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Retail & Ecommerce Industry

Retail Technology That
Converts, Retains & Grows.

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.

Headless Commerce Personalisation Omnichannel OMS Retail Analytics
Retail & Ecommerce Technology Solutions — Rackwave Technologies
90+
Retail Clients
34%
Avg CVR Improvement
28%
Avg AOV Increase
22%
Customer Retention Uplift
3s
Avg Page Load Target
4.9★
Client Rating
Industry Challenges

Where Retail Technology Breaks Down

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.

Online / DTC
Slow site speed — 1s delay = 7% CVR drop
Under-optimised checkout — 70%+ cart abandonment typical
Poor mobile UX despite 65%+ traffic on mobile
No personalisation — same experience for every visitor
Search relevance and filters too basic to convert
Returns rate high due to poor PDP content and sizing
In-Store / Physical
Store associates without real-time stock visibility
Fragmented POS systems preventing unified customer view
Manual inventory counting — expensive and inaccurate
Queue and wait time hurting basket completion rates
No digital touchpoints inside the store (kiosk, app)
Gift card and loyalty programme isolated from ecommerce
Omnichannel
Online/offline inventory not unified — overselling and stockouts
Click-and-collect process slow and manual at pickup
Customer returns across channels not systemically handled
Different pricing/promotions online vs in-store causing complaints
Loyalty points not consistent across channels
Customer support not seeing full channel interaction history
Data / Intelligence
Marketing attribution wrong — last-click over-credits paid search
No customer lifetime value model — budget misallocated to wrong segments
Product recommendation engine generic — not personalised
No real-time stock and demand signal for buying decisions
Churn prediction absent — losing high-value customers silently
A/B testing ad hoc — no systematic experimentation culture
Our Solutions

Retail & Ecommerce Technology Solutions

Commerce, personalisation, operations, and data — four capability domains that together determine whether a retail technology programme increases revenue or just adds complexity.

Commerce
Headless & Composable Commerce

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.

Headless storefront buildShopify Plus / CommercetoolsPWA & App architectureCore Web Vitals optimisation
Commerce
Checkout Optimisation

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.

Checkout UX redesignBNPL integration (Klarna, Afterpay)One-click & express checkoutAbandonment recovery automation
Personalisation
Personalisation & Recommendations

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.

Product recommendation enginePersonalised search (Algolia)Dynamic pricing & promotionsBehavioural segmentation
Personalisation
Retention & Lifecycle CRM

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.

Klaviyo & Braze retail automationWelcome & onboarding sequencesReplenishment & win-back flowsVIP loyalty programme design
Operations
Order Management & OMS

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.

OMS implementation (Fluent, Salesforce)Click-and-collect & ship-from-storeMarketplace (Amazon, eBay) integrationReturns management workflow
Operations
PIM & Catalogue Management

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.

Akeneo & Salsify implementationMulti-channel product syndicationDigital asset management integrationSEO-optimised PDP content workflow
Data
Retail Analytics & BI

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.

Customer LTV & RFM analyticsMulti-touch attribution modelStore & channel performance BIDemand forecasting & replenishment
Data
Search & Merchandising Intelligence

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.

Algolia / Klevu search implementationML query understanding & synonymsVisual merchandising rules engineSearch analytics & A/B testing
Retail Tech Stack

The Modern Retail Technology Stack

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.

Storefront
Customer Experience

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.

Shopify PlusCommercetoolsNext.jsNuxt.jsContentful CMSAlgolia SearchNostoDynamic Yield
OMS
Order Management

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.

Fluent CommerceSalesforce OMSManhattan ActiveBrightpearlCustom OMSExtensiv
PIM
Product Information

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.

AkeneoSalsifyPimcoreContentfulStibo SystemsinRiver
CRM / CDP
Customer Data & Engagement

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.

KlaviyoBrazeSalesforce Marketing CloudSegment CDPBloomreachEmarsys
Analytics
Business Intelligence

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.

