Data quality analysis

Our data quality analysis document your data quality

Today, you are likely already using customer data in your business for analyses, marketing automation, efficiency initiatives, or the optimisation of the customer experience. Data is at the centre of all these different activities, but how good is your data foundation? And what about the GDPR?

Insights and understanding. These two elements are the primary reasons for businesses to postpone working with data quality improvement. They doubt how bad  it actually is? How important? Where are their primary issues? And how do we even get started?

Our data quality analysis provide the ideal pre-analysis to set up the right KPIs for your data quality and prioritise the most important efforts for your business

Benchmark your organisation and set up measurable KPIs

In our data quality analyse, we share the knowledge we have obtained throughout the years on best practices within data quality, and you will find answers to questions like: what is the actual state of our data quality? Is it good enough to support our strategic and operational goals? Which areas are particularly vulnerable? How are we doing compared to other organisations? And, not least, how are we going to solve them with concrete recommendations to targets and actions, you can take home and put into practice?

These are all questions the data quality analysis answer and you get

• as an employee: the documentation and recommendations you need when talking to your manager. An essential part of a data quality project is to start off by documenting why the data quality improvements are necessary, where the problems are, and who will benefit from the improvements
• as a CEO:  the decision-making tool with analyses, benchmarks, and recommendations you can employ in your organisation
• KPIs to measure the data quality progress, e.g. on duplicates, address quality, telephone number quality, etc. 

How we make your data quality analysis

The data quality analysis is created based on your customer master data, i.e. your customers’ name, address, and phone number. Ahead of the analysis, we therefore sign a data processing agreement and data is transferred to us through a secure FTP connection. Then we carry out the analysis and create the report. Unless otherwise agreed, we delete your customer data in our systems shortly after our delivery

Data input

• You should have at least 1.000 rows in your file with customer master data to achieve a valid analysis result. The file must contain the customer’s name, address, and phone numbers
• The data file is uploaded to a secure FTP connection in a flat file format, e.g. Excel

You get

The output is a PowerPoint presentation where your data quality is presented in three sections: an executive summary that briefly summarises the analysis results, thereafter the analysis is presented in detail, and finally the report presents a section with our recommendations, including specific action points

file_downloadSee an example (in DK)

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