Gaurav Jain

Assistant Professor

  • Troy NY UNITED STATES
  • Lally School of Management

Behavioral economist focused on studying how individuals make judgments and decisions in the absence of complete information.

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Spotlight

3 min

The Role of Artificial Intelligence in Customer Experience

Gaurav Jain, assistant professor of marketing at the Rensselaer Lally School of Management, examines how individuals make judgments, estimates, and decisions in the absence of complete information. Previously, Jain served as the chief marketing advisor at multiple firms. Below are his thoughts on the impact of artificial intelligence (AI) on customer experience.Voice of the CustomerIn today's hyper-connected world, the voice of the customer (VoC) is louder and clearer than ever. But how do we sift through this cacophony to understand what our customers are really saying? Enter AI. It's revolutionizing the way customer experience teams handle VoC programs, and as a marketing leader, I find this incredibly exciting.Take direct customer feedback, for example. We're no longer just collecting survey responses and storing them in a database for quarterly review. AI algorithms, particularly those using natural language processing, are helping us instantly categorize and prioritize this feedback. Imagine an e-commerce platform that can immediately flag a customer's mention of "late delivery" in a post-purchase survey. That's not just efficient; it's customer-centric.But what about the things customers are saying when they're not directly talking to us? That's where AI-driven sentiment analysis comes in. These tools can scan social media, forums, and review sites to gauge the sentiment behind a customer's words. I've seen hotel chains use this technology to monitor travel forums and review sites. If a guest mentions "noisy rooms," even without lodging a direct complaint, the brand can proactively look into soundproofing solutions.Then there's inferred feedback, the kind you get by reading between the lines. AI can analyze customer behavior, like frequent page visits without conversion or cart abandonment, to suggest what might be going wrong. For instance, an online fashion retailer could use AI to figure out why a particular dress gets a lot of views but few purchases. Maybe it's the sizing, maybe it's the price, but the point is, you get to know without having to ask.And it doesn't stop at gathering feedback. AI is helping us turn this raw data into actionable insights. We can predict future behavior, like churn rates, based on past feedback. This allows us to be proactive rather than reactive, which is a game-changer in customer experience management.Finally, let's talk about what happens after we've gathered all this feedback. AI is ensuring that every customer who takes the time to share their thoughts receives an immediate and appropriate response. Chatbots can handle common queries or concerns, making the customer feel heard and valued right away.So, from the perspective of a marketing leader, it's not just about the efficiency that AI brings to VoC programs. It's about the opportunity to deepen our connection with customers. By truly understanding their words, their sentiments, and even their behaviors, we can craft experiences that resonate on a human level. And in a world that's increasingly digital, that human touch is what sets a brand apart.Customer ServiceIt's truly intriguing to observe how AI is weaving its way into the customers’ experience. Online, chatbots are making waves. Chatbots are not just digital tools; they're our first point of contact, bridging the gap between brands and consumers. However, there was always the question of accuracy versus efficiency while managing these chatbots – AI has answered that question. AI chatbots provide real-time yet accurate assistance, making the digital shopping journey feel more interactive. Companies can reduce customer dropout while avoiding the expense of managing a large human customer service team.AI is revolutionizing phone-based customer service as well. Voice recognition allows natural language processing for easier navigation, while predictive analysis anticipates caller needs based on their history. Enhanced personalization means customers no longer repetitively provide account details, and emotion detection aids in gauging caller mood. The result? Reduced wait times, more efficient interactions, and a significantly improved telephonic customer experience.In essence, AI is bridging the gap between technology and human touch in the retail world, making our interactions with brands more meaningful and personalized. Again, companies can do this in a cost-effective manner.Jain is available to speak with media simply click on his icon now to arrange an interview today.

Gaurav Jain

Areas of Expertise

Marketing Communication
Judgment and Decision Making
Consumer Choices and Behavior
Behavioral Economics in Business
Choice Architecture
Marketing Research and Analytics
New Product Development
Pricing Analysis
Behavioral Finance
Marketing Promotions

Biography

Gaurav Jain, an assistant professor of marketing at the Rensselaer Lally School of Management, examines how individuals make judgments, estimates, and decisions in the absence of complete information. Prior to earning his Ph.D. from the Tippie College of Business at the University of Iowa, Gaurav earned his bachelor’s degree in engineering and an MBA in marketing. More specifically, his research spans the fields of numerical cognition and judgment, working memory capacity, and, attention limitations. Using psycho-physical methods, such as eye tracking and facial expression analysis, Gaurav makes novel predictions about how various cognitive biases influence consumer choices.

