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Metrics, AI filters, and a full year of context: a competitor analysis framework that fits into your actual workflow.
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How to Analyze Competitors on Social Media (Best Practices)

6/4/2026
7 min
AuthorCover_TaniaRodríguez

One of my favorite parts of social media analytics is digging into competitor data. When I analyze a brand's performance and strategy, I need to look at what's happening around it. Yes, I need to dig around to better understand the brand, not just for the gossip. Though let's be honest, that's part of it too 💅

Over time, though, I've noticed this practice still doesn't happen as often as it should. In fact, the latest Marketing Paradise study on Social Media in Major Brands shows that only 13% of these companies rate competitor analysis as excellent in importance for decision-making.

This article isn't about convincing you why competitor analysis matters; I'm assuming you already know. What I do think is that many people skip it because it feels like too much work, too much time, and too little action that translates into quick results. In other words, it sounds great in theory but feels heavy in practice. So I've set out to simplify competitor analysis with this list of best practices that have helped me give it a more professional and, above all, more useful approach.

• Two public metrics that tell you everything about your competitors on social media.

• How to use AI to read the real strategy behind their data.

• Why excluding giveaways and promotions completely changes the analysis.

• How many brands to analyze and for how long to get real context.

• What nobody looks at: competitor mistakes as a free competitive advantage.

TWO METRICS ARE ENOUGH TO ANALYZE YOUR COMPETITORS

You don't need twenty metrics to analyze your competitors (or your own brand). In fact, a few well-chosen ones will usually serve you much better than an infinite battery of data that ends up being useless for decision-making. That said, the metrics you use should meet two conditions: they need to be calculable from public data (interactions, followers, number of posts, etc.) and they need to be contextualized so the comparison is fair.

So which metrics best meet these requirements?

• Average engagement rate by followers (yes, the average not the total; here's why).

• Average interactions per post.

A bonus recommendation: also pull industry averages. That way you can show up with insights like "we're X% above the sector average," which looks great in a report and is actually useful too.

USE AI TO UNDERSTAND YOUR COMPETITORS' REAL STRATEGY

One of the hardest parts of competitor analysis is understanding what's behind the numbers: the intent, the strategy, the positioning, the real objectives driving their social media presence. In other words, the actually interesting stuff. Fortunately, AI can help here without requiring an enormous amount of manual work. Below are some of my favorite analysis examples; all detectable with a competitor data CSV and some simple prompts. Or, even better, with social media analytics tools that already have AI built in (like Welov.io), saving you a lot of manual work.

Aspirational positioning

Example output from the "Highlights by brand" prompt template in Welov.io. Applied to a view of the top 2025 content in the skincare sector. Summary example for Vichy (left) and Avène (right). Note: it's a recreation of the original Spanish output.

Content strategy

Example output from the "Sector content analysis" prompt template in Welov.io. Applied to a view of the top 2025 content in the skincare sector. Summary table of topics across the full sector. Note: it's a recreation of the original Spanish output.

Copywriting methods used

Example output from the "Copywriting methods" prompt template in Welov.io. Applied to a view of the top 2025 content in the skincare sector. Summary of methods across the full sector. Note: it's a recreation of the original Spanish output.

Target buyer persona

Example output from the "Buyer persona by brand" prompt template in Welov.io. Applied to a view of the top 2025 content in the skincare sector. Target example for Eucerin (left) and Bioderma (right). Note: it's a recreation of the original Spanish output.

Strengths they want to communicate

Example output from a custom prompt to analyze the top 3 communicated strengths per brand, from Welov.io. Applied to a view of the top 2025 content in the skincare sector. Summary table for Eucerin (top left), Cerave (top right), Vicht (bottom left) and Avène (bottom right). Note: it's a recreation of the original Spanish output.

EXCLUDE GIVEAWAYS AND PROMOTIONS TO READ REAL PERFORMANCE

In sectors where promotions and giveaways are common, it's worth excluding that type of content if you want a more organic read on performance. Otherwise, you risk confusing good content with good marketing spend, or forced follower acquisition. They're not the same thing, even if the spike on the graph looks great.

You can use AI to filter out these posts, sure; but to be completely honest, my recommendation is to do it with a content filter in a tool where your data is well-organized and the technology is more precise, like Welov.io. If you filter words like "giveaway", "contest", "winners" and similar, you cut out those interaction spikes that distort your averages and your competitors'. That way you can better identify which posts are generating genuine community interest and which ones are inflated by a promotional mechanic.

