Data-driven personalisation

The majority of consumers say that they are more likely to purchase if they receive some form of messaging that recognises that they are an individual, with needs and desires that are acknowledged. But only a modest percentage of companies make the effort to go beyond Dear [FirstName].

Well constructed, personalised messages work well to augment the customer experience, to increase customer engagement and to increase sales. In retail situations it also significantly reduces the percentage of goods returned.

What is personalisation?

Personalisation is about using data to know enough about an individual and what they might want, to be able to give them relevant information or encouragement before they ask. Sometimes personalisation is confused with letting people add their own personal touch to products, but that is more correctly known as customisation.

Steps to personalisation

1. You need to really know your customer. This means collecting as much data as possible on them, and having in place a streamlined method to stitching it together - remove data silos and embrace data unification.
2. Put customers in control. Happy customers are those who help themselves, so make sure that you provide self-service portals, give them FAQs and let me set up preferences on how they would like to be interacted with.
3. Engage with your customers. Make sure that your team is active where you customers are active. Use every opportunity to interact with them on social media, and to capture what is important to the market. Think and act in journeys - make sure that your customer knows where they are in a particular journey, and avoid successive but unrelated interventions.
4. Become fully customer-centric. Reorganise your workforce if necessary so that the entire company works cross-functionally to focus on delivering value to your customers. Put the needs of the customer above the needs of the company.

How to become more data-driven

It is tempting to create one enormous data lake and to imagine what insights you will be able to pull out of it.  The reality is somewhat different - you are likely to drown with this approach. Analytics tools are a new super-power, but must be used wisely. Here's how:

1. Understand what you want to achieve. Success often depends on knowing what outcome is needed, so clearly state the critical success factors and work back from there.
2. Know what data you need. What is the relevant or necessary data that you need to collect to engage with a customer, make a better decision or improve a product? Collect what you need - any more and you'll get side-tracked or become blind to the core data.
3. Test and repeat. You will almost certainly not get it right first time, so go with what you think will work, and then check the results. Alter one thing at a time and run the data again. Keep going until the customer response indicates that you've got it right.
4. Update behaviours. When sometime in your team presents a fact or makes a decision, ask them to make sure that they have the relevant analytics as justification. There should be no need to actually ask them for it as proof, but the mindset needs to change.

Using data to make every customer feel like they are the only customer increases revenue. Technology has the power to create empathy. Building recognition and trust means that your customers will love you back. You will need to personalise your company's messages to your customers, so that they feel that they know who you are, and take that next step with excitement.