AI solutions for eCommerce

April 30, 2019

AI for E-Commerce

Artificial intelligence in e-commerce is more than a hype. Developments that are still in their infancy at present will probably be the norm in a short space of time. The successes are measurable and speak for themselves. But how can one benefit from AI in e-commerce? Simply by being up to date and keeping pace with the trends in AI solutions.

AI is becoming user-friendly

Three aspects have made significant contributions to the success of artificial intelligence:

  • A marked increase in processing power,
  • larger quantities of data,
  • and an increase in the number of AI platforms and software.

The third item is of particular interest to e-commerce. User-friendly software that is based on AI is easy to implement and quickly shows striking results. Today, you do not have to be a mathematician to analyze developments and make them available to your own company. Clear graphics immediately make trends visible and comprehensible.

They help you to quickly identify what connections are significant in your own online shop: Are the movements of the customers coming from channel A different to those of the customers coming from channel B? What keywords are associated with changes in Customer Journey in your own online shop? What customer group has a positive reaction to specific offers? Good AI software provides more than facts; it also gives practical guidance tips, and carries them out if requested.

Search entries as food for AI

Every online shop must have a search box. But it simplifies more than just surfing on the website for the user. The small text box also provides users with answers to further questions. The most popular search queries can of course easily be identified without the help of AI. However, artificial intelligence makes gathering valuable insight from these search entries possible. And that is the purpose behind a search entry. This purpose can be more and more accurately ascertained. The search context can provide valuable tips in interaction with other user behavior. In the results, the answers to search queries are also more precise. This leads to a significant drop in termination rates. The prospective customer stays on the website and is still open to a conversion.

New links make user behavior predictions even more accurate. Machine learning works based on the trial and error principle and it therefore continuously acquires new knowledge. The hit ratios get better all the time. The software algorithms optimize themselves step by step – and simultaneously, the conversion rates grow.

clickworker offers you the service “search relevance” to optimize the search function on your website.
Clickworkers look at numerous results from your search function and rate them according to their relevance to the search term. The integration of this data into the algorithm significantly improves your search function.

Personalized landing pages

However, artificial intelligence can do much more. Systems based on AI can, for instance, design personalized landing pages. These pages not only directly address the customer (“Hello Mr. Jones”) – the content also corresponds exactly to the customer’s needs. Among other things, the surf behavior of the user also provides a basis for the individual filling in of landing page templates – enhanced with the empirical values of big data.

For example:

  • Someone who is interested in product X is often also interested in product Y or Z
  • Based on this knowledge, offers are individually selected and put in the correct order

A personalized landing page is ideal for offers with a limited duration. Because the content of a landing page in this case most likely meets the exact needs of the addressee, conversion rates are especially high here.

Propensity modeling

Propensity modeling is the new keyword in marketing. In doing so, artificial intelligence not only gathers a prospective customer’s willingness to buy, it also uses the right moment to initiate a purchase.

This is a simple example of propensity modeling:

Features including

  • father,
  • date of birth of the child
  • and previous purchases for the child

can, in connection with the time of day and date (even with the device the father is using to access the page) create effective incentives. These incentives can be used at any level of the digital shopping experience:

  • in the creation of an individual landing page,
  • selecting the best moment for the mailing of a newsletter,
  • as an additional offer just before completing the purchase process.

This example illustrates how extensive the possibilities of AI are. Furthermore, it shows that AI sets no limits to the imagination. Quite the contrary is true: innovative marketing models are often based on knowledge that has only been gathered with artificial intelligence.

Integrating AI in existing processes

But how can AI be integrated into existing marketing processes? Artificial intelligence does not change the old principle of complying with the customer’s interests. The only difference is that customer wishes are now transparent because they are based on reliable and verifiable data. Facts are replaced by assumptions and new marketing ideas can be verified in real time.

However, a slow integration of AI in existing processes as an additional source of information is advisable. The effectiveness of AI solutions for e-commerce is convincing, and they can therefore be used, little by little, in ever more marketing aspects. Anyone who focuses on the subject now will profit from an information advantage in the long run.


It goes without saying that artificial intelligence will change the rules of e-commerce. Anyone who starts focusing on the possibilities of machine learning and artificial intelligence for his business now, safeguards his connection to the future. Obviously, nobody knows what e-commerce will look like in ten years. But one thing is for sure: AI will certainly play a large and perhaps even decisive role.


Dieser Artikel wurde am 30.April 2019 von Jan Knupper geschrieben.


Jan Knupper