Innovating with analytics to help families get more out of life
- 2,000 Brands sold
- 4.4M Active customers
- 160K SKUs
How does a retailer better understand and serve its customers without the presence of brick-and-mortar stores? By forensically understanding customers and their behaviors, creating digital fingerprints across online channels.
As a 100% pure play digital retailer, The Very Group knows the value of its data. With one of the U.K.’s oldest, richest, and deepest consumer-focused datasets, The Very Group turns data and insights into actions, delighting customers and helping families get more out of life. The online retailer calls this “DNA: Data, iNsight, Action”—a data strategy that powers more relevant, timely, and personalized experiences.
Selling fashion, home decor, electronic devices, household appliances, and everything in between, The Very Group serves an array of customers with ever-evolving behaviors. The retailer even offers financial services products to help families on a budget.
“We really want to understand our families,” says Steve Pimblett, chief data officer at The Very Group. “How they shop; where they shop; at what time they shop; where they live; how they value product, price, promotion, delivery—the quantitative side of data. But also the qualitative side of data—attitudes to risk and life and what they need from an online retailer—so we can better understand the customer and offer better products and services to those families on a budget.”
Understanding customers requires data
The Very Group’s single customer view arms the retailer with robust data and a greater understanding of its customers. This improves customer satisfaction and advocacy by better informing product assortment, predicting demand to ensure product availability, and tailoring financial services products.
“When it comes to understanding customers, we seek to understand categories, products, brand preferences, shopping frequency and recency, value, and customer lifetime value,” continues Pimblett. “We think about how the flow of data across the organization can lead to value creation for our customers, whether that’s through better pricing, promotion, offers, delivery, and even customer-centric marketing. Our usage of data is very much to delight customers.”
As a digital retailer, The Very Group prioritizes digital channels—desktop, mobile, web, and native apps. Teradata partner Celebrus captures and contextualizes customer interactions to detect intent and opportunity signals, feeding interaction data to Teradata to create real-time, individual personalization.
Shifts in browser consumer privacy rules have led organizations to devise digital strategies for a future without third-party cookies. Celebrus’ first-party and no-party cookie solution supports organizations like The Very Group across digital channels to create digital identities that maintain regulatory compliance.
However, Pimblett says the benefits go even further. “Why is it so important to have digital fingerprints that can understand an individual on a device?” he asks. “We can start to spot potential fraud. The same Celebrus and Teradata solution can be used in different ways to protect our customers, in addition to offering them the better experiences.”
ClearScape Analytics™ operationalizes machine learning at scale
Understanding customers is one half of the equation. The other half: ensuring the right products are in stock and ready to ship to meet demand.
More accurate insights into future product demand optimize product availability. Ensuring that in-demand products are in stock drives customer satisfaction and increases revenue. To accomplish this, a set of demand forecast models feed insights into the stock replenishment process.
“There's nothing worse than going to a retailer when something's out of stock,” says Pimblett. “Out-of-stocks normally mean you've got your forecast wrong. We've developed machine learning analytical models to help us better predict future demand for 2,000 brands and 160,000 SKUs across every product size and color you can imagine, to make sure that we optimize availability.”
With ClearScape Analytics complex machine learning (ML) functions easily integrate into analytics pipelines—a collection of related operations that go from data preparation all the way through modeling and deployment—and can be packaged together to address specific problems.
Peter Murty, head of technology, data platforms and governance, at The Very Group, describes one example of ClearScape Analytics’ integration with Amazon Web Services (AWS) and SageMaker for ML forecast models.
“SageMaker brings the model governance, and behind that, the data for those forecasting models is powered by Teradata VantageCloud,” he says.
Every week, 160,000 stock-keeping units (SKUs) are forecasted using the SageMaker ML models with VantageCloud on AWS. Product forecasts predict the next 26 weeks of demand. Outputs include forecast accuracy and key drivers behind trends. These forecasting models leverage data sources such as:
- Transactional data
- Pricing events
- Promotional events
- Future pricing
- Calendar events
- Item attributes
- Hierarchy information
- Three years of data for all SKUs
ClearScape Analytics gives The Very Group the ability to continuously score complex ML models at scale, scoring its customer and product data in minutes instead of hours and days. This creates a rapid acceleration of insights and decisions, fueling growth and exceeding customer expectations by preventing out-of-stocks.
The Very Group’s retail teams act on insights when the forecasting models are combined with business rules and data related to buying decisions that generate recommendations.
Business users leverage these recommendations through a replenishment app to place more informed weekly stock orders.
Exceptional performance and increased business value
None of this is possible when data is fragmented and inaccessible. The Very Group’s first task was to modernize its information technology (IT) stack. Moving its data platform from on premises to the cloud provides connectivity to an extensive ecosystem of integrations and powerful data analytics capabilities. This drives innovation and provides insights to customer experience, retail, supply chain, marketing, finance, and financial services teams.
VantageCloud on AWS delivers a next-generation, cloud-native deployment and expanded analytics capabilities. The flexible and elastic cloud data and analytics platform provides an industry-leading price-performance ratio through superior workload management, cost optimization, and QueryGrid capabilities. One example is VantageCloud’s integration with Amazon S3 for native object storage (NOS) connectivity.
“For example, our clickstream data produces 30 terabytes of data per year,” he continues. “We realized that we could offload that data into Amazon S3 and connect to Teradata with NOS. Now, we can keep up to six months of fresh data in Analytics Database and keep many years of historic data in NOS. It’s a brilliant achievement.”
However, the cloud’s promise of infinite elasticity and flexibility requires financial governance through cost controls, without sacrificing performance. This is extremely relevant for retailers, whose narrow margins and fierce competitive pricing demand cost control and best-in-class price-performance.
Achieving financial governance with VantageCloud
“We are a lean, efficient business,” says Pimblett. “Total cost of ownership and efficiency are really important to us. It’s easy to innovate in the cloud by spending to scale. Platform thinking, economies of scale, and reuse across our businesses is how we think about it.”
Murty adds: “We can control the amount of compute, so it gives us cost governance and control over scalability. When we choose to scale, we can make that financial commitment and choice.”
Pimblett concludes: “Everybody wants scale and flexibility, but they still want that total cost of ownership and financial governance. Teradata just brings that naturally. If we can be more efficient, we can pass those savings on to our customers.”
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