Jun
04
2014

The next big thing in e-commerce — predicting customer behavior

A retailer’s website best illustrates the brand and has the potential to build a connection with each individual customer. However, building this connection requires the right online personalization. To achieve true personalization, marketer’s need accurate customer intelligence.

A recent Experian Data Quality study found that 61 percent of respondents wish to use customer insight to enhance consumer engagement. Additionally, those looking to improve customer insight and intelligence are doing so to increase revenue. I doubt this information surprises many readers. Without a deep understand of your customer base, how can marketers be expected to drive purchases?

While customer insight is a critical first step, marketers need a strong plan in place if they wish to see results. While insight can provide marketers with powerful information, they need to make data actionable in order to improve customer engagement.

A real-time data insight strategy will lead to a new level of online personalization for retailers, which will ultimately translate into a better customer experience. Moreover, marketers can ensure that the top customers are treated according to their value to the brand.

But how can marketers transition to real-time personalization? It all hinges on data and analytics.

First, make sure you have the right data in place. Unfortunately, the vast majority of companies suspect that a quarter of their contact data might be inaccurate in some way. Without confidence in customer information, businesses struggle with customer profiling and marketing efforts. Look to link customer records to gain a single view of purchasing patterns and preferences.

Second, consider how you can predict future customer behavior. Transactional history is very important; however, it only tells part of the story. A predictive model can indicate propensity to buy. Depending on availability, this can be solely based on first party data, or a combination of first and third party data. In either scenario, the data should be processed in real time, as the customer interacts online.

With predictive analytics in place, the e-commerce department can tailor online displays to lead customers down the optimal purchasing path. Moreover, consider the implication to customer retention. The business can begin personalizing offers based on each individual’s lifetime value.

This transition will not occur overnight – but already, our research indicates that businesses want to implement more robust personalization capabilities. To stay ahead of the curve, focus on the analytics behind customer behavior. From there, look for ways to tie customer indicators to dynamic online personalization.

Learn more about the value of first and third party data by reading our new white paper, ‘Data Quality and Predictive Analytics.’


Comment are closed.