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How marketers can use cognitive biases to influence customer decisions

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How marketers can use cognitive biases to influence customer decisions

You’re not rational — and neither are your customers. In an effort to make efficient decisions, the human brain takes shortcuts. As such, your customers rely on a variety of heuristics and cognitive biases to make decisions efficiently. And they don’t even know it. 

The utilitarian theory of economic behavior, postulated by 19th-century philosopher John Stuart Mill, suggested that all economic decisions were rational. It was a rational thought at the time, but it failed to consider how the brain worked in real-world situations. 

People, including your customers, tend to make decisions that don’t always make sense, often succumbing to the biases lurking below the surface. As a marketer, you can yield more influence by understanding how your customers’ behaviors are influenced by cognitive biases and psychological processes that lead to better — and sometimes worse — decisions. 

In this article, let’s explore three cognitive biases you can use to shape how customers think about your product or service while interacting with your brand. 

Cognitive bias 1: The framing effect 

In the article, the researchers presented findings from a study in which participants were given a choice about a life and death scenario.

Given the stakes, how did the researchers frame the different treatment options? The first treatment was framed around saving 200 lives whereas the second treatment was framed around a 1/3 probability that 600 people would be saved along with a 2/3 probability that everyone will perish. 

Which outcome do you prefer? If you’re like most people, you selected the treatment as the life-saving option, which is likely to result in 200 saved lives. But do you see something unusual about the treatment options? Regardless of which treatment you selected, 200 people are likely to survive and 400 are likely to perish (and only the first treatment, the one you selected, will certainly result in the death of 400 people). 

Despite offering “equal expected value” according to the researchers, participants overwhelmingly selected the first treatment (72% to 28%). The impact of the framing effect was starting to come into focus. 

Today the framing effect is alive and well. And marketers are making good use of it. In a world with COVID-19 concerns, household cleaning items are using the framing effect. In an industry with a projected global value of $46.9 billion by 2026, the Reckitt Benckiser Group, the maker of Lysol Disinfectant Max Cover Mist, claims that 

the disinfectant “kills 99.9% of viruses and bacteria.” Would you be more or less likely to buy the same product if it claimed to allow 1% of viruses to survive? 

The good times are not limited to cleaning products. Mission Foods, for example, found success by labeling its large flour tortillas as 95% fat-free. That certainly sounds a lot better than offering a tortilla that’s loaded with 5% fat. How about Haleon, the maker of Sensodyne toothpaste? Using a combination of three cognitive biases (social proof, authority, and the framing effect), Haleon claims that nine of 10 dentists recommend Sensodyne. That’s more appealing than a message claiming that only one of 10 dentists don’t like Sensodyne. 

How are you communicating your product or service? Remember, your customers unknowingly evaluate your value proposition based on how you frame it. And you don’t need to highlight statistics or numbers to do so. You can use the framing effect when you craft your message relative to what’s important to your audience — and then you can watch it take hold. 

Read next: Using psychology and better data practices to get customers closer to purchase

Cognitive bias 2: The decoy effect 

The decoy is all around you — and you probably don’t even know it. What’s even more interesting is that it can guide your customer’s decision at the time of purchase. Known as asymmetrical domination, the decoy effect pertains to an intentionally placed offering intended to increase the probability of selecting an alternative option. 

The Economist, a British economic and world news publication used the decoy effect to drive sales to its preferred subscription tier. Consider the following offers: 

  • Digital-Only Subscription: $59
  • Digital and Print Subscription: $125 

To nudge buyers towards the higher price point, the marketers at the Economist added another option: 

  • Print-Only Subscription: $125

Yes, the new option was priced the same as the digital and print version, but it didn’t include access to digital content. As you might imagine, the print-only option was never intended to solicit any real consideration. Instead, it was a decoy. 

Dan Ariely, a former professor of psychology and behavioral economics at MIT, learned about the pricing strategy at the Economist and wanted to learn how the decoy effect influenced behavior among his students. Using the same pricing tiers as the Economist, Ariely surveyed his students to select one of the subscription options. What happened? A whopping 84% selected the most expensive option for the $125 bundle, whereas only 16% selected the digital-only offering at $59. 

But did the decoy really play a big role in nudging students towards the $125 bundle? To find out, Ariely surveyed a second group of students. After eliminating the decoy, the percentage of students who selected the $125 bundle dropped from 84% to 32%. As such, Ariely discovered that participants became significantly more likely to choose the higher-priced option in the presence of a decoy. 

