Customer data is exploding. This provides a great opportunity for personalisation but often companies are unsure of how to make sense of this data and create value.
It’s no secret that we are in the age of customer personalisation; companies in all industries are challenging and winning on a differentiated customer experience, and they are supported by powerful technology that helps to provide a deep understanding of customer needs.
Over the years, traditional CRM has struggled to keep up. Although it has promised a 360 degree view of the customer, in reality it has only provided a ‘central view’ of customer records without rich contextual detail and insight. In many cases it is regarded by users as a glorified address book, which has damaged adoption and value realisation.
This situation is, however, changing. Artificial intelligence is increasingly becoming part of the customer personalisation toolkit, along with advanced analytics, and the convergence of these technologies on customer data in CRM opens up exciting possibilities, and new ways of doing business.
However, as with any technology investment this needs to be done smartly.
Now, more than ever, every customer expects to be treated like an individual. This means that the state of each customer relationship must be known at every touch point. And you must also appreciate the unique context of that relationship, so that you can direct each customer to success.
Personas, not data schemas, are the core artifacts of the design process.
At the same time, as the world becomes more digital, customer bases are growing and customers are dropping more digital breadcrumbs so volumes of customer data is exploding. This provides a great opportunity for personalisation but often companies are unsure of how to make sense of this data and create value.
So, how do you retain rich contextual data about every single relationship, at scale and with intelligent direction? And how do you get your people to use CRM? Achieving this in real time is key to what we call ‘smart CRM’.
Our approach has been to reinvent the CRM implementation project from the ground up.
It involves rapidly designing and visualising smart CRM solutions in days, ensuring project delivery stays user driven and value aligned.
Personas, not data schemas, are the core artifacts of the design process. By empathising with the daily needs of users, understanding their gains and pains, dashboard layouts and data solutions can be designed which zero in on pain points and unleash intelligence.
By fusing this human centric design with cloud agility and next generation unstructured data processing, 360 degree analytical displays powered by artificial intelligence can be built, which skip business rule modelling and go straight to insights.
Across almost every industry sector, there is a move to smarter CRM.
In financial services, organisations are imbedding highly scalable analytics and machine learning into both investment and retail banking user flows, empowering agents and brokers to have detailed advice conversations that are tailored to the individual.
While in communications, the influx of connected devices is driving a new role for telcos as the brokers of the internet of things. This is leading to a need for data-rich customer conversations that are demanding sophisticated insight solutions combining CRM with the internet of things.
But perhaps what is most striking about this exciting new rush of artificial intelligence adoption is the consistency of how it is being deployed: machine learning makes the complexity of human relationships manageable at scale without the loss of individualism.
That's why it was the missing piece of the puzzle for building a 'smart CRM'.
Daniel Lund leads Accenture’s cloud practice in New Zealand.
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