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Measuring diversity in advertising: A challenge of scale

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Measuring diversity in advertising: A challenge of scale

“The vast majority of people, when they look at ad content, say they don’t see themselves in it, they don’t see themselves represented. We spend all this time and money telling stories and yet most of the people who look at them don’t see themselves in it. Not only is this clearly inefficient, it’s also quite alienating.” Comments from Anastasia Leng, founder and CEO of CreativeX.

CreativeX’s software provides AI-powered analysis of visual content — images and video — at scale, enabling brands to make data-driven creative decisions, supporting quality, brand consistency and compliance. Recently, it has turned its attention to driving insights into representation in partnership with Geena Davis Institute for Gender in Media. The Institute’s mission is to create gender balance, foster inclusion and reduce negative stereotyping in family entertainment and media. Creative X isn’t just looking at gender, however. “We’re looking at gender, skin tone and age range,” said Leng.

The state of representation

Using its proprietary Representation technology, CreativeX last week released results from an analysis of some 3,500 ads containing images or video (from 2021 and U.S. only). Among the findings:

  • Although 55% of ads featured women, men were 1.5X more likely to be shown in professional environments;
  • Individuals with light to medium skin tones featured twice as often in professional environments; and
  • Individuals in the over-60 age range featured hardly at all (around 1% of the ads) despite their formidable disposable income.

Madeline Di Nonno, CEO of the Geena Davis Institute explained: “What we have found is that, since 2016, there has been a very serious intent by some of the leading global brands – like P&G, Google, Facebook, Mars – to invest in people, to invest in resources and invest in process in order to come up with ways for them to not only absorb the information, but for them to figure out what’s going to work so that we can have improvements.”

Leng confirmed this from her experience with her own clients. “The intentions are there. The other big trigger is that consumers are pushing them in the right direction. Consumers care more than ever.”

So what’s the problem?

The problem is scale

One of the major obstacles to meaningful change is the scale and complexity of ad creative when it comes to global brands like the ones Di Nonno referenced — brands with significant influence on the culture. “It’s been very challenging, especially when you’re dealing with global organizations and you have different regions, different entities around the world. These infrastructures are so big. How many brands, how many ads per brand per year? You’re talking about thousands and thousands, and the pace is so fast.”

That’s where CreativeX comes in, with its use of AI to automate the analysis of vast quantities of creative. “We connect all the different places where they’re running advertising to our system. This then allows us, via APIs, to pull in all of their content. What we then do is look through all their images and videos and basically append a bunch of metadata that helps us determine everything from who is in the creative – what kinds of people – all the way down to what settings they’re in, percentage of men versus women, under 21, over 60, and differences around stories you are telling about men versus women.”

It’s easy for brands to find excuses, Leng said. “You do a bit of research on a small sample size and people say, ‘But you didn’t look at all my content.’ In this case, we’ve taken those excuses off the table. We can look at all your content.” For some large brands CreativeX has so far looked at U.S. content only, Leng said.

She added: “We had an instance of one brand which said ‘We are the most diverse financial brand on the high street.’ We looked at all of their content – tens of thousands of pieces of content – and there was not a single person of color in a single one of their ads.” An extreme example, she admits. “The reason I talk about it is not because they were lying to us, not because they didn’t care, but when you have a large brand with thousands of marketers distributed across multiple locations, and a bunch of agencies, unless you have the systemic infrastructure to track this – everyone thought they were being diverse but no-one was actually doing it.”

Read next: When it comes to women, marketing is behind the times

The goal is systemic change

CreativeX and the Geena Davis Institute happen to share some clients, but the way the partnership is intended to work is that Geena Davis can introduce major global media and entertainment brands to the potential of CreativeX’s technology, while CreativeX can point its clients toward the Institute for advice and counseling on their representation policies.