How can you create a decoy in your line of business? As you think about leveraging the decoy effect, you must keep in mind that you want the price of the decoy to be close enough to the preferred item while offering dramatically inferior features. In other words, you want the decoy to be significantly less feature-rich than the preferred option but only slightly more feature-rich than the least expensive option. 

Imagine that you work for a streaming service that’s considering a new pricing strategy for access to its content library. The audience to whom the service appeals enjoy consuming exclusive movies, documentaries and podcasts on the platform. And according to new survey data, customers are willing to pay around $10 per month for access to your content. But your business strategy requires you to nudge a percentage of your customers into a higher price tier. 

How could you use the decoy effect to increase the price your customers are willing to pay for a monthly membership? You can start by creating an introductory tier that aligns with the survey data and offer access to a limited library of movies at $9.99. Next, you want to focus on the desired price point, which is, say $14.99. At this price, your customers can access all movies, documentaries and podcasts. 

Knowing that most customers like to consume each type of content equally, you can create a decoy that offers access to all movies for $13.99. After all, this is the decoy. As you can see, the decoy offers an expanded version of the first offer but doesn’t provide access to the various types of content your audience wants. As a result, your customers start to perceive the $14.99 option as a value choice — even though it represents the highest price point. 

The goal is to use the decoy effect to nudge your customers towards a specific choice. Once the decoy is in place, your customers begin comparing the company-preferred option (the bundled option in the Economist example and the $14.99 option in the above scenario) against the decoy. And if you create a large enough gap in value while maintaining a small enough gap in price, you might find yourself with more high-paying customers. 


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Cognitive bias 3: Frequency bias 

Frequency bias is something that can alter perception over time. When a person encounters something new, whether a new word, a slogan, an idea or a product, frequency bias posits that the person perceives the new thing to appear more frequently. It might seem like the new item is everywhere. Have you ever been introduced to a new product and noticed more of the same advertisements at every turn? 

According to Anina Rich, a Professor in the School of Psychological Sciences at Macquarie University in Sydney, Australia, frequency bias is related to working memory-driven attentional capture — a process by which specific environmental stimuli attract your attention because it’s now occupying a space in your mind. Interestingly, the new word, phrase, idea, or product that’s occupying your mind is likely occupying it below the level of consciousness. As Rich puts it, “what you are thinking about unconsciously guides you to relevant information in the environment.”2

Frequency bias is particularly relevant in marketing within the context of a larger campaign. Do you have one marketing channel through which you can more easily capture your customer’s attention — and then carefully place your message in other areas that can draw upon this subconscious phenomenon? 

By understanding that people perceive repetitive information with greater frequency after initial exposure, you can be more diligent in how you build your multichannel marketing strategy. Specifically, you can develop a strategy in which you emphasize capturing attention across a highly engaged channel, thus setting the stage for your message appearing everywhere during the course of your campaign. 

Read next: How anthropology can drive insights from your customer data

Conclusion 

Cognitive biases constantly pull the decision-making strings inside your customers’ heads. Do you see yourself as a marketing puppeteer? As you attempt to build a rational marketing strategy, you might want to remember that your customers don’t always make rational decisions. And that understanding must inform part of your marketing strategy. 

1Amos Tversky, Daniel Kahneman, “The Framing of Decisions and the Psychology of Choice,https://www.science.org/doi/10.1126/science.7455683

2Anina Rich, “What Is the Baader Meinhof Phenomenon?, https://lighthouse.mq.edu.au/article/july-2020/What-is-the-Baader-Meinhof-Phenomenon


Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.


About The Author

Jade Bunke is the vice president of marketing at National Technical Systems and is a leading authority in marketing science, messaging and demand generation. As a marketing scientist with expertise in buyer behavior, Bunke blends creative marketing with aspects of cognitive neuroscience, social psychology and behavioral economics to yield optimal results.

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YouTube Ad Specs, Sizes, and Examples [2024 Update]

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YouTube Ad Specs, Sizes, and Examples

Introduction

With billions of users each month, YouTube is the world’s second largest search engine and top website for video content. This makes it a great place for advertising. To succeed, advertisers need to follow the correct YouTube ad specifications. These rules help your ad reach more viewers, increasing the chance of gaining new customers and boosting brand awareness.

