Trending Topics on Shopping Research in India in 2026
Consumer shopping behaviour is undergoing a rapid transformation, driven by technological innovation, platform-led business models, and changing lifestyle expectations. From 10-minute deliveries and immersive AR try-ons to AI-powered recommendations and omnichannel journeys, today’s shoppers interact with brands in ways that were unimaginable a decade ago.
These shifts have not only reshaped how consumers discover, evaluate, and purchase products, but have also opened up exciting new avenues for academic research in shopping and consumer behaviour. This blog highlights some of the most trending topics in shopping research, with a special focus on the Indian market, and illustrates how researchers can design impactful survey-based studies to understand emerging consumer attitudes, experiences, and decision-making processes.
1. Rise of Quick Commerce and Its Impact on Consumer Shopping Behaviour in India
Quick Commerce delivery is the faster version of e-commerce in which the customer orders products using a mobile application and the products are delivered ‘quickly with speed’ within 10-15 minutes. Common brand names – Swiggy Instamart, Blinkit, Zepto, BigBasket Now, Dunzo, are the leading players in the Indian market. This has caught interest of many researchers in the field of shopping research and consumer research.
Example Survey Questions:
- How often do you use Quick Commerce apps in a month?
- Using Quick Commerce apps would be convenient for me.
Research Tip:
Run a national level study with a focus on recruiting representative sampling and cover diversified demographics. Analyse results based on different age groups, income groups or even tier-wise distribution of participants.
2. Adoption and Effectiveness of AR/VR Technologies in Enhancing Shopping Experiences
Many of us have used Augmented Reality (AR) features to try on products before making a purchase. Whether it’s spectacles on Lenskart, makeup on Nykaa, or outfits using AR-enabled e-commerce platforms. This topic of shopping research aims to explore consumer behaviour specifically related to these AR shopping experiences.
Example Survey Questions:
- Which Augmented Reality (AR) app did you use in your last shopping?
- Rate your experience while using AR shopping app?
Live Example:
This research team from IIM Jammu ran online data collection for seamless survey and data collection process. This enabled them recruit participants from 40+ cities across India in less than 10 days.
3. Omnichannel Shopping Behaviour: Online, Offline or Both
Omnichannel shopping enables customers to shop from anywhere, at any time, through various channels like physical stores, websites, mobile apps, and social media, while providing a seamless experience even while switching channels during the purchasing journey. This field of shopping research explores consumer value co-creation in omnichannel shopping.
Example Survey Questions:
- Which mode of shopping is more convenient while purchasing from your favourite brand – the retailer’s online website or via physical stores?
- Your favourite brand’s customer service is most active on which channels?
Research Tip:
Run a comparative study among online only and offline only buyers. Compare their preferences, choices and perception with shoppers who buy from multiple channels. Covering tier 1, tier 2 and tier 3 cities equally will add better data for the study.
4. Online Reviews and Information Overload while Shopping
Consumer reviews play a critical role in modern shopping journeys. While reviews are intended to reduce uncertainty and build confidence, the overwhelming volume of opinions, ratings, comparisons, and conflicting information often leads to information overload. In shopping research, this phenomenon is increasingly linked to purchase indecision.
Example Survey Questions:
- The information available in the online consumer reviews – are they helpful or vague while making a purchase decision?
- Comparison of different product and features – is it convenient or barely possible from the available online consumer reviews?
ThinkSurvey Tip:
Use recall-based survey designs where respondents reflect on a recent shopping experience involving making a purchase after consuming lots of reviews. This approach captures realistic cognitive and emotional responses to information overload and improves the validity of online shopping behaviour studies.
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5. Personalization Algorithms and Consumer Response to AI-Based Recommendations
This topic on shopping research explores the consumer experience towards Gen AI-driven product recommendations provided by online shopping and service platforms (e.g., Amazon, Flipkart, Myntra, Makemytrip). They allow you to ask open-ended questions (e.g., “Suggest a budget-friendly phone with good camera,” “What should I wear for a beach holiday,” “Show me easy dinner options for two”) and provide tailored, interactive responses.
Example Survey Questions:
- Do AI recommendations of your favourite shopping brand reflect your shopping preferences?
- Were the last Gen AI recommendations useful?
Live Example:
This team from IIM Raipur utilised online survey solution to survey more than 600 participants from across India to study their perception and acceptance towards using AI-features by their favourite online shopping brands.
How to Select the Right Topic in Shopping Research
Selecting the right topic is one of the most critical steps in shopping research, especially for researchers studying evolving consumer behaviour, retail technologies, and digital commerce. A well-chosen topic should balance academic relevance, real-world impact, and research feasibility.
Start by mapping the shopping research literature. Go beyond abstracts and explore recent review papers, empirical studies, and conference proceedings related to consumer shopping behaviour, online retailing, omnichannel experiences, and technology-enabled shopping. This helps you identify trending themes while narrowing down areas that genuinely interest you—an important factor for sustaining motivation throughout the research process.
Next, focus on identifying research gaps. Look closely at the discussion and limitation sections of recent shopping behaviour studies to spot unanswered questions or emerging challenges. These gaps often form the foundation for novel and impactful consumer research topics.
Once potential questions are identified, evaluate their feasibility. Consider your access to respondents, data collection methods (such as online surveys), time constraints, and analytical skills. Topics that align with available resources are more likely to lead to successful outcomes.
Finally, seek feedback from peers or supervisors and refine your topic before designing your study. A strong shopping research topic is not only timely and novel, but also practical, scalable, and meaningful to both academia and industry.
How ThinkSurvey is enabling Shopping and Consumer Behaviour Research
- Audience Panel – Access a pre-screened panel of Indian consumers from all states, ensuring your study reflects real-world habits and market diversity.
- Wide Demographics – Students, working professionals, homemakers, business owners — with responses balanced by gender, age, income, and region.
- Expert Research Team – Specialists who understand both academic consumer behaviour research methodologies and market validation studies.
- Scalable Data Collection – From 50 to 5,000+ responses, tailored to your project scope — whether it’s concept testing, consumer surveys, or persona mapping.
- Timely Delivery – End-to-end project execution delivered within the agreed timeline.
- Dedicated Support – A single point of contact guides you from survey design to data analysis.
