Online shopping is exploding and so is competition to win consumer dollars in an increasingly fierce market. In the U.S. alone, $335 billion was spent online last year and that’s on track to balloon to $523 billion by 2020, according to Forrester. Adding fuel to the fire and an increased thirst for data insights to outmaneuver retail challengers and capture shoppers’ purchases is the rise of the on-demand economy and the real-time fulfillment of goods and services.

Consumers have grown choosier, more sophisticated and demanding. They value transparency and immediate gratification, and will quickly abandon online shopping carts at high rates if the experience is confusing, below par, or if they think they can get a better bargain or selection elsewhere. They’re using numerous devices and digital channels to make their purchase selections, and the emerging retail reality of omni-channel shoppers as “digital continues to touch every step of the customer journey” —whether shopping online, in-store or both at once.

Seeing “what’s happening” as it happens so suppliers can capture the consumer and drive fast conversions in shopping carts, accelerate sales, improve consumer experience, spot shopper and buying trends, optimize inventories, build brand loyalty, and more.

Here are five ways retail leaders can use fast-cycle data insights to succeed and thrive:

Shopping Cart Fulfillment

Approximately $4 trillion worth of merchandise was abandoned in online shopping carts last year, and about 63 percent of that is potentially recoverable by savvy online retailers, according to BI Intelligence. Retailers can increase conversions and reduce abandonment rates by streamlining the checkout process, monitoring for errors in the checkout process so they can be corrected, and being transparent about shipping costs and stock inventory availability before shoppers move through the checkout process. Retargeting shoppers with emails sent within three hours after shoppers leave websites without purchasing can be quite effective. They average an open rate of 40 percent and a 20 percent click-through rate, according to Listrak.

Dynamic Pricing

With so many digital channels and comparison data at their fingertips, today’s consumers are empowered to quickly cross-compare pricing before they purchase. Dynamic pricing or offering special pricing or low price guarantees based on data analysis can provide a huge competitive advantage. Determining the right pricing to close sales requires taking data from multiple sources—such as competitor pricing, product sales, regional preferences and customer actions. Fast, hourly, or near real-time data analysis that retailers can view, explore and act on has become absolutely critical to competing on price successfully.

Personalization

By tracking customer preferences, frequent categories they shop for, price sensitivity, and factors such as clothing sizes, retailers can remove extra work, reduce time spent by customers and deliver a more personal, tailor-made experience. Depending on their day and mood, the same consumer can even shop with the same retailer in different ways. Data from multiple customer touch points can be blended, tracked and analyzed to offer shoppers more personalized service such as specific content or promotion types they’re most likely to react to in a positive way and take action on.

Supply Chain Visibility

Today’s shoppers expect to know the exact availability and status of their orders, and merchandise that takes too long to arrive will frequently be abandoned in shopping carts. This type of data analysis can be more complex for retailers if multiple third parties are involved in the supply chain, which requires more data sources to be blended and harmonized together quickly to provide real-time visibility into stock inventory and shipping time estimates. By factoring external influences into data analysis—like warmer weather in California this spring spiking sales of lighter jackets—retailers can optimize inventories in their fulfillment centers.

Improved Efficiency and Service

With the growth of on-demand business and more customers blending online and in-store shopping, data can be used to optimize operational efficiency and deliver improved service. For example, on-demand food operators can see hourly insights that automatically analyze which stores are delivering on time and ways to make the delivery process more efficient. For mass-market retailers that sell goods or services, shoppers can ensure products they prefer to select in person are in stock in particular store locations, distribution centers, and retail service providers can ensure they’re staffed properly to handle peak shopping or visitor periods based on advance reservation systems and customer analysis.

ClearStory Data provides data-analysis software.

 

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