By automatically counting the amount of floating population in subway stations where outdoor advertisements are installed, you can check the effectiveness of advertisements in the location and how long the average floating population stops as objective indicators.
By automatically counting road traffic such as intersections where the billboards can be placed, you can check the amount of exposure the billboard has at the location and what the average vehicle idling time is as an objective indicator.
One of the most common problems in the marketing process is considered that you are well aware of your target audience. If you set up a marketing strategy based on misguided target information, you will not only be able to expect sales improvement but also lead to customer churn. We can predict future purchasing patterns of specific customers more efficiently with a trained artificial intelligence model.
The key to brand management is to maintain, position, and define a good brand reputation. A marketing strategy that does not reflect customer feedback cannot achieve the expected effect. In addition, as the service expands, analyzing reviews and feedback individually to derive results is a very laborious task. When artificial intelligence is in charge of this role, more objective feedback analysis results can provide a direction for the future planning process.
Chatbots are built to increase customer convenience while securing potential customers. In particular, there are a lot of chatbots that operate at an advanced level using deep learning. However, even these chatbots sometimes don't get what their customers want. Therefore, by analyzing the correlation between chatbot conversation and purchase rate, the chatbot algorithm must be gradually supplemented in a direction that can increase the purchase rate. We propose that customers' emotional analysis in conversations with chatbots can increase the purchase rate by predicting what visitors are looking for on the website and whether they have led to purchase through conversation with chatbots.
It is important to maintain a customer from a costly perspective rather than acquiring a new customer. If you can prevent churn by knowing in advance which of your existing customers are likely to churn, the effect can be greater than acquiring new customers. You can analyze customer attributes, behavior, engagement, and external factors to help predict the most likely customers to leave and prevent churn. Customer churn can optimize corporate profitability. By predicting customer churn, financial services companies can increase customer satisfaction as well as increase customer lifetime value.
With AutoML + Consulting, you can request a professional consultant of DS2.ai to develop artificial intelligence.