In order to create personalised customer experiences you need to understand your customers. By creating a consolidated dataset of all anonymous and known information about a customer, accessible across all channels, you have the opportunity to provide unique experiences that include personalised information, service and promotions.
Evaluating your data collection
The starting point for knowing your customer is evaluating where and how you collect their data. By aligning with the data owners across the business, you can better understand the data collection process and how it can be improved. Use of validation, verification and cleansing software or services at capture points can help enforce consistent data-governance standards around the business. This will make it easier to consolidate and maintain data over time.
It’s also important that alongside any data collection, you are obtaining permission and preferences for any customer information. A preference centre built into your my account areas is an easy way of allowing customers to maintain their permissions and preferences, and personalise the frequency, format and content of the communications they receive.
Ultimately data collection is based on a balanced value exchange. Is the incentive or change in service for a customer as valuable as their perception of the data or information they are providing?
Creating a consolidated view of each customer
Once you have reviewed your existing data collection points and ensured that appropriate validation and verification is providing quality data, the next step is to consolidate all direct and related information about a customer into individual unified profiles.
These individual profiles for each customer need to be made available across channels within the business so employees and systems are all using a consistent and complete view of each customer. This single customer view (SCV) provides the ability to:
1. Track customers and their communications across every channel
2. Have a consistent and continuous conversation as customers traverse channels
3. Create personalised experiences based on all information known about a customer
The obvious outcomes of this include much improved customer service levels, better customer retention, higher conversion rates and an improved overall customer lifetime value. Alongside this, building a complete and personalised picture of each customer and their journey can generate insight that guides customer experience improvement programmes.
Once you have created a SCV using your owned data, you can pair it with external, third party data to create an incredibly powerful view of each customer that enables broader marketing initiatives. The most common is social graph. By layering onto your data a representation of a customer’s connections and relationships within an online social network, you can build a bespoke data set that provides greater understanding of the customer, and allows you to develop products and services that are personalised for them.
Maintaining and enhancing the customer profile
Unfortunately data becomes out-dated very quickly. Alongside initial data collection your strategy needs to include how you’re going to maintain and enhance your customer information to ensure its ongoing accuracy.
One method is by using progressive profiling – a marketing technique that gathers information incrementally instead of all in one go. By obtaining minimum initial information you lower the initial barriers for customer interaction. Additional information is then gathered over a longer period of time through prompted and reactive touchpoints with a customer.
This can be achieved through some simple best practice steps:
1. Ask for the minimum information that is required to provide your core services and create a profile
2. Enhance the customer’s profile with the most relevant information based on where the user is in the customer lifecycle
3. Include previously captured contact details so customers can correct mistakes
4. Provide transparent access to update marketing permissions and preferences
5. Monitor your progressive profiling to identify drop offs and optimise the process through experience design changes or improved value exchange for the customer
By planning out different customer journey paths, progressive profiling can also incorporate dynamic collection and enhancement of data that is based on the current customer profile or the preceding information they provided.