UMAP is an internally consistent and generalizable model of consumer behavior from bottom to top, and back down. The framework establishes a method to incorporate multiple sources of data, recording multiple consumer behaviors, as well as records of market stimuli at multiple levels of aggregation with overlapping information. Competitor models unknowingly skew and blurr resolution with fused, inconsistent sets of models estimated in various stages.
The consistency of the UMAP model ensures that the results upon which actions are evaluated and executed are both structurally concordant and glean the maximal amount of information from each and every data source, exacting the complete, measured response of consumers and markets to the full spectrum of market stimuli.
Whether consumers convert on online or at retail location or via call center, and whether they are motivated to respond due to a TV spot, a price promotion, or a digital marketing tactic, or a combination of these things, our unified model simultaneously extracts all the available information from the data and harmoniously links the bottom and the top.
Much like the robust and scalable stack that makes Convertro the best in data ingestion, model training cadence, and intuitive dashboard delivery, our unified science scales to any data situation and is retrofittable to new sources or data at ever-finer levels of detail. This ensures that our solution is widely applicable and can evolve over time as a client’s business changes.
Convertro’s unified modeling approach can leverage aggregate mass-media data at the same time as shopper-specific digital media exposure, as well as environmental factors. This means that we can have multiple data sources simultaneously measuring some of the same things (e.g. an individual conversion and the total conversions for, say, a product), informing the single model of consumer choice with more precision than a marketing mix model, which on its own only looks at average consumer response, and with more breadth and coverage than an multi-touch attribution model, which on its own does not account for total market demand.
This is a departure from the way we typically think about an econometric model, with each stream of data being a separate dependent variable; rather, multiple streams of data can be fed to inform key dependent variables. In other words, we have a model for consumer choice that uses two different streams of data, total demand and individual demand, to estimate a unique relationship between marketing and demand (e.g. sales and/or quotes). This means that even where we almost never observe all mass-media, we can still estimate a consumer choice model for conversions without necessarily observing mass-media at the consumer level.