Ultimately, the goal is to drive systemic change, said Di Nonno. “We’ve been doing what we define as narrative culture-change work since 2004, we’ve had the privilege of being able to expand across many global verticals. We started doing global work in advertising in 2015, a result of me having the privilege of being the second jury president for the Glass Lions.” (The Glass Lion “recognises work that implicitly or explicitly addresses issues of gender inequality or prejudice, through the conscious representation of gender in advertising.”)

“However, as a research institute that is data-driven,” she continued, “when you think about the massiveness and volume of global advertising, to really come up with a turnkey, systemic auditing solution, there’s no way we could ever scale to be able to embrace that. So, with Creative X having created their representation project and having the opportunity to join forces, it really allows us to continue to do what we’re doing but also to have that scalability.”


About The Author

The holiday season is upon us
Kim Davis is the Editorial Director of MarTech. Born in London, but a New Yorker for over two decades, Kim started covering enterprise software ten years ago. His experience encompasses SaaS for the enterprise, digital- ad data-driven urban planning, and applications of SaaS, digital technology, and data in the marketing space. He first wrote about marketing technology as editor of Haymarket’s The Hub, a dedicated marketing tech website, which subsequently became a channel on the established direct marketing brand DMN. Kim joined DMN proper in 2016, as a senior editor, becoming Executive Editor, then Editor-in-Chief a position he held until January 2020. Prior to working in tech journalism, Kim was Associate Editor at a New York Times hyper-local news site, The Local: East Village, and has previously worked as an editor of an academic publication, and as a music journalist. He has written hundreds of New York restaurant reviews for a personal blog, and has been an occasional guest contributor to Eater.


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The Complete Guide to Becoming an Authentic Thought Leader

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The Complete Guide to Becoming an Authentic Thought Leader

Introduce your processes: If you’ve streamlined a particular process, share it. It could be the solution someone else is looking for.

Jump on trends and news: If there’s a hot topic or emerging trend, offer your unique perspective.

Share industry insights: Attended a webinar or podcast that offered valuable insights. Summarize the key takeaways and how they can be applied.

Share your successes: Write about strategies that have worked exceptionally well for you. Your audience will appreciate the proven advice. For example, I shared the process I used to help a former client rank for a keyword with over 2.2 million monthly searches.

Question outdated strategies: If you see a strategy that’s losing steam, suggest alternatives based on your experience and data.

5. Establish communication channels (How)

Once you know who your audience is and what they want to hear, the next step is figuring out how to reach them. Here’s how:

Choose the right platforms: You don’t need to have a presence on every social media platform. Pick two platforms where your audience hangs out and create content for that platform. For example, I’m active on LinkedIn and X because my target audience (SEOs, B2B SaaS, and marketers) is active on these platforms.

Repurpose content: Don’t limit yourself to just one type of content. Consider repurposing your content on Quora, Reddit, or even in webinars and podcasts. This increases your reach and reinforces your message.

Follow Your audience: Go where your audience goes. If they’re active on X, that’s where you should be posting. If they frequent industry webinars, consider becoming a guest on these webinars.

Daily vs. In-depth content: Balance is key. Use social media for daily tips and insights, and reserve your blog for more comprehensive guides and articles.

Network with influencers: Your audience is likely following other experts in the field. Engaging with these influencers puts your content in front of a like-minded audience. I try to spend 30 minutes to an hour daily engaging with content on X and LinkedIn. This is the best way to build a relationship so you’re not a complete stranger when you DM privately.

6. Think of thought leadership as part of your content marketing efforts

As with other content efforts, thought leadership doesn’t exist in a vacuum. It thrives when woven into a cohesive content marketing strategy. By aligning individual authority with your brand, you amplify the credibility of both.

Think of it as top-of-the-funnel content to:

  • Build awareness about your brand

  • Highlight the problems you solve

  • Demonstrate expertise by platforming experts within the company who deliver solutions

Consider the user journey. An individual enters at the top through a social media post, podcast, or blog post. Intrigued, they want to learn more about you and either search your name on Google or social media. If they like what they see, they might visit your website, and if the information fits their needs, they move from passive readers to active prospects in your sales pipeline.

