We recently wrote about how creating a Single Customer View of your data is almost a pre-requisite for being GDPR compliant. This process involved using data discovery tools to find and catalogue all the personal information your company holds about individuals, and then creating a repository of this data that can be used to handle requests from data subjects.
This repository of customer and prospect data includes name, address and other contact details, ledgers of historical interactions and purchases, and even meta-data tracking individuals’ activities on company websites and other systems.
Some recent post-GDPR surveys have found that 65% companies have too much data, 54% don’t know where all sensitive data is stored, 68% don’t do what’s necessary to maintain GDPR compliance, and 59% failing to carry out necessary procedures to make sure they’re compliant.
Companies that haven’t created a repository of the personal and sensitive information they hold are already complaining of the time-consuming process of complying with GDPR-related requests, which can involve finding and reviewing older data inside legacy systems that can span back years.
But there is an equally compelling commercia reason to catalogue sensitive and personal customer data. That’s because having all this data accessible in one place – or at least all tagged and tied together even if it remains in dispersed over multiple databases and systems – automatically gives you a Single Customer View.
You can mine this data for sales and marketing to personalise offers and design unique customer experiences. You can also make it available to contact centre agents (and automated systems) to improve the efficiency of customer service.
A Single Customer View makes all the difference
The lack of a Single Customer View is often cited by senior managers as one of the main roadblocks to providing the personalised, omni-channel experiences customers are now demanding.
With a Single Customer View your contact centre can seamlessly manage interactions that cross multiple channels without asking the customer to repeat information; personalise upsell, cross-sell, and renewals offers to meet a customer’s exact needs and circumstances; route enquiries to exactly the right team or person without delay; and proactively engage customers to head off service issues before they become a problem.
From a marketing point of view, you can understand the commonalities of your best customers so that you can find more like them, as well as identify customer segments, lifecycle stages, and purchasing patterns to inform everything from product development to pricing and payment options.
And of course, you can also use it to remain GDPR compliant by making it easier to request from data subjects. An important part of compliance is to have processes in place to be able to tell a customer exactly what data you hold, where you hold it, and why – and completely delete this information if the customer requests it. Without having all the data you hold on each customer tagged and linked together this is going to be a costly and time consuming exercise every time you have to do it.
Getting data where it’s needed
Having all customer data either in a central repository or accessible across multiple systems because it has been tagged is only useful if you can get it to the appropriate people and systems as and when they need it.
It’s also useful if contact centre agents, for example, don’t have to explore this data during interactions to see what data you hold on a given customer, but rather get presented with whatever data you hold that is most appropriate to the situation with which they are dealing.
For example, if the agent is doing an upsell it would be handy to tell them what products on your website the customer they are speaking to has recently looked at. Assuming you have this meta data, and it is tagged to the appropriate customer, it doesn’t take a sophisticated workflow solution to do this. The agent could then be prompted to provide that customer with a personalised offer around those products.
Interestingly one of the other most mentioned roadblocks to delivering personalised, omni-channel customer service is inappropriate, outdated or overly-complex technology. However, the technology required to get the right data to an agent at the right time needn’t be complex, expensive, or even terribly cutting-edge.
Workflow software needn’t employ fancy machine learning algorithms to understand what a customer interaction is about, because it knows what the customer interaction is about from the options the agent chooses in the very workflow it is running. For example, if an agent starts running the “upsell product” workflow, then the customer’s purchase history and any other data you think is relevant can just automatically be presented to the agent in that workflow. No AI required.
In this case the workflow software just acts as a central point of control, pulling in data from multiple siloes and systems. Assuming all that data has been catalogued then the workflow can easily find the most appropriate information to show the agent.
All the integration happens in the workflow software on the agent’s desktop, so just as you can create a virtual repository of all customer data, you can create a virtual viewer of that data without integrating all those legacy systems and databases with one another.
As well as making it far easier to handle GDPR requests, the result of having a central data repository and integrating it with your workflow software is that you turn all your legacy and siloed data into useful and actionable commercial information.
For more information, download our e-guide.
Geoff Land is Managing Director of Infinity CCS. He previously held senior positions at Bright Star Communications (Saudi Arabia), founded Inspire FZE in the United Arab Emirates and has held a number of local and international positions at Nortel Networks. When Geoff is not travelling around the world he lives in Monmouthshire with his family and enjoys walking and working on his property.