Every User Arrives With Context.
Your Experience Should Already Know It.
Real-time personalisation is not about knowing your users in general — it is about responding to what each person is doing right now. The page they are on, the action they just took, the segment they belong to, the device they are using. We build event-driven personalisation systems that adapt the experience your users have in the moment they are having it — without page reloads, without delays, and without the engineering overhead of building it from scratch.
"71%" of consumers expect personalised experiences — and "76%" report frustration when brands fail to deliver them. The gap between expectation and execution is where loyalty is lost. (McKinsey)
The Experience You Are Showing Everyone Is Right for Almost No One.
Static experiences treat every visitor identically — the same hero, the same CTA, the same content sequence — regardless of what you know about who they are and what they are trying to do. That uniformity is a choice with a measurable cost.
The same page serves every visitor, regardless of their context
A returning customer who has purchased three times sees the same new-visitor welcome messaging as someone who has never heard of your brand. A user who just abandoned a specific product sees no acknowledgement of that intent when they return. A visitor from a paid campaign sees the same generic homepage as someone who navigated directly. The context is available. The experience does not use it.
Your personalisation runs on the next page load, not the current moment
Batch personalisation — updating a user's experience overnight based on yesterday's behaviour — is already obsolete as a competitive differentiator. The moment of intent is immediate: a user who adds a product to their cart, views a pricing page, reads a specific article, or reaches a scroll depth threshold is signalling something right now. An experience that responds to that signal in the same session is categorically more valuable than one that responds on their next visit.
Your teams cannot ship personalised experiences without developer involvement
A marketing team that needs to personalise a banner for a specific audience segment should not need to file a development ticket to do it. When personalisation logic lives in the application codebase rather than a configurable personalisation layer, every variation requires engineering time — which means most variations never get built, and the personalisation programme stays narrow regardless of the team's ambition.
You are running A/B tests when you should be running experiences
A/B testing picks a winner and ends. Real-time personalisation adapts continuously — serving each user the variation most likely to serve them based on their specific signals, not the version that performed best on average for the population. The difference in outcome between these approaches compounds with every interaction.
Personalisation Infrastructure That Responds to Each User in the Moment They Are Present
We design and build real-time personalisation systems — the event collection layer that captures what users are doing as they do it, the decision engine that determines the right experience for each person in real time, and the delivery infrastructure that adapts the UI without friction. The result is an experience that responds to context, intent, and identity simultaneously — not as a batch process running overnight, but as a live system making decisions in milliseconds. Your marketing and product teams configure the rules. The system executes them at the speed of user behaviour.
Real-Time Personalisation Looks Different in Every Context
The signals that matter for personalising a retail experience in real time are different from those that matter for a SaaS onboarding flow, a financial services product comparison, or a healthcare patient portal. The latency requirements differ. The data available differs. The compliance constraints differ. We bring that contextual understanding to every engagement — so the personalisation system we build is calibrated for the specific signals, decisions, and delivery requirements of your industry.
Retail & E-commerce
Where real-time signals — product views, cart additions, category browsing patterns, exit intent — are the most immediate indicators of purchase readiness and where the window between intent and departure is measured in seconds.
SaaS & Technology
Where in-product behaviour signals — feature usage, activation milestones, idle patterns, plan-limit approaches — determine which message, which prompt, and which upgrade path to surface at the moment each user is most receptive.
Financial Services
Where life-stage signals, product interaction patterns, and session behaviour indicate the specific product conversation most likely to be relevant — with compliance constraints that require personalisation to be precisely governed and auditable.
Media & Publishing
Where scroll depth, article completion, topic affinity, and return visit patterns create the real-time signal set that determines which content, which offer, and which subscription prompt to surface to each reader at each session.
Healthcare & Digital Health
Where patient journey stage, symptom search patterns, appointment status, and care pathway progress create the context for personalised health information and communication that must be delivered with precision and sensitivity.
Travel & Hospitality
Where search intent, destination affinity, booking stage, and loyalty status create a real-time context that determines whether to show availability, offer an upgrade, surface a package, or trigger a time-sensitive incentive.
