Customer Experience Platforms: optimising the customer experience using data

Customer experience is at the heart of companies' strategies to stand out from the crowd and build lasting loyalty. A study by Forrester shows that companies that focus on customer experience outperform their competitors in terms of growth. 

A Customer Experience Platform (CXP) helps to improve customer satisfaction. It centralises interactions to deliver personalised experiences across all channels.

CXPs help to better understand the preferences and behaviour of each customer. They promote engagement through personalised communication and tailored commercial offers. 

The accuracy and effectiveness of these tools has been enhanced with the integration of AI.

🔎 Discover the key features and benefits of CXP. Find practical advice on how to integrate them effectively. 👌

The CXP uses customer data from multiple sources: CRM, website, social networks and in-store transactions. By integrating this information, companies can tailor every interaction to the specific needs and expectations of their customers.

It complements CDPs (Customer Data Platforms), which organise and activate data around a unified customer view. The CXP acts as an additional layer, to deliver an optimised omnichannel experience.

Machine learning enhances the ability of CXPs to deliver a personalised customer experience across all touchpoints.

Customer Experience Platforms are changing the way companies interact with their customers, building trust and loyalty.

CXPs analyse data from multiple sources. These may be internal sources (website, applications, CRM) or external (social networks, partners, etc.). This analysis helps companies to understand customer behaviour:

Let's take the example of a ready-to-wear brand that studies in-store and online purchases. 

A customer regularly buys shirts in shop but consults trousers on the application without making a final purchase. The CXP can then offer a personalised promotion on the trousers, valid in shop and online.

Thanks to a unified view of exchanges with customers, CXPs enable personalised communication. They strengthen engagement by offering experiences tailored to each individual's expectations.

For example, a mobile phone operator can identify a recurring problem reported by a customer to the technical department. The sales department can then offer the customer a new subscription or tailored options.

Les CXPs améliorent le retour sur investissement (ROI) en automatisant les processus. Elles augmentent aussi les conversions grâce à une communication omnicanale plus efficace.

According to a McKinsey study, 78% of consumers are more likely to buy from brands that offer them tailored content.

CXPs don't just manage interactions: they create opportunities for long-term loyalty and increased profitability.

Machine learning is revolutionising CXPs by making customer interactions simpler and more personalised. With predictive AI, these platforms anticipate customer needs based on past behaviour.

Le machine learning révolutionne les CXPs en rendant les interactions clients plus simples et personnalisées. Avec l’IA prédictive, ces plateformes anticipent les besoins des clients en s’appuyant sur leurs comportements passés.

Here are a few concrete examples:

CXPs rely on reliable, up-to-date data collected and organised by Customer Data Platforms (CDPs).

Some Martech solutions offer a monolithic approach, combining CXP and CDP in a single system. Although interesting, they often require duplication of data and are more complex to deploy.

Another trend is the emergence of xCDPs, designed to meet the challenge of large-scale personalisation in real time.

DinMo's composable CDP offers greater flexibility. It adapts to the data stack and marketing tools already in place within the company. Its AI-powered predictive attributes and no-code interface make it easy to learn. 

It guarantees a 360° view of the customer, for successful omnichannel campaigns.

A CXP uses data from a variety of sources, such as digital channels, in-store purchases or interactions with technical support. 

Thanks to a complete view of each customer's profile and predictive analysis, it customises the experience according to each person's unique preferences and needs. 

This makes it possible to offer tailored recommendations, offers and communications.

A CXP examines data at every point of contact with the customer. It maps the customer journey to identify repetitive actions or obstacles.

By pinpointing these friction points, the company can make targeted improvements to offer a smoother experience.

If your business interacts with customers across multiple channels (website, shop, mobile app, social networks) and you want to offer a more consistent and personalised experience, a CXP could be beneficial. 

If you want to harness the power of your data to personalise your communications, please contact us.