Personalisation, conversion, and lifetime value at e-commerce scale
Lognatech helps retailers, marketplaces, D2C brands, and subscription businesses turn customer behaviour into revenue. We build the streaming pipelines, recommendation engines, and analytics platforms that improve conversion, increase basket size, reduce churn, and make every customer interaction more relevant.
What we deliver for e-commerce teams
Four core capabilities, each designed around the realities of high-volume online retail. Every solution is built to integrate with your storefront, CRM, ad platforms, and warehouse systems without disrupting live traffic.
Personalisation engines
Real-time recommendations, dynamic pricing, and personalised journeys that lift conversion and average order value across every channel.
Customer analytics
Segmentation, cohort analysis, LTV modelling, and churn prediction that show you exactly which customers matter and why.
Inventory and demand
SKU-level forecasting, stockout prevention, and dynamic allocation that keep fast-movers in stock without tying up capital in slow-movers.
Marketing and attribution
Multi-touch attribution, campaign optimisation, and paid media efficiency models that show where every dollar actually earns its return.
Where we make the biggest difference
These are the highest-value use cases our e-commerce clients ask us to solve first. Each one is measured against a clear business case: conversion rate, AOV, LTV, CAC, or gross margin.
Real-time personalisation and recommendations
We ingest every click, view, cart add, and purchase event through a streaming pipeline and score it in real time. The recommendation engine updates as the customer browses, so the right product, price, and message appear at the right moment.
Homepages, category pages, search results, emails, and push notifications all draw from the same personalised model. Conversion improves, average order value rises, and customers see a store that understands them instead of one that treats everyone the same.
Discuss personalisationCustomer analytics, LTV, and churn prediction
We unify purchase history, browsing behaviour, support interactions, and marketing engagement into a single customer view. From there, we build segmentation, cohort, and LTV models that show exactly which customers are worth acquiring and which are at risk of leaving.
Churn models trigger retention campaigns before customers go quiet. High-value segments receive VIP treatment. Acquisition spend is reallocated away from low-LTV audiences. The result is a customer base that is more profitable and more loyal over time.
Discuss customer analyticsInventory, demand, and fulfilment optimisation
We forecast demand at the SKU, region, and channel level using your sales history, seasonality, promotions, and market signals. The forecasts feed directly into buying, allocation, and warehouse capacity decisions.
Stockouts on best-sellers drop. Excess inventory on slow-movers shrinks. Warehouse labour is scheduled against real demand. Working capital is freed up and customers find the products they came for, which is the single biggest driver of repeat purchase.
Discuss inventory analyticsMarketing attribution and media efficiency
We build multi-touch attribution models that show which channels, campaigns, and creatives actually drive revenue, not just clicks. Paid search, social, email, affiliates, and organic are all measured on the same consistent basis.
Budgets are reallocated to the channels that earn their return. Customer acquisition cost falls. Return on ad spend improves measurably. Marketing stops guessing and starts making decisions grounded in data.
Discuss marketing analyticsBuilt for volume, speed, and real-time behaviour
E-commerce analytics is not a generic data science problem. It involves millions of events per hour, dozens of systems, constant experimentation, and customers who expect relevance in milliseconds. We design for all of that from day one.
We integrate with your stack
Shopify, Magento, Salesforce Commerce, BigCommerce, custom storefronts, CRM, ERP, ad platforms, and warehouse systems. We connect them all without disrupting live traffic.
We build for real time, not yesterday
Streaming pipelines on Kafka, Spark, and cloud event services so personalisation and pricing decisions happen while the customer is still on the page.
We respect privacy and compliance
GDPR, CCPA, POPIA, and consent management are built into every pipeline. Customer data is governed, auditable, and used only where consent allows.
Talk to our e-commerce team27%
lift in conversion within the first quarter
18%
increase in average order value
93%
predictive accuracy on production models
24/7
real-time monitoring of your storefront
How we engage with e-commerce teams
We work in short, focused phases so you see value quickly and can scale investment based on proven results, not promises. Every phase ships working software to production.
1. Discovery
Two to four weeks to map your funnel, systems, and priority use cases, and to agree the business case with clear success metrics.
2. Prototype
Four to six weeks to build a working model or pipeline on your live data so you can see the outcome and validate the economics.
3. Production
One quarter to take the prototype into production, integrated with your storefront and marketing stack, with monitoring in place.
4. Scale
Ongoing optimisation and expansion into adjacent use cases, with a dedicated team that knows your catalogue and your customers.