Comparing competitors by opening each one’s Instagram on some random Tuesday is the most common way to run competitive analysis, and also the most misleading: you capture one competitor’s peak week, another’s promotional hangover, and walk away convinced of a “pattern” that doesn’t exist. This guide shows how to build a side by side competitor comparison that reveals a real pattern: same window, same ruler, same metrics for everyone, without a spreadsheet.
The path has three parts: understanding why a one off comparison lies, knowing what each row of the dashboard comparison shows and, above all, knowing which decision comes out of each reading. A metric that doesn’t change a decision is just decoration.
Why a one off comparison lies
Picture a supplements store that opens its biggest rival’s profile during Consumer Day week, in March. It finds coupons, free shipping and bundles stacked up and concludes: “this competitor is aggressive, we need to react.” Another store makes the same visit in the first week of December, right after the Black Friday hangover, finds a quiet feed and concludes the opposite: “that one is asleep at the wheel.” Both photographed an extreme and called it routine.
The problem isn’t lack of attention, it’s method: a one week sample, with no common denominator across competitors and no record of what was seen. Two weeks later, the data source becomes the memory of whoever looked. Any serious comparison demands the opposite of this: a fixed window, continuous collection and the same metrics calculated the same way for everyone.
One off comparison
You open the profile when you remember, usually on an atypical date
Each competitor seen at a different moment
The conclusion becomes an “impression” with no record
You react to a peak as if it were routine
Continuous comparison
Fixed window (last 60 days), the same for everyone
Automatic 24/7 scanning, no need to remember
Metrics on record: you can compare with the previous month
Tells a seasonal peak apart from a strategy change
We’ve already written about why a spreadsheet can’t sustain this kind of routine: someone has to feed the tab every week, and it dies in the second month. The alternative is a screen that comes already filled in.
The side by side competitor comparison: what each column shows
In the Batedor dashboard, the screen lives under Competitors > Compare. You pick 2 to 4 competitors and the dashboard builds one card per competitor, side by side, always on the same window: the last 60 days. Every metric comes from the same automatic scan (Instagram, Facebook, YouTube, website and, if configured, the Meta Ad Library and TikTok), with each detection classified by AI into one of 16 campaign types. The ruler, therefore, is the same for everyone.
| Row | What it shows | Question it answers |
|---|---|---|
| Total | Campaigns detected in the 60 day window | Who produces the most promotional activity? |
| Active | How many are still live now (and how many have already ended) | Is the pressure current or old backlog? |
| Cadence | Campaigns per week (total divided by the ~8.6 weeks in the window) | What steady pace does each one keep? |
| Dominant type | The most detected campaign type in the period | What is this competitor’s weapon of choice? |
| Mix by type | The 6 most frequent types, with count and percentage | What is the whole promotional strategy, beyond the main weapon? |
| Dominant platform | Where campaigns show up the most | On which channel does this group’s war play out? |
| Latest campaigns | The 5 most recent detections, clickable, with active/ended status | What exactly did they run most recently? |
| Sources and last crawl | How many sources per platform and when the last scan ran | Does this data deserve trust before it becomes a decision? |
Two details on the screen save you work. On the three big numbers (Total, Active and Cadence), a “Comparison leader” marker appears next to whoever is ahead, so you don’t have to check number by number. And if a competitor doesn’t have synced sources yet, its column shows an explicit warning instead of a silent zero, which would lead to the wrong conclusion that they’ve gone quiet.
How to read each row (and the decision it drives)
Cadence: who can keep up the pace
Total impresses, cadence reveals. A competitor with 26 campaigns in 60 days keeps up 3.0 per week; another with 6 campaigns runs at 0.7. That changes the nature of the response: against the first, planning one big quarterly campaign is pointless, because they bury you in between. The decision that comes out of here is about the calendar: if the leader in your set keeps up 3 per week and you post an offer once a month, your problem isn’t creativity, it’s frequency. And a specific rival’s cadence climbing weeks before a key date (the warm up) is the signal to move your own entry earlier.
