For agencies that grow D2C brands
What should a multi-brand dashboard show your agency every morning?
A multi-brand dashboard should open on what changed for each brand since yesterday, measured against that brand's own baseline, with the channel, the evidence and anything waiting for your approval. Brands where nothing moved should take one line, not a tab. That is how one person runs Moolwan's nine channels in about an hour a day.
9 channels · 1 person · about 1 hour each working dayMoolwan, run on ai-dm · Team · Sep 2026 · real data
What you'll see in 10 minutes
- Your first brand's report, built from its domain alone.
- Four starter research runs: website health, search visibility, AI assistant visibility and brand mentions.
- Your next brand added the same way, each with its own private brand model.
Isn't a Google Ads manager account or Meta Business Manager enough?
Monday, 9:30. Your Google Ads manager account shows every brand's spend on one screen, and Meta's business portfolio (formerly Business Manager) does the same for Meta. Then the rest of the morning goes on Search Console, each Business Profile, the review sites and rivals' ads, one brand at a time.
Manager accounts solve access, not attention. Each covers one platform, and neither tells you whether a number is unusual for that brand. So the brand whose Maps rank slipped, or whose rival doubled its ads with nobody tracking competitor ads, waits until someone happens to look. Here is what each option covers across a roster of brands.
| Option | What it shows across brands | What it leaves out |
|---|---|---|
| Google Ads manager account | Every brand's Google Ads accounts from one sign-in | Meta, organic search, AI answers, reviews, Maps and rivals; no comparison with each brand's normal range |
| Meta business portfolio | The Meta ad accounts and Pages each brand has shared with you | Everything outside Meta; no comparison with each brand's normal range |
| A spreadsheet or report you build | Whatever columns you build and keep filled | The hours to keep it current every morning; totals rather than change against each brand's baseline |
| ai-dm | Each brand's ads, search, AI search, reviews, Maps, rivals and site health, read against that brand's own baseline every day | Shopify revenue and order data; attribution models |
Keep your manager accounts for making changes. ai-dm reads each brand's channels and shows what moved, and nothing changes in a brand's account until a person on your team approves it. You can check how brand data is protected.
No plan to pick. Pay as you go, per brand.
What should each brand's row show?
One answer per brand: does this need us today? Totals can't answer it. A ₹40 rise in cost per purchase is routine for one brand and a warning for another, so every row needs the brand's normal range beside today's number. Five things make a row useful.
What changed, against the brand's own baseline
Today's number next to its normal range, so a real shift stands out from a quiet day.
Where it changed
The channel, so the right person on your team picks it up first.
Why it probably changed, and how sure that is
The likely cause with a confidence level, and the raw record behind the number.
What is waiting for your approval
Drafted review replies, posts or ad changes that do nothing until a person says yes.
When the data was last read
A stale number looks exactly like a calm one.
Leave off: lifetime totals, charts of numbers that did not move, and metrics no brand has asked about. They make the view longer, not clearer.
Build your own morning sheet
Type the brands you manage and pick the channels you watch. You'll get a sheet with these columns for every brand and channel, ready for Google Sheets or Excel.
21 rows3 brands × 7 channels to fill before anyone acts, every working day.
Free, no login. The starting brands are an illustrative example. ai-dm reads these rows for every brand you add, each morning.
Which brand should you look at first each morning?
Alphabetical order puts the brand in trouble wherever its name happens to fall. Sort by what changed instead, so the first ten minutes go where money or trust is leaking. Work down in this order.
Brands below their own baseline
A rising cost per purchase or a dropped AI mention costs more every hour it waits.
below baselineBrands with something waiting for approval
A drafted reply to a one-star review helps no one until a person approves it.
to approveBrands where a rival moved
New ads, a burst of reviews or a jump in the Maps local pack.
rival moveBrands with an opportunity
A page gaining impressions in Google's AI results, or a search query on the rise.
opportunityEverything within its normal range
One line for all of them. No tab needs opening.
within normal range
(login required) · Walk into the next brand review with the answer already open.
How does ai-dm run the morning view across brands?
