Often difficult to generalize

A The danger lies in the chatbot, which learns the preferences and needs of your customers. The vast majority of these chatbots come from third-party providers who can use the data collected from your customers to then target them with advertising on social media. So pay particular attention to the contractual agreements and ensure that the data collected cannot be used by third parties and is anonymized, otherwise you will quickly find yourself dealing with angry customers who will be bombarded with advertising containing their personal data after they visited your website. Pricing and A/B testing In addition to chatbots.

Machine learning offers numerous other possible applications. For example, you can send customers an email when the price of a particular airline ticket drops or when the water filter level philippines photo editor drops and needs to be reordered. For example, online stores could offer coupons or lower the prices of certain products before the holidays to encourage sales. For example, if I knew that you would buy my product if you could get two T-shirts for euros, I would send you an offer accordingly. Next month I could make you a new offer for euros, maybe that would interest you. The machine learning process saves a lot of work and you no longer have to rely on your gut feeling.



The system uses your customers' data and purchasing habits to make new offers based on various variables such as profit margin, existing inventory and repeat purchases. More personalization requires additional customer personas, which can ultimately lead to a large number of personas because customers are . You need to find a healthy balance between the price and the period of your special offer, because the customer might be upset if they click on your link too late and suddenly see a higher price. Pros: Improved order fulfillment Machine learning has the potential to reward customers with extras. Delivery conditions are always one of the most important.