Transforming Customer Engagement with Braze
Within 90 days of implementation: …
We help retailers, D2C brands, marketplaces, and ecommerce operators build the technology that drives conversion, increases basket value, and keeps customers coming back — from headless commerce architecture and personalisation engines through omnichannel operations, inventory intelligence, and the data platform that makes every customer interaction smarter than the last.
Retail technology challenges fall into four categories — online performance, in-store experience, cross-channel consistency, and data intelligence. Most retailers struggle with all four simultaneously.
Commerce, personalisation, operations, and data — four capability domains that together determine whether a retail technology programme increases revenue or just adds complexity.
We architect and build headless commerce platforms — decoupling the frontend experience from the commerce backend — using Shopify Plus, Commercetools, MACH-architecture approaches, and custom storefront builds that load in under 2 seconds and convert at rates impossible on legacy monolithic platforms.
We redesign and rebuild checkout flows — reducing steps, eliminating form friction, implementing one-click purchasing, buy-now-pay-later integration, and A/B tested checkout variants — targeting the 70%+ of shoppers who abandon carts before payment.
We build product recommendation engines, personalised search, dynamic pricing capabilities, and behavioural segmentation systems — using Algolia, Nosto, Dynamic Yield, and custom ML models — that increase average order value and session conversion by delivering the right product to the right customer at the right moment.
We implement and optimise retail CRM programmes — Klaviyo, Salesforce Commerce Cloud, Braze — managing welcome series, replenishment triggers, win-back campaigns, VIP loyalty journeys, and the post-purchase sequences that increase repeat purchase rate and customer lifetime value.
We implement and integrate Order Management Systems — enabling click-and-collect, ship-from-store, marketplace fulfilment, unified inventory, split shipments, and the returns workflow that treats returns as a retention opportunity rather than just a cost.
We implement Product Information Management systems — Akeneo, Salsify, Contentful — enabling a single master product catalogue that syncs enriched product content to all channels, eliminating the manual data entry and inconsistency that drives up returns rates and hurts search ranking.
We build retail analytics platforms — customer cohort analysis, basket analysis, channel attribution, store performance dashboards, and demand forecasting — giving merchandising, marketing, and operations teams the data they need to make faster, evidence-based decisions.
We implement and optimise site search and merchandising — Algolia, Klevu, Elasticsearch — with ML-based query understanding, synonym management, personalised ranking, and the A/B testing framework that continuously improves search relevance and category page conversion.
Modern retail technology is built in layers. Each layer must work reliably for the one above it to deliver value. We design, implement, and integrate across all five.
The customer-facing layer — website, mobile app, and in-store digital touchpoints. Performance, UX, and personalisation at this layer directly determine conversion rate, bounce rate, and revenue per session.
Orchestrates order flow from purchase through fulfilment — routing orders to the best fulfilment location, managing click-and-collect, handling split shipments, marketplace orders, and returns across all channels.
The single source of truth for product data — attributes, descriptions, images, variants, pricing, and compliance data — enriched and syndicated to all channels to ensure consistent, accurate product information everywhere.
Manages unified customer profiles — purchase history, behavioural data, email and SMS engagement, loyalty points — and drives the marketing automation, personalisation, and lifecycle campaigns that increase retention and LTV.
The intelligence layer — unified commerce data warehouse, real-time dashboards, ML-based demand forecasting, attribution modelling, and self-service analytics for merchandising, buying, and marketing teams.
Most retail personalisation fails because it is grafted onto the wrong data foundation. Our approach starts with data unification, builds a reliable model layer, and only then activates across channels.
Build a unified customer profile that combines behavioural signals, purchase history, search queries, email engagement, and loyalty data — from every online and offline touchpoint — into a single identity that persists across sessions, devices, and channels.
Transform raw customer data into actionable intelligence — RFM and CLV models that identify high-value customers and those at risk of churn, affinity models that identify product preferences, and predictive models that score the probability of each customer's next purchase.
Deploy personalisation signals to every customer touchpoint — personalised product recommendations on-site, personalised email and SMS content, dynamic homepage and category pages, personalised search ranking, and paid media audience sync — ensuring every channel serves the same coherent individual experience.
The test of retail technology is commercial outcome — not technical implementation. Here is how our clients perform against industry benchmarks after working with us.
Results vary by retailer, category, and starting baseline. Figures represent averages across Rackwave client engagements 2024–2025.
Feedback from Heads of Ecommerce, CMOs, and Digital Directors at fashion, beauty, home, and D2C retail brands.
