October 3, 2016 | Written by: Samrah Khan
Categorized: eCommerce & Merchandising
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The power to accurately predict has helped people gain an edge in business, in politics, and in life. It’s traditionally been hard to do, more art or magic than science—but in recent years, that is changing. The rise of big data and machine learning has led to methodologies that can be applied to many scenarios. Often called “predictive intelligence” or “predictive analytics,” these methodologies more accurately predict the weather, financial markets, elections… even the building of a competitive baseball team.
Predictive intelligence is based on observation of customer behavior and, with every action taken, building a profile of customer preferences. That information is used to anticipate customer wants and needs and predict which content would be the best to deliver in real time across any channel.
The Rise of Predictive Intelligence in eCommerce
Understanding user intent allows online retailers to improve the customer shopping experience by making it more engaging and relevant to users. Predictive intelligence enables retailers to achieve this.
Personalization allows brands to meet their consumers’ expectations of a unique, customized experience without a lot of work. Companies leveraging data and predictive intelligence to develop a better understanding of their customers so they can provide a tailored, yet scalable user experience is becoming the norm.
Predictive intelligence in eCommerce takes many forms, such as a product recommendation engine that can analyze a consumer’s purchase history and online behavior. With this data, the product recommendation engine determines the user’s intent-to-purchase to provide a tailored experience to the user. The goal is twofold: customer retention and sales conversion. As an example of the potential power of this tool, Amazon’s recommendation engine drives 35 percent of its revenues.
Transparency Market Research forecasts that the overall market for predictive analytics will reach $6.5 billion by 2019, up from $2 billion in 2012. According to Salesforce, a benchmark survey found that companies using predictive intelligence saw increases of 10 percent in website revenue, 35 percent in email click-through rates, and 25 percent on email conversion rates.
Instart Logic’s Predictive Intelligence Solution: Personalization with Better Performance
As a Ready for IBM Commerce partner validated with IBM WebSphere Commerce and IBM Commerce on Cloud, Instart Logic understands the role of predictive intelligence online. Fast-loading websites are crucial.
Consumers expect a quick-loading, relevant, customized online shopping experience. Predictive intelligence helps achieve the relevance goal, but how does it improve performance?
Instart Logic’s Multi-page Predictive Prefetching solution provides the ability to predict what pages a user will visit next and optimize delivery of those pages by preloading the content they are most likely to request. This provides a great customer experience by speeding up page load times, improving the user experience and conversions.
In today’s world of eCommerce, predictive intelligence has evolved from a nice-to-have feature into a must-have tool—delivering more relevant experiences faster.