Playbook Priorities Across Your Whole Portfolio
Stop catching ROAS drops after the client does. Playbook surfaces proposed next steps per client from live data on the scheduled sync—your team reviews trends early and decides what to change across every platform.
Alpomi prioritises recommendations and proposed tasks from live data—your team reviews, approves, and executes.
What Playbook at scale gives agencies
Priorities and proposed tasks—your team stays in control
- Daily Playbook per client from synced Google Ads, Meta, TikTok, and Shopify data
- Proposed tasks on the Action Board—your team accepts, assigns, or skips before anything runs
- Trend and pacing signals so gradual declines surface before the client call
- Budget and creative recommendations with evidence attached, not black-box scores
- Portfolio view: see which accounts have open proposed tasks this week
- Plain-language priorities—no data science degree required to brief a client
- Alpomi prioritises recommendations and proposed tasks from live data—your team reviews, approves, and executes.
Why Agencies Need Playbook at Scale
The real performance challenges behind managing 20+ client ad accounts without a shared workflow
Too many client accounts to check deeply every day
With 15–50+ clients, most teams can only dig into a handful of accounts each week. The rest wait for the monthly report or a client email. Playbook surfaces proposed next steps per client from synced performance data so you know which accounts deserve attention first.
Slow ROAS drift shows up late on client calls
Gradual declines rarely trip platform threshold alerts. By the time someone notices in a spreadsheet, the client may already be frustrated. Trend signals in Playbook flag week-on-week movement your team can investigate before the QBR.
'Why did performance drop?' shouldn't take an hour to answer
Diagnosing a drop means cross-referencing creatives, audiences, bids, and Shopify conversion in separate tabs. Playbook ties evidence from connected sources into plain-language context so account managers walk into calls prepared.
Budget moves still live in spreadsheets
Reallocating spend across platforms and clients is manual modelling every week. Playbook proposes budget and platform shifts with supporting metrics; your team accepts proposed tasks on the Action Board or skips them.
This is what you'd see in Alpomi
A real example of the AI recommendation format: clear, actionable, and already explained
Client: Midlands Roofing Co.
Alert
⚠️ ROAS declining 8% week-on-week for 3 weeks. Now at 1.8× (was 2.5×)
Root cause identified
Creative fatigue detected: top 3 ad creatives running for 47+ days with no refresh
AI Recommendation
Pause underperforming creatives. Reallocate £400/week budget from Brand Search to Performance Max. Expected ROAS: 2.3× within 14 days.
High confidence. Pattern matched across 12 similar accounts
Everything You Need to Scale Performance Without Scaling Headcount
AI that does the monitoring, diagnosis, and recommendation. So your team does the optimising
Playbook priorities per client account
Each client gets a daily Playbook grounded in live performance: which campaigns to review, where spend is pacing, and what to test next. Priorities come with evidence your team can defend on a call.
Trend signals, not just threshold alerts
Platform alerts fire on single-day spikes. Playbook highlights multi-week trajectories—ROAS direction, spend pacing, creative fatigue patterns—so your team reviews accounts before issues become renewals conversations.
Cross-platform budget proposals
When spend efficiency differs across Google, Meta, and TikTok, Playbook proposes reallocation with supporting metrics. Your team approves on the Action Board—no autonomous budget changes.
Context before the client asks
Creative fatigue, audience saturation, seasonal shifts, and auction pressure show up with linked metrics. Account managers see likely drivers before joining the call.
Why AI Monitoring Is No Longer Optional at Scale
Daily
Playbook refresh per client on the scheduled sync
Pro+
Playbook and cross-domain recommendations (see pricing)
One
Action Board workflow for proposed tasks your team controls
Portfolio
Oversight across every client without adding surveillance headcount
Before Alpomi AI vs After Alpomi AI
From reactive firefighting to proactive optimisation across every client account
Before: Reactive, periodic checks
- •Hope the client doesn't notice ROAS declining between your weekly checks
- •Get a 'what's happening?' email from the client on Friday afternoon
- •Spend 30+ minutes diagnosing across platforms, ad sets, and Shopify
- •Present findings on Monday. 5 days after the problem started
- •Repeat for every client. No capacity to monitor all accounts proactively
After: Proactive AI intelligence
- Playbook refreshes from synced performance across clients on the scheduled sync
- Trend signals highlight accounts to review: pacing, ROAS direction, creative fatigue
- Proposed tasks land on the Action Board with evidence attached
- Your team accepts, assigns, or skips—no autonomous campaign changes
- Account managers walk into client calls with context already assembled
- Portfolio oversight scales without hiring purely for account surveillance
Alpomi AI vs Manual Monitoring and Enterprise Tools
Enterprise-grade AI insights at a price built for mid-market agencies
| Capability | Alpomi (Pro+) | Manual / periodic checks | Enterprise AI platforms |
|---|---|---|---|
| Daily Playbook per client | ✓ From synced platform data | ❌ Spreadsheet spot checks | Varies |
| Proposed tasks (human-in-the-loop) | ✓ Action Board accept/skip | ❌ Ad hoc email threads | Varies |
| Trend and pacing signals | ✓ Multi-week trajectories | ❌ Misses slow-burn issues | ✓ |
| Budget proposals with evidence | ✓ Team approves before changes | ❌ Manual modelling | ✓ |
| Multi-client portfolio view | ✓ One Workspace | ❌ Tab overload | ✓ (expensive) |
| Plain-language priorities | ✓ Brief clients without jargon | ❌ Analyst-dependent | Varies |
| Transparent pricing | ✓ Pro+ playbook (see pricing) | ✓ (but your time isn't free) | ❌ Custom/opaque |
Explore other agency features
Alpomi's Agency tier includes all of these. See how they work together.
Frequently asked questions
- What does Playbook at scale mean for a marketing agency?
- Playbook surfaces proposed next steps per client from synced Google Ads, Meta, TikTok, and Shopify data. Your team reviews priorities, accepts proposed tasks on the Action Board, and executes—Alpomi prioritises recommendations and proposed tasks from live data—your team reviews, approves, and executes. AI playbook and cross-domain recommendations: Pro+ (see pricing).
- How does Alpomi help agencies catch performance drops early?
- On the scheduled sync, Playbook highlights trend and pacing signals—ROAS direction, spend pacing, creative fatigue patterns—so account managers know which clients to review before the monthly report or an angry email.
- Can Playbook propose budget reallocation across platforms?
- Yes. Playbook can propose shifts between campaigns and platforms with supporting metrics. Your team accepts or skips each proposed task on the Action Board; budgets change only after your team approves.
- Does this work for small agencies with fewer than 10 clients?
- Yes. Even with a handful of clients, a shared Playbook and Action Board workflow reduces the cognitive load of checking every account manually and keeps priorities documented for the team.
- How is Alpomi different from enterprise analytics stacks?
- Enterprise platforms often stop at dashboards and exports. Alpomi adds a daily Playbook and proposed tasks your team controls—aimed at mid-market agencies who need portfolio oversight without a six-figure analytics contract.
Stop Catching ROAS Drops After the Client Does
See Playbook priorities and proposed tasks across a multi-client setup. Book a 20-minute demo—we'll walk through a sample client workflow.
Also see how AI optimisation works alongside client health monitoring and portfolio management.