Some people prefer to try a new product before purchasing it. To address this consumer preference, try-and-sample companies offer samples and mini sizes across a wide range of products, including skincare items, cosmetics, health supplements, and gourmet snacks. This business model assumes that allowing consumers to test these products in the comfort of their homes not only helps them to make informed purchase decisions but also enhances their overall shopping experience. By leveraging data analytics and AI, these companies can personalise the sample offerings based on consumer preferences and behaviour patterns identified through their platforms. This not only optimises the sampling process but also ensures that consumers receive products tailored to their interests, increasing the likelihood of conversion from trial to purchase.
In a conversation with BrandWagon Online, Swagat Sarangi, co-founder, Smytten, talks about how the Brand Track integrates AI and sophisticated analytics to streamline brand performance monitoring, promising to redefine industry standards in measuring brand impact and consumer engagement, among others. (Edited Excerpts)
What is the rationale behind your current business model, particularly as a trial and beauty app service provider to brands? Additionally, why have you now launched a brand tracker?
We primarily focus on lifestyle categories, including F&B (food & beverages), health and wellness, and pet care, in addition to beauty. Our main proposition is to enable users to discover and try various lifestyle consumables. After the trial phase, users can purchase directly on our platform, which operates like a marketplace. At the top of the funnel, we offer Smytten Pulse, a SaaS product that provides brands with research solutions, advertising solutions, and analytics, among others.
Smytten has always been a full-funnel solution, addressing both the demand and supply sides. Our trial and consumer platform, available via a mobile app and website, has been downloaded over 20 million times, making us one of the top-rated apps on any app store. Think of it as an enhanced Instagram, where discovery and trial happen simultaneously. This logical journey leads from discovery to product introduction and trial.
At the top of the funnel, we have the Pulse platform. Pulse is powered by the intent data of our 20 million users and other data sources, enriching consumer insights. Typically, a brand’s growth journey involves three critical stages: launch, consumer opportunity identification, and more.
What is the role of sampling, data, and AI in your business?
The great thing about sampling is that it interacts with consumers when they are still indecisive and experimenting with new things. We are likely the best proxy available today to understand what consumers are likely to buy in the future because they are always trying new things to expand their basket.
When we layer AI on this data and build our SaaS platform, there are three core offerings. First, we provide true analytics driven by the real consumption behaviour of millions of users, not just internet analytics. Second, we offer consumer research to validate hypotheses in a more scientific and structured way. This includes everything from concept studies to communication testing and complex usage and attitude studies. You can recruit and engage with your audience, obtaining results much quicker, faster, and cheaper compared to other platforms. Third, we have ad tech, where post-sampling, you can reach out to users not only on Smytten but across the open web. You can use our platform to advertise to this audience on Google, Meta, or any other programmatic platform to bring them back into the funnel.
In the Pulse platform, we have three segments. Pulse Scan focuses on analytics, Pulse Boost is the advertising engine, and Pulse Check is the complete research tech. The brand tracker is part of our research suite. Many new consumer brands are not measuring their brand metrics correctly because traditional research methods are cumbersome, time-consuming, complex, and expensive. Our brand tracker offers a simplified, DIY solution. Brands can set it up with just three clicks, deciding their audience profile and frequency.
The analysis is reported in a simple format with an interactive dashboard, allowing real-time tracking and comparison of data. Our AI provides insights into key metrics like top-of-mind awareness or response rates. For instance, if your brand’s response rate dips in a specific region, the system analyses multiple factors and provides reasons and suggestions for corrective actions. You can then do deeper analysis through research, all integrated closely on the platform. Our goal is to standardise measurement for the new digital audience and create a benchmark for tracking and measuring key metrics.
With so many platforms like Google, Meta, Amazon, and Flipkart each providing their data, isn’t adding another tracker just creating data overload? How does this new system simplify the media planning process for brands amidst the confusion of multiple walled gardens?
We are not dictating where you should allocate your budget. Brand tracking is essential for every brand, and traditionally, it has been done inefficiently. Typically, data from various sources like Google, Meta, media analytics teams, etc., is scattered, making decision-making difficult. Our new tracking system aims to replace the traditional method by streamlining the process with technology. Instead of recruiting people, having them fill out survey forms, and manually processing the data, our system automates and integrates these steps. This ensures accurate and efficient data collection and analysis. If you’re a brand, brand tracking is something you should do, and our solution simplifies and enhances this process.
We provide advanced technology and data to make sense of brand tracking. For instance, if your brand’s awareness in Uttar Pradesh suddenly drops, our system can contextualise this for you. We scrape data from sources like Google Trends and the open Internet and integrate it with platform-specific data. This allows our AI models to identify potential reasons for the drop. We’re leveraging Gemini LLM models to process unstructured data from multiple sources.
As a brand marketer, you no longer need to guess why there’s a drop in your metrics. Our system can tell you whether it’s a broader trend affecting everyone or specific to your brand and whether it’s influenced by macroeconomic factors. Traditionally, you would need to go back to an agency and commission more research to find these answers, but now, all this information is available in one place, streamlining your decision-making process.