1. Data Based Decision Making - Profiling
Profiling Your Business Data for More Informed Decision Making

2. Why Profile Your Customers?
Customer profiling will help you to understand your customers, highlighting who they are, what they look like, their interests and wants. This insight will help you to recognise your customer’s characteristics, behaviour and traits. Having a better understanding of your customers,  you will understand what they are interested in and will be able to communicate with them more effectively.

3. What Is Customer Profiling?
Profiling of customer data is a method of using known attributes (demographics) to describe particular groups within the data.
Group examples may be – highest spenders, most loyal,
Typical demographics depend on whether your customers are businesses or consumers but can include – industry, company size, location, gender, age, income
Outcome of the process is an indicator of the significance of each value in the demographics as a descriptor of the group e.g. My highest spenders are companies in construction, employees 10 – 50, established over 5 years.
After you have identified the profile of your best and most profitable customers, you can then find look alike prospects and target them in an effective manner. These prospects should have a higher propensity to take up your offer and therefore provide a more cost-effective means of targeting new customers.
Machine learning – software runs to apply proven algorithms
Classification as well as predictive modeling
Business decisions based on model results
Larger data sets yield statistically confident results

4. How can profiling help? Marketing Improve customer acquisition
Increase customer retention
Improve return on marketing spend – targeting – identify cross/upsell
Find prospects where there’s the best chance of a quick win
Reduce acquisition costs

5. Example: Acquisition Campaign
Brief: Company A wanted to understand the make up of its best existing customers and to find more people just like them. Taking Company A’s marketing and operational customer files to create a single customer view, we developed a profile of their customers in order to understand who they are, how they behave and how best to communicate with them. Action: Once we had a picture of Company A’s best (highest spending) customers by income, age, lifestyle, behaviour, housing, gender, hobbies, spend and ethnicity etc., we used this profile to find new prospects with similar characteristics.

6. Outcome Improved understanding of the different customer groups.
Improved acquisition rates from targeted multi-channel campaigns
Improved ROI on marketing spend
Improved customer lifetime value through targeting