Does situationalization contradict personalization efforts, which have been used by companies for years? Definitely not. Both approaches can help companies with conversion rate optimization. Moreover situationalization helps to eliminate the weaknesses of personalization.
The dilemma of personalization
Personalization holds a big dilemma: Every user always wants to see the most relevant content in an online shop, news portal or app. And, of course, companies also want to display the most relevant content in order to keep users on/in their website/app and increase conversions (purchases, ad clicks, etc.). But most websites unfortunately know only 20% of the users before the first click – so personalization alone is quite inefficient. There are many reasons for this: first-time visitors, GDPR, script blockers and much more. Therefore, personalization can usually only be used for 20% of the users. 80% of the users receive a website according to the “one size fits all” principle and bounce more often.
Personal data serves as the basis for personalization. Their usage requires an opt-in by the persons concerned. Since the GDPR, many users have become significantly more sensitive to the disclosure of their data, making the opt-in process a higher hurdle for many companies. The user experience suffers as a result!
Situationalization solves precisely this problem: The situational data used for this purpose does not require an opt-in and will be sent for every session. Furthermore, data such as device, time, date, referrer or anonymous IP do not allow any conclusions to be drawn about the identity of the visitor. Who exactly the person sitting in front of the screen is, is completely irrelevant for situationalization. This innovative method is fully GDPR compliant and allows you to optimize your digital channels for 100% of your visitors.
But how can the two methods be combined?
Combination of situationalization and personalization
Although both methods have many differences, they can still be combined very well. This allows the advantages of personalization (precise data on purchase history, user behavior, individual interests, etc.) to be combined with the potential of situationalization. The combination of the two methods delivers great results and addresses each individual user as individually as possible.
A good example of this is the individualization of product recommendations using a combination of the two. In this way, the recommendations of Asambeauty, for example, can shine by recommending the optimal products for everyone. These are calculated for each individual visitor in his current situation – making use of both situational data (in the example: operating system, referrer, weekday and weather) and personal characteristics (in this case interests: skin care or hair care). For example, a young woman entering asambeauty.de on a Sunday evening via Instagram in search of a trendy face cream will be recommended completely different products than a user who enters the platform on Thursday afternoons via Google and clicks on hair care products.
Situationalization by ODOSCOPE
The ODOSCOPE platform makes exactly this possible: With its help, both personal and situational data from different data silos can be merged. Classic examples of such silos include systems for Customer Relationship Management (CRM), Enterprise Resource Planning (ERP) or Product Information Management (PIM).
The result: Revenue and conversion uplifts of 20% and more. Further information and various concrete use cases from our customers can be found under references
Differences between personalization and situationalization
The most important differences between the two methods for optimizing the user and customer experience can be found in the following table.
|Online shops know only about 20% of their users at first glance.||Online shops know the situational data of 100% of their users before the first click.|
|GDPR makes personalization considerably more difficult, especially with regard to 3rd party data.||Situationalization is 100% GDPR compliant and requires no opt-in.|
|Personas are usually formed on the basis of historical purchases and are relatively rigid.||Situation-based personas develop with every click in real time and therefore change depending on the situation.|
|Personalization does not take into account that even known users have different buying behaviors – depending on their particular situation.||Situationalization also takes into account the current situation of known users and automatically adapts the digital channels.|
How does situationalization work?
Situationalization became possible only through the evolution of digital analysis methods. In the context of situationalization, automated decisions about the placement of content and elements of digital channels are made and implemented in real time – i.e. within a few milliseconds while loading a page.
Before such high-tech software and hardware solutions were widespread, data was often only available with a time difference between their collection and evaluation. Until recently, large amounts of data could only be combined and evaluated overnight with classic Business Intelligence (BI) solutions. In concrete terms, this means that today’s data could only be used profitably tomorrow. In summary, BI only enables a review, i.e. an analysis of historical data.