Our checkout was six steps and losing 74% of shoppers who added to cart. Rackwave redesigned it to three steps, implemented Klarna, and added real-time inventory messaging at the cart stage. Checkout conversion went from 1.9% to 2.6% in 6 weeks. At our revenue scale, that one change was worth £1.4 million in incremental annual revenue. They did not build everything — they identified the single highest-impact intervention and delivered it fast.
We were recommending products using a "customers also viewed" rule that was based purely on category matches. Rackwave replaced it with an ML recommendation engine trained on our actual purchase sequence data — what people buy together, not what they browse together. Average order value went from £62 to £81 in three months. The algorithm is now our highest-performing merchandising tool, generating more AOV lift than any manual cross-sell page we have ever built.
Our Klaviyo programme was sending the same email to 280,000 subscribers and generating 0.8% click rates. Rackwave rebuilt it from scratch — RFM segmentation, predictive churn scores, personalised replenishment timing, and a win-back series for customers who had been dormant for 90 days. Email revenue went from 12% of total to 31% of total within eight months. The win-back series alone recovered £280,000 of customers who had stopped buying.
“Rackwave Technologies has significantly improved our marketing performance while providing reliable cloud services. We’ve been using their solutions for a while now, and the experience has been seamless, scalable, and results-driven.”
David Larry
Founder & CEOCommon questions about retail and ecommerce technology services with Rackwave Technologies.
It depends on your specific constraints and growth trajectory, not on what is fashionable. Headless architecture makes sense when your current platform's templating system is preventing the UX improvements that would materially improve conversion, when your site speed is bottlenecked by the platform's rendering approach, or when you need to deliver the same commerce capability across multiple frontends (web, app, in-store). For most retailers generating under £10 million GMV, a well-optimised theme-based Shopify Plus store outperforms a poorly executed headless implementation. We assess your specific situation and give you an honest recommendation — including the full cost and complexity of going headless — before you commit to an architecture.
Meaningful checkout conversion improvements typically take 4 to 8 weeks — audit, redesign, build, and A/B test. Site speed improvements (Core Web Vitals) can deliver measurable results in 2 to 4 weeks for well-structured sites. Personalisation and recommendation engines take 8 to 12 weeks to implement and tune before the results are statistically significant. The fastest wins are usually checkout friction reduction and site speed — both have direct, measurable causal relationships with conversion that are visible in A/B test results within weeks. We prioritise the interventions with the clearest conversion impact and the fastest implementation timeline.
Klaviyo is the leading email and SMS marketing platform for ecommerce — it integrates natively with Shopify, Magento, and WooCommerce, pulling purchase, browse, and cart data to enable behavioural automation that generic ESPs cannot match. Most retailers using Klaviyo are using a fraction of its capability — sending one-size-fits-all newsletters when they should be sending personalised flows triggered by individual behaviour. The highest-return Klaviyo implementations include: abandoned cart and browse abandonment flows, welcome series with RFM-based branching, post-purchase sequences that reduce returns and drive second purchase, replenishment flows for consumable products, and win-back series for lapsed customers. Our clients average 27-35% of total revenue attributed to email after proper Klaviyo implementation.
Yes — Order Management System implementation is one of our core retail capabilities. We implement Fluent Commerce, Salesforce Order Management, Manhattan Active, and custom OMS solutions depending on your scale and complexity. The key omnichannel capabilities an OMS enables are: unified inventory visibility across all locations (warehouse, stores, DC), intelligent order routing to minimise fulfilment cost and meet delivery promises, click-and-collect and ship-from-store workflows, and returns management across channels. OMS projects typically take 4 to 6 months for a full implementation with multiple channels and locations — the complexity is mostly in the integrations to your ERP, WMS, and store systems.
Most retail attribution is wrong — typically because it relies on last-click attribution, which over-credits paid search and under-credits email, social, and organic. We build multi-touch attribution models that assign credit across the actual customer journey — first-touch for awareness, last-touch for conversion, and proportional credit for middle-funnel interactions. We implement this on top of a unified commerce data warehouse (Snowflake or BigQuery) that combines web analytics, CRM, email, paid media, and transaction data into a single customer journey record. This allows marketing budget allocation decisions to be made on genuine revenue impact rather than the platform that happens to be last in the cookie chain.
For a new D2C launch, we typically recommend starting with a well-configured Shopify Plus store (not headless) with Klaviyo from day one and Google Analytics 4 with proper event tracking. The first 12 months are about understanding who is buying, why, and what is stopping others from completing purchase — data you cannot get from a headless implementation that takes 6 months to build. We help D2C brands design the technology architecture that fits their first 12 months while avoiding the decisions that will limit them at scale — specifically: choosing a PIM before you have a complex catalogue, over-investing in personalisation before you have enough first-party data, and going headless before your site traffic justifies the operational overhead.