Understanding Your Customers Down to the Individual-Level
By collecting every piece of information and learning from every interaction, you’ll quickly be able to tailor and optimize the experiences your brand delivers.
So, where do you start? What if you could store absolutely everything there is to know about your customer in one place? Not just the factual data usually stored in a CRM customer profile, but also:
- All behavioral data (transactions, POS data, social media feeds, web clicks, email responses).
- All context data (location, device used, time, web pages visited).
- Any preference data, stated AND observed (channel preference, time of week, time of day).
- Customers intentions (how likely they are going to engage with you, via a certain channel or on a specific type of offer).
It’s the totality of that knowledge about your customers that we, at NGDATA, call Customer DNA. We aren’t talking about storing this information in a huge data warehouse or having it in multiple systems and databases. We’re talking about having that entire Customer DNA profile in a single, nimble software platform, based on big data technology.
Customer DNA consists of literally hundreds of attributes and values that describe an individual customer in a very detailed way. It calculates and visualizes socio-demographic values, describes mobility, communication preferences, spending behavior, customer engagement and much more. We call these attributes “metrics,” and there are a few types:
- The first kind of metrics are the factual customer data (socio-demographic information from a CRM system, like name, gender, address, etc.).
- The second type of metrics are calculated metrics. They are formula-based metrics that contain an aggregated value about customer interactions or other customer entities (number of cash withdrawals per week or the total number of active products a customer has).
It doesn’t stop there:
- A metric can also contain the outcome of a scoring model, such as a product propensity model.
- A metric can contain the outcome of an external model that will be operationalized within the Customer DNA.
- Customer DNA contains preference-based metrics (machine learning metrics or smart metrics) whereby the metrics automatically learn about the behavior or the affinity of a customer towards certain triggers or exposures, such as a response model.
All of those different types of metrics are part of the Customer DNA. For every customer, the Customer DNA is built automatically and updated in real-time. It’s a holistic and atomic view of your customer that always up-to-date.