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How to Increase Survey Completion Rate With 5 Top Tips

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How to Increase Survey Completion Rate With 5 Top Tips

Collecting high-quality data is crucial to making strategic observations about your customers. Researchers have to consider the best ways to design their surveys and then how to increase survey completion, because it makes the data more reliable.

→ Free Download: 5 Customer Survey Templates [Access Now]

I’m going to explain how survey completion plays into the reliability of data. Then, we’ll get into how to calculate your survey completion rate versus the number of questions you ask. Finally, I’ll offer some tips to help you increase survey completion rates.

My goal is to make your data-driven decisions more accurate and effective. And just for fun, I’ll use cats in the examples because mine won’t stop walking across my keyboard.

Why Measure Survey Completion

Let’s set the scene: We’re inside a laboratory with a group of cat researchers. They’re wearing little white coats and goggles — and they desperately want to know what other cats think of various fish.

They’ve written up a 10-question survey and invited 100 cats from all socioeconomic rungs — rough and hungry alley cats all the way up to the ones that thrice daily enjoy their Fancy Feast from a crystal dish.

Now, survey completion rates are measured with two metrics: response rate and completion rate. Combining those metrics determines what percentage, out of all 100 cats, finished the entire survey. If all 100 give their full report on how delicious fish is, you’d achieve 100% survey completion and know that your information is as accurate as possible.

But the truth is, nobody achieves 100% survey completion, not even golden retrievers.

With this in mind, here’s how it plays out:

  • Let’s say 10 cats never show up for the survey because they were sleeping.
  • Of the 90 cats that started the survey, only 25 got through a few questions. Then, they wandered off to knock over drinks.
  • Thus, 90 cats gave some level of response, and 65 completed the survey (90 – 25 = 65).
  • Unfortunately, those 25 cats who only partially completed the survey had important opinions — they like salmon way more than any other fish.

The cat researchers achieved 72% survey completion (65 divided by 90), but their survey will not reflect the 25% of cats — a full quarter! — that vastly prefer salmon. (The other 65 cats had no statistically significant preference, by the way. They just wanted to eat whatever fish they saw.)

Now, the Kitty Committee reviews the research and decides, well, if they like any old fish they see, then offer the least expensive ones so they get the highest profit margin.

CatCorp, their competitors, ran the same survey; however, they offered all 100 participants their own glass of water to knock over — with a fish inside, even!

Only 10 of their 100 cats started, but did not finish the survey. And the same 10 lazy cats from the other survey didn’t show up to this one, either.

So, there were 90 respondents and 80 completed surveys. CatCorp achieved an 88% completion rate (80 divided by 90), which recorded that most cats don’t care, but some really want salmon. CatCorp made salmon available and enjoyed higher profits than the Kitty Committee.

So you see, the higher your survey completion rates, the more reliable your data is. From there, you can make solid, data-driven decisions that are more accurate and effective. That’s the goal.

We measure the completion rates to be able to say, “Here’s how sure we can feel that this information is accurate.”

And if there’s a Maine Coon tycoon looking to invest, will they be more likely to do business with a cat food company whose decision-making metrics are 72% accurate or 88%? I suppose it could depend on who’s serving salmon.

While math was not my strongest subject in school, I had the great opportunity to take several college-level research and statistics classes, and the software we used did the math for us. That’s why I used 100 cats — to keep the math easy so we could focus on the importance of building reliable data.

Now, we’re going to talk equations and use more realistic numbers. Here’s the formula:

Completion rate equals the # of completed surveys divided by the # of survey respondents.

So, we need to take the number of completed surveys and divide that by the number of people who responded to at least one of your survey questions. Even just one question answered qualifies them as a respondent (versus nonrespondent, i.e., the 10 lazy cats who never show up).

