Audience clustering and personalization: Understanding the true value of your consumer data

Audience clustering and personalization: Understanding the true value of your consumer data


The importance of personalization

In today’s world of self-directed consumers, the ability to fully understand your customers’ digital journey is more important than ever, with 86% of consumers saying that personalization plays a role in their purchasing decisions. Differentiated customer experiences allow new and existing customers to feel like the brands they interact with recognize them as individuals, increasing engagement. Forrester’s 2018 Tech Tide report found that 95% of marketers said personalized content was key to success, and our recent case study with Contentive, showed that personalized messaging improved click-through rates by 300% over a 90-day period.

Personalization also helps to grow brand loyalty, improve return on investment (ROI), and increase revenue – 79% of marketers who exceeded revenue goals in 2017 had a documented personalization strategy. However, effective personalization doesn’t just mean suggesting similar products or content based on consumers’ interests. Instead, customers are seeking entirely individual experiences that engage them on a personal level, whilst saving time by only showing them the most relevant information.

Clustering can help you to understand your consumers’ digital journey, from conception to conversion, anticipating their problems and providing them with a seamless and individual customer experience.


How clustering can help achieve personalization

Mass marketing has an important role in digital marketing, however, it has its drawbacks. The same can be said of traditional market segmentation which isn’t perfect either. Indeed, grouping consumers according to age or location assumes similarities that simply don’t exist. This is where our Audience Clustering tool can provide more advanced, and more accurate insights into key consumer groups – classifying and grouping data on a scale that isn’t possible manually.

We then build a unified consumer data platform, powered by AIDA (Fospha’s data-science platform) to consolidate this fragmented data, using machine learning to identify clusters of customers with similar attributes and behavior. Cross referencing this broad variety of data not only allows a more in-depth view of consumer interests, but also helps to present customers’ digital journeys in a way that’s easy to understand. This allows marketers to see where spend is really working, and to tailor existing campaigns to focus on more profitable groups of consumers. Allowing powerful analytical algorithms to decide which consumer groups are most valuable, removes an element of human error and allows more in-depth personalization, by defining key similarities of these clusters across a wide range of metrics, ranging from purchase country, to local weather, or payment method.

This variety of detailed insights allows you to understand and anticipate your customers’ entire digital journey, from what problems they have, to what kinds of promotions, and content they might be interested in. For example, the clustering algorithm might group a selection of travel consumers based on recent European travel, making them likely customer prospects for future European travel deals.


How to implement important insights

Greater visibility is only one of the hurdles to automating personalization. To create personal customer experiences, you need to be able to fully integrate your customer and marketing data platforms, deepening your understanding of key consumer groups by testing, measuring and refining your activities in real-time.

Compatible with existing customer data platforms (CDPs) and traditional email automation providers (such as Marketo, Adestra, or Mailchimp), our Audience Clustering tool replaces more simplistic methods of customer segmentation, allowing marketers to ensure that email content is relevant to all clusters, based on both shared interests and behavior.

These clusters can also be used to create ‘lookalike’ audiences on Facebook, targeting users, who share the same interests as existing profitable groups, with the same personalized ads.

Going one step further, our Audience Clustering tool doesn’t just share interest level data to help tailor messages, content, and offers, but also makes specific suggestions as to personalization for each consumer group, helping to develop effective targeted email campaigns aimed at the most valuable clusters. Effective implementation of advanced clustering algorithms can give you the power to personalize customer experience across your entire business, improving marketing effectiveness, building brand loyalty, and increasing revenue. Creating a more engaging and positive brand experience for customers.


At Fospha, we’re passionate about converting, serving and retaining buyers on a personalized basis, at scale. No longer satisfied with segmenting customers according to their gender or age, our advanced clustering algorithms deliver consumer insights on a more granular level – drilling down to the details that will increase engagement and brand experience. So if you want to get smarter in the way you cluster customers, and get real insights into the customers at the heart of your business, contact us on: or visit our website

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