As the digital transformation has pushed data-driven approaches to the forefront, the need to identify and interact with consumers has accelerated the need for individually compiled data, or deterministic data as it has more recently been referred to. “The ability to accurately identify a customer is the most basic assumption made at every step of the marketing process – whether it is deliberately considered or not – making accurate identity resolution the literal foundation of all marketing activities.” – The Strategic Role of Identity Resolution, a Forrester report released 10.17.2016.
Identity management and recognition cross-channel, and even cross-device, is the key to managing the customer journey and measuring online to offline behavior. We routinely hear from companies that are not able to reconcile these two data universes. Consumer recognition through identity matching and validation will become the hub of the marketing and operational transformation as this will ultimately enable business to personalize offers and campaigns, dynamically alter web content and drive in app marketing as part of managing the customer journey.
The importance of understanding changes cannot be over-exaggerated when looking at the forecasts for mobile commerce (mCommerce) in 2017 being pegged around $150 billion dollars, or 1/3 of all eCommerce, driven by mobile penetration rates that are near saturation:
Source: DMA Statistical Fact Book
The importance of the right data layer capable of working across these environments cannot be overstated. So how does Audience Acuity help business address these new needs? We have developed a Super Identify Graph, which is an organized database containing nearly every adult in the U.S., and the known identifiers we have that associate with each. This includes some, or all, of the following:
Our product compares favorably with the more common Identify Graphs, or ID Graphs as they are commonly known, as those only have one or a few identifiers that can be used to identify a consumer. We also differentiate from our competitors in a critical way; our data is matched using deterministic matching logic that provides near certainty on the identify of each person whereas most graphs are built using a probabilistic approach that use signals that are probable but not exact.
This massive digital consumer footprint database contains over 300 million records. Through linkage identification the Super Identity Graph can also be used to map the appropriate channel data of interest or any of our 300+ attributes spanning demographic, psychographic, lifestyle, behavioral and transaction attributes back to their original full consumer record. This data is proven to drive better onboarding match rates as well.