Built with BigQuery: Retailers Drive Profitable Growth with SoundCommerce

As economic conditions change, retail brands’ reliance on ever-growing customer demand puts these companies at financial and even existential risk. Top-line revenue and active customer growth do not equal profitable growth. 

Despite multi-billion dollar valuations for some brands, especially those operating the direct-to-consumer model, the rising costs of meeting shoppers’ high expectations (i.e. free shipping, free returns) along with the escalating cost of goods, fulfillment operations, and delivery costs, create pressure for brands to turn a profit. The ONLY way brands drive profitable growth is by managing variable costs in real-time. This in turn mandates adopting modern data cloud infrastructure including Google Cloud services such as BigQuery.

To unlock the value of data, Google Cloud has partnered with SoundCommerce, a retail data and analytics platform that offers a unique way of connecting marketing, merchandising, and operations data and modeling it within a retail context – all so brands can optimize profitability across the business.

Profitability can be measured per order through short-term metrics like contribution profit or long-term metrics like Customer Lifetime Value (CLV).  Often, retailers calculate CLV as a measure of revenue with no consideration for the variable costs of serving that customer, for instance: the costs of marketing, discounting, delivering orders to the doorstep, or post-conversion operational exceptions (e.g. cancellations, returns). 

What may first appear to be a high lifetime value customer through revenue-based CLV models, may not be profitable at all. By connecting marketing, merchandising, and operations data together, brands can understand their most profitable programs, channels, and products through the lens of actual customer value – and optimize accordingly. 

The journey for brands starts with the awareness and data enablement of a more complex data set containing all variable revenue, cost, and margin inputs. What does a retailer need to do to achieve this?

  1. All data together in one place
  2. Matched and deduplicated disparate data
  3. Data is organized into entities and concepts that business decision makers can understand
  4. A common definition of key business metrics (this is especially important yet challenging for retailers because systems are siloed by the department and common KPIs like contribution profit per order may be defined differently across a company)
  5. Branched outputs for actionability: BI dashboards vs. data activation to improve marginal profit.

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