Education & EdTech
Where learner progress, engagement patterns, time-on-task, and course completion signals determine the right encouragement, the right next module, and the right intervention — in the moment each learner needs it rather than in a weekly digest.
Professional Services
Where content consumption patterns, service page visits, and returning visitor signals indicate the specific expertise area and the specific conversation stage that personalised content and CTAs should reflect.
Deep Technical Expertise
What we build, integrated seamlessly into your existing operations.
Real-Time Event Collection & Processing
Client-side and server-side event instrumentation that captures user behaviour — page views, clicks, scroll depth, form interactions, purchases, API calls — and streams it into the personalisation decision layer in real time, with the latency and reliability that in-session personalisation demands.
Personalisation Decision Engine
The rules engine, model scoring layer, and audience matching logic that evaluates each user's current context against defined personalisation rules and returns the right experience variant in milliseconds — configurable by your team without code deployment.
Dynamic UI Personalisation
Frontend personalisation delivery that swaps content, rearranges components, shows or hides UI elements, and adapts page structure in real time — without full page reloads, without layout shift, and without the flicker that undermines the perception of a personalised experience.
Audience Segmentation Engine
Real-time audience evaluation that assigns users to segments based on their live session behaviour, their historical profile, their source, their device, and any combination of attributes — updated with each event rather than on a nightly batch cycle.
Triggered Messaging & Notifications
Event-triggered in-app messages, banners, modals, tooltips, and push notifications that fire based on specific user actions in the current session — exit intent, idle detection, milestone completion, error encounter — delivered at the moment of maximum relevance.
A/B and Multivariate Testing Infrastructure
Experimentation infrastructure built into the personalisation layer — so every personalisation rule can be tested against a control, results are measured with statistical rigour, and winning variants are promoted without code deployment.
Content Targeting & Slot Management
A content targeting system that defines personalisation slots — the zones of your UI where personalised content can be delivered — and maps audience segments and behavioural triggers to the content variants that should appear in each slot for each user.
Identity Resolution & Profile Stitching
The infrastructure that connects anonymous session behaviour to known user profiles — resolving identities across sessions, devices, and channels so personalisation is consistent from first anonymous visit through to identified customer without gaps at the join.
Journey Orchestration
Multi-step personalisation flows that guide users through defined journeys — onboarding sequences, upgrade paths, re-engagement flows — adapting the next step based on what the user has done in the current and previous sessions.
Personalisation Analytics & Attribution
Reporting that connects personalisation activity to outcomes — conversion uplift by variant, engagement depth by segment, revenue attribution by personalisation rule — with the statistical rigour to distinguish signal from noise.
CDP & Data Platform Integration
Integration with your Customer Data Platform, analytics warehouse, CRM, and marketing automation tools — so the personalisation engine has access to the full historical and real-time profile of each user, not just the data it collects itself.
Personalisation Layer API
A clean API surface through which your applications — web, mobile, email, in-product — can request personalised content, configuration, and decisions for each user context, enabling consistent personalisation across every channel from a single decision layer.
From Identifying the Right Signals to a System That Responds to Them in Real Time
Real-time personalisation systems succeed when they are built on a clear understanding of which signals matter, which decisions they should drive, and how those decisions are delivered without disrupting the experience they are meant to improve. Here is how we develop that understanding and translate it into infrastructure that works.
Identifying the Signals and the Decisions They Should Drive
We begin by mapping the behavioural signals available in your product — the events users generate as they interact — and identifying which signals are the most predictive of intent, preference, and need. For each meaningful signal, we define the personalisation decision it should drive: what content, what variant, what message, what journey step should follow. This signal-to-decision map is the specification the system is built from.
Designing the Event Architecture and Data Layer
We design the event instrumentation — the specific events to capture, the properties to include with each, the client-side and server-side collection strategy, and the real-time streaming infrastructure that delivers events to the decision engine with the latency in-session personalisation requires. The quality of the event layer determines the quality of every personalisation decision made on top of it.
Building the Decision Engine and Audience Architecture
We implement the personalisation decision layer — the rules engine, the audience segments, the content slots, and the variant mapping that translates user context into the specific experience to deliver. We design for configurability: your teams should be able to add segments, modify rules, and launch new personalisation campaigns without code deployment.
