Certainly not, segmenting them and being able to offer them different types of results can make a huge difference. It is in this phase that it becomes essential to be able to Integrate search with profiling systems based on artificial intelligence, which will be able to recognize our users and learn from their behavior, thus improving search results over time. Let's see three concrete examples of algorithms that can be used with different types of users:
Is the searcher an anonymous user on their first visit? We may use an algorithm related to the most popular products, possibly influencing the result based on our product rotation or sales rotation management policies (e.g. showing popular products with high stock first, or not showing products where we have particularly low stock).
Is the searcher a user, still anonymous, who has a browsing history or who el salvador cell phone number list comes from specific product campaigns? In this case, I will be able to use an algorithm that gives prevalence to results based on his browsing history, for example by displaying those based on his previous browsing as the first results.
The person looking for a customer, maybe a VIP, who always buys high-end products? The right choice in this case might be to not show results for low-end products so as not to diminish your perception of our store and at the same time increase the chances that your average cart will continue to be high.
As you can see, internal search is for all intents and purposes an integral and essential part of building a cohesive user experience. However, in order to properly integrate this tool into our personalized marketing strategy, it is essential to equip ourselves with technology that can recognize users and apply different strategies in real time to show results.
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