Types of YouTube Ads

Video Ads

  • Description: These play before, during, or after a YouTube video on computers or mobile devices.
  • Types:
    • In-stream ads: Can be skippable or non-skippable.
    • Bumper ads: Non-skippable, short ads that play before, during, or after a video.

Display Ads

  • Description: These appear in different spots on YouTube and usually use text or static images.
  • Note: YouTube does not support display image ads directly on its app, but these can be targeted to YouTube.com through Google Display Network (GDN).

Companion Banners

  • Description: Appears to the right of the YouTube player on desktop.
  • Requirement: Must be purchased alongside In-stream ads, Bumper ads, or In-feed ads.

In-feed Ads

  • Description: Resemble videos with images, headlines, and text. They link to a public or unlisted YouTube video.

Outstream Ads

  • Description: Mobile-only video ads that play outside of YouTube, on websites and apps within the Google video partner network.

Masthead Ads

  • Description: Premium, high-visibility banner ads displayed at the top of the YouTube homepage for both desktop and mobile users.

YouTube Ad Specs by Type

Skippable In-stream Video Ads

  • Placement: Before, during, or after a YouTube video.
  • Resolution:
    • Horizontal: 1920 x 1080px
    • Vertical: 1080 x 1920px
    • Square: 1080 x 1080px
  • Aspect Ratio:
    • Horizontal: 16:9
    • Vertical: 9:16
    • Square: 1:1
  • Length:
    • Awareness: 15-20 seconds
    • Consideration: 2-3 minutes
    • Action: 15-20 seconds

Non-skippable In-stream Video Ads

  • Description: Must be watched completely before the main video.
  • Length: 15 seconds (or 20 seconds in certain markets).
  • Resolution:
    • Horizontal: 1920 x 1080px
    • Vertical: 1080 x 1920px
    • Square: 1080 x 1080px
  • Aspect Ratio:
    • Horizontal: 16:9
    • Vertical: 9:16
    • Square: 1:1

Bumper Ads

  • Length: Maximum 6 seconds.
  • File Format: MP4, Quicktime, AVI, ASF, Windows Media, or MPEG.
  • Resolution:
    • Horizontal: 640 x 360px
    • Vertical: 480 x 360px

In-feed Ads

  • Description: Show alongside YouTube content, like search results or the Home feed.
  • Resolution:
    • Horizontal: 1920 x 1080px
    • Vertical: 1080 x 1920px
    • Square: 1080 x 1080px
  • Aspect Ratio:
    • Horizontal: 16:9
    • Square: 1:1
  • Length:
    • Awareness: 15-20 seconds
    • Consideration: 2-3 minutes
  • Headline/Description:
    • Headline: Up to 2 lines, 40 characters per line
    • Description: Up to 2 lines, 35 characters per line

Display Ads

  • Description: Static images or animated media that appear on YouTube next to video suggestions, in search results, or on the homepage.
  • Image Size: 300×60 pixels.
  • File Type: GIF, JPG, PNG.
  • File Size: Max 150KB.
  • Max Animation Length: 30 seconds.

Outstream Ads

  • Description: Mobile-only video ads that appear on websites and apps within the Google video partner network, not on YouTube itself.
  • Logo Specs:
    • Square: 1:1 (200 x 200px).
    • File Type: JPG, GIF, PNG.
    • Max Size: 200KB.

Masthead Ads

  • Description: High-visibility ads at the top of the YouTube homepage.
  • Resolution: 1920 x 1080 or higher.
  • File Type: JPG or PNG (without transparency).

Conclusion

YouTube offers a variety of ad formats to reach audiences effectively in 2024. Whether you want to build brand awareness, drive conversions, or target specific demographics, YouTube provides a dynamic platform for your advertising needs. Always follow Google’s advertising policies and the technical ad specs to ensure your ads perform their best. Ready to start using YouTube ads? Contact us today to get started!

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Why We Are Always ‘Clicking to Buy’, According to Psychologists

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Why We Are Always 'Clicking to Buy', According to Psychologists

Amazon pillows.

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A deeper dive into data, personalization and Copilots

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A deeper dive into data, personalization and Copilots

Salesforce launched a collection of new, generative AI-related products at Connections in Chicago this week. They included new Einstein Copilots for marketers and merchants and Einstein Personalization.

