On June 10, 2026, Indomie brought back its Goreng Cabe Ijo flavor after the product had been difficult to find in the market for years. This article examines the momentum behind the comeback using social listening data from Socindex. It also demonstrates how brands can use comment sections as an intelligence radar for product development. The campaign was carefully planned, from a press conference in Jakarta and collaborations with content creators to the launch of a new jumbo-sized package. However, conversations in the comment sections soon moved beyond what the marketing team had initially planned.

Amid messages of excitement from loyal fans, a wave of requests emerged for other discontinued flavors, including Sate, Sambal Matah, and Goreng Soto. Some brands might view these off-topic comments as promotional noise. For an observant product team, however, they represent free, large-scale market research generated directly by consumers.

Source: Socindex

When Consumers “Hijack” a Campaign’s Comment Section

The return of Indomie Cabe Ijo was not an ordinary product launch. The flavor, first introduced more than a decade ago, had become scarce and was only available in certain regions, as reported by Kompas.com. It has now returned with an improved seasoning formula and a new 120-gram jumbo package. The product was officially relaunched at a press conference in Jakarta on June 10, 2026.

Indomie’s management stated that the comeback was a direct response to fans who had consistently expressed their demand through social media. Julia Atman, General Manager of Marketing for Indofood’s Noodle Division, told KapanLagi that the relaunch was intended to meet the expectations of Indomie Lovers who had actively voiced their requests through digital channels. Strong market enthusiasm also encouraged Indofood to expand the product’s distribution nationwide, as confirmed by Andrew Hallatu, Head of Corporate Public Relations at Indofood, to Detik.

Socindex data clearly captured the scale of the organic conversation:

• Monitoring period: June 10–July 13, 2026
• Total conversation volume: 2,849 data points
• Channel distribution: Instagram dominated with 2,188 data points, followed by X with 186 and Threads with 157
• Sentiment analysis: Of the 2,402 comments recorded, 479 were positive, 91 were negative, and the remainder were neutral, including stock inquiries, friend tags, and nostalgic comments

Source: Socindex

The conversation peaked rapidly. Daily volume surged to approximately 890 data points on June 11–12, within 24 to 48 hours of the launch, before falling close to zero within a week.

Source: Socindex

A subtle form of “campaign hijacking” occurred within these thousands of comments. Instead of discussing only the Cabe Ijo flavor, consumers used the momentum to demand the return of other discontinued products. Indomie was promoting one product, but consumers responded by submitting their own list of products that should be brought back next.

How Is Social Listening Different from Basic Performance Monitoring?

Social listening is the practice of monitoring and analysing public conversations on social media to support strategic business decisions. Its main difference from conventional social media monitoring lies in the depth of analysis. Research published in the BISMA Journal describes social listening as a sensing mechanism for product-development decisions, rather than merely a marketing term promoted by technology vendors.

Fitur	Social Media Monitoring	Social Listening
Focus Questions	What (What happened? How many mentions? Who spoke?)	Why & How (Why is sentiment shifting? What are recurring demand patterns? What business decisions should be made?)
Main Function	Measuring current campaign performance.	Be a radar of market needs and guide product development(sensing mechanism).

Compared with conventional market research methods, such as surveys or focus group discussions, social listening offers three major advantages.

1. Lower Response Bias: The data emerges organically without being prompted by questionnaires or structured interview questions.
2. Real-Time Information: Social listening provides an immediate picture of how trends and consumer conversations are developing.
3. Cost-Efficiency: Consumers voluntarily explain their preferences and needs through channels already owned or monitored by the brand.

These three advantages explain why the Cabe Ijo case should be treated as market research rather than a temporary wave of social media reactions. The data emerged without being artificially engineered, was captured almost immediately, and did not require an additional market-research budget.

Comment Sections as Automatically Ranked Demand Boards

Many brands still treat comment sections solely as customer-service spaces. Administrators respond with friendly templates, answer basic questions, and consider the task complete. The Cabe Ijo case reveals a far more valuable function: comment sections can operate as demand boards validated directly by the audience.

Based on the Socindex dashboard during the same monitoring period, several discontinued flavors were repeatedly requested by consumers:

Source: Socindex

These requests were validated through two main indicators. The first was repetition. Similar requests were expressed by different accounts over an extended period. The second was the number of likes. Comments requesting a specific product that received hundreds or thousands of likes effectively functioned as self-running micro-polls. The combination of these two signals automatically ranked consumer demand without requiring the research team to manually review every individual comment.

