Syno International

16/10/2026

: a test audience basically saved two movie characters from being eaten. 🌱🎬

The 1986 Little Shop of Horrors originally had a much darker ending:

👉 Audrey II wins.
👉 Seymour and Audrey die.
👉 Giant plants take over New York.

Then came the test screenings.

People had been laughing and enjoying the film… until the main characters died. 😅

A second screening got a similar reaction, so the ending was reshot and the theatrical version became much happier.

📊 A pretty wild example of audience research in action: sometimes feedback doesn’t just review the product - it changes it.

09/10/2026

: same drink, lower price, worse result. 👀

In a 2005 study, people drank the same SoBe energy drink before solving puzzles.

👉 $1.89 - better performance
👉 $0.89 - worse performance

Same drink. But different price tag!

💡 Researchers linked the difference to expectations: paying less may have made the drink seem less effective, which may have influenced performance.

So apparently, a discount can change more than the bill. 😄

02/10/2026

: spin first - think later. 🎡

In a classic 1974 study, people first saw a wheel land on 10 or 65.

Then they estimated the percentage of African countries in the United Nations.

The wheel number was completely irrelevant.

And yet:

👉 saw 10 - median estimate 25%
👉 saw 65 - median estimate 45%

That’s anchoring: an unrelated number can still pull our judgment toward it.

Sometimes a number just needs to show up first. 📊

30/09/2026

Data can be compliant on paper. Trust takes a bit more. 🔒

As AI becomes part of everyday data workflows, businesses need to understand not just what they can do with data, but how they can explain it.

Our General Counsel, Jurgita Sakalauskieneė, unpacks that in the latest Syno newsletter.

Worth a read. 👇

📌 https://www.linkedin.com/pulse/data-ai-trust-why-compliant-only-beginning-synoint-abcsf

AI is making data easier to use. And harder to explain A dataset enters an AI tool.

25/09/2026

: you chose this jam. Or did you? 🍓👀

In a 2010 Lund University study, shoppers picked their favourite jam or tea and explained why.

Plot twist: researchers sometimes secretly swapped the samples.

So people were occasionally tasting the option they had just rejected - and in roughly two-thirds of manipulated trials, they didn’t notice.

Even with very different flavours like Cinnamon-Apple vs. bitter Grapefruit, many still explained why they preferred what was in front of them.

Researchers call this choice blindness.

Sometimes, the story we tell about why we chose something comes after the choice itself. 📊

18/09/2026

: you know how a zipper works… right? 😅

A 2002 Yale study asked people how well they understood everyday things like:

👉 zippers
👉 toilets
👉 speedometers
👉 locks

Then researchers asked them to explain exactly how they worked.

That’s when confidence dropped. 📉

Researchers called it the “illusion of explanatory depth” - we often think we understand something much better than we actually do, until we have to explain it.

So… how does a zipper work? 👀

14/09/2026

Skål! 🥂

This year’s Crayfish Party, organised by the Swedish Chamber of Commerce in Lithuania, was another festive hit. 🦞

Our Syno teammates joined the celebration, where snaps songs were sung, Swedish dishes were enjoyed, and a wonderful community came together.

Thank you for another lovely evening, everyone. What an event!☀️

11/09/2026

: apparently, 10% of this survey sample had been to space. 🚀

Pew Research Center tested ways of spotting bogus respondents in online opt-in surveys by adding questions where the truthful answer was almost certainly “no”.

One was:

👉 “Have you ever visited the International Space Station?”

10% said yes. 😄

Others claimed to use a fake social platform or receive payments from a U.S. agency that had stopped existing in 1920.

Overall, 18% said yes to at least one trap question and were flagged by the screening method.

Moral of the story?

A completed survey doesn’t automatically mean good data. 📊

11/09/2026

A customer visits your pricing page three times.

So, are they planning to buy? Maybe.

Or maybe they’re comparing options for work, researching for someone else, or simply curious.🤷‍♀️
Clicks, website visits and purchase histories can tell us a lot about what people do. But the reason behind those actions is often still missing.

This is where zero-party data comes in. ⬇️

It’s information people intentionally choose to share with a business: preferences, interests, purchase intentions, expectations and brand perceptions. But better data doesn’t always mean more data.

In our latest article, we look at:
➡️ What zero-party data actually means
➡️ How it differs from first-party and third-party data
➡️ Why it can add useful context to behavioural data
➡️ How surveys can help collect it
➡️ The common mistakes that can weaken its value

📌Take a look: https://www.synoint.com/blog/2026-08-17-what-is-zero-party-data/

04/09/2026

: one word changed the answer, and maybe the memory too. 👀

In a famous 1974 study, people watched car accidents and were asked how fast the cars were going when they:

👉 “bumped”
👉 “hit”
👉 “smashed”

Stronger wording led to higher speed estimates.

And it got weirder.

One week later, 32% of the “smashed” group said they remembered broken glass.

There was none. 🤷‍♀️

In the “hit” group, only 14% said the same.

One tiny word. Very different answers.

HOW we ask can influence WHAT people tell us.