Mix by type: each one’s weapon of choice
The mix is where competitors stop being a single block. Within the same category you usually find one rival that lives on percentage discounts and coupons, another that does almost nothing but product launches and giveaways, a third betting on free shipping. The decision here is don’t copy the leader’s weapon by reflex: respond where your margin allows. If the two biggest players fight on percentage discounts, joining that war burns cash; installments, bundles/kits or shipping can hurt less and convert just as well.
And if the columns show everyone crammed into the same type (four cards with percentage discount dominant), you’re looking at a portrait of the crowded center of the category. The next step isn’t one more promotion, it’s to look for the white space no one is occupying.
Dominant platform and sources: where the war happens
If two rivals concentrate their campaigns on Instagram and no one touches YouTube, there’s a channel with attention to spare and too little competition. This row decides media and content allocation. An honest caveat before concluding anything: dominant platform reflects the sources you configured. If you only monitor Instagram for a given competitor, they’ll be “Instagram dominant” by construction. That’s why the sources row sits at the bottom of each card: check that the competitors have similar coverage before comparing this reading.
Latest campaigns: the reality check
The numbers tell you how much; the last five campaigns tell you what. Each item is clickable and opens the full detection: title, classified type, when it was first seen and whether it’s still active. Use this row to validate the quantity: a high cadence made only of brand reposts weighs less than a medium cadence of offers with the price right there. Typical decision: before reacting to a number, look at three or four of the rival’s actual campaigns and judge the offer itself.
Reading share of voice: your slice of the noise
With the cards side by side, a simple bit of math turns the comparison into a share meter: add up the totals of every column (that’s the “pie” of promotional activity for the group) and divide each one’s total by the sum. A practical trick: register your own store as one of the monitored profiles (the dashboard scans any public profile, including yours) and put your column into the comparison.
Example: your store with 18 campaigns in 60 days, rivals with 34, 22 and 15. The pie is 89, your slice is 20%. The absolute number alone would mislead: if in the next comparison you rise to 24 campaigns but the pie goes to 140, your slice dropped to 17%, meaning the group sped up more than you did.
It’s worth naming the limit: this is share of voice of detected promotional activity, not of sales or reach. For the full version of the metric, with mentions, engagement and the excess share of voice rule, see how to measure share of voice and benchmark engagement.
From photo to film: the daily history behind the comparison
The comparison is the photo of the last 60 days. Behind it, the dashboard captures a snapshot per competitor every day, in the early morning: total campaigns, how many are active, how many appeared in the last 24 hours, the mix by type and by platform and an estimated posts per day rate. On each competitor’s page, those snapshots become the timeline: “Campaigns today,” “30 day change,” “New in the period” and a chart of the total over the last 30 days (the query stretches to a full year).
It’s this longitudinal layer that separates a peak from a pattern. Three shapes show up often: the ramp (cadence climbing week after week, typical of a warm up: whoever starts accelerating in mid July is aiming at Father’s Day, which in Brazil in 2026 falls on August 9), the step (a shift to a new level that holds, a sign of new budget or a new strategy) and the valley (the post date hangover, which a one off comparison mistakes for permanent weakness).
One limitation for planning ahead: the history starts counting on the day the competitor enters the dashboard. The snapshot is daily and not retroactive, so no one can “go back in time” to see the past quarter of a newly added rival. That’s why it pays to start before the question comes up: the 14 day trial, no card required, already keeps this collection running while you evaluate the tool.
What the comparison doesn’t do
- It doesn’t measure sales. A detected campaign is a sign of promotional effort, not of revenue. A rival can run 40 campaigns and sell poorly.
- It doesn’t read anything private. Collection covers only competitors’ public content (posts, visible ads, website pages), in compliance with the LGPD (Brazil’s data protection law). Closed email lists and WhatsApp groups are left out.
- The comparison window is fixed at 60 days. For a longer horizon, use the timeline on the competitor’s page, which queries up to a year of snapshots.
- The data is only as good as the sources. A competitor with one configured source yields fewer detections than a competitor with four. The sources row exists for you to check this before concluding.
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