How many ads do you see on social media? It might be more than you realize. Scientists studying how ads work on Instagram-style social media have found that people are not as good at spotting them as they think. If people recognized ads, they usually ignored them – but some, designed to blend in with your friends’ posts, flew under the radar.

“We wanted to understand how ads are really experienced in daily scrolling — beyond what people say they notice, to what they actually process,” said Maike Hübner, PhD candidate at the University of Twente, corresponding author of the article in Frontiers in Psychology. “It’s not that people are worse at spotting ads. It’s that platforms have made ads better at blending in. We scroll on autopilot, and that’s when ads slip through. We may even engage with ads on purpose, because they’re designed to reflect the trends or products our friends are talking about and of course we want to keep up. That’s what makes them especially hard to resist.”

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The scientists wanted to test how much time people spent looking at sponsored versus organic posts, how they looked at different areas of these different posts, and how they behaved after realizing they were looking at sponsored content. They randomly assigned 152 participants, all of whom were regular Instagram users, to one of three mocked-up social media feeds, each of which was made up of 29 posts — eight ads and 21 organic posts. 

They were asked to imagine that the feed was their own and to scroll through it as they would normally. Using eye-tracking software, the scientists measured fixations — the number of times a participant’s gaze stopped on different features of a post — and dwell time, how long the fixations last. A low dwell time suggests that someone just noticed the feature, while a high dwell time might indicate they were paying attention. After each session, the scientists interviewed the participants about their experience.

Although people did notice disclosures when they were visible, the eye-tracking data suggested that participants paid more attention to calls to action — like a link to sign up for something — which could indicate that this is how they recognize ads. Participants were also quick to recognize an ad by the profile name or verification badge of a brand’s official account, or glossy visuals, which caused participants to express distrust. 

“People picked up on design details like logos, polished images, or ‘shop now’ buttons before they noticed an actual disclosure,” said Hübner. “On brand posts, that label is right under the username at the top, while on influencer content or reels, it might be hidden in a hashtag or buried in the ‘read more’ section.”

Although the scientists found that the ads often went unnoticed, if people realized that the content wasn’t organic, many of them stopped engaging with the post. Dwell time dropped immediately.

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This was less likely to happen to ads that blended in better, with less polished visuals and a tone and format more typical of organic content. If ad cues like disclosures or call-to-action buttons weren’t noticed right away, they got similar levels of engagement to organic posts. 

“Many participants were shocked to learn how many ads they had missed. Some felt tricked, others didn’t mind — and that last group might be the most worrying,” said Hübner. “When we stop noticing or caring that something is an ad, the boundary between persuasion and information becomes very thin.”

The scientists say these findings show that transparency goes well beyond just labelling ads. Understanding how people really process ads should lead to a rethink of platform design and regulation to make sure that people know when they’re looking at advertising. 

However, this was a lab-based study with simulated feeds, and it’s possible that studies on different cultures, age groups, or types of social media might get different results. It’s also possible that ads are even harder to recognize under real-life conditions.

“Even in a neutral, non-personalized feed, participants struggled to tell ads apart from regular content,” Hübner pointed out. “In their own feeds which are shaped around their interests, habits, and social circles it might be even harder to spot ads, because they feel more familiar and trustworthy.”

Personalized pricing, where merchants adjust prices according to the pile of data about a consumer’s willingness to pay, has been criticized for its potential to unfairly drive-up prices for certain customers.

But new research shows that the practice can also hurt sellers’ profits.

Consumers commonly experience personalized pricing through digital coupons or other discount offers they receive either as potential customers or after making a purchase. Other recent examples include the practice of “Buy Now, Pay Later” plans that bundles the sale of a product with a subsidized loan, which can offer different prices to different customers based on their willingness to pay, and airlines using artificial intelligence to customize prices for individual airfares.

Companies can tweak their prices according to data about a customer’s digital footprint, including their buying preferences, location, lifestyle and even what kind of digital device and operating system they use—all in pursuit of squeezing maximum profit out of the buyer.

The downside though, says Liyan Yang, a professor of finance and the Peter L. Mitchelson/SIT Investment Associates Foundation Chair in Investment Strategy at the University of Toronto’s Rotman School of Management, is that this practice typically obscures the price information available to other consumers, an important factor in their decision to buy.

