Retailers and consumer brands run a health check before peak season or a customer data project, when consumer volume and consent gaps turn small issues into expensive ones.
In retail and consumer goods, a health check examines two very different customer groups. For shoppers, we review consumer record volume, identity matching, consent and preference storage, service case handling and the sync with commerce and order systems. For brands selling into retailers and distributors, we look at retail account hierarchies, trade promotion data and field sales visit records. Across both, we check storage use, automation load during peak periods and who can export consumer data. Findings are ranked by privacy exposure and by their likely impact on the next holiday or promotional peak.
Retail orgs operate at a scale most business-to-business orgs never reach. Consumer records, orders and service cases grow quickly, so storage limits, slow list views and automation that runs on every record update show up here first. Consumers also have privacy rights under a growing set of state laws, and they expect preferences to be respected across email, text and service. Consumer goods companies add a second world of retail buyers, distributors and store visits, often in the same org. Peak season compresses everything into a few intense weeks. A health check has to consider volume and timing as seriously as configuration quality.
We measure record growth on contacts, person accounts, cases, orders and activities, and identify objects approaching storage limits or causing slow searches and reports. Old guest records, abandoned carts and email activity kept indefinitely are common contributors. The findings recommend what to archive, summarize or stop copying into Salesforce, balanced against reporting and service needs, before storage costs or performance become a crisis.
We review how marketing consent, channel preferences and privacy requests such as access or deletion are captured and fulfilled across Salesforce and connected tools. Gaps often appear where a deletion request removes a contact from one system but leaves copies elsewhere. The review documents each path a consumer's data takes, so your privacy team can confirm requests are completed everywhere they need to be.
Service volume, order updates and marketing sends spike during promotions and holidays. We inventory flows and triggers on high-volume objects, check for automation that calls external systems on every change and review case routing capacity. Items likely to hit platform limits or slow agents at peak are ranked highest, with time left to change them before the busiest weeks arrive.
For consumer goods companies, we review how retail chains, banners, stores, distributors and brokers are modeled, and whether store visit, audit and order data from field reps is complete. Duplicate store records and broken chain hierarchies distort sell-in reporting. We also check how trade promotion and retailer agreement data is stored and who can see sensitive terms. Broker access is tested separately.
We start with the owners of ecommerce, customer service and Salesforce, and add privacy and security leads early because consumer data drives much of the risk. For consumer goods brands, sales operations and a few field reps join. The review is read-only and completed well before peak season code freezes, so high-priority fixes can still be deployed. Privacy findings are shared with your privacy team as they arise. The final report sorts actions into before-peak, after-peak and longer-term groups. Each item names an owner.
We check how customer accounts and orders sync, whether guest checkouts create duplicate consumers and whether order status reaches service agents without delay.
We review how shipping, return and refund updates reach cases, and whether integration errors during high volume are logged and retried.
We confirm how in-store purchases and loyalty data connect to consumer records, what is stored in Salesforce and whether payment data is kept out.
Consumer privacy laws in a growing number of states give shoppers rights to access, delete and limit use of their data, alongside PCI DSS for any payment handling. The health check traces where consumer data and requests flow, and your privacy counsel interprets which obligations apply to each flow.
Unifying consumer profiles across commerce, service, loyalty and marketing depends on reliable matching keys and clean source data. If the org already struggles with duplicate consumers, fix matching and source quality first, or unified profiles will merge the wrong people and split the right ones.
AI service agents answering order and return questions need current order status, accurate policies and strict limits on which customer's data they can reference. Test identity verification steps and confirm the agent cannot reveal another shopper's order details before launch, especially during peak season.
Early enough to act on what it finds. Most retailers freeze significant changes well before peak, so the review should finish with time left to fix high-priority items and test them. We usually recommend completing the health check in the quieter period after the previous peak, so fixes can be scheduled calmly through the year rather than rushed.
Yes, with a different emphasis. Brands selling mainly through retail partners focus more on account structures, broker relationships, trade promotion and field execution than on consumer volume. We review how those records support sell-in and sell-through reporting and whether the direct-to-consumer side, if you have one, is kept cleanly separate from wholesale customer data and pricing.
It can pinpoint the causes. We identify which objects, files and activity records drive growth, what is still needed for service or reporting and what could be archived or summarized. Often a large share of storage comes from data copied from other systems and never used. The findings give you an evidence-based retention plan rather than a blanket purge.
We review the configuration that supports them: case types, entitlement rules, return authorization flows and how refunds sync with order and payment systems. We also check whether agents can issue credits beyond policy without approval and whether those actions are logged. Findings help reduce both customer frustration and financial leakage during high-volume periods. Appeasement credits are sampled too.
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