A Competitive Analysis Example: Maggi vs Indomie vs Nongshim, Worked End to End

A competitive analysis example is only useful if it is real, so this one is: a report my tool produced on 6 August 2026 comparing Maggi with Indomie and Nongshim in Malaysia, sixteen pages, every number measured on that date and every finding graded. I am going to walk through it end to end, including the parts where it refused to recommend something and the part where it argued against its own top move.

Every page ranking for this phrase today is a filled-in SWOT template. Four boxes, some bullet points, no sources and no sense of how sure anyone is. That is not an example of a competitive analysis. It is an example of a form. What follows is what the real thing looks like: a decision you can defend, with the evidence graded and the weak points named first.

One thing before the numbers. The report is AI created. It was produced by a proprietary research engine, the findings below are presented as what the report found with its grade attached, not as my assertions about Nestlé, Indofood or Nongshim, and I read it with my own judgement, which is what I would ask you to do with any report about your own market.

What was run, on whom, and what did it find?

Maggi was the subject, Indomie and Nongshim the rivals, Malaysia the market, 6 August 2026 the date. The sharpest finding is that Maggi leads on every measured row and is still absent from the moment a shopper decides to buy noodles, because both rivals own the purchase-intent search terms and Maggi does not rank for any of them.

That one finding is the whole value of the exercise. A scoreboard read quickly says Maggi wins and there is nothing to do. Read slowly, it says the leader is winning the wrong moment. The rest of this piece is how the report got there, what it was sure of, what it was not, and what it declined to suggest.

How were the competitors chosen?

The set was two instant-noodle specialists against a culinary brand that also sells noodles, which is the set a Malaysian shopper actually weighs in the noodle aisle rather than the set that flatters Maggi. Choosing the rivals is the step most worked examples skip, and it decides everything downstream, because share of voice is only as honest as the set it is measured across.

The report says so itself. Its opening memo reads the market as “leader-dominated, read across 3 measured brands” and adds, in its own words, “This reads the brands in this analysis, not the whole market. It describes the field you chose to measure yourself against.” That sentence belongs in every competitive analysis and appears in almost none. How to pick the set for your own work is in how to run a competitor analysis before a pitch; the short version is two or three names your buyer actually compares you against, chosen before you start.

What does the scoreboard say?

Maggi holds 80.5% share of voice across the three brands, 781 referring domains, about 2,000 organic keywords and an estimated 122,000 organic visits a month, against rivals under 5,000 visits and under 70 keywords each. The report marks which of those are counts and which are estimates, and that marking is the part to copy.

Two caveats in that table come straight from the report and I have kept both. Share of voice is measured across whole sites, so a rival with a broad catalogue scores partly on unrelated terms. And the traffic row, which is the one everybody quotes first, is the only estimated count in the grid. A competitive analysis that presents modelled visits as a fact has already overclaimed before it reaches a conclusion. The method for building this grid yourself from public data is in competitor benchmarking without a big team.

What do the AI visibility rows show?

Maggi is named in 324 Google AI Overview answers and 672 ChatGPT answers, against 91 and 166 for Indomie and 68 and 411 for Nongshim. This is the one row the traditional tools do not give you, and it is the bridge to the question more buyers now ask before they search: who does the assistant name.

The report attaches a caveat here too, and it matters. The Google AI Overview row is measured in Malaysia. The ChatGPT row is measured from answers given in English and cannot be set to a market, so it is not a reading of Malaysia specifically. Read the two rows with that difference in mind rather than adding them up. The metrics behind this row, and how to count them for your own brand, are in LLM visibility and how to measure it.

What the numbers say, graded: Maggi leads both surfaces, verified. Nongshim’s 411 ChatGPT mentions, six in ten of Maggi’s, show that the AI answer lead can be contested even by a brand with a thirtieth of the search traffic. The report reads that as the threat to watch, and labels the reading inferred.

Where did the report say Maggi could win?

In everyday Malaysian recipe and ingredient searches, where cooking intent lives and neither rival has a content engine. The report frames this as a hypothesis, says so in those words, and lists what it verified underneath.

Verified, with two sources each: Maggi ranks for about 2,000 organic keywords whose top terms are recipe and ingredient searches like cantonese kuey teow and carbonara maggi, and its positioning is built on cooking with its ingredients. Verified, one source: the rivals rank almost entirely for their own brand names, indomie goreng and kimchi ramyun nongshim, with no recipe-intent overlap.