One particularly valuable insight emerged during the monitoring period. A consumer stated that they had repeatedly requested the restocking of Cabe Ijo in previous comment sections. Although the brand’s administrator had never responded, the product was eventually brought back. This illustrates an important distinction. Responding to comments is a customer-service responsibility. Listening, grouping, and identifying patterns across thousands of comments is the function of social listening platforms such as Socindex.

Why Product Comebacks Can Carry Lower Business Risks

Reviving a discontinued product often carries less business risk than launching a completely new one. This is because the brand already possesses three important forms of capital.

1. Established Brand Awareness: The company does not need to educate the market from the beginning. Consumers already know the product, understand its flavor, and know how they prefer to consume it. A completely new product must first build this familiarity.
2. Scarcity: Years of limited availability can strengthen consumer nostalgia and desire. This accumulated sense of scarcity may translate into high demand when the product eventually returns.
3. Market-Data Validation: Consumer demand is no longer based solely on internal assumptions. It can be documented through social listening data and recurring online conversations.

The relatively low risk of the comeback was reflected in Socindex’s sentiment data. Negative sentiment remained below 4%. For a mass-market product relaunch, such a low level of resistance is a positive result. Product comebacks can easily trigger disappointment when consumers believe that the new flavor, formulation, or packaging does not meet their memories and expectations. Reviving a discontinued product often carries less business risk than launching a completely new one. This is because the brand already possesses three important forms of capital.

Beware of the “Nostalgia Trap”

When a product returns after a long absence, consumers do not necessarily compare it with the original product. They compare it with a memory that may have been idealised over many years. The remembered taste may seem better than the actual experience. The business implication is straightforward: nostalgia may drive the first purchase, but product quality determines repeat purchases. This trap causes many product comebacks to fail after the initial wave. Early enthusiasm may be high, but repeat purchases can fall sharply when the actual product does not match the consumer’s expectations.

Indomie appears to have anticipated this risk. Instead of simply reusing the previous formula, the company improved the seasoning to produce a spicier and more savoury taste. This was a crucial step to ensure that the current product could compete with consumers’ idealised memories of the past. The role of social listening should therefore continue beyond the launch. Monitoring post-purchase sentiment over the following weeks can help a brand identify whether nostalgia has successfully been converted into real satisfaction or has instead turned into disappointment that could weaken the comeback.

How to Use Social Listening for Product Intelligence

The lessons from Indomie Cabe Ijo can be applied across industries, not only in the food and beverage sector. The basic principle remains the same: comment sections contain demand signals that are frequently ignored because they are treated as casual online conversations. The following three steps can help brands capture these signals systematically.

1. Expand the Monitoring Keywords

Do not monitor only the main brand name.

ThDon’t just monitor your main brand name. Include specific product variant names, including discontinued ones, and combine them with verbs indicative of Indonesian demand, such as “balikin,” “restock,” or “kapan ada lagi” (when will it be available again). The Cabe Ijo case demonstrates this approach works. Older variant keywords like “Sate” and “Sambal Matah” capture much sharper demand signals than simply monitoring “Indomie” alone.e Cabe Ijo case demonstrates the effectiveness of this approach. Keywords related to discontinued variants, such as Sate and Sambal Matah, captured more specific demand signals than monitoring the word “Indomie” alone.

2. Focus on Data Patterns, Not Individual Comments

One comment that goes viral on Instagram or X could be biased and misleading if taken partially. What is worth basing product decisions on are macro patterns: which variants have the highest volume of requests, consistent conversation duration, and a healthy sentiment graph. The automatic topic cluster feature can turn thousands of text comments into ready-to-use priority lists for board meetings.

3. Cross-Reference the Data with Timing

The Socindex data curve shows that conversation peaks in the first 48 hours and declines dramatically over the course of a week. This demonstrates that the window of opportunity to capture market intelligence from a campaign is very short. Constant digital monitoring is far more effective than occasional audits. For brands launching a new campaign, intensive monitoring in the first 48 hours is sufficient to capture most relevant demand signals.

Conclusion

The comment sections surrounding the Indomie Cabe Ijo campaign reveal two sides of the same story. At the surface level, they functioned as digital celebration spaces for loyal consumers. At a deeper data level, however, they became a valuable product backlog that had already been validated and ranked by the target market. Brands that treat comments merely as a queue of administrative tasks risk losing this opportunity.

Brands that treat them as data assets can gain access to continuously updated market research without relying exclusively on surveys or focus group discussions.

Companies seeking to understand public conversations and transform them into more precise business decisions can use the Socindex social listening platform for this purpose.

Contributor

Muhammad Reza

Aan K. Riyadi