You are in the middle of a meeting; ideas are swirling around you. One idea, in particular, catches your attention, planting a seed of possibility in your mind. It's a good feeling, this spark of innovation, but it begs the question: What do your consumers think about it? What are they ready to do?

You don't trust your memory. So, you start typing out your idea in your notepad.

The meeting drones on, but your screen starts blinking—a sign that something is demanding your immediate attention. You glance at your tablet to find a message waiting for you:

"Your idea has merit. 73% of your target audience is in favour of trying it out. You should go ahead with a pilot."

You sit up straighter. The "Engine" has processed your written note, understood its target, surveyed the audience, and returned with results and a straightforward go-ahead—all in minutes.

Does this scenario sound like a snippet from a science fiction novel? 

Think again. 

Thanks to technological advances and the broader world of synthetic data, we're on the cusp of making this a reality. This is where the future begins. 

In a landscape where synthetic data generation becomes a crucial tool, we're not just guessing what the market wants; we're knowing it—often before the market knows itself. Synthetic data is reshaping how we approach innovation, offering a glimpse into consumer behaviour and preferences with a speed and precision we've never seen before.

**

What do we do today? 

We find answers.

We want to deep-profile customers and our prospects.

We want to find out what's in the customer's mind.

What will they do today under specific environments and trigger conditions?

What will their view be about a new packaging, service, or idea?

People. We can ask.

How about questioning “Synthetic people”?

**

Welcome to the world of synthetic data:

Synthetic data is artificial data that mimics the statistical properties of real-world data without compromising individual privacy. Imagine you have a collection of data on customer preferences and responses gathered over time. This data is then fed into an algorithm that you train. The engine processes this information and generates mock data, effectively expanding your original dataset. This process, known as "upsampling," has significant applications.

The resulting synthetic data looks and behaves like the real data we obtain from the world around us. It's a safe, fabricated set of data that enables businesses to understand what customers might like or dislike without needing to question them directly.

What are the possibilities of synthetic data in decision-making?

• An on-demand dataset for the insight teams. Idea-testing in real-time!

• Find out more. Map out scenarios and the possibilities. All within the laid down rules for legal and ethical compliance.

• Rapid iteration and Idea optimization: Simulate consumer responses to new products or changes in existing ones in a virtual setting. Accelerate product development while reducing the costs and risks associated with physical market testing.

• (Near) Realistic behaviour models: Simulate reactions to new products, packaging, messaging, or marketing strategies. Such data will enhance decision-making, the accuracy of market forecasts, and the effectiveness of marketing initiatives. It is good to find out how a brand's Super-promoters and detractors will act on specific cues. We can test/find out the extremes in behaviour.

• Tailor branding messages: Hyper-personalization and customization are possible through deeper market segmentation. Personalized marketing efforts will help reach out to diverse customers and micro-markets, leading to increased brand loyalty.

• Synthetic image generation, enhanced product visualisation, dynamic scenario testing, VR consumer engagement, and A/B testing at scale are some of the possibilities. 

• What are you working on today?
  
  

Who is already doing something now?

A lot of experimentation is going on. Here are three firms that I am tracking today.

• MOSTLY.AI provides tools that generate synthetic data that can be used for a multitude of purposes, including NLP tasks, computer vision projects, and more. 

• Neurolabs provides CPG brands with synthetic data-driven solutions to optimize store execution and boost revenue. Their technology, such as the ZIA (Zero Image Annotations) tool, utilizes synthetic computer vision to create realistic 3D digital twins of SKUs from minimal initial data.

• Yabble is making significant strides in using synthetic data for market research, offering innovative solutions that leverage artificial intelligence for data creation and analysis. Their technology, Virtual Audiences, represents a significant advancement in the industry, allowing for the generation of accurate, deep, and meaningful insights on almost any topic without the need for traditional fieldwork. 

  
  

A Use-case example specific to healthcare: 

Digital twin technology in healthcare represents a cutting-edge application of synthetic data. It involves creating virtual replicas of physical healthcare systems or processes, allowing for real-time simulation and prediction of behaviours. This technology will revolutionize patient care by enabling personalized treatment plans and optimizing healthcare operations. For instance, digital twins could simulate patient responses to different treatment options, helping medical professionals tailor interventions for the best outcomes. Additionally, by modelling hospital operations, digital twins can improve efficiency, reduce costs, and enhance patient care through strategic resource allocation and management.

What does this mean for you and me?

Experiment or die.

You can run, but you can't hide!

With newer companies with alternate models of reaching and satisfying customers, we need to keep running.

Synthetic data gives us many reasons to reboot our ideation and execution loop cycle.This is a new era of privacy-preserving, highly personalized experiences without compromising our data security.

Test ideas and products virtually before they even hit the market, drastically reducing the risk of flops and enhancing the chances of success.

We are stepping into a future where our digital interactions can be tailored to our exact preferences. We must remain vigilant about how these capabilities are used. The potential for misuse and the implications for privacy and consent are real concerns that need addressing.

Synthetic data is reshaping decision-making and everything we know about it.

When used well, it is a win-win.

For corporates, it opens new opportunities and growth.

For customers, they get to enjoy more relevant and engaging experiences.

What next?

Synthetic data is changing the game.

It is also changing our roles and how we execute it.

This article is a brief primer to trigger you into the world of synthetic data (if you aren't already).