By Stephan van Heusden (Digital Marketing Services Manager, m—wise) 

In recent years, companies have really woken up to the fact that they can compete more effectively by analysing their customer data. However, the truth is marketing teams often struggle to gain customer insights from what can seem like an ever-growing range of available data.

Overcoming the roadblocks

Frustrations arise when external factors come into play. Perhaps the implementation is dominated by an IT department, or GDPR has prompted privacy concerns, or maybe the team started collecting data without a proper definition of the objectives. The important message is don’t give up.

Getting value from your customer data is possible when you focus on the impact of your efforts. Let’s look at the two main types of value creation and it will soon fall into place:

(Adapted from Verhoef, Kooge, Walk, 2016)

Value to the Customer (V2C)

To put it simply: V2C metrics focus on the delivered value to customers. These metrics answer questions like ‘is the customer satisfied?’, ‘will they recommend our brand?’, ‘do they engage on social media?’

Historically, data collection in this field was focused on market research, NPS, CES and brand equity. Today, online sources like social media and customer reviews come into the mix. If your brand has a strong online presence, online data can really help you derive opinions, sentiments and buying intentions.

Value to the Firm (V2F)

V2F metrics focus on value delivered by customers to companies. These metrics are typically behavioural and frequently financial: customer acquisition, retention and churn value. You will need the combination of customer contact, customer behaviour and buying transaction data to get the metrics you need.

Where V2C meets V2F

Example 1: Attracting customers

To be able to attract customers you will need to know why you are of interest to them. By tracking social media sources you will understand consumers’ sentiments about your market, category and brand.

By tracking the sources of web visitors you get to how they are being referred to you and what causes people to contact you. This data, combined with the fact that some of these consumers convert (i.e. become clients) and others don’t, can even help you predict the conversion from prospect to customer. With these insights you are assured that your budget for (online) advertising, sales and other channels is well spent.

Example 2: Development of customers

You’re probably aware of those “others also bought…”-style recommended product features. These are based on what the data shows that other customers do. Why not go a step further and take the customer’s past behaviour as input too?

Did the customer look at products but not buy them? Do they show high frequency buying behaviour? Are they spending a large amount only once a year? All these observations are great input for creating more relevant communications and inspiring new purchases.

Now you’re ready to get started with customer data analysis

Try starting with clearly defined projects. To measure the success of your project you will need metrics. These determine the variables and the sources needed to get the data. Of course, m–wise can help with this too. Our loyalty software comes with comprehensive Insights as standard. We also offer a Data Science service to help grow your business.

We hope this has inspired you to dig deeper into the data. If you need support with your efforts, m—wise can certainly help guide you. Don’t hesitate to get in touch.