Start with Your Program Story

• Tell the story of how your retail media program began and what success would look like to you in 12 months.
• How many active ad placements do you operate across web, mobile app, and in-store screens in a typical month? Options: Fewer than 10, 10–50, 51–200, 201–1,000, More than 1,000
• Who owns the commercial decisions for retail media, and who runs the day-to-day campaign operations?
• Which teams raise the strongest objections to adding paid ads into the shopper journey, and what are their main concerns? Options: E-commerce UX, Merchandising, Customer experience, Privacy/legal, CIO/engineering, Other
• Describe the top three business outcomes you want advertising to influence, ranked by priority.
• Which statement best describes your current maturity level, sponsored product experimentation, semi-automated campaigns, or platform-driven automation? Options: Experimentation only, Semi-automated operations, Operated via a dedicated platform, No program yet
• Imagine the program operates for six months with no measurable lift in advertiser retention, would you deprioritize retail media as a strategic initiative? Options: Yes, deprioritize, No, continue iterating, Depends on other KPIs, Unsure

Where the Current Approach Stalls

• If your program stopped delivering incremental sales next quarter, what single failure would you point to as the most likely cause?
• When campaigns underperform today, which downstream teams feel the impact first and how does that show up in their metrics? Options: Category sales decline, Merchandising escalations, Advertiser churn, Operational support tickets, Other
• Can you share a recent campaign that missed expectations and what fixes were attempted before pausing it?
• How often do your brand partners dispute reported attribution or request audits? Options: Weekly, Monthly, Quarterly, Rarely, Never
• Name the KPI shortfall that would make you stop pursuing this initiative immediately. Options: No incremental sales, Negative shopper experience metrics, Advertiser churn above target, Compliance failure, Other

Where Data and Catalog Trip You Up

• Point to the single catalog or shopper data gap that would make integration impossible for a pilot.
• Who currently owns the canonical product catalog, pricing, and inventory feeds, and are they enabled to provide access?
• Estimate the SKU count you expect in an initial pilot and the percent of SKUs with stable product identifiers usable for matching. Options: Under 5k, under 50%, 5k–25k, 50–75%, 25k–100k, 75–90%, Over 100k, over 90%
• Describe any existing identity joins between shopper signals (email, loyalty ID, transaction history) and whether an identity graph is maintained. Options: No identity joins, Partial joins, manual processes, Automated identity graph with API, Third-party identity provider
• If a critical feed cannot be delivered via API for the pilot, what workaround would you accept and for how long?

Targeting, Measurement, and Success Metrics Reimagined

• Assume a major brand asked for purchase-level attribution tomorrow, can your systems trace an impression to a transaction without manual reconciliation? Options: Yes, end-to-end, Partially, with manual joins, No, not currently, Unsure
• List the attribution windows and purchase events you consider valid evidence of ad-driven sales for your advertisers. Options: Same-session purchases, 24–72 hour window, 7–30 day window, Subscription conversions, Basket-level lift measures
• Point to the team or role responsible for measurement and the cadence they need for reporting during a pilot.
• Rate how critical closed-loop purchase attribution is to your top advertisers and internal sponsors. Options: Mission critical, Important but not essential, Nice to have, Not required
• Identify the specific attribution failure that would make you walk away from a vendor or pilot immediately.

Integration Realities and Resource Map

• Name the people who would need to be dedicated to the integration and confirm whether they can be assigned without delaying other projects.
• List the external systems that must be connected for the pilot and indicate whether each exposes production APIs. Options: E-commerce storefront (API), Inventory system (API), POS/transaction system (API or batch), Loyalty/CRM (API), Payment gateway (limited)
• Estimate the engineering effort and a realistic calendar for catalog ingestion and identity joins for a first pilot.
• Are there upcoming compliance, legal, or privacy reviews that could delay access to shopper data, and when are they scheduled? Options: None known, Privacy review this quarter, Legal review this quarter, Other scheduled reviews
• What security or infrastructure certifications must our platform meet before you will allow production connections? Options: Standard security review, SOC 2 type II, ISO certifications, Custom vendor assessment, Other

The Other Paths You Could Take

• Share the alternatives you are evaluating right now and the single reason each is on your shortlist.
• Explain what would have to be true about your current approach for you to decide to keep it instead of switching to an outside platform.
• Tell me which stakeholders have proposed an internal build and summarize their main arguments.
• Select the options currently on the table from this list. Options: Build internally, Use existing ad server, Partner with a platform, Rely on marketplace native ads, Pause expansion
• Identify the single factor that would make you switch away from your incumbent even if price and contract terms were matched.

