Hyperpersonalization: promise, reality and activation of customer data

The starting point is therefore a solid data platform: all customer data - from purchases and website behavior to CRM and support data - are brought together centrally. This prevents data silos and provides a uniform customer view, also known as a Golden Customer Record. The perfect basis for deploying smart models and technologies for personalized interactions.

What is hyperpersonalization?
Hyperpersonalization goes beyond simply inserting a customer's first name or creating some customer groups. It's about combining all available data and deploying insights in real time for the most relevant message across all channels. The approach consists of three layers:

1. Integrated data foundation - All customer data from different systems is streamlined into a single platform or data warehouse. This creates a reliable, up-to-date customer profile. Master Data Management (MDM) or Customer Data Platforms (CDP) play an important role here.
2. Smart analytics - Predictive models and machine learning determine which offer or content per customer has the greatest chance of success. For example, you can predict who will respond to a product first or which customer is likely to drop out.
3. Cross-channel activation - The insights are applied real-time across all customer channels: email, app, website, social media and customer portals. Thus, data is converted from storage to dialogue and the customer experiences a consistent approach everywhere.

This combination allows an organization to deliver the most impactful message at the right time through the right channel, transforming the data warehouse into a true growth engine.

From segmentation to 1-to-1 interactions
Hyperpersonalization is usually an end goal, not a starting point. Organizations often start with segmentation and quick wins: a small group of loyal customers often generates most of the revenue (80/20 rule). Target this audience first with targeted, semi-personalized offers.

Then personalization can incrementally scale up to 1-to-1 interactions. Many companies use maturity models to determine the right sequence of actions. For example, telecom company Odido developed Maestro, a platform that predicts what the Next Best Action is for each customer. As more data becomes available, the approach shifts to more complex models and real-time decisions, with AI playing a larger role.

Important: hyperpersonalization does not have to be present in every expression. Sometimes smart segmentation and timing is enough to make an impact.

Data technology as a growth engine
Modern cloud platforms offer scalable storage and analytics, but marketing teams do not always leverage this data to its full potential. The missing link is data activation: making data from the warehouse readily available to marketing, sales and service. This allows real-time segmentation and campaign creation, while data engineers focus on data quality and integration.

Composable CDPs and data activation platforms turn the warehouse into a "marketing powerhouse." Segmentations and forecasting models run directly on the data, with automatic syncing to email systems, advertising platforms and websites. Thus, data silos between Analytics and Marketing disappear and customer data becomes actionable in every customer contact moment.

Loyalty through relevance
The goal of hyperpersonalization is not a short-term KPI, but customer loyalty and higher Customer Lifetime Value. Personalized interactions make customers feel seen. Research shows that personalized messages significantly increase brand preference and repeat purchases. It's not about sending as many messages as possible, but about delivering the right value at crucial moments.

Practical steps and focal points

1. Clear definition and scope - Define internally what hyperpersonalization means and where it will be applied.
2. Data foundation in place - Invest in data quality, integration and a single customer view with Golden Records.
3. Data activation - Ensure marketing teams can execute real-time segments and actions without IT intervention.
4. Organization-wide support - Involve teams of data engineers, IT, marketing and customer service and align short-term campaigns with the long-term vision.
5. Work Iteratively - Start small, measure results such as retention and Customer Lifetime Value, and expand step by step.

Make personalization measurable
So hyperpersonalization is not a trend, but a strategic shift: from static campaigns to true one-to-one interactions. The promise is great - from direct sales growth to stronger loyalty - but the road to it requires patience, good data engineering and collaboration. Start at the basics, activate customer data across all channels and support this with smart models.

Organizations climbing this maturity ladder will see data, technology and human insight come together. By making customer data truly driving results, you transform marketing and service. Hyperpersonalization is about impact, not perfection. With the right foundation and mindset, data can be transformed into lasting customer value.

Personalization is no longer a nice-to-have, it's a must. Our speakers Jeffrey Ploeg of Odido Netherlands (Data & AI Product Manager) and Guus Rutten of GX (Strategy & Innovation Manager) show how Odido made the step from "one to all" to "one to one" with a powerful personalization model. Practical, concrete and directly applicable in any sector.

Hyperpersonalization in action: how Odido makes customer interactions truly relevant
Thursday 11 September | 13:30 - 14:00 | Lecture Hall 6