The moral of the story isn’t that we should stop spending money on digital marketing. For many companies, online is just about the only place people will see your advertisements. To stay ahead, marketers need robust reporting tools to outsmart ad platforms.
With the right setup, paid advertising specialists can continually adjust by tracking benchmarks, experimenting with ad types, optimizing timing, and fine-tuning bids. Most importantly, marketing teams should leverage multi-touch attribution to capture the full impact of awareness and early-stage activities, ensuring you’re not underreporting the value of your efforts.
Ready to make every marketing dollar count? Discover how CaliberMind’s advanced multi-touch attribution and actionable insights can help you understand what’s driving real results. Measure everything, stay flexible, and experiment often!
Contact us today to optimize your ad spend and maximize your impact.