Thanks to the further development of Business Intelligence into a disruptive Operational Intelligence (OI) technology, data can now be collected and evaluated in real time. OI is a novel technology that allows an unlimited number of rapidly changing live data sets to be stored, updated and analyzed. This is made possible by the In-Memory Data Grid (IMDG), an innovative database structure that sits completely in memory instead of on the hard disk and is distributed across several servers. Therefore it is possible to perform hundreds of thousands of data updates per second.
Based on this real-time analysis of large amounts of data, Operational Intelligence is also able to make data-based decisions within milliseconds. Here, too, the classic BI is not enough: Because it usually only makes it possible to uncover connections in the past – conclusions and forecasts about the future must then be made by human analysts. The solution is präskriptive Analysen, which calculate the best alternatives for action and implement them directly.
This requires a high computing power of the servers for the execution of self-optimizing algorithms. The prescriptive analyses of the algorithms answer the question: “What should ideally be done to achieve a certain goal?” and initiate the necessary measures – if desired, even fully automatically. That way you can achieve and even surpass your goals with the help of situationalization!
Situationalization usually works in four steps:
The process of situationalization
Data collection and tracking:
Companies continuously collect usage and interaction data in different data silos (e.g. web analysis tools, PIM, ERP).
Consolidation of the data:
The raw data of these silos is regularly imported into a central platform and forms the historical database for situationalization.
As soon as a user accesses the digital touchpoint, his relevant situational data is transmitted. These are recorded and compared with the existing database. Using correlation-based real-time analyses, the so-called statistical siblings of the current visitor can be determined for each individual page element – i.e. the historical users who are most similar to the current visitor (real-time clustering). In this way, a user is perceived in all its versatility and addressed perfectly.
Prescriptive Analyses & Self-Learning:
Prescriptive analyses calculate in real time which page elements are most relevant for the current user. The calculated page elements with the highest conversion probability are automatically displayed – in less than 20 ms.
All reactions of the user to the displayed content are then stored anonymously and integrated into the database. Thus, the analysis can be continuously refined and optimized – and also the database is constantly updated and improved.
The advantages of situationalization
The situationalization of content, products and information offers some advantages over other optimization methods such as personalization.
Important advantages of situationalization are
- The data basis: situational data is already available in the companies’ data warehouse
- Situational data is always sent along and is necessary for technical functions.
- The use of this data is 100% GDPR compliant, as it is not personal and therefore no opt-in is required for its use
- The Customer Experience (CX) of users is improved by increased efficiency
- No additional collection of data is necessary due to the use of already existing data. Uplifts can therefore be achieved faster
- Even unknown users can be addressed individually with the help of peer groups (statistical siblings)
- Considering all interactions with already displayed content for constant refinement of results: Algorithms are constantly learning new things
- Continuous adaptation and optimization of content, products and offers in real time
- User is not assigned to a persona, but can be addressed individually depending on the situation via real-time personas
- the combination with other data sources such as ERP, PIM and CRM is possible
Application of situationalization
Situationalization is revolutionizing the user experience in many industries and at the same time also enables significant added value for (digital) providers. Customer and company satisfaction therefore go hand in hand, because situationalization enables a win-win situation: the relevance for users increases and companies can achieve significant uplifts in their KPIs.
|E-Commerce||Display individually relevant products, search results, recommendations and much more.||Conversion and revenue uplifts of 20% and more|
|Publishing||Display of individually relevant content such as articles, videos, picture galleries, etc.||Significant uplifts in retention time and page impressions and thus higher advertising revenues|
|Games||Display of better items depending on situations||More sales of digital items, longer retention time, more advertising revenues|
|Out-Of-Home Advertising||Advertising on truck rear walls depending on the situation, e.g. the nearest road service area like in Germany done byRoad Ads)||More relevant advertising messages, higher awareness |
|IoT||A cross-linked refrigerator could order other products depending on the situation, e.g. sparkling wine for New Year’s Eve.||Adjustment of purchases to the season, higher customer satisfaction|
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