Implementing the Delivery Layer Without Disrupting the Experience
We build the frontend personalisation delivery — the component-level dynamic rendering, the flicker prevention strategy, the performance architecture that ensures personalised experiences load as fast as static ones, and the fallback logic that ensures users always see a coherent experience even when the personalisation system is unavailable.
Measuring, Iterating, and Expanding Coverage
After launch, we measure personalisation performance against the outcomes defined before build — conversion uplift, engagement improvement, journey completion rates — and use those signals to refine existing rules and identify the next highest-value personalisation opportunities. The system grows in coverage and precision with every iteration.
Who This Works Best For
Real-time personalisation infrastructure creates the most meaningful value in specific conditions. We would rather help you understand whether the investment is proportionate to your current situation than build a system whose complexity exceeds the signal it is responding to.
Your users generate meaningful behavioural signals in session
Real-time personalisation is powered by what users do as they do it. If your product has multiple distinct interaction types — browsing, searching, viewing, comparing, configuring, purchasing — and those interactions carry different implications for what the user needs next, you have the signal set that real-time personalisation is built to respond to.
The gap between your best and average user experience is knowable and closeable
If you know — or strongly suspect — that different users in different contexts would respond significantly better to different content, different CTAs, or different UI configurations, real-time personalisation is the infrastructure that closes that gap at scale. The more clearly you can define 'better experience for this user in this context,' the more precisely the system can deliver it.
Your team has the content and the operational capacity to run personalisation programmes
A personalisation engine requires content variants to serve. A triggered message system requires messages to send. A journey orchestration layer requires journeys to orchestrate. The infrastructure amplifies what your team creates — it cannot substitute for it. Organisations that benefit most from real-time personalisation are those that have the content capacity to feed it and the operational structure to manage it.
You are at a scale where one-size-fits-all experiences are measurably costing you
The return from real-time personalisation infrastructure scales with the volume of users it serves. At early-stage traffic levels, the effort of configuring and maintaining personalisation rules may not be justified by the number of users it affects. At the scale where the aggregate impact of experience improvements is commercially significant, it becomes one of the highest-return investments available.
And when a simpler starting point would serve you better
If your personalisation ambitions are primarily about email timing, batch segment campaigns, or static landing page variants — these are better served by marketing automation and A/B testing tools than by real-time personalisation infrastructure. If your user base is small enough that the aggregate impact of real-time personalisation would not justify the implementation investment, we will tell you so. And if your primary data challenge is data quality and identity resolution rather than real-time delivery, we will recommend addressing the foundation before building the real-time layer on top of it.
Personalisation Infrastructure Your Teams Can Operate and Your Users Will Feel
Everything we build belongs entirely to you — the event layer, the decision engine configuration, the delivery infrastructure, the analytics, the documentation. Here is what a thoughtfully scoped real-time personalisation engagement delivers.
A production-ready event instrumentation layer
Client-side and server-side event tracking implemented across your product — capturing the behavioural signals your personalisation engine needs with the reliability, latency, and data quality that real-time decision-making demands.
A configured personalisation decision engine
Audience segments, personalisation rules, content slots, and variant mappings configured for your initial use cases — with a management interface your marketing and product teams can use to add, modify, and launch personalisation campaigns without engineering involvement.
Frontend delivery infrastructure with flicker prevention
Dynamic component rendering, personalisation slot implementation, and the performance architecture that ensures personalised experiences load without the visible flash of default content that undermines the perception of seamless personalisation.
Analytics and experimentation reporting
Personalisation performance dashboards that connect each rule and segment to conversion outcomes, engagement metrics, and revenue attribution — with the A/B testing infrastructure that allows every personalisation hypothesis to be validated before it is fully deployed.
Documentation, team training, and an expansion roadmap
Complete documentation of the event schema, the decision engine configuration, and the delivery architecture — alongside training for the teams who will operate and expand the personalisation programme, and a roadmap for the next use cases and channels.
The Kinds of Problems We Are Built For
Every organisation that comes to us arrives with something specific. Here are the situations where real-time personalisation infrastructure has made a genuine, measurable difference to the experience users have and the outcomes that follow.
