The tech behind the personal touch: How to build an efficient personalisation stack 

Customers today expect brands to understand them and serve products and messaging that reflect their tastes. 

Many marketers are eager to meet these expectations with personalised content. But few know where to start.
Without solid foundations – proper planning and the right tech stack – personalisation becomes time-consuming and a whole lot of guesswork. Not exactly what today’s savvy consumers are after.

The good news? With the right tools and structure, you can automate smarter, more efficient personalisation.

Let us explain.
 

_{New to personalisation? Or want a refresher on why it matters? Check out our introduction to the topic: How personalisation can transform your customers’ experience.}

Stacking the odds in your favour

Today’s customer journeys span multiple channels and touchpoints, from email and SMS to apps, websites and social platforms. To deliver cohesive, timely personalisation across this ecosystem, you need a suite of connected tools that work seamlessly together. 

That’s where your personalisation tech stack comes in: the collection of marketing and customer experience (CX) technologies you use to deliver personalised experiences.

Without the right tech stack in place, personalisation efforts can become fragmented, manual and inefficient, meaning missed opportunities, inconsistent customer experiences and poor ROI. 

With a robust, well-integrated stack, you can deliver timely, relevant experiences every time – and scale them as your customer base grows. 

What’s in a personalisation tech stack?

So, what exactly goes into an effective personalisation stack? Below are some of the core components many brands use today.

1.    Customer Data Platform (CDP)

A CDP acts as the central nervous system of your stack, pulling together customer data from multiple sources and creating a unified view of each individual. This enables more intelligent, targeted personalisation across channels.

Key functions include:

• Unifying customer data from multiple sources

• Creating a single customer view

• Enabling real-time segmentation and decision-making

Examples of widely used CDPs include Salesforce Data Cloud, Twilio Segment, Tealium AudienceStream and Adobe Real-Time CDP.

2.    Customer Relationship Management (CRM) system

While a CDP focuses on data unification, your CRM manages the details of your customer relationships – helping you track interactions and deliver personalised communications that nurture loyalty over time.

Key functions include:

• Managing customer interactions and relationships

• Powering personalised communications and offers

• Integrating with marketing automation tools

Examples of widely used CRMs include Salesforce, HubSpot, Microsoft Dynamics 365 and Zoho CRM.

3.    Content Management System (CMS) with personalisation capabilities

Your CMS controls the content customers see on your website and apps. With personalisation capabilities built in, it can dynamically serve up content tailored to each user’s behaviour and preferences.

Key functions include:

• Powering dynamic website and app content

• Supporting real-time personalisation based on behaviour and preferences

Examples of CMSs with built-in or extendable personalisation features include Adobe Experience Manager, Sitecore, Kentico Xperience and Optimizely.

4.    Personalisation and journey orchestration tools 

These tools make it easy to personalise experiences across channels. They guide each customer along their journey – from the first interaction to conversion and beyond. Best of all, you don’t need to trigger each message manually. The system does it for you.

Key functions include:

• Automating personalised experiences across channels (email, SMS, web, in-app)

• Supporting next-best-action recommendations and behavioural triggers

Examples of personalisation and journey orchestration tools include Salesforce Marketing Cloud, Adobe Journey Optimizer, Braze and Dotdigital.

5.    AI and machine learning (ML) tools

AI and ML take personalisation to the next level, enabling more predictive and adaptive experiences. These tools can anticipate customer needs, personalise content on the fly and optimise campaigns based on real-time insights.

Key functions include:

• Driving predictive personalisation

• Enabling dynamic content creation and optimisation

Examples of widely used AI/ML tools for personalisation include Salesforce Einstein, Adobe Sensei, Dynamic Yield and Bloomreach.

6.    Analytics and measurement tools

Robust analytics tools allow you to track the impact of your personalisation efforts, helping you understand what’s working and what’s not. These insights enable you to continually refine your strategy for better results.

Key functions include:

• Tracking the impact of personalisation efforts

• Helping to improve strategies over time

Examples of popular analytics and measurement tools include Google Analytics, Adobe Analytics, Salesforce Marketing Cloud Intelligence and Mixpanel.

Building your stack the smart way

Of course, having the right tools is only part of the equation. To get the most from your stack, you also need to manage it strategically, with efficiency in mind.

Below are a few things to consider. 

1.    Start with your data

Clean, unified customer data is the foundation of any personalisation strategy. Even if you don’t have a CDP, you need a data strategy that defines:

• What customer data you’re collecting

• How it’s stored and accessed

• How it supports personalisation and CX goals

2.    Avoid tool sprawl

Many marketing teams accumulate too many disconnected tools, which results in inefficiencies and fragmented customer experiences.

When deciding which tools to use, prioritise those that connect easily and work well together. To keep your stack streamlined and avoid unnecessary complexity, make sure you:  

• Choose tools that integrate seamlessly

• Audit your stack regularly to identify overlaps or gaps

• Involve your IT or data teams early to ensure alignment

3.    Automate what matters

You don’t need to personalise everything. Focus on high-value moments that drive impact, such as:

• Cart abandonment follow-ups

• Onboarding journeys

• Loyalty program engagement

• Re-engagement campaigns

By focusing automation where it matters most, you’ll maximise ROI – and avoid wasting resources on low-impact personalisation.

4.    Layer automation gradually

Don’t try to do everything at once. Build automation capabilities in stages:

• Start simple: triggered emails, product recommendations and dynamic website content

• Expand: cross-channel orchestration, next-best-action recommendations

• Advance: AI-driven personalisation, predictive modelling

Layering gradually helps ensure your team can manage and optimise effectively.

5.    Keep testing and optimising

The most efficient personalisation strategies are continually refined. Don’t just set and forget! Make sure you:

• Use analytics to measure what’s working

• Test different personalisation tactics and journeys

• Create feedback loops so data from customer interactions can help your stack get smarter over time

The more you test and learn, the more effective and efficient your personalisation efforts will become.

A stack that delivers

Efficient personalisation is about more than buying the latest tools. It’s about building an integrated, purposeful stack that serves both your business and your customers.

By starting with the right foundations, layering automation strategically and continuously optimising, you can give your customers the tailored interactions they expect – and deserve.

Keen to master the art of automation-powered personalisation? ADMA’s Unlocking Personalisation and Automation course is the perfect place to start.