The technological advantage of the plugin

More efficient retargeting through artificial intelligence

Why is the plugin superior to traditional retargeting providers and technologies? Because we have developed the data center. Here, user and ad data is analyzed using deep learning algorithms and your ongoing retargeting campaigns are optimized in real-time. So you'll notice a significant increase in your online sales after just a short period of time.


An overview of the plugin functionality


Step 1: Online store visitors are tagged

In order for the plugin to get to know your visitors, it needs to tag them in the first step. Typical for retargeting is the use of so called pixels.

If a potential buyer visits your online store, he retrieves retargeting pixels in addition to the website content. The pixel then places a browser cookie with your visitor. From this point on, user behavior relevant to retargeting is stored in the data center. For example, which products he looked at, which store categories he looked at and what he put into his shopping cart.

The tagging through retargeting pixels as well as the placement of the cookie are basic requirements for the targeted placement of online banners on external websites.

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Step 2: Visitors are classified

A large amount of raw data grows out of the collected user information. Only through user classification does this data become useful for retargeting. To make this process as fast and efficient as possible, machine learning algorithms based on neural networks are used in the data center.

The classification categorizes the visitor according to the following criteria, among others:

    • Where - e.g. from which source - did the visitor come from?
    • Which categories and products did he look at?
    • How long did he look at certain categories or products?
    • Which product categories is he particularly interested in?
    • Which products did he put in his shopping cart?
    • Which products sell best in the web store?
    • What cross- and upselling potential does the viewed product have?
    • And about 100 other factors ...

Step 3: Automatic creation of personalized ads

Since the plugin knows your visitors by now and has classified them, it knows exactly which products they are interested in and how much they are interested. With this information, the algorithm creates product-related online ads that are composed of the individual components of these products, e.g. product name, product images and price.

On a side note, ads for the most promising products are created with priority. If a visitor has already placed a product in their shopping cart, it can be assumed that he is more interested in it than if he just stumbles across it by chance in the product category. Thus, many factors already come into play in the automatic ad creation, which sustainably increase your store sales.

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Step 4: Budget optimization through automated bidding strategies.

The success of retargeting depends largely on correctly assessing the user's intention. At what point did he abandon the order process? Did he take a closer look at product details? How long did he look at certain products? For each of these eventualities, there are suitable bidding strategies in retargeting.

The plugin applies the most promising strategy for these different cases and fully automates what experienced retargeting specialists would configure otherwise.

And we go one step further: by analyzing large amounts of data, we can pretty much tell at what point users start to feel bothered by your retargeting ads. Is acceptance on mobile devices significantly higher than on the desktop? At what frequency do ads need to be displayed so that your potential buyers are not annoyed? The algorithm takes all this into account in the background and implements it in real time.

Step 5: Automatic ad placement on external pages.

Anyone who has ever created a retargeting campaign using conventional methods knows that success depends on the combination of a wide variety of factors. Often, however, this works anything but intuitively. For example, ads are usually created completely independently of bidding strategies and must be linked manually. In addition, there is a time-consuming registration process with ad networks.

The plugin takes care of all this fully automatically. Our data center is connected to the world's largest ad networks and we distribute ads through our own ad servers. This ensures smooth placement of ads in topic and product relevant environments on external websites.

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Step 6: Continuous optimization of ad placement.

For us, dynamic retargeting doesn't just mean creating personalized ad banners. The placement of ads on external pages is also embedded in a dynamic process. Our data center processes information on ad acceptance that we receive from the connected ad networks.

In this way, our algorithm quickly learns at what time of day your store visitors are most receptive to online advertising, which browsers are used most often, which screen sizes are clicked on the most, which geographical locations work best, and which end device is preferred for clicks and purchases. Added to this is the analysis of other socio-demographic data such as gender, age, net household income and current consumer interests. Time-consuming A/B testing is thus a thing of the past.

Step 7: Significant increase in sales

The above steps will result in shopping cart abandoners returning to your online store via dynamic retargeting. A significant part will also complete the purchase. You will notice how your conversion rate increases after a short time.

To guarantee that your budget can be invested in further shopping cart abandoners directly after a successful purchase, the plugin removes the tag from the buyer. He will then no longer be shown ads on external websites for the already purchased product(s).


The intelligent heart of the plugin

At the heart of our unique retargeting technology for online store operators is our internally developed data management platform, which we also call the data center.

With the help of artificial intelligence, we analyze and process large amounts of data from our customers' websites as well as ad networks and use it to develop bidding strategies and personalized ads. To be a bit more precise, we use neural networks to analyze and control complex retargeting processes.

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