SnowflakeBigQuerydbtTableauLookerPower BIGA4Northbeam
Personalisation

How We Build Personalisation That Actually Works

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.

01
Collect & Unify

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.

  • First-party behavioural data collection (GA4, segment)
  • Identity resolution across devices and channels
  • Purchase history and returns data unification
  • Email and SMS engagement signal ingestion
  • In-store transaction and loyalty data merge
  • Real-time profile update on every interaction
02
Model & Segment

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.

  • RFM segmentation and CLV scoring
  • Product affinity and category preference models
  • Churn propensity prediction
  • Next best product and cross-sell models
  • Price sensitivity segmentation
  • Seasonal and browse pattern analysis
03
Activate Across Channels

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.

  • On-site product and content personalisation
  • Personalised email and SMS sequences (Klaviyo, Braze)
  • Dynamic homepage and PLP merchandising
  • Personalised search result ranking (Algolia)
  • Paid media custom audience sync (Meta, Google)
  • In-store and clientelling personalisation
Why Rackwave

Our Client Results vs Retail Industry Benchmarks

The test of retail technology is commercial outcome — not technical implementation. Here is how our clients perform against industry benchmarks after working with us.

Metric
Retail Industry Benchmark
Our Client Average (Post-Engagement)
Ecommerce Conversion Rate
1.8–2.5% (apparel & fashion)
+34% from baseline — average 2.8–3.6% post-optimisation
Average Order Value (AOV)
Baseline varies widely by category
+28% average AOV increase through personalised recommendations and upsell
Cart Abandonment Rate
70–75% of shoppers abandon cart
Reduced to 55–62% through checkout optimisation and abandonment flows
Customer Retention Rate
32% for ecommerce (first-year repeat)
41% average — driven by lifecycle CRM and post-purchase journeys
Site Speed (Core Web Vitals)
LCP 3.5–5s (many retailers)
LCP under 2.5s on all implementations — Good threshold achieved
Email Revenue Attribution
15–20% of total revenue
27–35% average post-Klaviyo/Braze implementation with lifecycle automation
Customer NPS (CX score)
Retail sector avg 32–38 NPS
58–72 NPS range across retail CX implementations
Search Conversion Rate
1.5–2% on-site search CVR
3.8–5.2% after Algolia implementation with personalised ranking

Results vary by retailer, category, and starting baseline. Figures represent averages across Rackwave client engagements 2024–2025.

90+
Retail & Ecommerce Clients
34%
Avg CVR Improvement
28%
Avg AOV Increase
4.9★
Average Client Rating

Ready to Build Retail Technology That Converts?

Book a free consultation. We will audit your current ecommerce and retail technology, benchmark your conversion rate and AOV against sector averages, and identify the highest-impact improvements — before any commercial commitment.

Client Testimonials

What Retail Clients Say

Feedback from Heads of Ecommerce, CMOs, and Digital Directors at fashion, beauty, home, and D2C retail brands.

+38% Conversion Rate
★★★★★

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.

Sophie Chen
Sophie Chen
Head of Ecommerce, Fashion Retailer (£45M GMV)
+31% Average Order Value
★★★★★

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.

Marcus Wright
Marcus Wright
CMO, Home & Living D2C Brand
+26% Repeat Purchase Rate
★★★★★

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.

Priya Kapoor
Priya Kapoor
Digital Director, Beauty & Wellness Brand
star-1
star-2
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“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 & CEO

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FAQ

Frequently Asked Questions

Common questions about retail and ecommerce technology services with Rackwave Technologies.

  • Should we go headless or stay on our current Shopify/Magento setup?

    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.

  • How quickly can you improve our conversion rate?

    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.

  • What is Klaviyo and how should we be using it for retention?

    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.

  • Can you help us build an omnichannel OMS?

    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.

  • How do you approach retail analytics and attribution?

    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.

  • We are launching a new D2C brand — where should we start?

    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.