Every customer segment has a maximum price point for a given product or service. SparkBeyond Discovery helps organizations determine pricing elasticity by product, channel, customer segment and sales period, for competitive, contextually relevant pricing that adapts to market sensitivities. 

To help organizations identify the price threshold, optimize pricing and eliminate the least profitable discounts and segments, the Discovery platform combines complex internal datasets on brand, item, customer segment, location (specialist, impulse, seasonal stores), with external data such as competitor trends, social media trends, traffic, footfall/mobility, weather, demographics and economic/trade.  

Automatically scanning for ‘hidden’ patterns, SparkBeyond Discovery identifies emerging micro-segments and unexpected/loss-making production combinations and determines consumer response according to seasonality/location.  Using these insights, it generates highly accurate pricing recommendations according to item, brand, category and inventory.

The platform’s continuously updating pricing models forecast fluctuations, helping teams improve strategy by correlating deal size to discounts and predicting customer response to a bundling or pricing offer, e-mail campaign, or other call-to-action.  

Demand volatility equals complex pricing challenges.  Against this backdrop, Europe’s largest pure-play convenience chain wanted to optimize revenue per store, but its internal data was disparate (store, transaction, promotion, assortment, stock).  SparkBeyond augmented the store’s data with external sources including competitor stats, weather and zip code-level demographics and built a model to determine store-specific elastic pricing.  Outcomes:

• Insights on price sensitivity across all product categories, adjusted per store.
• €15 million of impact.

Smart marketers use AI-powered analytics to leverage data from millions of consumer interactions and shape a flexible pricing strategy that adapts to changing consumer lifestyles.