Introduction: Generative AI Technology and Synthetic Data

Organizations today face an environment where data collection is riddled with challenges. As company and consumer interests evolve rapidly, it can be difficult to collect sufficient data, let alone high-quality data that accurately and reliably encompasses niche, large, and under-represented demographics. Many companies are looking for new, innovative ways to gain a competitive advantage to enhance decision-making via technology, with synthetic data being of particular interest.

What is Synthetic Data?

Synthetic data is AI generated data that reflects the same statistical properties of the original dataset. Synthetic data looks and feels like real data, but can be generated to represent new knowledge and information - and to extend data beyond what was included in the original collection. It is generated from, retains the structure of, and maintains relationships present in real data, and can be used as real data, but has no direct relationship with input data, removing privacy and security concerns. 

In an increasingly digital world, leading companies must adapt to and integrate the use of sophisticated technologies like artificial intelligence (AI), machine learning (ML), and data analytics to stay ahead of their competition and changes in consumer behaviors. Companies need large volumes of high-quality, reliable data to innovate and deliver more customer-centric products and services in order to stay competitive. In fact, by 2024, Gartner predicts that 60% of the data used for the development of AI and analytics solutions will be synthetically generated (Judah, White, Sicular et al., “Predicts 2021: Data and Analytics Strategies,” Gartner)

AI for CPG?

In the rapidly evolving world of consumer products, data-backed decision-making is paramount. The consumer goods industry is one of the world’s most competitive industries, with thousands of products and brands launching each year - necessitating faster and more cost-effective consumer research. CPG companies, market research firms, and retailers are sitting on an underutilized data resource which, paired with new technology, can be used to enhance their prior research studies as well as consolidate better product market fit. With synthetic data, companies can update and re-use prior studies to make predictions about today while running simulations about the future.

Simulacra Data Studio

Simulacra Synthetic Data Studio supports companies by using the most advanced data generating AI to synthesize new data from real, existing data sets (“seed data”). The AI learns the patterns and relationships in the original input data, producing hundreds to thousands of rows of robust, synthetic data that accurately models and predicts consumer behavior patterns, preserving all conditional probabilities from the seed data with strong guarantees of convergence. The advantage of synthetic data is its flexibility: it can be parameterized at will.  Simulacra SDS is the only synthetic data generator that can generate data meeting any arbitrary set of filters and conditions that could occur from the original seed data. The generated data can thus be customized and parameterized at the user’s discretion: the platform contains dozens of tools that allow companies to simulate shifts in demographic proportions and model changing consumer behavior. The benefits and use cases of synthetic data differ for every company and team. The most common benefits include higher ROI through faster and cost-effective data collection and analysis, new revenue streams through a more comprehensive understanding of consumer behavior, and improved product adoption.

Consumer Packaged Goods and AI: Find Your Market from Existing Data

Specifically for CPG, synthetic data has a number of key, advantageous benefits and use cases. This list is by no means exhaustive. It highlights some primary examples of how CPG companies can utilize synthetic data.

Enhance Consumer Behavior Research
‍The cost of conducting traditional consumer research can be substantial when taking into account time, screening practices, research base sizing, and monetary cost, especially when attempting to collect data on low-incidence products or harder-to-reach demographics. As it ages, previously good data goes to waste since it is no longer relevant to the present and therefore cannot serve as a reliable guide to the future. This results in significant decay in data accuracy. Additionally, traditional data collection methods may carry inherent risks, such as privacy concerns.With synthetic data powered by AI, CPG companies can rapidly generate realistic consumer behavior data from their past consumer surveys and research, cutting down data collection time, and reducing the interval between research and product development or retail changes. Simulacra SDS allows organizations to create impactful datasets that mimic and expand on real consumer interactions, helping them understand consumer preferences, patterns, and trends more strategically and comprehensively. This also provides a cost-effective and risk-free way to explore diverse scenarios without detracting from real-world operations.

‍Accelerate Purchase Intent Studies
‍The ability to predict and understand consumer purchase intent influences all stages of the product life cycle, from supply chain to product development to marketing. Synthetic data enables companies to simulate various purchase scenarios and test the impact of different factors on consumer choice. Users of Simulacra have the ability to parameterize custom scenarios utilizing the built-in real-time causal belief network trained on your generated data - allowing infinite predictive simulations on the impact of different behaviors for the purchases of your consumers. This accelerates the process of identifying what drives consumers to make a purchase, leading to more effective go-to-market, branding, and advertising strategies.

‍Optimize Retail Placement with Shopping Cart Data
‍Understanding cross-category shopping behavior is pivotal for CPG companies, retailers, and distributors looking to optimize their product placement and distribution strategies. Synthetic data provides the means to simulate new co-purchasing and cross-category purchase data that accurately represent the complex relationships between brand availability, distribution, and consumer behavior. This data can drive more effective product bundling, product placement, e-commerce suggestions, pricing strategies, and more. 

‍Simulate the Future You Want
‍CPG companies rely on tabular data for everything from inventory management to sales forecasting to pricing. Simulacra SDS works on any relational tabular dataset - not just consumer behavior research. The Synthetic Data Studio makes it possible to generate synthetic tabular data that aligns with the company's historical records and predicts the desired future state - tested through data generation and simulation. This enables more accurate predictions and enhanced decision-making across various business functions.

Continuous Improvement and Innovation
‍CPG companies must constantly innovate and improve their product offerings. With AI and synthetic data, they can test new product ideas, features, and marketing strategies in a simulated environment. Iterative testing and optimization can lead to more successful product launches, marketing campaigns, and durable consumer product adoption.AI-driven synthetic data, as facilitated by Simulacra Synthetic Data Studio, empowers CPG companies to extract more value from their existing data, gain deeper insights into consumer behavior, and make data-driven decisions with confidence. By embracing this technology, CPG companies can maintain a competitive edge in a dynamic and fast-paced industry, delivering products and experiences that align more closely with consumer preferences and demands.

Conclusion: Stop Running Surveys, Start Running Simulations

Synthetic data has a transformative ability to improve efficiency and speed of data utilization. For CPG companies, integrating synthetic data into business operations yields a high ROI, ranging from stronger product development, more strategic and tailored marketing techniques, and a more holistic, comprehensive understanding of consumer behavior - while saving time and money on new consumer research without compromising on insights. Consumer behavior shifts and evolves over time, leading to a complex relationship with the products individuals buy and consume. As more competitors and products enter the market, the need to generate, manage, and analyze high-quality data is more important than ever.

To remain competitive, the leading CPG companies are starting to take advantage of AI-generated synthetic data to understand and analyze dynamic consumer behavior and make decisions that are data-driven, reliable, and accurate. Simulacra Synthetic Data Studio is a leading synthetic data vendor, designed with CPG companies and needs in mind, that has the ability to rapidly and accurately generate, model, and analyze relationships in consumer behavior, allowing CPG companies to understand their consumers and drive their decision-making with confidence.