I have always been a huge sci-fi movie fan. These movies creatively challenge your imagination and provide a sense that “anything and everything is possible”. I tend to use the same approach in my research.
It was Iron Man that introduced me to the power of Artificial Intelligence, and I started dreaming of having my own JARVIS, an AI assist, who would instantly answer all my research questions and help me make informed and strategic decisions. With advancements in AI, this dream looked very plausible, and I further started to explore opportunities for an AI-based automated qual process [voice-to-text – NLP – transcripts – translations – data + sentiment analysis – auto-filled report] and makings quals 100% digital [i.e. recruitment, data acquisition, data storage, real-time data analysis, automated dashboard or report]
Thanks to Covid – which acted as a strong catalyst especially with regard to digitalization – Consumer Research has advanced so much. With our consumers going digital, all our research methods are also digital. Online quals, quants, consumer panels, and communities are the new normal. Video calls and What’s App chats are common means of data collection today, virtual whiteboard and Zoom break-out rooms are more and more frequently used for creative consumer discussions, and now we are even doing our ethnographies online! Additionally, we have seen a lot of advancement in sensors and devices, for example, smart mirrors and video analysis for emotion decoding, eye tracking, and heat maps to decode consumer engagement, heart rate monitoring to understand user experience, and EEG-like devices to track brain waves.
While I can go on and on, let me instead focus on the one topic that fascinates me the most: Artificial Intelligence! AI is everywhere and almost every person I talk to shares some experience or another with AI. And, from my experience, three AI topics are talked about the most: Web crawling, ratings & review [R&R] analysis, and augmented products.
Per the Digital 2021 April Global Statshot Report, there are 5.27 billion unique mobile users around the world, 4.72 billion people using the internet, and 4.33 billion social media users. It’s obvious why web crawling has gained so much importance. Most agencies today offer simple [like buzz words/topics, brand recall & image, consumer trends/shifts] to more sophisticated [like competition landscaping/business intelligence from social circus & consumer/lifestyle segmentation from Quilt AI] techniques. I was surprised to know that even consumer journeys, a legacy of qualitative research variety for me, can also be built through the web or via social media listening! R&R Analysis is another example of such web crawling.
Scott D. Cook said, “A brand is no longer what we tell the consumers it is – it is what consumers tell each other it is” and it’s so true! With a boom in e-commerce, this review-based purchase decision-making is unavoidable. This also explains the upsurge of Key Opinion Leaders [bloggers and influencers], thereby making R&R analysis very strong and relevant. Many research agencies have built AI-fueled smart & user-friendly dashboards for their clients [e.g., Revuze, SemantiWeb Beauty, Aspectiva, SentiGeek, Shopalyst, and so on].
Lastly, let talk about augmented products. Augmented products are personalized products and services that draw from a consumer database [lifestyle, purchase history, measurements, and so on] at the back-end and, by way of the assistance of ML and AI algorithms, suggest customized solutions to enhance the consumer experience. This space is growing exponentially. Products in this category can be classified in four ways:
- Personalized services: Typically, diagnosis or measurement systems at Point of Sale to understand consumers’ current state & preferences. For example, Lancôme Skin Screen analyzes and scores key skin parameters to help build a tailored skincare routine with a skincare expert at the Lancôme shop.
- Personalized @home solutions: Devices and tools that run diagnosis basis selfies, videos, or general body measurements, and recommend customized product routines, dosage, or a specific combination of products to be used. For example, O.S.E by Skinceuticals is a state-of-the-art service engineered to scan and evaluate consumers’ unique skin needs. The service combines active ingredients into a tailor-made, corrective serum. Another example is SkinConsult AI Vichy, where with one selfie – one can measure skin aging, followed by a dermatologist reference scale. This allows the product to deliver a personalized skincare prescription.
- User apps: I am sure these will sound familiar. Brands today are launching apps that track consumer progress and offer customized solutions. For example, My Skin Track UV from La Roche-Posay records UV exposure and notifies consumers on ideal product usage, and Gx Sweat Patch (from Gatorade) analyzes sweat content and, through the app, reports to users hydration levels and provides recovery recommendations.
- Augmented Reality: A well-known example of this category is Ikea’s virtual store, which allows users to build their own room. Other apps or web pages that provide a virtual store setup experience include L’Oréal’s AI-powered Virtual Makeup Try-on To Amazon and Style My Hair from L’Oréal Professional. The latter allows consumers to try out an augmented reality hair makeover.
I don’t know about you, but I am certainly smitten by AI!
I’m restless to find out what’s next! In fact, I wonder, given how the advanced state of these developments, what can we expect the future to look like?
Let’s start with data. Consumer data will be easily accessible to all [i.e., data generated via mobile, images, conversations, chats, purchase reviews, apps, fitness trackers, public cameras, GPS tracking, smart homes, smart appliances, and cars, etc]. Thereby making Data Science and Management the most sought-after skillset in a researcher, making way for more complex meta-analysis.
Conducting research will be fun, exciting, and super cool with chatbots performing classical quals and drones producing ethnographies. Holograms and/or virtual avatars will be used for face-to-face interviews (an upgraded and more realistic technology compared to video calls). This will further diminish geographic boundaries, which I expect will make research truly inclusive.
Data collection will also upgrade – and yet simplify – by way of body scanners. Such scanners will collect all information needed [e.g., aging signs, skin tone changes, acne / dark spot correction, hydration levels, body hot/cold areas, etc.]. These advancements will be backed by ML plus AI algorithms to calculate consumer satisfaction and happiness index basis body language – and emotions, so we won’t need any questionnaires anymore!
And my most favorite part: Report formats! Welcome to highly sophisticated, live, and interactive consoles. These will collect, analyze, and display data [like stock exchange dashboards], all in real-time. All types of structured and unstructured data [images, GIFs, video, text, etc.] from everywhere will be combined into a single console. This advancement will provide a holistic view of past, present, and future trends, further ensuring that we don’t miss anything. Go on, imagine it: If a consumer responds with a very high happiness index in an ongoing study, this console will connect and show all similar consumer groups and geographies where the product is most likely to succeed. It will link to formulation, ingredients, and/or products to see what worked best, and what can be used as communication to attract these consumers, all based on their preference plus purchase plus review history – and so much more.
It may seem like robots are taking over, but (as clichéd as it is) accurate interpretation and decision-making skills will always be indispensable for a researcher.
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