A retail chain's social accounts now get as much traffic as its shop windows: a single campaign post can collect size questions, stock questions, delivery complaints and praise on the same day. Social media account tracking lets you read those comments with the same rigour as store reviews, without hopping from app to app. This post explains how BranchVoice monitors your brand's own accounts and what that gives your team.
Why your own accounts are a separate source
A Google review describes a store visit; a Şikayetvar complaint (Turkey's largest public complaint platform) describes an unresolved problem. A comment under your social post is usually a reaction to content: people who like the campaign, ask about price, want to know where to buy, or bring up a past order all write in the same thread. These comments don't move your store rating, but they sit on the most visible face of the brand, in public.
The problem is scale. Reading every comment on every post across Instagram, TikTok, Facebook, X, YouTube, LinkedIn and Reddit fills a social team's day, and separating the comments that need a reply from the ones that point to an operational issue is a job of its own.
Posts and comments arrive every day
In BranchVoice you add an account under Social Media → Accounts with its handle or profile link. Once a day the system reads the account's recent posts, refreshes likes, comments, shares and views, then collects comments for posts whose comment count changed or that have never been read. The same comment is never stored twice; an edited comment is updated and analysed again.
The tracking window and limits are set per account: how many days of posts to follow, how many posts per fetch and how many comments per post. When something urgent comes up, "Fetch now" pulls only what's new, or all comments of a single post, without waiting for the daily run.
A fair comparison across platforms
Raw totals mislead across platforms: a large Facebook audience and a young YouTube channel are not on the same scale. So the Overview page compares with rates. Each of the six headline metrics shows a separate row per platform:
- Followers, with a daily follower curve,
- Posts, with engagement per post,
- Engagement rate: likes, comments and shares relative to posts and followers,
- Collected comments, and how much of the platform's comment count was collected,
- Negative comment share.
Alongside them you get top posts, hashtag performance and a day-and-hour heatmap that shows when your content earns the most engagement. When the same campaign is published on several platforms, AI groups the copies into one post group so you see the campaign's combined impact on a single line. You can unlink a wrong match or link a missed one from the post detail.
What AI reads in the comments
Comment analysis is switched on per account. When it's on, comments run through social-specific analysis groups: comment type and subject, whether it needs a reply, price or stock questions, purchase interest, complaint category, reaction to the creative, brand advocacy, campaign references, humour and tone. You can add your own social analysis groups as well; see analysis groups and topic taxonomy.
Those questions turn into three concrete work lists:
| Need | In BranchVoice |
|---|---|
| Find questions left unanswered | Awaiting-reply comments list |
| Separate operational issues from social chatter | Complaint category and topic analysis |
| Tell whether content is working | Creative reaction, tone and engagement rate |
If store linking is enabled for the account and a comment points to a specific branch, AI moves it to that store; anything uncertain stays at brand level. The logic is covered in matching reviews to stores.
It doesn't mix with your store reviews
Social comments are kept as a separate population. The main dashboard, review list, store ratings and reports count only store and platform reviews, so hundreds of emoji comments on a campaign post won't distort a store's negative share. Social Media has its own Topic Analysis, Comments and Alerts pages. For example, you can set a rule for "negative social comments in a day exceed a threshold" and route it to the social team; rule design is covered in critical review alerts.
The AI summary on the Overview page interprets the period: which post stood out, which topic drew negative comments, how many comments are awaiting a reply. Walking into the weekly meeting with that summary beats collecting screenshots.
What your team gains
- One screen: accounts on seven platforms, one set of filters.
- Time back: posts and comments arrive daily, nobody browses platforms by hand.
- Fair comparison: rate-based metrics show which platform really performs.
- No missed questions: awaiting-reply comments and stock or price questions are listed separately.
- Clean data: social comments never skew store metrics; the two are read separately.
- Campaign impact: cross-platform copies are measured together.
Next steps
Social media account tracking lets you run your most visible channel with the same discipline as your store reviews. To see it with your own accounts, request a demo.