To better understand, not only the potential impact of the new products, but the evolving Salesforce architecture, we sat down with Bobby Jania, CMO, Marketing Cloud.

Dig deeper: Salesforce piles on the Einstein Copilots

Salesforce’s evolving architecture

It’s hard to deny that Salesforce likes coming up with new names for platforms and products (what happened to Customer 360?) and this can sometimes make the observer wonder if something is brand new, or old but with a brand new name. In particular, what exactly is Einstein 1 and how is it related to Salesforce Data Cloud?

“Data Cloud is built on the Einstein 1 platform,” Jania explained. “The Einstein 1 platform is our entire Salesforce platform and that includes products like Sales Cloud, Service Cloud — that it includes the original idea of Salesforce not just being in the cloud, but being multi-tenancy.”

Data Cloud — not an acquisition, of course — was built natively on that platform. It was the first product built on Hyperforce, Salesforce’s new cloud infrastructure architecture. “Since Data Cloud was on what we now call the Einstein 1 platform from Day One, it has always natively connected to, and been able to read anything in Sales Cloud, Service Cloud [and so on]. On top of that, we can now bring in, not only structured but unstructured data.”

That’s a significant progression from the position, several years ago, when Salesforce had stitched together a platform around various acquisitions (ExactTarget, for example) that didn’t necessarily talk to each other.

“At times, what we would do is have a kind of behind-the-scenes flow where data from one product could be moved into another product,” said Jania, “but in many of those cases the data would then be in both, whereas now the data is in Data Cloud. Tableau will run natively off Data Cloud; Commerce Cloud, Service Cloud, Marketing Cloud — they’re all going to the same operational customer profile.” They’re not copying the data from Data Cloud, Jania confirmed.

Another thing to know is tit’s possible for Salesforce customers to import their own datasets into Data Cloud. “We wanted to create a federated data model,” said Jania. “If you’re using Snowflake, for example, we more or less virtually sit on your data lake. The value we add is that we will look at all your data and help you form these operational customer profiles.”

Let’s learn more about Einstein Copilot

“Copilot means that I have an assistant with me in the tool where I need to be working that contextually knows what I am trying to do and helps me at every step of the process,” Jania said.

For marketers, this might begin with a campaign brief developed with Copilot’s assistance, the identification of an audience based on the brief, and then the development of email or other content. “What’s really cool is the idea of Einstein Studio where our customers will create actions [for Copilot] that we hadn’t even thought about.”

Here’s a key insight (back to nomenclature). We reported on Copilot for markets, Copilot for merchants, Copilot for shoppers. It turns out, however, that there is just one Copilot, Einstein Copilot, and these are use cases. “There’s just one Copilot, we just add these for a little clarity; we’re going to talk about marketing use cases, about shoppers’ use cases. These are actions for the marketing use cases we built out of the box; you can build your own.”

It’s surely going to take a little time for marketers to learn to work easily with Copilot. “There’s always time for adoption,” Jania agreed. “What is directly connected with this is, this is my ninth Connections and this one has the most hands-on training that I’ve seen since 2014 — and a lot of that is getting people using Data Cloud, using these tools rather than just being given a demo.”

What’s new about Einstein Personalization

Salesforce Einstein has been around since 2016 and many of the use cases seem to have involved personalization in various forms. What’s new?

“Einstein Personalization is a real-time decision engine and it’s going to choose next-best-action, next-best-offer. What is new is that it’s a service now that runs natively on top of Data Cloud.” A lot of real-time decision engines need their own set of data that might actually be a subset of data. “Einstein Personalization is going to look holistically at a customer and recommend a next-best-action that could be natively surfaced in Service Cloud, Sales Cloud or Marketing Cloud.”

Finally, trust

One feature of the presentations at Connections was the reassurance that, although public LLMs like ChatGPT could be selected for application to customer data, none of that data would be retained by the LLMs. Is this just a matter of written agreements? No, not just that, said Jania.

“In the Einstein Trust Layer, all of the data, when it connects to an LLM, runs through our gateway. If there was a prompt that had personally identifiable information — a credit card number, an email address — at a mimum, all that is stripped out. The LLMs do not store the output; we store the output for auditing back in Salesforce. Any output that comes back through our gateway is logged in our system; it runs through a toxicity model; and only at the end do we put PII data back into the answer. There are real pieces beyond a handshake that this data is safe.”

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