Connected Customer: Understanding the Person

Connections and Consumer Behavior

Personalized Customer Interactions with ONgDB

At this point in time, we’re living in the connected customer age. Frequently exposed to the internet, shoppers can easily find out important details on nearly every different product and company, making comparisons to competitors, and sharing their input through online ratings and/or social media. And yet there is largely a disconnect between what companies know about their customers how they engage personally with them.

For the last several years, companies would try sizing up customers based on basic household data and demographics. At this time though, consumers have the advantage of sizing up businesses and their products. To keep pace with this trend, companies will need to be more personable in their digital interactions. This requires a higher level of intelligence to be built into those systems that facilitate personalized interactions with the customer. The data to do this is likely being collected and simply needs to be leveraged holistically to provide a personalized profile of their connected customer. Being able to build this connected knowledge graph by more meaningfully and dynamically connecting all their data points in a real-time manner as interaction with the customer happen will provide a significant engagement advantage over their market competitors.

What enables a business to be personable and engaging will depend on the agility of their people and systems because a customer is an ever evolving being with complex feelings, opinions and experiences that drive their consumption and interaction preferences. Accomplishing this depends on a company’s ability to be flexible, comprehensive and personalized in knowing holistically each consumers they’re reaching to create personalized engagement with them accordingly in real-time.

For instance, if a vehicle maker knows that a customer has previously owned one of their convertibles and then moved to a sedan after getting married and now has 2.5 kids, this consumer may well be heading towards the need for an SUV or mini-van. Need is very different than desire, but a connected customer has both and they need to be understood. The realization that this male in mid-life may really be desiring the freedom associated with his memories of cruising in his convertible with it not being realistic anymore should be considered when making recommendations and engaging with him. When presented in a personalized way that shows the vehicle maker understands the phases of life being experienced the customer will respond.

A connected customer perspective moves beyond general classification and into personalized engagement with the individual and all their nuanced personality habits. Understanding these contextually rich relationships between your customer and all their behaviors, preferences and actions is a challenging task for any non-native graph database due to the amount of variation in the types of things to which they’re connected. Fortunately the native graph database, ONgDB, has been built for just this capability of modeling contextually specific, highly connected data.

The Open Native Graph Database (ONgDB) lets you take in critical data of a customer and relate it to the people they know, how they communicate online, what they’ve bought, etc. It offers further understanding of who your customers really are and what would motivate them to buy, and how you can cater to their needs and wants.

ONgDB graph database can offer companies further flexibility in exploring their information. Within the graph, new and dynamic questions can be asked of the connected customer data. For companies who want to succeed in the competitive market occupied by knowledgeable consumers, such freedom is essential to having an edge through personal engagement with each connected customer.

The Open Native Graph Database (ONgDB) is not limited by JOINs and so unlocks contextual intelligence of relationships by enabling querying about all data aspects of a connected customer in real-time. For personalized and dynamic real-time interactions with customers there is no better option.