create meaningful interactions

Understand your customers

Logickube has extensive experience in building large scale personalisation engines in the retail and media industries. We can help you build a rich ecosystem of services across personalisation, measurement and media optimisation.

Our personalisation services take inputs from a wide range of customer signals and behaviours (both offline and online) to select the “next best action” to achieve a significant uplift in sales, customer engagement, and brand loyalty.

These are complemented by our attribution capabilities that reliably measure the effectiveness of marketing and media initiatives, by tracking each customer touchpoints over time. Reliable and trusted metrics are the foundations for better strategic decisions and more accurate personalisation models for your business.

next best action

Powerful decision engine to drive customer engagement



Recommend products to make shopping quicker and easier, for both one-off and repeated buys.



Invest efficiently in your customers with one-to-one marketing offers to drive desirable behaviours.



Create a unique browsing experience through content curation in real time.



Helps customers find what they want quickly, by understanding the intents behind their queries.

Understand your customers

To build timely and relevant experiences for your customers, it is important to empathically understand each customer and where they are in their journey.

We will help you to build out a Customer 360 database that stitches together a wide range of customer information - purchase history, demographics, location, past engagement and so on. This "Customer DNA" will be fed into AI models to generate personalised recommendations that drive values and engagement.

state of the art ai

Our team of data scientists and machine learning engineers build powerful AI models to understand the relationships between your customers, products, offers, and digital touchpoints.

Under the hood, neural networks and knowledge graphs - algorithms behind some of the best AI technologies in the world - are built to convert complex relationships into highly relevant recommendations.

Flexible and adaptive

We build personalisation capabilities with business in mind. Models are meant to enhance, rather than replace, your existing decision capabilities in marketing and customer experience. As such, we build models that can be configured to optimise on different business objectives and be deployed in both batch and real time settings.

Personalisation models can be developed on top of our proprietary automated ML framework. This means they are ready to be deployed in weeks rather than months and can be regularly retrained to support changing business needs or customer behaviours.

data driven attribution

A statistically robust method to measure success



Measure the direct effect on sales from an offer or content, compared to what would have happened in absence of it.


Channel & campaign attribution

Model-driven attribution of overall success to each component on a customer’s journey to conversion. Removes double counting.


Paid media measurement

A privacy compliant measurement tool that combines 1st and 3rd party aggregated data for omnichannel measurement.


Self-serve dashboard

Empower decision makers with self-serve analytics to drive fast actionable insights for marketing and media spending.

Removes double counting

Customers can be exposed to multiple marketing touchpoints across different channels in their journeys to conversions. Often their effects are measured in isolation and thus double counted.

Our measurement methodology addresses this by applying attribution modelling holistically across the full customer journey to give you clean performance metrics of each touch point.

actionable insights

Having a single source of truth and self-serve interactivity of performance metrics will empower your business to quickly and easily generate actionable insights to improve marketing and media spending.

Our team of experienced Business Intelligence developers, combining powerful BI solutions such as Looker, Tableau and PowerBI, can design, build and deploy self-serve analytics dashboards suitable for all technical levels to drive fast time to value.

Privacy compliant approach

Data protection and online privacy initiatives have seen significant progress in recent years. With the phasing out of third-party cookies by the end of 2023, it is now more important than ever to overhaul traditional attribution practices.

Logickube can help your business transition to privacy compliant measurement methodologies that focus on zero and first party data, which are much more reliable and allow for more accurate reporting even in a post-cookie future.

targeted marketing with logickube

Audience selection & value measurement

With our targeted marketing quick start, we can demonstrate the value of AI-driven marketing for an upcoming campaign in your business - by building a simple audience selection model in 6 weeks* and measuring its benefits post campaign execution.

During this time, we design and build the appropriate model structure that will produce incremental improvement for a business objective of your choice, then design the appropriate experimentation to enable value measurement post campaign.

Benefits to your business:

  • Understand how AI can be used to select the right audience for a marketing campaign
  • See the model in action in a real world campaign
  • Understand the importance of data collection and experiment design
  • Understand the incremental values AI can generate for your marketing
Get started today

step #1


We run an introductory workshop to understand the business objective of your marketing campaigns and demonstrate how AI can be used in targeted marketing to select the right audience and content. At the end, we will select one campaign for the Proof-Of-Concept work.

step #2

Model build

We build a simple audience selection model for the chosen campaign that will produce improvement on a given business objective. On completion, we use the model to select the audience for execution and design appropriate experimental groups.

step #3

Value measurement

After the campaign is finished and with the corresponding feedback data collected, we will measure the incremental value the model has generated.