With Epoq, you can already create personalized shopping experiences that delight customers—based on their actual behavior in the store. Clicks and purchases—such as search behavior and responses to recommendations—generate valuable personalization insights: They show which products are bought together, which recommendations work, which content supports purchasing decisions, and where customers might abandon their carts.
Censhare offers a PIM system (short for Product Information Management System)—that is, software that centrally manages product information such as descriptions, images, variants, and technical specifications, and makes it available for various channels.
Selected insights from Epoq Personalization can thus be incorporated as product logic in Censhare PIM for use across additional channels, enabling successful store models to drive omnichannel growth.
Behind this is Entirely, the open MarTech ecosystem to which both companies belong.
When a bundle performs particularly well in the store, it’s not just a signal for the next product recommendation. It can also be a relevant indicator for Google Shopping, Amazon, marketplaces, newsletters, or campaigns. This is exactly where the Combined Solution from Epoq and Censhare comes in: Insights from personalization are not only analyzed but also translated into structured product data, product relationships, and bundle logic. This creates a seamless interplay between personalization intelligence, product data management, and the digital product experience. And because structured product data also serves as the foundation for more precise personalization in the online store, this interplay works both ways.
| Personalization Insights from Epoq | Implementation in Censhare PIM |
|---|---|
| ✓ These products are often purchased together | ✓ Manage bundle or product relationships centrally |
| ✓ Search and click signals indicate relevant attributes | ✓ Prioritize attributes and enrich product data |
| ✓ Recommendations regularly lead to conversions | ✓ Save recommendation as a curated product link |
When Personalization Insights from Epoq are integrated into Censhare PIM, successful store patterns can also be applied outside the online store—for example, on Google Shopping, Amazon, marketplaces, in newsletters, retail media, or campaigns.
Insights derived from click and purchase behavior can be incorporated into product data processes beyond the online store and utilized there.
Relevant attributes, terms, and content can be derived from Shop Insights and further developed in a targeted manner across product groups or product lines.
Centrally managed product information helps ensure that products are communicated in a consistent and transparent manner across the online store, campaigns, and other digital channels.
Concrete examples illustrate particularly well how click and purchase behavior give rise to structured product data and product logic that can be used across channels.
In the PIM, an outdoor shoe is classified as a “hiking shoe.” However, analysis of click-through and purchase behavior shows that many customers tend to find and buy it through categories such as “Travel,” “Everyday,” “City Outdoor,” or “waterproof sneakers.”
Personalization only:
This allows us to better recommend these products in the store or display them in specific categories.
PIM only:
Reflects the official category, but not necessarily actual customer behavior.
Together:
Click and purchase behavior indicate that customers perceive the product differently than it is classified internally. PIM can use this information to create additional categories, tags, or channel-specific classifications.
Added Value:
Products are not only sorted correctly internally, but also in the way customers actually search for and purchase them.
Click-through and purchasing behavior reveal which products are frequently bought together. For example, when it comes to cameras, it turns out that customers do not choose the officially recommended memory card, but usually opt for a different model with more storage.
Personalization only:
I often recommend this memory card in the store.
PIM only:
May have a well-maintained accessory relationship, but this is based more on manufacturer logic than on actual purchasing behavior.
Together:
The actual combination is identified based on click and purchase behavior. The PIM system records this relationship as a verified product relationship—for example, as an accessory, bundle, cross-sell, replacement product, or recommendation.
Added Value:
Purchasing behavior is transformed into official product relationships that can be used across all channels.
Analysis of click and purchase behavior shows that certain product recommendations are particularly effective. For example, people who buy running shoes click on certain running socks and a care product more often than average.
Personalization only:
Display this recommendation in the store.
PIM only:
It can manage bundles, but it doesn't automatically know which combinations actually perform well.
Together:
Click-through and purchase behavior are used to identify which combinations work. The PIM then turns this into an official bundle or a robust product relationship.
Added Value:
Personalized recommendations become scalable commercial product packages.
An email tests various messages, such as “sustainably produced,” “especially lightweight,” or “ideal for long distances.” The click data shows which message actually works best.
Personalization only:
Can better personalize future emails.
PIM Only:
Manages product descriptions and attributes, but doesn't automatically know which selling point is truly effective.
Together:
Click-through and purchase behavior clearly indicate which product message is effective. The PIM can incorporate this information into channel-specific product descriptions, priorities, or attributes.
Added Value:
Performance data from emails improves product communication across all channels.
In addition to clicks, purchases and shopping cart patterns also become visible through store personalization. This makes it possible to see that customers are particularly likely to buy sustainable products when they cost less than 100 €.
Personalization only:
I can highly recommend more affordable sustainable products.
PIM only:
Knows price, sustainability attributes, and product data, but does not automatically recognize this combination of demand.
Together:
Personalization reveals which combinations of attributes are actually relevant to purchasing decisions. The PIM can use this information to develop product assortment logic, for example, for tags, landing pages, filters, campaign products, or internal product assortment decisions.
Added Value:
Behavior translates into robust product line knowledge.
Some products are viewed frequently but rarely purchased. At the same time, customers search for terms such as “size chart,” “material,” “washable,” or “goes well with.”
Personalization only:
Identifies the problem and can recommend alternative products.
PIM only:
Can maintain product information, but does not automatically know what information is missing.
Together:
By analyzing click and purchase behavior, we can identify where users are leaving the site and what information appears to be missing. The PIM can use this information to generate specific tasks for product data maintenance.
Added Value:
Conversion issues become specific product data tasks.
The more product search, recommendations, and digital visibility are shaped by AI-based systems such as LLMs, generative search results, and intelligent assistant functions, the more important centrally maintained and consistently formatted product information becomes. This is because products can only be presented in these contexts in a uniform, understandable, and discoverable way if relevant attributes, descriptions, and product features are available in a structured format. This is precisely where the combination of Epoq Personalization and Censhare PIM can make an additional impact.
When relevant attributes and content are structured within the PIM, they can be used more clearly and consistently not only in the online store but also in new digital contexts. The combination of Epoq Personalization and Censhare PIM thus creates a better foundation for consistent product communication across organizational boundaries and supports the growing requirements related to LLM visibility.
Bundles, recommendations, purchase patterns, search queries, and relevant attributes become visible.
Product relationships, attributes, text, images, and bundle logic are managed centrally.
Google Shopping, Amazon, marketplaces, newsletters, and campaigns all rely on consistent, performance-based product information.
Let's work together to see which insights from your Epoq personalization could already be applied to other channels today—from successful bundles to improved product data feeds for Amazon, Google Shopping, and marketplaces.
For companies that already use Epoq for personalization and would like to apply the insights gained from it to other sales channels as well—especially those with large product assortments, many product variants, marketplace operations, or cross-channel campaigns.
For example, products that are frequently purchased together, successful recommendations, relevant click-and-purchase patterns, seasonal product combinations, or indications of missing product information.
Depending on the setup, for example, on Google Shopping, Amazon, marketplaces, newsletters, retail media, campaigns, social commerce, or other touchpoints.
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