NewStore POS and Akeneo
Integration Agency & Consultants
Inaccurate product data at the point of sale usually manifests as a breakdown in store associate confidence. When a SKU scanned in NewStore POS displays incorrect attributes or missing descriptions because the Akeneo sync stalled, it creates immediate transaction friction. At scale, these data quality gaps between the PIM and the till lead to launch delays and inconsistent customer experiences across the shop floor. Cogent2 designs these connections to ensure the catalogue truth in Akeneo reflects accurately in NewStore, preventing the operational drag of manual data corrections.
Auditing your stack and integration gaps
We connect your NewStore POS and Akeneo PIM quickly, ensuring your POS and PIM work together efficiently. Our consulting services are invaluable, with our system audit services providing a thorough review of your tech stack. This enables our consultants and your team to identify and resolve issues, keeping your NewStore POS and Akeneo integrations running smoothly. By addressing inefficiencies and integration gaps, we help your technology ecosystem operate efficiently, so you can deliver an excellent experience to your customers.
Solution Design
Design decisions for NewStore and Akeneo start with establishing Akeneo as the master for all product enrichment. We typically sequence core product data first, ensuring hierarchy mapping is precise before enabling store-level availability. A key trade-off involves sync frequency: frequent attribute updates ensure in-store accuracy but may increase system load. We often recommend scheduled updates for heavy media assets to protect POS performance during trading hours. This design prioritises store-floor reliability and product data integrity. Finance closes off the primary system of record, while store associates rely on Akeneo-enriched data for customer service consistency. What stays manual at launch is clearly defined to ensure operational control.
Mapping variant hierarchies to flat SKUs
This integration establishes Akeneo as the master source for all product attributes, with data flowing to NewStore POS for store-front execution. A critical control point involves filtering Akeneo Product Models before the sync; NewStore expects flat SKUs, so the integration must decompose parent-level abstractions to prevent import failures. We map Akeneo attributes, including specific brand fields, directly to NewStore’s mandatory requirements to avoid silent record rejection. Monitoring is embedded to catch attribute mismatches, ensuring data is formatted for NewStore’s specific API requirements. By managing this catalogue fan-out, we protect the shop floor from the sync illusion of real-time data that often fails under the complexity of variant hierarchies.
Secure orchestration on accredited infrastructure
Leveraging IPaaS with ISO 27001 and SOC 2 and above accreditations, NewStore POS and Akeneo PIM integrations are delivered securely and efficiently. IPaaS enables NewStore POS and Akeneo PIM to connect without complex coding, automating data between POS and PIM systems. This approach reduces risk, simplifies management, and ensures compliance, while providing robust security and scalability for all integration needs.
Surfacing silent data and sync failures
Basic dashboards often miss the quiet failures that degrade customer trust. Visibility means knowing exactly when a product update in Akeneo fails to reach the NewStore POS, even if the rest of the sync appears green. Hidden issues, such as a missing attribute that prevents an item from being scanned in-store, can compound into lost revenue over time. Monitoring surfaces these operational exceptions early, categorising them so your team knows which errors require immediate intervention. We focus on identifying data integrity issues, allowing operations teams to address the root cause of sync errors before they result in transaction failures at the point of sale.
Operational handover for business owners
Handover ensures that ecommerce, operations, and finance teams take ownership of the new operating model. Training focuses on exactly where product attributes live and how data moves to the POS, based on the specific design decisions of your implementation. We provide operational documentation written for the people running the business, not a technical archive for IT. Your team will learn how to interpret integration alerts and exactly who owns each exception type, such as mapping failures or missing variant data. We define what to check on a regular cadence to maintain data integrity between Akeneo and NewStore. Training is anchored in the reality of your data flow, ensuring the business runs confidently after we step back.
Post-launch governance and system stability
Support after launch focuses on active operational ownership. We monitor the health of the sync between Akeneo and NewStore, identifying mapping errors or system delays before they disrupt store operations. Ownership for issues is clearly defined so that data errors in the PIM are resolved by the content team, while sync issues are handled by support. We provide regular reviews of the integration to ensure it continues to support your store expansion and SKU growth. This ensures that your point of sale remains a reliable tool for store associates, backed by an integration that is managed for long-term stability.
Common failures
Incomplete product data at the point of sale.
Operational impact: When product data from Akeneo is incomplete, store associates cannot answer basic customer questions about product specifications, materials, or origin. This leads to a poor customer experience, transaction delays, and lost sales. Furthermore, missing core attributes like a barcode or price on a SKU can make an item entirely unsellable, requiring manual overrides at the till and creating reconciliation issues for the finance team.
Prevention / Action: The integration should be designed to validate product data against a set of mandatory attributes before it can be synchronised to NewStore POS. Akeneo's completeness rules should be configured per channel to ensure that all data required for the point of sale is present. This establishes a clear process where merchandising must resolve data quality issues within Akeneo, which remains the source of truth, before publishing.
Category tree changes do not update associated products.
Operational impact: Merchandising teams often update or reorganise the Akeneo category tree, but these changes may not automatically trigger updates to the thousands of associated SKUs in NewStore. This results in an inconsistent product hierarchy at the POS, where products appear under old categories or fail to show up in new ones. This directly impacts in-store navigation, filtering, and the accuracy of sales reporting based on product categories.
Prevention / Action: Avoid relying exclusively on individual product webhooks, which are not triggered by changes to parent categories. The integration architecture should include a scheduled process that queries Akeneo for products within recently modified categories. This process then forces an update for each affected SKU in NewStore, ensuring structural catalogue changes are reflected reliably.
Mismatched simple and variant product structures.
Operational impact: If a 'Simple' product in Akeneo is later converted into a 'Product Model' with variants (e.g., size or colour), the integration can fail to handle the change correctly. This results in duplicate or orphaned products in NewStore POS, where both the old simple SKU and the new variants might appear. This confuses store staff, corrupts inventory records, and leads to sales being recorded against incorrect or obsolete SKUs, which complicates sales and inventory reporting.
Prevention / Action: The integration logic must be designed to explicitly manage product model conversions. When a product's type changes, the process should sequence the API calls to first archive or remove the original simple SKU in NewStore before creating the new product model and its associated variant SKUs. This requires robust error handling to prevent data corruption during the transition.
Frequently asked questions
How quickly do attribute updates in Akeneo reflect in NewStore POS?
Updates typically sync based on defined triggers, such as Akeneo completeness status changes. A common failure occurs when an attribute label is updated without changing its underlying code, which may not trigger a delta sync. This results in operational latency where store staff see outdated information despite the PIM appearing correct.
How does the integration handle Akeneo 'Product Models' and variants?
NewStore consumes flat SKUs rather than the parent-level abstractions used for PIM enrichment. The integration must filter Product Models and map the resulting variants into NewStore compatible records. Failing to handle this transition correctly usually leads to import failures or orphaned records at the point of sale.
Will reorganising the Akeneo category tree update NewStore navigation?
Not automatically. Changes to the category tree hierarchy often do not trigger individual product update events. Without a specific workflow to monitor tree changes, products in NewStore remain mapped to legacy categories, creating source-of-truth ambiguity for store associates trying to locate stock.
How are incomplete product records handled?
We use Akeneo's channel-specific completeness score as a gate. Records only post to NewStore once they meet the 'retail store' channel requirements. This prevents missing mandatory data, such as brand attributes, from reaching the till.
Can we sync high-resolution imagery to POS devices?
Syncing original assets from Akeneo can cause performance lag on handheld devices. We typically generate optimised renditions during the sync process. This ensures store staff have the visual context they need without slowing down the POS responsiveness.