A peak Bengaluru moment shows a tender coconut vendor doing a competitive analysis against big names like Zepto, Blinkit, and BigBasket. Now, if this vendor can pull this off on his own, imagine what you could do with the power of AI.
With AI tools such as ChatGPT, Claude 3.5 Sonnet, and others at one's disposal, anyone can now conduct in-depth market analysis and customer feedback assessments using just natural language, making traditional consultants and analysts look outdated.
In a conversation with AIM, Rajiv Lamba, founder and CEO of customer feedback platform SurveySensum, said, "AI plays a critical role here, particularly with text-based feedback. Traditionally, analysing textual feedback took a lot of time and effort in the market research industry, as humans would read, code, and analyse it manually."
SurveySensum has developed an AI engine that uses natural language processing (NLP) to automatically summarise textual data in multiple languages. This provides a real-time summary without the need to read every individual response.
Lamba, while highlighting another AI-powered feature, explained, "Our platform automatically generates summaries and insights, translating data into actionable insights, even for those who may not be trained analysts. For example, it can provide a quick summary of why customer satisfaction is trending up or down, giving clients instant, AI-driven analysis in an easily understandable format."
Using the automotive industry as an example, Lamba explained how the typical customer journey includes various touchpoints like dealership visits, social media interactions, after-sales services, insurance, and roadside assistance. Each of these stages is an opportunity to gather feedback.
"We use our platform to track and integrate feedback across this entire journey. Through API integration, we capture data at every stage -- whether a customer visited a Maruti or Honda showroom, interacted with sales, purchased a car, or used post-sales services," he added.
Traditionally, companies focus on customer acquisition, but now, with markets becoming saturated, retention has gained importance, especially in sectors like telecom. SurveySensum supports this shift by offering actionable, real-time insights into why customers are satisfied or dissatisfied.
"Unlike traditional market research that aggregates feedback and can take months to deliver, our solution provides instant, individualised data. For example, if a customer gives a low score, a 'ticket' is immediately sent to the customer experience team to address it," he mentioned.
"Platforms like ours help companies reduce research costs by up to 80%," Lamba said, suggesting that the savings come from reduced human intervention, as AI handles tasks that would traditionally require consultants or face-to-face surveys. Clients enjoy high-quality, real-time data at a fraction of traditional research costs, which is a huge advantage.
Addressing potential job threats posed by AI, the SurveySensum founder said, "With AI, including tools like ChatGPT, many job profiles are indeed at risk. However, the key for professionals, especially analysts, is to upgrade their skills."
Previously, analysts focused on data interpretation and insights delivery, but today's roles demand expertise in predictive analytics. "Simply reading and interpreting data can now be automated. Professionals should view this shift as an opportunity to learn more, exploring areas like data modelling and predictive analytics to provide value beyond what AI can deliver," he emphasised.
Since SurveySensum operates in Indonesia and India, Lamba noted differences and similarities between the two markets.
"In terms of customer experience management, Southeast Asia, particularly Indonesia, is still in the early stages of development. India, in comparison, is roughly five years ahead in implementing and deepening customer experience strategies. While Indian businesses approach the standards seen in the US, especially due to significant US and European clients, Indonesia is still building foundational awareness," he said.
Lamba further mentioned that companies in India are already familiar with customer feedback platforms, so the focus is on differentiation and added value. In Indonesia, however, there is a need to start with the basics like explaining what customer experience management is and how these platforms can benefit them.
Each country's unique languages and dialects add another layer of complexity. Surveys in Indonesia, for example, must be in Bahasa, while in Thailand or Vietnam, they must be in their respective local languages.
"Our NLP systems must be trained in these languages to ensure accuracy. In India, we typically focus on English or Hindi, but in Indonesia, achieving the same level of precision requires NLP training in Bahasa," he stated.
Companies like IBM and Genesys are exploring the application of AI in feedback and analytics. Genesys offers conversational analytics to help businesses discover trends and engagement levels, driving performance improvements and enabling data-driven decision-making.
Adaptive AI solutions by IBM are tailored for real business needs and offer flexible integration with core business systems like SAP, Salesforce, and AWS. Through a consultative approach, they help companies incorporate AI into workflows, solving business problems effectively.
