Real-Time Segmentation
Take advantage of our unparalleled flexibility to engage your users: benefit from automated, real-time look-alike-audiences. Or take control with our easy-to-use interface to create targeted campaigns and peer groups. Seamlessly tailor your shop's offering to the individual needs of your users - all without creating new landing pages.
Real-time, automatically generated look-alike-audiences
Look-alike audiences are dynamically generated groups of users being automatically created at a page hit. Look-alike-audiences are as similar as possible to the current user, as large as necessary and as small as possible. Look-alike audiences make statistically probable statements about the interests of the current user so that personalized content can be delivered based on the corresponding look-alike audiences. This works for both unknown and known users.
User-centric approach Users like you for max. precision
Automatic peer groups for each user and their clicks
Full dynamics thanks to real-time adaption
Quickly and easily target your sales strategies
Easily define and create your customized audiences with our intuitive editor. Specify your audiences, define a strategy, and preview your results. You stay data-driven and automatically respond to different devices, times, etc. This works for both known and unknown users.
Be flexible and simplify in one
Boost your merchandising
Maintain a data-driven approach
Unveil the Power of Our Customer Engagement Platform
Real-Time Automation for a perfect UX for all users
Dynamic real-time personalization for all your users whether known or not. Maximizing your marketing efficiency.
Intuitive Interfaces to Manage your Strategies
Effortlessly manage customer engagement and A/B/n testing. Preview strategies across devices, locations etc. in a snap.
Fast Dashboard for In-Depth Product Analysis
Deep insights into product performance and all the KPIs that matter to you. With shared workspaces for both operations and management level.
Round-the-clock Support for your Convenience
Our support spans from implementation assistance and strategy guidance to advising, performance checks, and beyond.
Key Features at a Glance
Cookieless personalization
ODOSCOPE can personalize also for users without cookies, deleted cookies, or who deny any consent. ODOSCOPE personalizes your content for 100% of your traffic individually.
No additional pixel
Since ODOSCOPE is based on your existing data, no additional pixels need to be integrated. We do not track. ODOSCOPE is productive from day 1, no additional data silo, no redundancy.
Consent-free personalization
ODOSCOPE does not place a cookie to track a user, nor does it use any 3rd party data. Instead, it uses in-session data and is stateless, i.e. it makes and displays a decision, but does not store a status.
Individual relevance ranking for each user and their click
ODOSCOPE ranks any search and product list by each user click and according to their actual in-session behavior. It, therefore, dynamically analyzes each user's data points to determine their individual relevance.
AI-powered merchandising with easy-to-use interface
Although user conversion is generally good, it is not always profitable. This is the case when the product purchased has a low margin. Our AI-powered merchandising reliably strikes a balance between scalable personalization, high UX standards, and achieving your business goals.
Look-alike-audiences for each user, automated and in real time
ODOSCOPE identifies each single user’s individual look-alike-audience (LAA) from the shop’s data history in real time, and increasingly accurate by every click in the ongoing session. LAAs are large enough for statistic significance, but small enough to be mostly relevant for the current user.
Superfast technology for analyses and decisions made in real time
ODOSCOPE takes less than 20 milliseconds to analyze even hundreds of millions of rows of data and dynamically create a ranking based on user-specific relevance. ODOSCOPE can be integrated without impacting a shop's performance.
High-dimensional, fully automated prescriptive analytics
ODOSCOPE can handle many dimensions at once and across multiple data sources. The analysis results in a customized decision that is displayed immediately. It combines real-time analysis with real-time decision making and real-time data activation.
ODOSCOPE's Data Lake breaks down silos
Our Data Lake indicates all data points from the customer's data sources (web tracking, product data, optionally CRM data) at once and identifies relevant and meaningful correlations for each individual user. It breaks down silos and identifies the "gold nuggets" in data sources super fast.
Frequently Asked Questions
Find answers to common questions about our services and products.
In an A/B test, different elements like product presentations, colors, etc. are tested for their effect on users. 50% of the traffic is exposed to Variant A, 50% to Variant B. Depending on which variant performs better (cf. KPIs such as conversion rate etc.), that variant is used and the next test is set up. There are also A/B/C/D-tests with more than two variants, as well as multivariate tests (MVT), in which several elements on a page are tested in different combinations. A/B testing or MVTs are a common way to optimize page functionality and improve customer experience.
Customer experience (CX) and user experience (UX) are crucial aspects of the customer journey. CX is the customer's experience during his customer journey. If the CX is pleasant and the customer's request can be fulfilled effectively and smoothly, the customer is likely to return and may even recommend the company to others and be more receptive to the company's offers and advertising messages.
UX means the same thing. However, depending on the context, UX can also refer to the experience of potential customers (as opposed to existing customers).
A customer is a client. In contrast to a user, a customer is known because a purchase with order and payment has been made. However, known customers are often not recognizable as such during an online visit and can therefore only be recorded and treated as users (until they log in or place another order).
Customer engagement encompasses active behaviors like clicking, filtering, and purchasing. Each engagement fosters loyalty, with the right ones converting users into customers. ODOSCOPE enables instant personalization upon landing, ensuring users see the most relevant content immediately, ideal for fostering engagement.
Data activation is the use of data points to determine a (personalization) decision such as a specific selection, sorting of products, news, images, search results, recommendations, etc. according to individual relevance. ODOSCOPE works with real-time data activation, which adapts flexibly and dynamically to the user's current situation with every click.
The term real time is used in many different ways. Real time is not always real time. Technically, it refers to the quasi-instantaneous execution of computer-based analyses, decisions based on them and their display. ODOSCOPE has several real-time capabilities; both in terms of real-time analysis (even on very large amounts of data) and in terms of real-time display of personalization as a decision of real-time analysis ( cf. data activation).
A data lakehouse is a central platform for multiple data sources and their metadata. But unlike a traditional data warehouse (DWH), which is designed for SQL queries and traditional analytics, data is imported directly into the data lakehouse without a potentially error-prone and time-consuming extract, transform, load (ETL) process. A data lakehouse can store very large volumes of structured, semi-structured, and unstructured data in the same system, enabling machine learning applications and making data teams more efficient by eliminating the need to query and join data across multiple systems.
Situationalization refers to a user's current situation. It matters a lot whether someone is on the subway during rush hour surfing on a cell phone, at work on a desktop PC during the day, or at home on a tablet on the sofa on a Sunday evening. Each situation is different. So is user and customer behavior. How different that behavior is, and whether it differs more by time of day, device type, geography, or many other data points and combinations thereof, is contained in the shop's historical data and is determined for each user and click by real-time analysis.