Example of keywords used in a Welov.io content filter to exclude posts related to giveaways and contests. Check the recommended words list for excluding from your analysis here. Note: it's a recreation of the original Spanish screenshot.

ANALYZE THE FULL SECTOR, NOT JUST YOUR DIRECT COMPETITORS

For qualitative analysis, focusing on 2 or 3 direct competitors is perfectly sufficient, but don't stop there. If you can, broaden the scope and include more brands from the sector when analyzing thematic and stylistic trends, identifying content gaps, or spotting opportunities in narrative niches.

This lets you see what a leading brand might be doing, one you can't compete with in terms of resources or product, but absolutely can in terms of social media presence. It also helps you find new directions: formats that are growing, narrative or visual structures already working in the sector that your direct competitors haven't adopted yet, but leaders or more alternative brands have. This is how you spot niches your direct competition isn't working yet; and if they make sense for your brand, you can claim that space before anyone else does.

Example output from the "Topic trends over the last year" prompt template in Welov.io. Applied to a view of the top 2025 content in the skincare sector. Proposed new topic ideas for the full sector. Note: it's a recreation of the original Spanish output.

ANALYZE THE FULL YEAR, NOT JUST THE LAST QUARTER

Don't limit yourself to one month or one quarter. The real value comes from contextualizing those results with longer periods, like the entire previous year. With Welov.io you can review the historical data of any public profile and see how your competitors' performance has evolved month by month, without having to build a massive Excel from scratch.

This lets you see:

• Whether this month's results (good or bad) are anomalies or reflect a sustained trend over months.

• Identify sector-wide trends and spot shifts between brands and time periods.

• Detect seasonal patterns in your sector and adapt accordingly.

Example output from the "Topic trends over the last year" prompt in Welov.io. Applied to a view of the top 2025 content in the skincare sector. Trend analysis and sector-wide changes. Note: it's a recreation of the original Spanish output.

ANALYZING YOUR COMPETITORS' MISTAKES IS THE CHEAPEST RESOURCE YOU HAVE

Don't only focus on what your competitors are doing well. It's absolutely worth looking at what they've tried that didn't work. Because learning from others' mistakes is not only incredibly useful, it's a lot cheaper than making them yourself.

Paying attention to what doesn't work on similar profiles can save you time, resources, and a few ideas that sounded brilliant in a meeting but never materialized into results. You'll be able to spot:

• Post formats that seem like trends but don't perform well in your sector at all.

• Content topics that might look promising but are being approached in a way that doesn't connect with the audience.

• Marketing actions that don't work in the sector, like a specific type of giveaway or promotion.

Example output from a custom prompt to generate a report focused on the sector's worst-performing content, from the "Content Report" feature inWelov.io. Analysis of why content fails in the sector. Note: it's a recreation of the original Spanish report.

FREQUENTLY ASKED QUESTIONS ABOUT COMPETITOR ANALYSIS ON SOCIAL MEDIA

What metrics should you use to analyze competitors on social media?

The two most useful and comparable metrics using public data are average ER by followers and average interactions per post. They're enough to get a fair reading on any account's performance, as long as they're compared in the same context and promotional posts that skew the averages are excluded.

How often should you analyze competitors on social media?

Ideally, review competitor data monthly to detect changes, and do a deeper review quarterly with full-year context. One-off analyses without historical data are useful but limited: the interesting stuff shows up when you can tell whether something is a trend or a one-off.

How many competitors should you analyze on social media?

For quantitative performance analysis, 2 or 3 direct competitors is enough. For qualitative analysis (content trends, topic gaps, emerging formats), it's worth broadening the scope to 5 or more sector brands, including reference brands that aren't direct competitors.

How do you exclude giveaways from competitor analysis on social media?

The most reliable method is applying a keyword filter to posts: "giveaway", "contest", "winners", "enter to win" and similar variants. This removes both the entry posts and the winner announcement posts, which also generate artificial interaction spikes. Tools like Welov.io allow you to apply this filter directly in the analysis without manually cleaning data.

If you want to do all of this without building a separate data collection process, Welov centralizes competitor metrics, content filters, and historical analysis in one place. And yes, you can try it for free 😏

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