Media

Education

University of Iowa, Tippie College of Business

Ph.D

Marketing

Management Development Institute (MDI)

MBA

Manipal Institute of Technology

Bachelor of Engineering

Media Appearances

Why researchers are 100 percent sure we love round numbers

Washington Post  print

2020-11-07

"Numbers have a language of their own. People think that numbers are used for quantitative information only, but they often indicate qualitative information, as well,” said Gaurav Jain, a Rensselaer Polytechnic Institute marketing assistant professor who co-wrote a new study published in Organizational Behavior and Human Decision Processes.

In his research involving hundreds of participants, Jain found that people take longer to process non-round numbers. As they work to make sense of such a number, they tend to compare it to an ideal round number for the given situation.

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Gaurav Jain

Scientific Sense podcast  online

2020-10-19

Fluency and perceptions of decision making, numerosity and allocation behavior, and the impact of number roundedness on framing. Dr. Gaurav Jain is an assistant professor of marketing at the Rensselaer Polytechnic Institute. His research examines how individuals make judgments, estimates, and decisions in the absence of complete information.

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New Research Finds That Confusing Marketing Can Lead to Consumers Making More Informed Decisions

Martha Stewart  print

2020-09-21

A buzzy product with flashy social media posts and clear descriptions may seem like the best way to market your product and get consumers to invest it in. However, a new study has found that advertisements with confusing language and a more chaotic layout can actually lead to consumers conducting more research on that product and ultimately making a more informed buying decision.

"Most of the time, marketing communicators try to make their message clear. What we learned, however, is that there are certain times, especially when people need to make choices, when we should actually use disfluent stimuli so that whatever people are choosing, they will like it once time has passed," explains co-author Gaurav Jain, an assistant professor of marketing in the Lally School of Management at Rensselaer Polytechnic Institute.

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Articles

Perceptual Anchoring and Adjustment

Journal of Behavioral Decision Making

Gaurav Jain Dhananjay Nayakankuppam Gary J. Gaeth

2021-01-07

Anchoring and adjustment, a ubiquitous heuristic process in judgment and decision making, has been vastly demonstrated in the numerical domain. We, with the help of four studies, demonstrate the anchoring and adjustment bias in perceptual domains. Our results show that anchoring and adjustment can bias our judgments at relatively low levels of cognition. Additionally, we outline a process by which anchoring and adjustment biases individuals' judgments in perceptual domains. Our results indicate a process wherein individuals search for an answer by testing plausible answers, the search being biased by the anchor question. We show that this movement is dominated by adjustments to adjacent possible responses indicating a search process constrained by selective accessibility. This process account explains the extant data in numerical domains as well—thus providing a way for a potential resolution to the disagreement among different existing process accounts for the anchoring phenomenon.

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Revisiting attribute framing: The impact of number roundedness on framing

Organizational Behavior and Human Decision Process

Gaurav Jain, Gary J. Gaeth, Dhananjay Nayakankuppam, Irwin P. Levin

2020-11-01

We compare the impact of round and non-round numbers used in a communication message on consumers’ evaluations and judgments towards the associated target entity. We find that the use of non-round numbers, in contrast to round numbers, in a message frame results in increased attention to numerical values, which further leads to a comparison of the associated measures with ideal reference points. This leads to an increased framing effect in the non-round numbers condition compared to the round numbers condition. Interestingly, this also negatively affects consumers’ overall evaluations of the target entity. We demonstrate that such a decreased positivity in attitudes when using non-round numbers is more pronounced in negatively expressed frames. We explain this using an ‘attention shift-comparison’ process. Additionally, using multiple methodologies, we provide elaborated support for the attention-association based reasoning for framing effects in general and thus add to the literature on processes underlying framing effects. This extends the original valence-shift based account originally proposed by Levin and Gaeth (1988) and provides an avenue for future research on attention-association based framing effects.

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(The lack of) fluency and perceptions of decision making

Journal of Marketing Communications

Gaurav Jain, Sunaina Shrivastava, Dhananjay Nayakankuppam, Gary J. Gaeth

2020-09-07

Research consistently finds that fluent stimuli in marketing communications are better liked and more trusted than more difficult to process stimuli. This paper describes four studies showing that the attitudes towards difficult-to-process stimuli increase significantly when compared to the easy-to-process stimuli, thus adding to the growing ‘disfluency’ literature. We show that attitudes increase towards a less fluent option when individuals misattribute the extra effort, spent in processing the information, to the decision making rather than the stimuli itself. The studies have important theoretical implications for understanding the mechanism by which lack of processing fluency influences attitude formation, and, have practical implications for understanding how and when to use disfluent stimuli in marketing communications.

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