E-commerce
A fashion retailer was showing the same homepage hero and primary CTA to every visitor — new visitors, returning customers, and high-value loyalty members alike. We implemented a real-time personalisation layer that evaluated each visitor's session context, loyalty status, and browsing history on page load and adapted the hero content, featured products, and primary CTA accordingly. Returning customers saw their most recently viewed category. Loyalty members saw their points balance and a personalised reward. New visitors saw a social-proof-forward acquisition message. Conversion rate on the homepage increased by 34% across all segments within the first eight weeks.
SaaS & Technology
A project management SaaS was experiencing high free-to-paid conversion drop-off during trial — users reaching the end of their trial without having encountered the features most predictive of conversion. We built a real-time in-product personalisation system that tracked feature usage milestones and surfaced contextual prompts at the moments each user was most likely to benefit from specific paid features — triggered by the specific actions that preceded conversion in historical data. Trial conversion rate improved by 28% in the first quarter. The average time-to-conversion shortened by four days.
Media & Publishing
A digital publisher was showing the same subscription prompt to every reader at the same scroll depth — regardless of whether the reader was on their first visit or their fortieth, reading their second article or their twelfth. We implemented a real-time content targeting system that evaluated each reader's engagement history and served subscription prompts calibrated to their stage — soft brand messaging for first-time readers, value-proposition-forward prompts for engaged returning readers, and a time-limited offer for high-frequency readers showing churn signals. Subscription conversion from the prompt increased by 41% while prompt opt-out rates fell.
Financial Services
A fintech company's product comparison pages were static — serving identical content to users whether they had been browsing savings products, investment products, or current accounts. We built a real-time content targeting layer that evaluated each user's browsing session and surfaced the product comparison and contextual education most relevant to the category they were actively exploring. Time on comparison pages increased by 52%. Application starts from comparison pages increased by 29%. The compliance team were involved in the configuration layer design from the outset — every personalisation rule was reviewable and auditable before deployment.
Healthcare
A digital health platform was showing the same onboarding sequence to every new user regardless of their stated health concern, their demographic, or the symptom search that brought them to the platform. We implemented a journey orchestration system that branched the onboarding flow based on the specific health context each user arrived with — serving relevant condition information, appropriate care pathway options, and the specific next steps most likely to lead to a completed health profile. Onboarding completion rate increased from 31% to 67%. Health profiles created in the first session — the primary activation metric — more than doubled.
The Immediate and Lasting Value
Experiences that respond to what users are doing right now
Not what they did last week, not what their segment did on average — what this specific user is doing in this specific session. Real-time personalisation closes the gap between intent signal and experience response from days to milliseconds.
Marketing and product teams that can personalise without engineering
A well-built personalisation layer gives the teams closest to your audience the ability to configure, launch, and modify personalisation rules through a management interface — without filing development tickets, without deployment cycles, and without the latency that kills campaign relevance.
Experimentation that improves the system with every test
Real-time personalisation infrastructure and A/B testing are complementary rather than alternatives. Every personalisation hypothesis is testable, every result feeds back into the decision engine, and every winning variant becomes part of the live system — compounding the return from each experiment.
Consistent personalisation across every channel
A centralised personalisation decision layer serves the same user context to every channel that queries it — web, mobile app, email, in-product, support — so personalisation is coherent across the full customer relationship rather than siloed within each channel's own logic.
Performance that does not sacrifice speed for relevance
Real-time personalisation built correctly is imperceptibly fast — decisions made in under 50 milliseconds, content delivered without layout shift, fallbacks that ensure the experience is always coherent. Personalisation should feel like the experience was made for the user, not like the page is deciding what to show them.
Measurable outcomes from the first campaign
Conversion uplift, engagement depth, session length, journey completion — real-time personalisation produces measurable outcomes from the first campaign that is live and the first segment that is served. We define the measurement framework before build so every outcome is attributable to the decision that produced it.
What Changes When Experiences Respond to Users in the Moment
These are the kinds of outcomes our clients experience — not as projections, but as the natural result of building real-time personalisation infrastructure grounded in genuine signal, precise decision logic, and delivery that respects the speed users expect.
