The customer, a major Nordic builder of apartments had experienced problems with customer satisfaction.

Problem

• Their existing survey process, which was carried out once per year, revealed every year the same strengths and weaknesses.
• Management did not know how to utilize this information to improve situation.
• Pricing went also wrong, judged from sales times that fluctuated in a mysterious way.
• The management also felt that customer values and the company's own values did not match.

Solution

• BayMiner was used to determine the correlations between customer complaints and company processes using existing data.
• The customer feedback system was changed to enable joining of feedback data with all mutual data for each object.
• The data structure was realized to suit analysis at two transaction moments, at handover and end of claims period.
• BayesIT designed a system that allowed the knowledge model to be used to predict future project satisfaction as well as commercial success.

Benefits

• A much more detailed satisfaction picture helped focus quality actions both product wise as well as regionally.
• Quality at hand-over was improved reducing customer complaints.
• Essential cost savings were achieved from less complaints handling.

Business case

• The cost of the project was approx. 50.000 euros.
• Savings in costs of complaints were first year approx. 100.000 euros.
• Payback period was less than a year.