Now, you’re running an email survey for, let’s say, Patton Avenue Pet Company. We’ll guess that the email list has 5,000 unique addresses to contact. You send out your survey to all of them.

Your analytics data reports that 3,000 people responded to one or more of your survey questions. Then, 1,200 of those respondents actually completed the entire survey.

3,000/5000 = 0.6 = 60% — that’s your pool of survey respondents who answered at least one question. That sounds pretty good! But some of them didn’t finish the survey. You need to know the percentage of people who completed the entire survey. So here we go:

Completion rate equals the # of completed surveys divided by the # of survey respondents.

Completion rate = (1,200/3,000) = 0.40 = 40%

Voila, 40% of your respondents did the entire survey.

Response Rate vs. Completion Rate

Okay, so we know why the completion rate matters and how we find the right number. But did you also hear the term response rate? They are completely different figures based on separate equations, and I’ll show them side by side to highlight the differences.

  • Completion Rate = # of Completed Surveys divided by # of Respondents
  • Response Rate = # of Respondents divided by Total # of surveys sent out

Here are examples using the same numbers from above:

Completion Rate = (1200/3,000) = 0.40 = 40%

Response Rate = (3,000/5000) = 0.60 = 60%

So, they are different figures that describe different things:

  • Completion rate: The percentage of your respondents that completed the entire survey. As a result, it indicates how sure we are that the information we have is accurate.
  • Response rate: The percentage of people who responded in any way to our survey questions.

The follow-up question is: How can we make this number as high as possible in order to be closer to a truer and more complete data set from the population we surveyed?

There’s more to learn about response rates and how to bump them up as high as you can, but we’re going to keep trucking with completion rates!

What’s a good survey completion rate?

That is a heavily loaded question. People in our industry have to say, “It depends,” far more than anybody wants to hear it, but it depends. Sorry about that.

There are lots of factors at play, such as what kind of survey you’re doing, what industry you’re doing it in, if it’s an internal or external survey, the population or sample size, the confidence level you’d like to hit, the margin of error you’re willing to accept, etc.

But you can’t really get a high completion rate unless you increase response rates first.

So instead of focusing on what’s a good completion rate, I think it’s more important to understand what makes a good response rate. Aim high enough, and survey completions should follow.

I checked in with the Qualtrics community and found this discussion about survey response rates:

“Just wondering what are the average response rates we see for online B2B CX surveys? […]

Current response rates: 6%–8%… We are looking at boosting the response rates but would first like to understand what is the average.”

The best answer came from a government service provider that works with businesses. The poster notes that their service is free to use, so they get very high response rates.

“I would say around 30–40% response rates to transactional surveys,” they write. “Our annual pulse survey usually sits closer to 12%. I think the type of survey and how long it has been since you rendered services is a huge factor.”

Since this conversation, “Delighted” (the Qualtrics blog) reported some fresher data:

survey completion rate vs number of questions new data, qualtrics data

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The takeaway here is that response rates vary widely depending on the channel you use to reach respondents. On the upper end, the Qualtrics blog reports that customers had 85% response rates for employee email NPS surveys and 33% for email NPS surveys.

A good response rate, the blog writes, “ranges between 5% and 30%. An excellent response rate is 50% or higher.”

This echoes reports from Customer Thermometer, which marks a response rate of 50% or higher as excellent. Response rates between 5%-30% are much more typical, the report notes. High response rates are driven by a strong motivation to complete the survey or a personal relationship between the brand and the customer.

If your business does little person-to-person contact, you’re out of luck. Customer Thermometer says you should expect responses on the lower end of the scale. The same goes for surveys distributed from unknown senders, which typically yield the lowest level of responses.

According to SurveyMonkey, surveys where the sender has no prior relationship have response rates of 20% to 30% on the high end.

Whatever numbers you do get, keep making those efforts to bring response rates up. That way, you have a better chance of increasing your survey completion rate. How, you ask?

