Transformational Analytics for Pricing

SparkBeyond Discovery

Build agile pricing strategies by understanding both the internal and external factors affecting profitability at a granular level.

Use a wider range of factors to determine price sensitivity.

Develop individual scores for each product category by incorporating and aggregating individual input factors for price sensitivity and promotion affinity.

Build a clearer picture of where to target promotions.

Achieve increases in revenue and margin with a granular view of the cumulative KPI—or “total customer effect”.

Optimally link prices and promotions.

Test smart price recommendations and identify key success factors that can be replicated across products and accounts.

Identify pockets of lost value.

Actively monitor customer-level profitability, including volume discounts, rebates, and cash discounts, to ensure they’re earned.

Campaign effectiveness

AI analytics can identify the right potential customers, shape the right message and pinpoint the best delivery methods – leveraging insights + speed for massive competitive advantage.

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Applications for SparkBeyond Discovery in Pricing

Customer retention

Accurately identify customers at the highest risk of lapse for effective, personalized retention campaigns.

Demand Forecasting

Analyze enormous volumes of various data to forecast demand, supply, quality issues, and market trends.

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Data & AI: the new efficiency of scale for global CPGs

Data & AI: the new efficiency of scale for global CPGs

Instead of leveraging physical scale to capture margins and share, leaders within the consumer packaged goods (CPG) industry are now using AI analytics, and its store-specific insights to be super agile, close to their customers, and faster than their competitors.

Pricing

Anticipate changes in consumer preferences to tailor promotions, prices, and products for each customer.

Global retailer empowers analysts with data science

Here's how a global retailer massively reduced time to value by equipping their analytics team with AI to find answers in complex, disconnected data sets.

New data models for a new world

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Generative AI for data analytics: the future of enterprise sense-making

In the case of enterprise data analytics, generative AI will radically change the way we interrogate our data to explore, react to and shape our business realities.

Generative AI for data analytics: the future of enterprise sense-making

New data models for a new world

Nearly all existing models have been invalidated by the coronavirus pandemic. They will presumably be invalidated again as the situation evolves as the world recovers. Even after recovery, it is unlikely that we will return to where we started before the crisis began. So how does that affect our data models?

The Game Changers: AI in Banking

AI analytics helps major banks stay connected to their customers – especially during the dramatic rise of online financial management use. As leading banks apply a range of strategies to navigate the new normal, AI analytics is opening greenfield opportunities to raise profits, combined with agility and ethical responsibility.