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Picture of Jon Lorenzini
Jon Lorenzini

Marketing Benchmarks are Worse Than Average

To understand the problem with marketing benchmarks, consider a company like SKIMS. A disruptor brand in the women’s shapewear space, SKIMS caters to women along a wide array of body shapes and skin tones – providing “solutions for everybody” that other shapewear brands overlook.

Benchmarks guide brands to “Keep up with the Joneses”–and that makes for a bad marketing strategy. 

By Jon Lorenzini, Vice-President of Marketing Science and Product Marketing.

To understand the problem with marketing benchmarks, consider a company like SKIMS. A disruptor brand in the women’s shapewear space, SKIMS caters to women along a wide array of body shapes and skin tones – providing “solutions for everybody” that other shapewear brands overlook. The brand’s marketing strategy relies heavily on social media and features a heavy dose of influencers, including co-founder Kim Kardashian. Comparable companies might include Savage X Fenty (founded by singer Rihanna). Still, depending on the parameters you’re comparing, they might also include brands as wide-ranging as Hanes (underwear), Glossier (another company with D to C roots), and — given the celebrity tie-ins — Nike. And therein lies the problem with benchmarking. 

a person making a strategic chess move
Marketing benchmarks do not give brands a competitive edge.

In theory, benchmarks are a perfect way for marketers to navigate the intricacies of strategy and execution. What’s the right percentage of a budget to spend on TV? How much do coupons typically drive sales? What’s the standard email open rate? What’s a reasonable ROI for a TikTok activation? For these and countless other questions, benchmarks provide seemingly clear answers by way of category averages. 

But considering a company like SKIMS, it becomes clear that “category average” is a tricky term. “Category” can be a highly subjective concept: again, SKIMS fits into categories with companies as varied as underwear, makeup, and athletic equipment – and it’s not hard to find an equal number of categories describing just about any other company. Meanwhile, “average” might not mean desirable, smart, or even wholly accurate.  

In other words, “benchmarks” of all kinds are held up as marketing gold standards, but the reality is that they’re often a waste of time or worse. The five problems below help to illustrate why benchmarking is so problematic: 

 

  1. Benchmarks assume an “average” marketing and business model. Benchmarks propose to hold up a single measure as universally relevant. But given businesses’ vast array of marketing strategies and business models, universally relevant numbers just don’t make sense. For a very simple example, take a theoretical benchmark for search spend. Search hardly operates in a vacuum, and one of many performance factors includes the landing page that customers see after the click. This means that a company with a better landing page may need to spend far less on search for the same ROI as another company with a poorly designed landing page. This is just one of countless examples where differences between one business and the next mean that the same activity can drive vastly different outcomes – which is why a universal “best” or “minimal” number to hit is nearly meaningless.  
  2. “Average” numbers don’t reflect dynamic marketing. Marketing performs differently over the lifecycle of the strategy and the campaign. Channels that are highly valuable at the start may hit diminishing returns quickly, down-funnel channels may start working better as top-funnel efforts get underway, and external factors like seasonality and the economy might impact all channels. Given the dynamic nature of marketing, it’s highly unlikely that there’s any single number that meaningfully represents where a given aspect of marketing ought to be at any given time.    
  3. Benchmarks ignore platform dynamics. When it comes to the algorithms that dominate digital ads, one brand’s experience may be very different than another’s. After all, algorithms are explicitly designed to direct outcomes based on a huge array of factors – which can mean every business may effectively operate under a different set of rules, and average benchmarks aren’t helpful at all. For instance, many platforms give some degree of preference to advertisers with a proven track record of ad engagement – which can mean newcomers need to spend far more than the average, and legacy brands need to spend far less to achieve identical results. If a benchmark is below the target for one company and too low for another, how can it help all companies find their way? The answer is it’s not – another example of how benchmarks just don’t meet the standard.   
  4. Benchmarks foster a false sense of security. If benchmarks don’t provide a meaningful picture of what your business should be doing, what they offer instead is the feeling that you know the numbers you should be hitting. If you get comfortable because you’ve outperformed a benchmark,  you’re operating on a false sense of security. Conversely, if you feel the need to take dramatic action – like upping or pulling spend – to get in line with benchmarks, you’re course-correcting with a faulty compass. Either way, you’re setting yourself up to move ahead with confidence that’s unwarranted.   
  5. Benchmarks reward the status quo. The whole benchmarking enterprise asks brands to ensure they align with other brands. Benchmarks promote a corporate version of “keeping up with the Joneses.” But at the end of the day, what makes brands great is that they stand for something unique. Average marketing is built on benchmarks. Great advertising is never average. 

 

To be clear, I’m not saying benchmarks have no value as you’re gathering data and setting goals. As one of many inputs in your marketing arsenal, benchmarks have their place. But too often, marketers – following vendors’ lead that give industry benchmarks outsized prominence – use these numbers as a Source of Truth and a North Star. That’s a huge mistake. 

 

Instead of looking at external benchmarks, I’d recommend a very different set of numbers to guide you: your baseline. Start with your spend and performance numbers, and use approaches like Agile Mix Modeling and Media Experimentation to iterate continually. Rather than working toward an imagined average, you’ll be putting real marketing science to work to improve constantly.