Competing with analytics-driven personalized customer experiences

With the rise in data-driven marketing strategy, personalization of customer experience has become one of the top differentiators among e-commerce businesses. The conventional one-size-fits for all approach is not working out anymore amongst tech-savvy consumers who are exposed to multi-channel e-commerce purchases. Findings from a recent survey conducted by the Ascend2 Research Partners states that “Offering personalized customer experience is the foremost goal of 70% of the e-commerce leaders” followed by revenue-seeking goals such as acquiring new customers or targeting individual market segments.

To gain momentum in this space, retail businesses have started to invest in delivering personalized customer experiences and toolsets that will payback multi-fold results when combined with real-time analytics. Continuous behavioral profiling, predictive technology, and real-time analytics help e-retailers deliver personalized messages, recommend suitable product offerings to customers and thereby increase engagement and sales conversions.

Personalized marketing is successful when combining technical expertise and domain expertise in the multi-channel e-Commerce domain. Implemention of toolsets such as Adobe’s Omniture, Google’s Optimize 360, IBM’s Coremetrics and Kissmetrics significantly improves the systematic data collection, data classification, data aggregation and data analysis.

Creating richer customer experiences takes a progressive approach in the following four phases.

Personalization

Personalization is possible over some time by consistently tracking & studying customer’s interests, browsing history, shopping patterns and other factors. To add more value in personalization, retailers profile their online customers in real-time, analyze customer value data, and apply modeling techniques on keyword search queries to upsell assorted products, offers, and discounts. A Forrester study reports that 10-30% of the revenue for e-commerce industry comes from upselling.

Integrated Communication

Mass marketing is not a focused effort and doesn’t bring targeted results. Integrated communication carries consistent, cohesive brand experience across all marketing channels to customers. Integrated communication analyzes customer responses from digital touchpoints like email marketing, social media, rich media advertisements and offline store feedback. Responses from integrated communication helps in effectively segmenting email lists, and conducting cohort analysis. The ideal online and offline marketing channels are finalized based on the information research & consumption pattern of customers.

Contextual communications

Analytics provide insights to facilitate contextual interactions during customer journeys by analyzing every facet of customer activity to understand the context.

Firstly, businesses leverage enterprise data such as demographic order history, shopping patterns, seasonality, trending items to effectively segment customer profiles. This helps in creating products that are in demand, devising targeted promotional strategies and maintaining optimal inventory levels. As a next step, retailers analyze user-generated data from the voice of customers, sentiment analysis, social listening and complaints to understand customers’ preferences on product variety, pricing, and delivery. Finally, retailers target shoppers with highly contextual, personalized offers from them and partnering businesses based on customers’ geo-location, time of the day, and day of the week.

Predictive communications

Now that retailers understand their customers better, they start applying predictive analytics techniques to predict customers’ needs, personalize messaging, and recommend products that meet compelling needs of customers.

Backed by clever algorithms, predictive analytics uses insights from past data on how customers responded to various marketing channels, campaigns performances to fine tune relationships with their customers, predict their next buying need and appropriately replenish adequate stock. Personalized shopping experiences help retailers acquire newer customers and retain existing customers with maximum brand loyalty.

In a highly competitive market environment that is characterized by lesser margins, retailers apply these advanced analytics techniques throughout customer journeys to offer differentiated customer experiences and maximize their share of wallet.