Modern customer graph – the secret sauce of sound customer intelligence

The Modern customer graph
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Or why it’s about time brands started treating Emily, Jane, and Bob as diverse individuals despite some common attributes, using the modern customer graph and identity resolution. Here we go.

As consumers evolve in 2020 and beyond, demanding privacy and hyper-personalization all at the same time, businesses and brands have no choice but to start connecting the dots about who their customers really are. The siloed manner in which customer data has existed, analysed, and leveraged so far just doesn’t work anymore. Nor does the way audience segments have been built till date. Add to it the deep disconnects between what brands know about customers and what customers think brands know about them. Naturally, this disconnect can cause disappointments in the customer journey, often with consumer touchpoints in moments that customers don’t need them and missing touchpoints in moments that require brand interventions. But is there a way to solve for this challenge?

Enter customer intelligence, powered by the modern customer graph.

Even as we speak, customer intelligence platforms are closing the erstwhile silos in enterprise-wide customer data points by enriching first party data with third party attributes to create a single, holistic truth about each consumer as an individual. Customer intelligence has been an evolving concept for some time now. What differentiates sound customer intelligence is the science of the modern customer graph – the final bridge in connecting the moving parts of customer data. How does the modern customer graph work?

Traditional customer databases used PII data such names and addresses to maintain a customer record, while newer digital databases utilize emails and web cookies as customer records. In recent years, CRM technology and how businesses maintain their customer data has evolved but data points continue to be disjointed enough for customer data to appear broken. For example, a customer buying an item in-store is recorded on a loyalty system and their online store may not know that someone who added an item to the cart is the same person who bought the product in-store. Most brands can only currently track the standard e-commerce path perfectly, which is where an ad is viewed, website is visited, product is added to cart and checked out. However, that linear path makes up a tiny percentage of customer journeys and there are an infinite possible combinations of other journeys. This is just the challenge that the modern customer graph solves.

The modern customer graph is a living, sentient, real-time database that connects online and offline behaviours by connecting 1st, 2nd and 3rd party data. At its core, the modern customer graph contains master identities of individual customers and is designed to constantly make, edit and find connections between hundreds of data attributes coming from hundreds of data sources for each master identity. 

Emily, Jane, and Bob and the case of similar attributes but diverse identities

Take for example the case of Emily. On a weekday after work, Emily casually walks into a store at the nearby mall and tries on a few dresses. She has time on hand, so she checks out the competitor store across the street too. She then gets herself a cup of coffee and walks home. Over the next weekend, Emily checks and compares costs of the dresses she tried across multi-brand and single brand marketplaces before finally making a purchase. The modern customer graph, laden with data points that include online and offline realms, understands Emily’s shopping behaviour. A brand that has access to this buying journey will be able to offer Emily online discounts over the weekend just in time for her price comparisons. 

Is Emily’s buying journey the same as her peer at work Jane, a single mom, who has no time to window shop? Or Bob, the fitness enthusiast who works with Emily and Jane and religiously visits the gym every morning and the running track every evening? The answer is anybody’s guess. The modern customer graph tells brands why Emily, Jane, and Bob’s buying journeys are as diverse as they come despite similar attributes like age and affluence levels. The modern customer graph is the only way brands can truly get to know and befriend their diverse customers – like Emily, Jane, and Bob – in their sentient customer journeys.

What this means for brands

It’s cases like Emily, Jane, and Bob that demonstrate why identity lies at the heart of the customer graph and people-based marketing. For a long time, marketers have been too focused on reaching devices and their behaviours, and not the people behind those devices. This led to inefficient online and offline marketing campaigns that were centred around reaching people inaccurately that caused a poor customer experience and wasted marketing dollars. The new customer graph is centred around using a single deterministic profile to execute people-based marketing and measurements while improving customer experiences. This allows the business to use the graph as a reference to understand who to send their marketing message to, what they should send and also what time, location and channel. Eventually, identity creates the truly personalized experience that 2020 and beyond demand. 

Modern customer graph is the secret sauce that is driving identity-based marketing and powering customer intelligence on the whole.

Ready to up your game?

We’ll go out and say it. Brands that leverage sound customer intelligence, powered by modern customer graphs and identity-based decision-making at their core are the ones that will survive the flux of 2020. Are you ready to make the most of these new opportunities? Because we’re here to help. All you have to do is ask for a demo!

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