What marketing roles does Cresva support?

Cresva supports growth teams, marketing executives (CMOs, VPs, directors), agencies, and brand teams with AI-powered intelligence that learns from each team's specific decisions and KPIs.

What types of ecommerce businesses does Cresva work with?

Cresva works with DTC brands, multi-channel retailers, subscription brands, high-SKU catalog businesses, and brands selling on both marketplaces and their own store. The AI learns business-model-specific patterns like seasonal trends, churn curves, SKU profitability, and channel dynamics.

How accurate are Cresva's forecasts?

Cresva's forecasts learn from each brand's specific seasonality, channel mix, and decision history. Architecture target: forecasts sharpen across the pilot's onboarding period and continue to improve with each cycle. Exact accuracy depends on data history and category.

Can agencies use Cresva for multiple clients?

Yes, agencies can manage 10+ clients in one dashboard. Each client gets smarter individually, and the system learns patterns across your entire portfolio for cross-client insights.

How does Cresva help marketing agencies manage multiple clients?

Cresva provides a unified dashboard where agencies manage all client accounts. Each client gets individual AI agents that learn their specific brand patterns, while the system also identifies cross-client patterns that surface insights from one client's performance to benefit another. Auto-generated per-client reports eliminate hours of manual reporting work.

Does Cresva's AI learn patterns across different agency clients?

Yes. While each client's data remains isolated and secure, Cresva's intelligence layer identifies anonymized patterns across your portfolio. If a seasonal trend or channel dynamic is working for one DTC client, the system can flag that pattern as potentially relevant for similar clients, giving your agency a genuine intelligence advantage.

How much time does Cresva save on client reporting?

Agencies typically spend 2-4 hours per client per week on reporting. With Cresva's delivery agent (Dex), per-client reports are generated automatically and delivered to Slack or Google Sheets. For an agency with 10 clients, this saves 20-40 hours per week, effectively freeing up a full-time analyst's workload.

Can agencies use Cresva to improve client retention?

Yes. The biggest driver of agency churn is clients questioning ROI. Cresva reconciles each client's platform-reported conversions against the revenue their store actually recorded, so an agency can show where the platform numbers and the till disagree rather than forwarding each platform's own claim.

How does pricing work for agencies with multiple clients?

Cresva offers agency-specific pricing tiers that scale with the number of client accounts. Contact us for agency pricing details. Per-client cost decreases as your portfolio grows, making Cresva more cost-effective than hiring additional analysts.

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See how

Agencies

Twenty hours a week on client reports. One intelligence layer across the portfolio.

Per-client AI that learns each brand. Cross-client patterns surfaced anonymously. Auto-reports in the format each client wants.

Book a demo How agents work →

Where dashboards break for agencies

Four reasons agency margins shrink as client count grows.

Every new client adds dashboard work that does not scale. These four failure modes are why analysts get hired faster than retainers grow.

Reporting eats 20 to 40 hours a week

Two to four hours per client, every week, pulling exports into decks. Analyst time on assembly instead of strategy.

Client churn from ROI questions

Clients ask what they actually got. Platform ROAS doesn't answer that. Without incrementality proof, retention slips at QBR season.

Scaling requires hiring

Every three to five new clients means another analyst. Headcount scales linearly while retainer pricing doesn't.

Insights stay siloed per client

What works for client A could help client B, but nobody connects the patterns. Portfolio intelligence stays untapped.

The four agents

Report, debias, retain, remember. One agents per client.

Parker proves the ROI clients actually want. Dana unifies the data per client. Dex generates and delivers the per-client recaps. Maya holds the cross-portfolio memory.

Attribution Analyst

Parker

Reconciles platform-reported ROAS against each client's P&L. Surfaces incremental contribution at the channel and campaign level. Architecture target: every QBR opens with a contribution number both sides agree on.

Defensible ROI, per client, every QBR.

Analytics Engineer

Dana

Builds the unified data layer per client across Meta, Google, TikTok, Shopify, GA4, Klaviyo. Reconciles spend and revenue every night. Architecture target: the rest of the agents reads from one source of truth per client.

One source of truth, per client.

Reporting Manager

Dex

Auto-generates and delivers the per-client recap on each client's preferred cadence. Slack, Sheets, Slides, Notion, email. Architecture target: replace the assembly time, not the strategist's review.

Per-client recaps, auto-delivered.

Account Lead

Maya

Holds the cross-portfolio pattern memory anonymously. When a tactic earns lift in one client's account, the agents surfaces it for the next similar client. Architecture target: portfolio learning that compounds without crossing client data lines.

Cross-client patterns, anonymized.

The other agents fill out the agents. See all of them →.

Targeted by the 7-day pilot

Concrete deltas. Architecture targets per client.

Four metrics targeted by the 7-day pilot structure for a representative 10-client agency. Exact numbers depend on client mix and current reporting workflow.

Reporting time per client

Manual per-client→Auto-recap + strategist review

Architecture target: Dex assembles the recap; the strategist reviews and adds context.

Total reporting time (10 clients)

Linear with client count→Sublinear: review-only at scale

Architecture target across a representative portfolio. Recovered hours go to strategy and new business.

Client retention defense

Platform ROAS only→P&L-reconciled

Architecture target: every QBR opens with an incremental contribution number, not a platform self-claim.

Per-client forecast accuracy

Predictions not written down→Every prediction scored against actuals

Each forecast is recorded before the period it covers, then compared with what actually happened. A miss is analyzed for cause and fed back into the model.

Agency Posture

Multi-client architecture for agencies.

How Cresva isolates client data, surfaces portfolio patterns anonymously, and connects to ad platforms with scoped OAuth.

Multi-Tenant Client Isolation

Each agency client gets a dedicated workspace with isolated data. Per-client OAuth scopes, per-client storage, per-client audit log. Raw data never crosses client lines.

Anonymized Portfolio Patterns

Maya's cross-client memory layer surfaces lift patterns and tactic outcomes anonymized across the portfolio. Pattern store carries no per-client identifiers; raw data stays in the client workspace.

Write Access, Per Client

Agents write to Meta, Google Ads, Shopify and Klaviyo: pausing campaigns and shifting budgets on the ad platforms, changing variant prices and publishing products on Shopify, and creating and scheduling Klaviyo campaigns. Connections use scoped OAuth per client, with write access requested only on the platforms agents act on. Every change is recorded in that client's audit log, and by default you approve it before it runs. Revoke access per client anytime.

Common questions

Questions agencies ask

How does Cresva handle multi-client management?

Each client gets a dedicated workspace with isolated data and per-client AI that learns the brand. The intelligence layer surfaces anonymized cross-client patterns; raw data never crosses client lines.

Can it learn patterns across different clients?

Yes. Maya holds an anonymized pattern store across the portfolio. When a tactic earns lift in one client's account, the agents flags it for similar clients. Client-level data stays in client-level workspaces.

How much time does reporting actually save?

Architecture target: Dex auto-assembles per-client recaps so the strategist's role moves from manual assembly to review. The recovery scales sublinearly with client count, where review-only stays roughly fixed as the portfolio grows. Exact number depends on the current reporting workflow and client mix.

Can Cresva improve client retention?

Parker's incremental contribution number gives agencies a defensible ROI answer at QBR season. Architecture target: replace platform-self-attribution with P&L-reconciled lift.

How does agency pricing work?

Agency tiers scale with client count and per-client cost decreases as the portfolio grows. See the pricing page or book a call.

Ready when you are

See it work on a single client account.

Pilot one client account. If the recap quality and contribution numbers earn it, scale across the portfolio.