27 percent visitor decline in January 2022

Page impressions fell by 27 percent in January. The reason is saturation in purchasing behavior after the Christmas business and a decline in search volume. Companies should counteract this by using technologies based on artificial intelligence to address customers personally and offer buying incentives.

In Germany, more than 100 billion euros were spent online on goods and services for the first time last year. The total volume of all e-commerce orders in 2021 amounted to 107 billion euros, according to the e-commerce association BEVH. This corresponds to growth of nearly 16 percent compared with the previous year, with orders for goods increasing even more strongly while services declined - due to the pandemic, consumers booked significantly fewer trips or event tickets.

The Christmas business was once again a revenue driver. German households have never received as many parcels as in the 2021 Christmas season. According to the Bundesverband Paket & Expresslogistik, the number of shipments sent in November and December rose by one percent to around 440 million compared with the same period of the previous year, because the parcel volume is also growing due to the online retail boom that has lasted for years. The consequences of the pandemic provided an additional boost.

27 percent visitor decline in January 2022

However, the revenue boom in December is currently also leading to an initial decline in January.

According to an analysis of the AI technology Bounce Commerce among 130 customers, 27 percent fewer page impressions were measured in January than in December.

The online shops and retailers that use Bounce Commerce for product recommendations based on artificial intelligence were still able to measure an average of 2.6 million page impressions per day in December. In January, there were only 1.9 million page views per day on the follow-up pages where users are offered products based on purchasing behavior. This corresponds to a decline of 27 percent.

Markus Kellermann, Co-Founder of Bounce Commerce, attributes this to a certain shopping saturation at the beginning of the year: "Many customers used the Christmas business and the 2G rule in brick-and-mortar retail to order gifts online. In January, there is therefore initially a saturation of purchasing behavior and, accordingly, a decline in search volume."

Google Trends, an online service of the Google search engine that provides information about how often search terms are entered by users of Google, also shows that search queries for gifts in particular have been declining since December 23 and in some cases have even fallen by more than 90 percent, while the peak was reached on December 12.

Use of AI technology for customer acquisition

Online shops should counteract this trend by turning visitors into customers through intelligent buying incentives and creating an individual shopping experience for the right target group.

Artificial intelligence is one of the central topics of our time. No industry, department or decision-maker can avoid the possibilities of the technology. AI is also becoming increasingly established in e-commerce, because online marketing is no longer just an attempt to sell a product to a mass of people. In the future, it will be much more about building a deep understanding of people's needs through data and then reaching the customer at the right moment through individual customer engagement. The challenge is to understand and anticipate each individual customer's purchase process well enough to determine that moment.

According to a DPD study from 2019, a total of 62 percent of customers have abandoned the purchase process sometimes (39 percent), often (16 percent) or very often (7 percent). Initial case studies show that with Bounce Commerce, up to 30 percent of visitors who would leave an online shop because they did not find the right product can be re-engaged with AI-based product recommendations, increasing conversions by up to 10 percent. In individual online shops, the share of new customers was even more than 50 percent.

This is made possible by AI technology, which uses machine learning based on CF-based recommendations, matrix factorization, nearest neighbor methods and association rules to continuously understand users better and recommend suitable products based on user behavior and neural networks.

In addition, attention maps of the recommendation pages are continuously created via eye tracking in order to further improve conversions and offer users the optimal shopping experience.

Fittkau & Maaß Consulting recently surveyed 120,000 internet users about their attitude toward personal product recommendations. 60.2 percent of respondents said they were neutral toward the topic and 15.4 percent were positive. For this reason, personalized product offers based on artificial intelligence should be represented everywhere in e-commerce in the future, because they are one of the most important e-commerce trends of the future. It is especially important to pay attention to the right applications, because outdated and unsuitable products are not well received by customers. Used correctly, however, product recommendations can lead to a personalized customer journey and thus contribute to an improved customer experience.