25–40%
Conversion rate improvement when primary CTAs, hero content, and offers are personalised to real-time session context rather than served uniformly
< 50ms
Personalisation decision latency — the time from event receipt to experience variant selection — in well-architected real-time personalisation systems
3–5×
Higher engagement with triggered in-session messages compared to time-based or page-load-based equivalents serving the same content
6–10 weeks
From kickoff to a live real-time personalisation system handling event collection, decision logic, and dynamic UI delivery for initial use cases
Responsive Without Being Intrusive. Relevant Without Being Manipulative.
Real-time personalisation systems that respond to user behaviour in the moment sit at the edge of a meaningful ethical boundary — between making an experience genuinely better for the person having it and using behavioural signals to pressure decisions. We build systems that stay clearly on the right side of that boundary, because the trust that real-time relevance can build is fragile and the damage from crossing it is immediate.
Personalisation should reduce friction, not manufacture urgency
A real-time system that detects exit intent and triggers a countdown timer, manufactures scarcity that doesn't exist, or escalates pressure with every signal is not personalising the experience — it is using real-time capability to exploit behavioural vulnerability. We build personalisation that responds to user context by making the experience more useful, more relevant, and more navigable. Urgency that is real can be communicated. Urgency that is manufactured will not be built.
Users should be able to understand and reset how their experience is shaped
A user who encounters a personalised experience has a reasonable expectation that they can understand it — that a preference centre, a clear data policy, or a visible reset mechanism exists. We design personalisation systems with transparency controls as a standard component — not as a compliance afterthought — because the experience of being understood should never feel the same as the experience of being watched.
Real-time data collection is scoped to what personalisation requires
Event instrumentation that collects every user interaction without a defined purpose for each data point is surveillance, not personalisation. We define the event schema around the decisions the personalisation engine needs to make — and we collect the signals those decisions require, not the maximum technically available. What is collected, what is stored, and how long it is retained are governance decisions we treat as design requirements.
We do not personalise toward decisions that harm the user
Personalisation systems can target vulnerability as precisely as they target intent. A real-time system that identifies financial stress signals and escalates lending offers, or identifies health anxiety and surfaces unvalidated treatments, is using personalisation capability against the interest of the person it is personalising for. We will not build systems designed to exploit the signals that indicate vulnerability — and we are direct about this with every client we work with.
The Values Behind Every Personalisation System We Build
Signal quality before decision complexity
The most sophisticated personalisation decision engine in the world produces poor personalisation on poor event data. We invest in event schema design, instrumentation quality, and data validation before we build the decision layer on top of it — because a system that makes precise decisions on imprecise signals is more confidently wrong than a simpler system that knows the limits of what it can know.
Configurability for the teams who will operate it
A personalisation system that requires engineering involvement to add an audience segment, launch a content variant, or modify a trigger rule has centralised the operational complexity rather than distributed it. We build management interfaces that give your marketing, product, and growth teams genuine autonomy over the personalisation programme — because the velocity of personalisation iteration should be limited by the speed of ideas, not the availability of developers.
Performance is part of the personalisation promise
A personalised experience that loads more slowly than a static one, that flickers as it resolves, or that causes layout shift as content swaps is an experience that undermines its own value proposition. We treat personalisation delivery performance — decision latency, rendering strategy, flicker prevention, fallback behaviour — as first-class engineering requirements, because the feeling of an experience made for you is destroyed the moment you can see it being decided.
We measure what the personalisation changes, not just what it touches
Impressions, click rates on personalised elements, and session-level engagement are activity metrics. Conversion uplift, revenue per user, and long-term retention change are outcome metrics. We design measurement frameworks that connect personalisation activity to the business outcomes that matter — and we distinguish the signal of genuine personalisation impact from the noise of correlation that does not establish causation.
Common Questions
Every Second Your Users Spend Without a Relevant Experience Is a Second You Don't Get Back.
Tell us about the moments in your product where you know a more relevant experience would change what users do next. We will be straightforward about what real-time personalisation can change — and what a sensible first step looks like.
No pitch decks. No obligations. Just an honest conversation about what your users are signalling and what your experience could do with it.