It reads every brand's channels against that brand's own baseline, then sorts by what changed. Brands within their normal range fold into one line, so the morning starts with the brand that needs you, not the brand that starts with A. Each amber row began as a daily change alert, measured against that brand's baseline.
- Dewleaf Skincarereading against baseline…meta · cost per purchase ₹412 → ₹569, +38% on its normal rangebelow baseline
- Terra Brew Coffeereading against baseline…ai search · named in 1 of 6 tracked ChatGPT answers, usually 4 of 6not mentioned
- Saltpan Snacksreading against baseline…reviews · 3 new reviews, 2 replies drafted2 to approve
- Kora Loom Homereading against baseline…rivals · a rival launched 7 Meta ads in 48 hoursrival move
- Velvet Fig Bakeryreading against baseline…search · a guide's AI-results impressions up 22% on its normal weekopportunity
- Ember & Oak Candlesreading against baseline…all channels · within normal rangecalm
- Juniper Pet Coreading against baseline…all channels · within normal rangecalm
- 2 brands within their normal range: Ember & Oak Candles, Juniper Pet Co
In this illustrative example, five of seven brands need a look: Dewleaf Skincare's Meta cost per purchase is 38% above its normal range, Terra Brew Coffee was named in 1 of 6 tracked ChatGPT answers, Saltpan Snacks has 2 review replies waiting for approval, a rival of Kora Loom Home launched 7 Meta ads in 48 hours, and a Velvet Fig Bakery guide is gaining impressions in Google's AI results. The other two take one line.
The same read, on a real brand. Every morning ai-dm posts one signal per channel across Moolwan's nine channels, and one person reads them in about an hour each working day. In September 2026 that person had 32 open suggestions, each with a confidence level, to approve or dismiss (ai-dm, Sep 2026). You can watch ai-dm run Moolwan, with the source and date of every number.
This view is for your team, problems and all, including signals a brand rarely checks for itself, such as whether ChatGPT names it: track AI search visibility for every brand in the same view. When a brand wants its own window into its results, give it a live portal under your agency's name, kept separate from your internal triage.
Related pages
Questions agencies ask about multi-brand dashboards
What is a multi-brand dashboard for a marketing agency?
A multi-brand dashboard is one view of every brand an agency manages, showing what changed for each brand across its channels so the team knows where to look first. The useful ones compare each number with that brand's own normal range instead of showing raw totals. ai-dm builds this view from each brand's ads, search, AI search, reviews, Maps and rivals. Add your first brand from its domain to see it.
Is a multi-brand dashboard the same as the dashboard we share with a brand?
No. A multi-brand dashboard is for your team: every brand side by side, including problems you are still working on. A brand portal shows one brand its own results under your agency's name. ai-dm keeps the two separate, so your internal triage is never what a brand sees.
Can a multi-brand dashboard show each brand's revenue, ROAS and CPA?
ai-dm shows spend, ROAS and cost per purchase as Meta and Google Ads report them, and traffic from GA4. It reads no order, revenue or customer data from Shopify, does not build attribution models and does not merge platforms into one "true" number. Each figure is traced to the platform record it came from, so you can show a brand exactly where a number came from.
How many brands can we add?
Add brands one at a time, each from its domain. Each brand is billed per brand or pay as you go, in USD and INR, so there is no plan to pick before you know how many brands you will run. Talk to the founder on WhatsApp if you are planning a large roster.
What happens to a brand's history when someone on our team leaves?
It stays with the brand. ai-dm keeps each brand's model, its daily signals and every approved decision in that brand's workspace, so the next person starts with the history, not a handover document. On Moolwan, every approved decision is recorded in its decision ledger.
Can we build a multi-brand dashboard in a spreadsheet or Looker Studio instead?
Yes, and the morning sheet on this page is a fair start. The cost is keeping it current: someone has to fill every brand and channel row each morning and work out each brand's normal range by hand. ai-dm reads those rows every day, which is how one person keeps Moolwan's nine channels to about an hour a day. Download the sheet, then add one brand to compare.
No plan to pick. Billed in USD and INR. A brand's data is deletable on request.