When prices are transparent to everyone and they’re low, “you know that on average, more people will be buying,” says Prof. Yang.

But if part of the product’s value depends on how many people are using it, think a social media network or e-commerce platform, not being able to see what others are being charged means consumers are fuzzier about how many people are likely to buy in and join the network.

The upshot? “Consumers are going to spend less,” says Prof. Yang.

The researcher put those ideas under a theoretical microscope when he and former Rotman PhD student Yan Xiong, who is now an associate professor at University of Hong Kong Business School, used mathematics and game theory to model what happens when consumers can’t see what other people are being charged for a network-based product. Their models revealed that a company ultimately charged more when prices were concealed compared to when they were transparent, leading to lower profits.

Luckily for companies, there are workarounds. Using similar modelling, the researchers found that the profit pitfall could be avoided through some kind of corporate commitment or backstop related to keeping prices low even as a company also pursued profits.

That could be done by the company committing to keep prices within a certain range or at least to lowering prices through a corporate social responsibility program, by developing a good reputation among consumers, by initially offering low prices that are transparent to attract consumers with a lower price threshold, or through the use of price caps either mandated by government or voluntarily adopted by the company.

Another option is for a government to require companies to charge the same price to all customers, a strategy promoted in China, the European Union and the United States where personalized pricing practices have become an issue.

While companies typically dislike regulation, Prof. Yang points out that theoretically at least, some form of price restriction may lead to better corporate profits in the end.

 “There are trade-offs,” he says, adding that regulators would have to “gauge precisely” where the limits should be to hit the pricing sweet spot that optimizes profits to the company.

The study appeared in the Journal of Economic Theory.

As intimidating and complex artificial intelligence (AI) tools may be, micro, small, and medium enterprises (MSMEs) should take gradual but steady steps towards exploring how these could make operations more efficient and scalable, according to Converge ICT Solutions Inc. CEO and 51st Philippine Business Conference and Expo (PBC&E) Chairman Dennis Anthony Uy. 

Speaking before the North Luzon Area Business Conference of the Philippine Chamber of Commerce and Industry (PCCI) held in Bataan province, Uy championed technology adoption, especially in the face of widespread use of new technologies such as generative AI. 

“Companies all over the world are trying to adapt to AI. Here in the Philippines, we’re barely scratching the surface. And the smaller businesses, which are just starting to embrace digitalization, have to learn new ways of doing business with the growing pervasiveness of these new technologies,” said Uy.

“AI is not just for medium to large companies. Micro and small businesses can also find a foothold in the use of the game-changing technology,” he added. “With AI adoption, MSMEs can potentially increase efficiency, reduce costs, and drive competitive edge.”

Coming from a trip to Taiwan which is known as the global hub for the semiconductor industry, Uy noted that artificial intelligence is making its way through the manufacturing value chains of most technology sectors.

“If the Philippines can find a niche spot in this value chain, the multiplier to employment, skills and knowledge upgrading, and the effect on downstream industries is massive,” he said. “While micro and small businesses may not yet be able to participate in these larger value chains, where they can benefit from is by taking small steps in adapting AI tools,” noted Uy. 

From the part of the local government, Bataan Governor Jose Enrique “Joet” Garcia III pledged his support to make his province “future-ready” by hosting start-ups and supporting digitally-enabled businesses.

“We want to express the support of the provincial government of Bataan, of course together with all the local government units for the creative and innovative industry. We know this sector is the key to accelerate more productivity and growth, especially for the youth who were born adept to digital devices,” noted Garcia. 

The possibilities of AI use were experienced first-hand by micro and small businesses in the Byte Forward Hackathon jointly organized by Converge, PCCI, the Department of Trade and Industry, and Converge subsidiary Rev21 Labs. 

Converge and the participating small businesses came up with problem statements stemming from actual pain points experienced in the course of business. Ten teams of third and fourth year college students from Bataan came up with solutions aided by AI tools. 

Artificial intelligence will come into bigger focus in the 51st Philippine Business Conference and Expo organized by the PCCI. As Chairman of the Conference, Uy deliberately made the move to make the event ‘technology-forward’ and bring modern, digital solutions to MSMEs. The Conference will be held on October 20-12 at the SMX Convention Center.