Retail

Machine learning is increasingly shaping the buying and selling experience for both consumers and retailers, adding both intelligence and personalisation to the way we purchase and trade goods and services. Leverage voluminous and unstructured data to deliver unparalleled, hyper-personalised customer experiences whilst maximising profitability.

Acquisition Marketing

Leverage voluminous structured and unstructured data to develop highly accurate customer segmentation that augments your CRM and automates campaign personalisation.
AI-driven promotions outperform any others. Predict customer lifetime value and save on digital advertising spend with hyper-targeted promotions and coupons.

Customer Retention

Keep customers for longer with AI-powered churn prediction. Real time prediction models help you take action to make your customers stay, before it’s too late.
Proactively address issues with anticipatory customer service. Analyse customer sentiment, predict what customers want, then respond and resolve faster.

Hyper-Personalisation

Use real-time behavioural and unstructured data from multiple sources to make hyper-relevant product recommendations based on a “customer segment of one”.
Recommender engines are one of the most widely used applications of machine learning within retail & ecommerce. BasisAI can help you build engines with 1000 queries a second and real time serving of recommendation at <50ms latency to keep the user experience snappy.
Enhance click-through rates to purchase, promote complementary products (cross-sell) or encourage existing customers to upgrade (upsell), powered by machine learning based on data already available to you.

Retail Operations

Optimise product availability, inventory and spoilage with inventory forecasting. Gain better insight into sales patterns to avoid stock outs.
AI-powered demand forecasting enables enterprises to incorporate many data streams to generate highly accurate daily forecasts plus ability to delineate between trends and seasonality. Machine learning predicts sales and drives enhanced forecasts based on real-time data using internal and external influencers from a number of dimensions.

Dynamic Pricing

Adopt greater intelligence in order to dynamically adjust prices in response to market conditions and maximise revenue. Dynamic pricing engines can leverage machine learning to propose price structures which can be adjusted on a dynamic basis. Move away from static, rules-based revenue management which relies heavily on human intervention and intuition.

Interested in exploring alternative AI use cases?

Speak to one of our team today.

From concept to execution

Get to live applications within months, a pathway to sustained ROI from AI over years.

1

Strategise, to Roadmap

40-60 days

Co-founding team work with your executives to identify a company wide roadmap and high impact opportunities for AI in weeks.

2

Prototype, to Validation

8 weeks

Our data scientists will work on your data, explore the possibilities and build prototype models. Technical and business metrics can be defined, impact estimated.

3

Deploy, to Engine

3 months

Leveraging our proprietary Bedrock platform, we deploy a production-grade, high throughput, real-time AI engine that can be easily integrated to power your systems with AI.

4

Sustain, and Learn

Over years

BasisAI will continue to manage and ensure the reliability and performance of the AI engine. Ensuring that the AI engines continue to learn to realise the true potential of AI.