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How does Arcalea use predictive analytics?

Using standard business variables and outputs, Arcalea transforms data into predictive models that can determine outcomes prior to making critical decisions.

As a data-driven consultancy partner, Arcalea uses a broad spectrum of data science tools and practices to gain competitive knowledge for brands. One approach, predictive analytics, uses data elements from across domains and attributes (internal and external) to understand future processes and results.


For example, Arcalea uses predictive analytics to determine marketing tactics with greatest return: most impactful channels, segments, ad types, even specific ads.  Using minimal financial data (ad spends, brand margin, etc.) and existing sets of marketing data (“add to cart” leads, checkout conversions, transaction totals), Arcalea determines greatest revenue drivers from available tactics. 


First, Arcalea creates formulae that calculate revenue from a wide-range of scenarios and decisions, allowing comparative analysis of dozens of decision points.  As a result, brands are able to understand the ramifications of marketing decisions in advance.


Avg LT to Expected Return

Once a predictive analytics scenario is tested and refined, it can be standardized into an input model, allowing the rapid testing of dozens of variables impacting revenue. Companies can test predictive revenue of various strategies and tactics, in scenarios with varied CTR, conversion rates, margins, and LTV, etc.   As a result, partners gain information to make critical revenue-driving decisions while limiting unnecessary marketing costs.


Learn more about predictive analytics here.