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.”
It turns out that not much has changed.
According to a January 2021 Forbes article, P&G turned off $200 million of digital marketing, Chase reduced website ad coverage by 99%, and Uber shut down $120 million of digital marketing. None of them saw a decline in sales.
You could jump to a few conclusions from these reports, but don’t assume digital marketing doesn’t work. These companies still use digital advertising tactics, but they changed how they use them.
“It’s Those Dang Algorithms”
It’s easy to get frustrated with Google or LinkedIn. An ad that worked two months ago may not work today, so our impulse is to blame a change in algorithms.
Algorithms are only part of the picture.
We noticed a big change in LinkedIn performance using similar tactics and ad types over three months. Upon further inspection, LinkedIn had changed what kind of ads it offered, began defaulting to Expanded Audiences, and now defaults to advertising across its affiliate networks.
This ultimately led to us to change what kind of ad we used, which meant we had to take a closer look at what we considered a conversion:
- 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?
We also ran some experiments with expanded audiences and affiliate sites, and we tried campaign types we had never tried in the past.
To figure out what worked and what didn’t, we had to define what success looked like at various stages of the buyer journey. This meant understanding how intent indicators preceded engagement and then monitoring lead generation and attribution metrics.
Early indicators like cost per click and landing page conversion rates are still useful for awareness or early consideration campaigns when they are first running. We know that multiple interactions are usually taken before an opportunity is created. An ad rarely leads to immediate form fills, but they do help familiarize people with our brand.
Pipeline influence is our north star, but sometimes we can’t wait to see how pipeline develops before changing an ad.
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
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 something out of your piece far better than visits alone. 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 ungating 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 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!
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)
We are quoting 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
- Bounce Rate: 60-90%
- 2.35% Conversion Rate (Top 25% convert at 5.31% or higher)
- 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, we noticed in CaliberMind that the engagement score for the accounts engaged interacting with the campaign didn’t continue to climb after they consumed the piece. We didn’t see form fills leading to deeper interest in the product.
Using that information, we pivoted again and changed the content to focus a more foundational marketing concept. We challenged the usefulness of the MQL measurement and encouraged people to aggregate qualification at the account level instead with 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
The moral of the story isn't that we should stop spending money on digital marketing. We can't take this approach, particularly during a pandemic. Online is just about the only place people will see your advertisements.
Marketers must have the right reporting infrastructure to outsmart paid advertising platforms. The better our reporting, the faster we can catch a problem in a constantly evolving and highly competitive field. Paid advertising specialists should understand industry benchmarks, adjust ad types, optimize when an ad is running, and update bidding to optimize performance.
Most importantly, marketing organizations need to understand how to use multi-touch attribution to explain the value of awareness and early consideration activities. Otherwise, you’re significantly underreporting the value of your efforts.
Measure everything important, experiment often, and try new things. You’ll see success in no time.
Camela Thompson Camela Thompson is a trusted expert with a long history in sales operations, marketing operations, and customer success operations. She advocated for revenue operations before it was a thing, and has managed tech stacks and data infrastructure for multiple companies.
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