Envision an in-store mobile experience that gives customers product reviews, suggests products based on shopping history and current cart contents, and instantly alerts sales associates to customers requiring advice or assistance.
What if stores could also offer real-time coupons at the point of customer interaction based on analytics of online competitor prices, inventory, and shipping costs? All such capabilities are achievable for brick-and-mortar retailers by embracing data velocity.
Retailers have missed the ball by the time nightly batch processing reveals that Joe Smith should have been offered a coupon when he was standing in the store eight hours before. The value of all of these actions lies in immediacy. And it’s this “now decisioning” on big data that will help retailers remain competitive with their online counterparts.
Today, brick-and-mortar retailers face several challenges from online shopping sites even more frightening than inventory, price, and tax-policy. They may lead big data adoption in areas of data-mining, analyzing supply chain, and marketing in comparison to online rivals, but they’re at a serious disadvantage with respect to leveraging data to improve customer experience and cross-selling at the point of product selection and sale.
In the back office, online retailers churn volumes of historical data to produce quality recommendations; they can present online reviews and product images to persuade purchasers. That creates a personalized experience that can be carefully monitored, a/b tested, and continually improved.
But now there is a game changer for brick-and-mortar retailers -- mobile. It’s no secret that customers love mobile; smartphone usage trends continue to show strong growth. There are an estimated six billion mobile subscribers worldwide. Correspondingly, mobile Internet usage is growing rapidly as a percentage of total Internet utilization. The stage is set for mobile-focused startups to attack staid industries (like what Uber is doing in transportation). Brick-and-mortar retailers have a golden opportunity to impact consumer buying behavior -- using mobile to answer online shopping’s advantages in micro-personalization, pricing, and cross-selling.
Mobile offers the opportunity for retailers to combine premier destination experience, a tangible look/interaction with products, and expert associate customer service with the big-data personalization and highly relevant recommendations previously exclusive to online properties.
How do they get there? By embracing data velocity. Producing an in-store experience is an experiment in the making. Several tools are emerging to bring this capability to businesses, such as geo-fencing and store-specific-apps, omni-channel selling, and disruptive data management platforms that enable real-time decisions, real-time offers, and real-time customer interaction.
The data management practice has, during the last ten years, matured and commoditized storage and evaluation of vast amounts of data. From special purpose hardware-based vendors including Teradata and Netezza, to optimized software stacks such as Vertica and Greenplum, to commoditized storage approaches like HDFS -- the volume facet of big data is well addressed.
However, similar to the way that youth is wasted on the young, volume is wasted without velocity. Where youth have capacity for action but lack wisdom and resources, those retailers with physical presence, vast purchase histories, strong customer loyalties, and loyalty identity information must not waste the opportunity to act at the very moment customers are making purchasing decisions in-store.
The market hasn’t figured out the full paradigm to use to solve this problem; the method for exploiting velocity has not reached the level of maturity that volume management has reached.
But, what has become clear are three key requirements:
- The ability to process many thousands of events per second. The sensors, mobile equipment, and video that will enable the future in-store experience generate vast amounts of data that must be ingested and processed in real-time. Velocity data management requires high-velocity write ability.
- The ability to make transactional decisions based on a combination of historical and real-time data. Decisions require transactions -- the ability to read and write multiple pieces of data in a consistent and repeatable fashion.
- Extremely low price-per-transaction. In retail in particular, a successful high-velocity data management solution must run at the lowest cost-per-transaction possible. That implies being architected to take full advantage of the performance of modern hardware, and having the ability to scale horizontally, both on-premises and in the cloud.
The impact of data velocity and mobile is clear: Brick-and-mortar retailers that master real-time decisioning presented through mobile user interfaces will win. Those building the new in-store, mobile-enabled experience share a vision of the features and capabilities that will enhance the shopping experience and improve store efficiency.
What’s crucial to supporting that vision is the ability to process high velocity data now -- to combine a customer’s location, interests, and cart contents with real-time inventory, pricing, and trends to deliver incentives and information through mobile applications. Retail solution providers that exploit velocity as they innovate will reduce costs, increase customer loyalty. and delight shoppers.