Then the intent split, which is the finding I would put on the first slide. Of the Maggi traffic the report sampled, 71.4% sits in comparing-products terms, 24.2% in learning terms, and 0.0% in ready-to-buy terms. Indomie and Nongshim show 50.3% and 87.6% in product terms, and those are noodle-purchase searches. The leader owns the recipe moment and nobody else wants it. The rivals own the purchase moment and the leader is not there. That is the difference between a competitor analysis and a list of facts about competitors, and it only appears when the same questions are asked of every brand in the same order, which is the whole point of a framework you can defend.

What did the report refuse to recommend, and why?

Three things, each with a reason, under a heading that reads “What we are deliberately not recommending”. That heading is the section I would pay for on its own, because a recommendation is only meaningful next to the things that were considered and rejected.

It refused to chase the rivals’ branded keywords, indomie goreng and nongshim kimchi ramyun, on the grounds that those are brand-name searches with loyalty already attached and Maggi wins nothing durable by bidding on another brand’s name.

It refused to suggest price promotions on Shopee and Lazada to match the rivals’ placements, because, in its words, no sourced pricing or margin data existed for any brand in Malaysia, so the evidence did not show that Maggi competes on price at all. Discounting would risk the premium without proof it wins share. An analysis that had invented a price gap here would have produced the most confident and most wrong slide in the deck.

And it refused to recommend restructuring Maggi’s separate country websites, with a line I have not seen a piece of software write before: “I cannot see whether it is a bug or design, so the fix stays with the client.” It flagged the risk, that a fragmented footprint could dilute the recipe hub’s authority, and left the decision where it belonged.

How does the report argue against itself?

By writing the strongest case against its own top recommendation, naming the condition under which to abandon it, and counting the assumptions it could not support. The top move was to build out localised recipe content around the terms Maggi already ranks for. The argument against it, in the report’s words: the move assumes there is still meaningful cooking-intent demand left to win beyond the terms Maggi already holds, and the evidence does not show that gap at all.

The kill condition followed: stop if new recipe pages fail to lift recipe-intent organic traffic above the current trend over a fair indexing window. And under the confidence band, it printed the drivers. Four of four supporting claims independently verified. One or more premises resting on an estimated figure rather than a measured one. And the line that made me stop: “5 assumptions behind this move had no supporting evidence when we tried to argue against it.”

A tool that counts the assumptions it could not support and prints the number is doing the opposite of what marketing software normally does. Across the whole report, 37 claims were researched, 28 data points measured, 22 sources graded, and 41 claims re-checked, of which 21 stood, 16 were downgraded and 4 removed as contradicted. The re-check can only lower a claim’s standing, never raise it. Roughly half of a first pass did not survive a second look. Most competitive analyses never take the second look, and ship that half as fact.

What would I actually do on Monday?

I would take the purchase-moment gap first and the recipe content second, which is the reverse of the report’s own ordering, and I would keep its kill conditions on both. I spent part of my career as digital lead for Nestlé Indonesia at dentsu, so I have sat on the brand side of exactly this kind of report, and the lesson that stayed with me is that in packaged food the shelf decides more than the search result does.

So, in order:

1. Close the buy path. Maggi’s site is a recipe hub with no route to a shelf, while both rivals sit on Shopee and Lazada with sponsored placements. The report’s own product action is to add buy-path links from the top recipe and product pages to retail listings and track click-through from a baseline of none, killing it if click-through stays under 1% of page visits after 60 days. That is a week of work and it converts traffic Maggi already has.
2. Take the noodle-purchase terms. Build variant landing pages against the competitor-only purchase terms, aiming at the top ten for at least five of them inside 90 days from a standing start of zero, and stop if none reach the top twenty by day 90. The kill condition is the report’s, and it is the right one.
3. Then extend the recipe hub, in Bahasa Malaysia, against the report’s own test: recipe-intent organic visits measured against the 122,000 a month baseline, with the kill condition above. This is the moat, and moats are widened after the gate is fixed, not instead of fixing it.
4. Do not discount. The evidence for it does not exist, and the report said so.

None of that is in the report as a ranked list. The report gave me graded evidence, three moves with confidence bands, the arguments against them and the things it would not touch. The ordering is my judgement, and a competitive analysis that leaves the judgement to the person who knows the category is doing its job.

The faster way to get one of these on your own market

The faster way is to have the evidence gathered and graded for you and to spend your time on the Monday list. By hand, the scoreboard, the AI rows, the intent split and the re-check take a week for three rivals, and most of it is gathering. Deciding whether it holds up is the part only you can do.

This is the tool that produced the report above: Vantage. You give it your website and up to three competitors, and it builds a graded, evidence-first report you can actually act on, including the section on what it will not recommend. The findings are AI created, so read them with your own judgement, but they give you a real starting point instead of a blank page. Your first analysis is free, which is enough to see your own scoreboard before deciding anything.