All Process in Real-Time
Today, the most sophisticated recommendation and personalization engines rely on long data collection phases consisting of processing data, analyzing it and then calculate targeted recommendations only after the customer is long gone. This classical method conflicts with one simple fact – customers make purchases when they are online, so offering recommendations once they leave the site is completely useless considering the dynamic requirements of the online world. Segmentify’s advanced and innovative recommendation engine fills this gap by generating on-the-spot recommendations, while the customers are still online and ready to buy.
On average a potential customer remains on a website for 2.5 minutes and checks 10 products and 2 campaigns during a visit to an online store. An efficiently functioning recommendation algorithm has to be able to analyze the online behaviour pattern of a user in this short period of time and combine the most relevant products and campaigns the user is most likely to be interested in. Otherwise that visitor would be easily lost to another competitor. This is why having an algorithm that works in real-time is one of the most crucial key points of running an online store.
Segmentify’s leading recommendation engine eliminates this long period by learning very fast, even in seconds. This is possible with real-time updates to underlying customer scoring and segmentation system. With every visitor information and behaviour- i.e. page views, clicks, purchases- Segmentify updates not only segment and score of that specific visitor, but also recalculates overall weight of each dimension that creates recommendation models like average time on page, pageviews per session, average basket size, etc. This leads to getting higher values from click-stream. Each visitor action updates customer model and scoring, and Segmentify engine returns recommended products and campaigns that is relevant and personalized for the visitor in real-time
In span of days, Segmentify recommendations can match classical recommendation engines and outrun them with quick feedback loops from visitors. With real-time recommendation model, Segmentify can offer right products to the right customers at the right time, which results in higher conversion rates and a significant boost in sales.