Pilot Acceptance and Deal Accelerants

• Say the pilot hits the KPIs you need, what are the contractual or organizational blockers that would keep you from signing that week?
• Outline the advertiser profile you would choose as the anchor for a pilot to prove ROI fastest, including category, spend level, and data readiness.
• What measurable acceptance criteria will you require for catalog ingestion, targeting accuracy, ad serving reliability, and closed-loop attribution?
• Identify the approver roles whose sign off is required to expand from pilot to full rollout, and the order in which they must sign.
• Explain your decision rule if the pilot misses one KPI but exceeds the others, do you proceed, iterate, or stop? Options: Proceed to phased rollout, Iterate with fixes and rerun, Stop and reassess, Depends on which KPI missed

Commitments, Timelines, and Next Steps

• Flag any legal, commercial, or privacy approvals that would prevent starting within your target 12-week window.
• Can you commit to target dates for integration kickoff, pilot launch, and the first performance review? Options: Yes, provide dates, Need internal alignment, No, timeline TBD
• Provide the internal stakeholder roles that should be invited to the kickoff meeting to clear dependencies and sequence work. Options: Head of e-commerce, Head of marketing, Head of engineering, Privacy/legal, Merchandising lead, Other
• Outline the budget approval path if pilot performance indicates the need for increased spend, including approver roles and typical lead time.
• For a compressed 6-week timeline, identify the changes in resources or approvals required inside your organization to make that feasible.

• Solution Experience — Map Targeting to Your Catalog and Shopper Journeys

• Confirm the current state and its cost to your teams
• You confirm the demonstrated workflow eliminates the manual insertion order rework and reduces time-to-launch as described in Discovery.
• Deliver a sample scenario mapping and run the live end-to-end demonstration based on the provided catalog extract.
• Map targeting to your catalog and shopper journeys
• You agree that targeting and pacing can be mapped to your catalog and shopper journeys and identify any remaining data or mapping gaps.
• Provide an exported catalog extract, top 50 SKUs by volume, and one representative shopper segment to use in the scenario.
• Demonstrate ad serving and pacing using a sample SKU journey
• Define pilot KPIs, anchor advertiser candidates, and a proposed 6- to 12-week pilot timeline.
• You approve pilot acceptance criteria and the remaining evidence required to move toward a pilot decision.
• Share an integration dependency checklist and the required environment access and data formats before the integration planning session.
• Show the closed-loop attribution flow to purchase
• Validate the future state
• Agree acceptance criteria and next evidence steps

• Solution Experience — Workflow Mapping Session
• Solution Experience Deck
• Solution Brief — Workflow Mapping

• meeting
• slides
• document

• Ingest Product Catalog and SKU Mapping
• Connect Shopper First-Party Data Feed
• Integrate Order and POS Data Streams
• Configure Ad Inventory and Placement Templates
• Implement Targeting and Pacing Engine
• Deploy Ad Server and Creative Asset Management
• Enable In-Store Digital Screen Ad Serving
• Activate Closed-Loop Purchase Attribution
• Configure Reporting Dashboards and Metrics
• Enable Cross-Retailer Campaign Orchestration
• Execute Pilot Campaign with Anchor Advertisers
• Train Retail Sales and Ad Operations Teams
• Configure Data Privacy, Identity and Consent Controls

Ingest Product Catalog and SKU Mapping

• Do you have a normalized product feed that includes GTIN (Global Trade Item Number), retailer SKU, and PDP (product detail page) URL? Options: Yes, No, Partial
• How many SKUs are in the catalog you expect to onboard for the initial integration? Options: Less than 10,000, 10,000-100,000, More than 100,000
• Which file format do you currently export for catalog ingestion (for example CSV with column headers, XML product feed, JSON API)? Options: CSV/TSV (file), XML feed, JSON/REST API, SFTP transfer
• Who owns the SKU taxonomy internally and who will be the approver for SKU-to-GTIN mapping exceptions?
• Specify the maximum acceptable unmapped SKU percentage for the pilot (mapping coverage acceptance criteria) Options: <1%, <5%, <10%, Custom
• Provide a sample extract of 5 representative product records (including SKU, GTIN, title, price, category, PDP URL) for testing mapping logic.