Tips to Increase Survey Completion

If you want to boost survey completions among your customers, try the following tips.

1. Keep your survey brief.

We shouldn’t cram lots of questions into one survey, even if it’s tempting. Sure, it’d be nice to have more data points, but random people will probably not hunker down for 100 questions when we catch them during their half-hour lunch break.

Keep it short. Pare it down in any way you can.

Survey completion rate versus number of questions is a correlative relationship — the more questions you ask, the fewer people will answer them all. If you have the budget to pay the respondents, it’s a different story — to a degree.

“If you’re paying for survey responses, you’re more likely to get completions of a decently-sized survey. You’ll just want to avoid survey lengths that might tire, confuse, or frustrate the user. You’ll want to aim for quality over quantity,” says Pamela Bump, Head of Content Growth at HubSpot.

2. Give your customers an incentive.

For instance, if they’re cats, you could give them a glass of water with a fish inside.

Offer incentives that make sense for your target audience. If they feel like they are being rewarded for giving their time, they will have more motivation to complete the survey.

This can even accomplish two things at once — if you offer promo codes, discounts on products, or free shipping, it encourages them to shop with you again.

3. Keep it smooth and easy.

Keep your survey easy to read. Simplifying your questions has at least two benefits: People will understand the question better and give you the information you need, and people won’t get confused or frustrated and just leave the survey.

4. Know your customers and how to meet them where they are.

Here’s an anecdote about understanding your customers and learning how best to meet them where they are.

Early on in her role, Pamela Bump, HubSpot’s Head of Content Growth, conducted a survey of HubSpot Blog readers to learn more about their expertise levels, interests, challenges, and opportunities. Once published, she shared the survey with the blog’s email subscribers and a top reader list she had developed, aiming to receive 150+ responses.

“When the 20-question survey was getting a low response rate, I realized that blog readers were on the blog to read — not to give feedback. I removed questions that wouldn’t serve actionable insights. When I reshared a shorter, 10-question survey, it passed 200 responses in one week,” Bump shares.

Tip 5. Gamify your survey.

Make it fun! Brands have started turning surveys into eye candy with entertaining interfaces so they’re enjoyable to interact with.

Your respondents could unlock micro incentives as they answer more questions. You can word your questions in a fun and exciting way so it feels more like a BuzzFeed quiz. Someone saw the opportunity to make surveys into entertainment, and your imagination — well, and your budget — is the limit!

Your Turn to Boost Survey Completion Rates

Now, it’s time to start surveying. Remember to keep your user at the heart of the experience. Value your respondents’ time, and they’re more likely to give you compelling information. Creating short, fun-to-take surveys can also boost your completion rates.

Editor’s note: This post was originally published in December 2010 and has been updated for comprehensiveness.

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Take back your ROI by owning your data

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Treasure Data 800x450

Treasure Data 800x450

Other brands can copy your style, tone and strategy — but they can’t copy your data.

Your data is your competitive advantage in an environment where enterprises are working to grab market share by designing can’t-miss, always-on customer experiences. Your marketing tech stack enables those experiences. 

Join ActionIQ and Snowplow to learn the value of composing your stack – decoupling the data collection and activation layers to drive more intelligent targeting.

Register and attend “Maximizing Marketing ROI With a Composable Stack: Separating Reality from Fallacy,” presented by Snowplow and ActionIQ.


Click here to view more MarTech webinars.


About the author

Cynthia RamsaranCynthia Ramsaran

Cynthia Ramsaran is director of custom content at Third Door Media, publishers of Search Engine Land and MarTech. A multi-channel storyteller with over two decades of editorial/content marketing experience, Cynthia’s expertise spans the marketing, technology, finance, manufacturing and gaming industries. She was a writer/producer for CNBC.com and produced thought leadership for KPMG. Cynthia hails from Queens, NY and earned her Bachelor’s and MBA from St. John’s University.

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