Data + Trends  |  Ali Tore  |  March 16, 2016

Fast-cycle Analysis and More Data Signals In the Age of Explosive Online Shopping

Five ways retailers can use rapid-fire data insights to capture consumer interest and accelerate sales

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. Kids, teenagers, men and women all flock to flash sales and shop online for obvious reasons: because it’s easy and convenient. Who would have thought my seven-year old could hop on Amazon, pick what she wants, and check out within minutes? Some of you may have heard the story of the little toddler, where his dad came home one day from work and found five drum sets waiting at the front door!

In one ClearStory-driven analysis, we witnessed shoppers come online after 10pm and sales peaked consistently between 10pm and midnight. I’m not telling you anything you don’t already know. But if you’re a retailer, the phenomenon we’re witnessing now – where it’s almost an addiction for consumers – presents a mecca of opportunity to be captured. The best way to capture it is obvious: which is to see information and insights on what is happening, as it happens and why, and then respond and act right away.

Starting today, we’ll join other select technology partners at the annual IBM Amplify 2016 conference to showcase work in progress for an IBM Commerce Insights project. IBM Amplify is being held in Tampa, Florida this week. We’ll be speaking there and will be showcased as a data analysis innovator with a modern BI platform that enables fast and insightful actions from data using the power of our Spark IP. The event’s theme is “outthink ordinary,” and the show features the latest solutions for smart insights and delivery of shopping experiences tailored to the moment to optimize retail and e-commerce operations, drive sales growth and build customer loyalty.

In today’s era of modern, fast-cycle analysis, intuitive insights that anyone can understand are critical. Retailers need to see living insights every hour, as data updates, as promotions occur and so on. They should be able to see how products move, who buys what, when, and which segments of consumers are responding to most. If shopping carts are stuck, rapid-fire data analysis lets them quickly understand what the pattern is for stuck carts and act fast.  They see consumers flock, pile up their shopping carts, and then that’s where things can go well…or not.

Checkouts frequently don’t happen as shopping carts can cause some sticker shock or, consumers’ sizes or style preferences are not found, or another retailer’s promotional ads pull online shoppers away. In this competitive environment, retailers need to use data analysis to quickly satisfy the consumer and drive conversions. A lost shopper is very hard to win back.

So what’s needed in your data solution? Retailers need a way to do immediate fast-cycle analysis, watch insights as they update, and augment more data on the fly to determine how to pull consumers in and convert shopping carts, by using data on demographic, region, customer profile, spending behavior, halo affect opportunities and more. To that end, ClearStory’s automated analysis solution for fast-cycle information presented in business-ready StoryBoards gives retailers the information and answers they need instantly.

Based on our experience and having worked closely with customers in retail, e-commerce and CPG, here are five ways retail leaders can use fast-cycle data insights to succeed and thrive:

1. 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. By seeing “what’s happening” as it happens, suppliers can capture the consumer and drive fast conversions in shopping carts. Over time, those collected data insights can guide strategic changes to retail sites to improve experience.

2. Dynamic Pricing
With so many digital channels and comparison data points 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.

3. 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 consumer 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 retail marketing offers customized to them.

4. 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.

5. 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 like HappyFresh can see hourly insights in the form of shared B2B StoryBoards 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 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.

Ali Tore will be speaking about “Intelligent Business: Fast-cycle Analysis for Real-time Visibility and Immediate Insights” on Wednesday, May 18 at 3:15 PM ET in Room 5 during the IBM Amplify Conference being held in Tampa, Florida.

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