Connect Shopper First-Party Data Feed

• Do you have a nightly or real-time first-party shopper feed that includes hashed email, loyalty ID, session IDs, or device identifiers? Options: Nightly batch (SFTP), Real-time API, Both, No feed yet
• How frequently do you update shopper profiles (for example hourly session updates, nightly loyalty sync)? Options: Near real-time (sub-hour), Hourly, Daily (nightly), Weekly
• Which identity keys are available in the feed (for example hashed_email, loyalty_id, cookie_id, mobile_ad_id)? Options: Hashed email, Loyalty ID, Cookie ID (first-party), Mobile ad ID, Other
• Who is the technical owner of the shopper feed and what is the integration endpoint (SFTP path, API base URL) for a read-only test account?
• Are there existing PII (personally identifiable information) transformation rules you apply (for example SHA256 hashing of email, tokenization of loyalty ID)? Options: Yes - hashing rules provided, Yes - tokenization rules, No - need recommended approach
• Indicate any SLA requirements for data latency from event generation to availability in the platform (for example <30 minutes for session updates). Options: <5 minutes, <30 minutes, <4 hours, Next-day

Integrate Order and POS Data Streams

• Which order sources will feed purchase events (for example ecommerce order API, nightly POS batch, OMS export)? Options: Ecommerce order API, Nightly POS batch, Order Management System (OMS) export, Other
• How many store locations and which store ID schema do your POS streams include for in-store attribution? Options: Single store cluster, 10-100 stores, 100+ stores, Provide store ID sample
• Describe the order event schema you can provide (fields such as order_id, timestamp, SKU, quantity, price, store_id, payment_type).
• Which file delivery mechanism will you use for POS/order data (for example SFTP daily batches, Kafka topic, REST webhook)? Options: SFTP daily batch, Streaming (Kafka/SQS), REST API, Other
• Who will own reconciling purchase-level discrepancies between catalog SKUs and POS SKUs during pilot (provide role or team contact)?
• Indicate acceptable data completeness thresholds for order feeds during pilot (for example percentage of orders with line-level SKU and price present). Options: >99%, >97%, >95%, Custom

Configure Ad Inventory and Placement Templates

• Which digital placements will be enabled (for example PDP banner, search results unit, cart module) and provide the placement IDs if available.
• Which creative sizes and formats are supported on your properties (for example 300x250 PNG, HTML5, native product card)? Options: Static image (PNG/JPG), HTML5 creatives, Native product card, Video
• Who will provide creative assets and what is the expected lead time for creative delivery (for example 5 business days prior to launch)?
• Do you require placement-level business rules such as priority capping, revenue share splits, or brand safety lists for specific placement IDs? Options: Yes - priority/capping, Yes - revenue share rules, Yes - brand safety, No
• Describe any page-level constraints that affect ad rendering (for example lazy-load on PDP, viewport size, number of organic recommendations shown).
• Provide the acceptance criteria for placement QA (for example correct creative rendering on PDP across desktop and mobile in 95% of sample pages). Options: 95% render success, 99% render success, Custom

Implement Targeting and Pacing Engine

• Which targeting dimensions must be supported at launch (for example SKU-level, category, shopper audience segments from loyalty attributes)? Options: SKU-level, Category-level, Audience segments (loyalty tiers), Behavioral segments
• How should pacing be handled for time windows and budget throttling (for example uniform hourly pacing, dayparting, store-level caps)? Options: Uniform hourly, Dayparting, Store-level caps, Custom rules
• Describe target match thresholds for audience inclusion (for example minimum segment size, maximum frequency per shopper per day).
• Who will own runtime changes to targeting rules during pilot (provide role and contact for ad ops changes)?
• Provide a sample campaign targeting requirement (for example reach loyalty tier A shoppers who viewed PDP in last 7 days for SKU X).
• Do you require deterministic identity joins only or should probabilistic joins be allowed for cross-device targeting during pilot? Options: Deterministic only, Allow probabilistic joins, Need recommendation

