PERSONALIZED RECOMMENDATION SYSTEM
Thousands Of People Online
Suoxinda PRS supports enterprises and financial institutions with the registration, management, and operation of various marketing placements, including mobile apps and such online channels as message notification, advertising space, application features and products. As the entrance of marketing traffic, online placements are important resources to win competition, making it imperative to better manage these placements and their traffic. Personalized marketing operation starts with marketers applying for traffic from these placements according to business needs, to be verified and scheduled by marketing resources administrators. Upon verification, marketers can activate personalized recommendation strategies for the placements. When customers access the marketing placements online, PRS shows them the results of its comprehensive decision-making mechanism by taking into consideration placement, customer profile, marketing strategy, optimization strategy and other factors.
Comprehensive & Systematic Recommendation Strategy & Arbitration
Suoxinda PRS supports the application, management, and flexible combination of various recommendation strategies, including white list, expert rule, offline model, and online model. The decision engine of PRS runs traffic diversion calculation among recommendation strategies based on factors such as customer profile, behavior pattern, preference, placement and product information. A list of candidate recommendations is thus generated, subject to arbitration by the decision engine. It filters invalid recommendations and merges duplicated ones, optimizes the remainders against a blacklist and by the order of content priority, organizational priority, and strategy priority, before producing a final list of recommendations. If there are inadequate recommendations for the final list, the system automatically fills in with default ones. This ensures maximal utility of placements and best marketing effects.
AI Model Support
Big data and AI models can be applied to forecast customer intent, including changes in customer life-cycle, product preference, format and content of interaction, etc. Its value is manifest in customer profiling, precision marketing, lead mining, and other scenarios.
Automated Traffic Management
When marketers initiate a campaign, they can configure its duration and marketing traffic (such as the number of exposure, visits, etc.). When the preset traffic target is reached, the system automatically switches to other campaigns. This enables effective use of traffic for marketing placements and maximizes return on resources.