Modern brands today are trying to benchmark their digital marketing campaigns to determine which ones are successful and inform improvements. But we find that many brands are often using their internal marketing benchmarks in an overly broad way.
Correcting this problem requires a more granular approach to digital marketing benchmarks, one that groups campaigns by various characteristics to attain the apples-to-apples comparison you’re looking for:
- Target audience engagement level
- Target audience size
- Digital marketing campaign goal
- Digital content stream
- Seasonality
For each, you’ll likely have two to four tags by which you’ll sort your campaigns to facilitate accurate comparisons. Let’s dive into these characteristics, along with the tags you might use.
1. Target Audience Engagement Level
Who you direct your campaign toward greatly affects the response you’re likely to get. For example, direct it at an audience with a demonstrated high affinity for your message, and the performance will be significantly better than from a more generalized audience.
For tagging purposes, we recommend using these three buckets of audience engagement:
- General audience. This is a broad-spectrum audience composed of a mix of engagement levels.
- High-engagement audience. This is a targeted audience known to have a high affinity for your message, which includes active customers, recent shoppers, and loyalty program members. From a channel perspective, it would also include customers and users who receive transactional messages and action-triggered behavioral messages, like shopping cart abandonment, etc.
- Low-engagement audience. This group includes contacts known to have a low affinity for your message, such as lapsed customers. In your email subscriber lifecycle, for example, this would include inactive subscribers receiving re-engagement campaigns and inactive customers receiving win-back campaigns.
Audience engagement is probably the most important digital marketing campaign characteristic for benchmarking. After all, a poorly crafted campaign sent to only your most active population will almost surely perform better than a great campaign sent to inactive populations.
2. Target Audience Size
The larger the campaign, the more significant the results. To keep things simple, try to limit yourself to two groupings:
- Large campaign. For display, search, and other ad campaigns, review your historical campaigns to decide what constitutes a large campaign. For your email, SMS, push, and other opt-in campaigns, consider including any campaign with an audience that’s within 80% of your full active file.
- Small campaign. Any campaigns that you don’t deem large.
This characteristic helps you avoid extrapolating results from small, targeted campaigns and comparing them to huge ones. Typically, the audience makeup is radically different, which makes comparisons ineffective.
3. Digital Marketing Campaign Goal
Your campaign’s call-to-action is a key factor. For example, a campaign that asks people to register for a webinar is always going to produce far less revenue than a product promotion campaign.
On the simplest level, we recommend grouping your campaigns by the level of funnel activity they are trying to drive:
- High-funnel goals. This activity includes:
- Web traffic, ad impressions, or email opens.
- Off-line activity that can’t be easily or directly tied back to the campaign, such as asking people to vote or watch a TV show.
- Mid-funnel goals. This activity includes:
- Web, ad, or email clicks.
- App or platform engagement or usage.
- Non-sales conversions, such as survey completions, webinar registrations, whitepaper download form submissions, petition signings, and other lead-generation or profiling efforts.
- Low-funnel goals. This activity includes all flavors of sales conversions that increase revenue.
For instance, a campaign sent to subscribers who have never bought anything from your brand that generates a high open rate could be considered successful given its focus on awareness. However, your goal would be much different for an abandoned cart campaign going to an active shopper, where you’re aiming for orders and revenue. You can see how the difference in audience and end goals can affect the success of your campaigns. Understanding these differences is essential.
4. Digital Content Stream
The content that you’re sending, particularly if it’s coming from different lines of business, can have a big effect on campaign performance. Account for that by tracking each of them separately; however, you could combine marketing benchmarks for content streams if they behave similarly.
Here are a few possible ways to categorize your messaging and track your content streams:
- Brand-wide: Addresses your business broadly or covers all of your lines of business.
- Product or service categories: Pertains to different categories within your business that behave differently. These groups can be broad, such as the pharmacy and grocery categories at a grocery store, or they can be narrow, such as men’s shoes and women’s shoes at a department store.
- Line of business: Pertains to only one line of business, such as your wholesaling, retail, or service operations.
- Permission stream: Composed of different content streams that require separate opt-ins from consumers.
- Global business regions: Pertains to business in one country or one region of the world since laws and consumer behaviors can differ wildly across borders.
From a marketing benchmark standpoint, it’s fine to roll together lines of business, permission streams, and business regions where campaigns and their audiences behave similarly. Don’t add complexity if it’s not helpful to understanding your performance.
If you see an advantage to going really granular, that’s fine, too. For instance, for one retail client, we tracked content streams down to the level of “men’s fleece” and “men’s rainwear” because at that level we could get a really good read on how similar campaigns performed.
5. Seasonality
Most brands have some seasonality to their business. To account for this, we recommend tracking your campaigns as such:
- Peak season: The best example for many retailers is the holiday season, but many companies have other strong seasonal peaks, including ski resorts (winter), RV rental companies (summer), and business conference organizers (spring and fall). Some companies even have multiple peaks of varying sizes.
- Off season: Essentially, this is the rest of the year that’s not peak for your business.
Defining the start and end of your peak season is important, but it’s likely to be a fuzzy line rather than a hard date, so don’t obsess too much about nailing the dates exactly since it isn’t going to affect your benchmarks materially.
If you use a fairly granular breakdown of content streams, comparing peak- and off-season benchmarks across categories can potentially reveal inefficiencies. For example, at one retail client, we saw a much more muted jump in performance in one product line compared to others during the holiday season. We investigated and found that various mistakes in creative and copywriting led to the performance gap, which we were then able to close by updating accordingly.
Putting the Benchmark Model into Action
Using those five campaign characteristics, you can then tag any campaign you send to create comparable cohorts. For each characteristic, you can dial up or down the complexity so that it accurately reflects your business. For instance, seasonality might be a non-factor in your business, or you might have three distinct seasons to your business—a peak, off-peak, and off season.
If you do dial up the number of tags that you’re using, just keep in mind that you introduce a little more complexity and dilute the power of your groups with every additional tag you add. Also, verify that any new groups behave differently from each other. For example, you might discover that the newsletters sent by two different lines of business actually perform similarly enough that you can tag them with the same content steam tag rather than using two different ones.
Forecasting Benefits of Digital Marketing Benchmarks
Once you fine-tune your benchmarking model, you’ll also be able to increase your forecasting abilities.
We used one of the first benchmark calculators we designed to help us forecast performance based on the characteristics of upcoming campaigns, along with the triggered digital marketing campaigns that were active. Thanks to our benchmarking data, we were able to walk into meetings and confidently offer feedback like, “If you stick with the planned email schedule, we’re going to miss our target by $100,000 next week.”
What This Model Says about External Digital Marketing Benchmarks
When it comes to external benchmarks, it’s important to remember you typically have no visibility on any of the characteristics mentioned above. What’s the mix of company sizes, the mix of geographic operations, and the level of marketing sophistication in terms of personalization, segmentation, and automation? Even if you knew these details on an aggregate level, it would be incredibly difficult to parse through that information to confidently inform campaign decisions.
In our opinion, external benchmarks are best used to create high-level guardrails to make sure your campaigns aren’t wildly underperforming. But if you want insights into the performance of your marketing programs and how to improve them, invest time in a strong, thoughtful internal benchmarking system.
Additional Resources
Whether you’re a B2B or B2C marketer, or both, we have more resources for you.
Download Essential Strategies for Marketing Automation.
Download Essential Strategies for Cross-Channel Marketing.
To find out more about the tools needed to succeed as a digital marketer, check out Oracle Marketing.
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