Deploy Ad Server and Creative Asset Management

• Confirm the ad server endpoint and credentials type that the integration team will use for creative push or tag calls (for example server-to-server API key).
• Which creative approval workflow must be followed before pushing creatives to placements (for example creative QA checklist, legal sign-off)? Options: Standard QA checklist, Legal and brand sign-off, Creative agency approval, Other
• List required creative metadata fields you need stored (for example campaign_id, creative_id, SKU_list, landing_page_url).
• Do you have existing creative asset storage (for example DAM - digital asset management) and require connector setup? Options: Yes - DAM connector, No - provide assets via upload, Need recommendation
• Provide expected throughput for creative requests per second for peak traffic on PDP and search result pages. Options: <10 req/sec, 10-100 req/sec, >100 req/sec
• Are there click or impression tracking pixels or server callbacks that must be included in creative templates? Options: Impression pixel, Click tracker, Server-to-server callbacks, None

Enable In-Store Digital Screen Ad Serving

• Are in-store digital screens part of the initial scope and which screen models or CMS (content management system) do you use? Options: Yes - list CMS/model, No
• Indicate the frequency and schedule for screen playlists (for example 30-second slots, rotation every 5 minutes, store local time). Options: 30s slots, 60s slots, Custom schedule
• Who manages local store approvals for screen creatives and what is the SLA for approval turnaround?
• Describe the signal available from screens for attribution such as beacon pings, camera-based anonymized visits, or POS tie-ins.
• Indicate network constraints for screens (for example offline stores, limited bandwidth, scheduled content pulls) that affect creative delivery. Options: Always online, Periodic sync (daily), Often offline
• Do you require device-level SDK deployment or server-side playlist ingestion for screen ad serving? Options: SDK on device, Server-side playlist (CMS), Both

Activate Closed-Loop Purchase Attribution

• Which attribution window should we use to link ad impression to purchase for the pilot (for example 7-day, 14-day view-through or click-through)? Options: 1 day, 7 days, 14 days, 30 days
• Which matching keys will you allow for closed-loop joins (for example hashed_email, loyalty_id, order_id), and which are prohibited for privacy reasons? Options: Hashed email, Loyalty ID, Order ID, Device ID, Other
• Describe the purchase events and line-item fields we should consume to produce SKU-level ROAS (for example order_id, SKU, quantity, price, discount).
• Provide the minimum acceptable match rate between impression-side identifiers and purchase-side identifiers for pilot acceptance (closed-loop acceptance criteria). Options: >70% match rate, >80% match rate, >90% match rate, Custom
• Who will approve the attribution model selection and any tie-breaking rules (for example last-touch, weighted multi-touch) during pilot?
• Are there regulatory or retailer consent constraints that prevent certain joins (for example opt-outs recorded in a consent management platform)? Options: Yes - list constraints, No

Configure Reporting Dashboards and Metrics

• Which KPIs must appear on the shared dashboard at launch (for example SKU-level revenue, ROAS, purchases per 1,000 impressions)? Options: SKU-level revenue, ROAS, Conversion rate, Impressions, Other
• Which reporting cadence do you need for executive and operational stakeholders (for example daily automated report, weekly detailed review)? Options: Daily, Weekly, Monthly, Ad-hoc
• Do you require row-level export of matched purchase events for reconciliation (for example CSV export of matched impression-to-order records)? Options: Yes - daily export, Yes - on-demand, No
• Who will be the recipients of scheduled report emails and what role-based access should be enforced on dashboards?
• Provide any visualization preferences for SKU-level trends such as heatmaps by category or time-series by daypart.
• Do you need certification or export formats for brand auditors (for example signed CSV, PDF audit report)? Options: Signed CSV, PDF audit report, No

Enable Cross-Retailer Campaign Orchestration

• Do you plan to run multi-retailer campaigns from a single dashboard during the initial rollout? Options: Yes - multi-retailer, No - single retailer, Plan later
• Which canonical identifiers should be used to normalize SKUs across retailers (for example GTIN, manufacturer SKU) for cross-retailer reporting? Options: GTIN, Manufacturer SKU, Retailer SKU mapping required, Other
• Describe any campaign governance rules to apply across retailers such as exclusive brand windows, minimum spend per retailer, or pacing harmonization.
• Who will coordinate campaign IDs and naming conventions across retailer accounts for reporting consistency?
• Do you require a single billing reconciliation or per-retailer invoice visibility for cross-retailer spend? Options: Single consolidated billing, Per-retailer invoices, Both
• Indicate any product assortment differences that will affect cross-retailer targeting (for example private label SKUs, retailer-exclusive items).

