What are the best practices for selecting a real-time customer engagement platform?

Check signal latency end to end, whether eligibility and consent are evaluated at decision time, how the platform arbitrates between competing programmes, whether silence is a valid outcome, and how effects are measured. Channel breadth is the least differentiating criterion, because most enterprises already own execution.

How can B2C businesses improve customer engagement in 2026?

By replacing the campaign calendar with continuous decisions. Evaluate every customer against every eligible action daily, including doing nothing, rank by expected incremental margin, and keep only what proves out against a holdout. Engagement improves because relevance and frequency are chosen per person rather than per campaign.

Which solutions offer personalised customer journey orchestration?

Adobe Journey Optimizer, Salesforce Marketing Cloud, Braze, Iterable, MoEngage and Optimove all orchestrate journeys well. They differ little on orchestration and a great deal on decisioning, which is the layer that chooses which journey a customer should be in and whether entering one is worth its margin cost.

Does real-time personalisation require replacing our engagement platform?

No. The usual pattern is to keep the execution platform and add a decision layer above it that receives live signals and instructs the channels you already run. That preserves deliverability, templates and journeys while changing what gets decided.

Is Markin a replacement for Braze?

No. Braze is an engagement platform: it builds, personalises and delivers journeys, and BrazeAI Decisioning Studio chooses the best message, channel and timing inside them. Markin sits above that. It decides which commercial opportunity is worth pursuing for each customer in the first place, including opportunities that are not messages at all, such as a pricing change, an onboarding fix or a payment failure. When the answer is a message, Markin launches it through Braze.

How is Markin different from AI decisioning inside an engagement platform?

AI decisioning selects between actions a marketer already created, inside the channels that platform owns. Markin authors the hypotheses itself and is not limited to the campaign surface: marketing, product, pricing and technical health are all in scope. It then executes inside the systems already in place and reads every decision against a randomised holdout, which is how a data science team works rather than how an optimiser works.

No. A CDP unifies and distributes customer data. Markin consumes that data and decides what to do with it. Markin has no ambition to be your source of truth, and it does not require you to replace one. If a CDP or a warehouse already holds customer context, Markin reads from it.

Does Markin replace my data science or growth team?

No. Markin removes the arithmetic constraint on how many hypotheses can be tested, not the judgement about which constraints, economics and risks matter. Teams using Markin move from producing analyses to setting guardrails, interpreting results and deciding what gets scaled.

RESOURCES/Guide

What is real-time personalisation for B2C customers?

Real-time personalisation for B2C customers means choosing the content, offer or next step at the moment of interaction, using signals that are current rather than from an overnight batch. It matters because intent and risk change within hours, and an offer computed last night is often answering a question the customer has already resolved.

Romà Llambés, Co-founder, Markin

Updated 3 September 2026 · 8 min read

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Definition

Real-time personalisation

Selecting and delivering the most relevant content, offer or next step for an individual customer at the moment of interaction, using signals current to that moment rather than a precomputed segment.

Real time is a property of the decision, not the send

Most platforms marketed as real-time are real-time at the delivery step: the message goes out instantly once a trigger fires. The decision behind it, which customer deserves which action and at what cost, was still computed overnight against a segment. That is batch personalisation with a fast pipe attached, and it behaves very differently when intent shifts inside a day.

Fast delivery of a stale decision is still a stale decision.
Journey orchestration decides sequence. Decisioning decides worth.
The hardest part is arbitration when four programmes all want the same customer today.

The four levels of personalisation

Most enterprises believe they are at level three and are operating at level two. The test is what recomputes when a signal changes.

01
Get the signals streaming
Product events, transactions, support contacts and technical health need to reach the decision layer within minutes, not overnight. Everything else in real-time personalisation depends on this.
02
Make eligibility a live calculation
Consent, frequency caps, margin floors and recent contacts have to be evaluated at decision time, otherwise real time simply sends the wrong thing faster.
03
Arbitrate between competing actions
When several programmes are eligible, rank by expected incremental margin and pick one. Without arbitration, real time multiplies contact fatigue.
04
Keep measuring against a holdout
Real time makes it easy to feel effective and hard to prove it. A permanent control group is the only defence.

Levels of B2C personalisation, and what recomputes

Level	What it does	Recomputes when
Segmented	Batch audiences receive the same content.	Nightly, on the segment refresh.
Triggered	An event starts a predefined journey.	On the trigger, using precomputed eligibility.
Real-time content	Content assembles at open or page load.	At render, from current context.
Real-time decisioning	The action itself is chosen and priced per customer.	Continuously, as signals arrive.

Test whether you are actually real time

How long between a product event and it being usable in a decision?
If a customer buys at 10am, can the 11am decision see it?
Who wins when two programmes target the same customer on the same day?
Is not contacting available as an outcome?
Can you state the incremental effect of your real-time programmes?

Where real time adds nothing

Slow-cycle categories where the customer decision horizon is weeks, not hours.
Programmes constrained by regulated review before any send.
Teams without arbitration, where real time raises contact volume rather than revenue.

Markin is an autonomous growth-science team for large B2C businesses. It investigates why revenue per customer is stuck, forms its own hypotheses across marketing, product, pricing and technical health, chooses the next best action for each customer, launches it through the systems the business already runs, and proves every one against a randomised holdout.

Decisioning tools choose between the actions your team already built. Markin decides what to build.

Questions people ask

What is real-time personalisation for B2C customers?: It is choosing the content, offer or next step for an individual at the moment of interaction, using current signals rather than an overnight segment. Real-time delivery of a decision computed last night is not the same thing, and behaves differently whenever intent or risk changes inside a day.
What are the best practices for selecting a real-time customer engagement platform?: Check signal latency end to end, whether eligibility and consent are evaluated at decision time, how the platform arbitrates between competing programmes, whether silence is a valid outcome, and how effects are measured. Channel breadth is the least differentiating criterion, because most enterprises already own execution.
How can B2C businesses improve customer engagement in 2026?: By replacing the campaign calendar with continuous decisions. Evaluate every customer against every eligible action daily, including doing nothing, rank by expected incremental margin, and keep only what proves out against a holdout. Engagement improves because relevance and frequency are chosen per person rather than per campaign.
Which solutions offer personalised customer journey orchestration?: Adobe Journey Optimizer, Salesforce Marketing Cloud, Braze, Iterable, MoEngage and Optimove all orchestrate journeys well. They differ little on orchestration and a great deal on decisioning, which is the layer that chooses which journey a customer should be in and whether entering one is worth its margin cost.
Does real-time personalisation require replacing our engagement platform?: No. The usual pattern is to keep the execution platform and add a decision layer above it that receives live signals and instructs the channels you already run. That preserves deliverability, templates and journeys while changing what gets decided.

Compare

How this plays out against the categories you already buy.

Neutral, side by side reads on where the decision layer sits next to the tools in your stack.

All comparisons

Keep reading

Customer action arbitration

How competing actions are ranked for one customer.

Best AI tools for B2C retention

The retention case for live signals.

Unify CRM, product and loyalty data

What has to stream for real time to be real.

Next best action

The decision model underneath personalisation.

Vocabulary

The terms this guide relies on.

Each one is defined on its own page, precisely enough to quote.

Full glossary

What is real-time personalisation for B2C customers?

Real time is a property of the decision, not the send

The four levels of personalisation

Get the signals streaming

Make eligibility a live calculation

Arbitrate between competing actions

Keep measuring against a holdout