• decision_readiness
• success_criteria
• stakeholders
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• Master Services Agreement (MSA)
• Statement of Work (SOW)
• Subscription Order Form
• Data Processing Agreement (DPA)
• Data Sharing and Privacy Addendum
• Mutual Non-Disclosure Agreement (NDA)
• Service Level Agreement (SLA) and Support Terms
• Pilot Acceptance Certificate
• Readiness & Go/No-Go Approval
• Change Order Agreement

• Go-live Health Check (weeks 1-4)
• First Measurement Review (weeks 4-10)
• Acceptance Gate — Outcomes Review and Formal Acceptance (around day 90)
• Quarterly Success Review (ongoing)

• Publish the quarterly success summary with metrics, open tickets, and agreed next-quarter actions.
• Log and schedule data-quality fixes and configuration changes required to improve attribution match rate and ingestion completeness.
• Set the date for the Acceptance Gate meeting and circulate the acceptance checklist drawn from Solution Scope.
• Restate Solution Scope acceptance criteria and numeric targets
• Produce a documented pass or fail outcome for each acceptance criterion as recorded in the Solution Scope.
• Obtain a formal acceptance decision with named buyer and seller signatories or capture a remediation plan with firm dates for any failed criteria.
• Confirm legacy manual campaign processes are retired or formally retained read-only and archived.
• Publish the acceptance decision document that lists pass/fail per criterion and includes signatory names or the remediation plan.
• Open remediation tasks for any failed acceptance criteria with deadlines that close before the next review.
• Execute the incumbent process wind-down steps: archive legacy campaign data, update process docs, and set old system to read-only if retained.
• Quarterly attribution performance trends
• Confirm the closed-loop attribution match rate (%) trend is stable or improving toward the Solution Scope target.
• Confirm campaign pacing variance (%) is within the agreed tolerance or identify remediation steps.
• Ensure all high-priority operational tickets have target resolution dates and are in active progress.
• Prioritize enhancement requests into the shared backlog with estimated effort and target quarter for delivery.
• Schedule measurement automation work to reduce manual reconciliation steps for attribution reporting.
• Re-confirm success criteria and owners
• Confirm production endpoints and catalog ingestion pipeline are processing without blocking errors.
• Document top open issues with target resolution dates and responsible party roles.
• Agree the validation checklist that will be used in the First Measurement Review.
• Publish deployment validation report including endpoint health, ingestion status, and access permissions.
• Create tickets for all critical defects with target resolution dates and verification steps.
• Confirm test advertiser campaigns remain active for measurement window.
• Present first 30- to 60-day data
• Determine whether catalog ingestion completeness (%) is on track to meet the Solution Scope target and list remediation if not.
• Determine whether the closed-loop attribution match rate (%) meets the Solution Scope target or identify concrete causes for shortfall.
• Agree a corrective action plan with dates that will prepare the engagement for the Acceptance Gate meeting.
• Publish the measurement data packet with queries and evidence used to calculate catalog ingestion completeness and attribution match rate.
• Present outcome data and evidence per criterion
• Campaign pacing and spend delivery
• Deployment and migration validation
• Campaign delivery and pacing check
• Document pass/fail per criterion and record decision
• Early adoption and usage signals
• Operational ticket burn-down and unresolved blockers
• Attribution reconciliation and data quality
• Enhancement requests and shared backlog review
• Agree remediation plan for any failed criteria
• Defect triage and open issues
• Root-cause analysis for gaps
• Confirm timeline to acceptance gate
• Incumbent process wind-down confirmation
• Agree next quarter actions and checkpoints
• Agree immediate remediation actions