Data integrity is one of the most important topics in a data driven world. The term <big data> has been around for a number of years now, but very few companies actually managed to work with the data that they have. The biggest challenge is not really to collect the data, but to collect it in such a way that you can work with it.
Data integrity describes the quality of the way that you have saved your data across its lifecycle. It is essential to save your customer data or transaction data in a clean matter – not just once, but systematically.
Data visualization tools such as tableau can really make a big difference to your daily work. If you would like to work with your data you will need to clean it up. Tools such as tableau can take the first step for you, but they cannot do everything.
When we start a project at GANDT Ventures, the first thing we look into is the usually customer data. We need to understand the customer,- and product-base before diving into any form of strategy. Yet, it does not happen very often that this data is readily available.
Be careful when selecting Third-Party Tools for Data integrity
One of the biggest challenges that we have, is that third party tools do not always put the user/client in charge of their own customer data. Many do not offer the possibility to download reports in a manner that is very useful. Some do not even offer the option to download anything at all. In the worst case, some tool-suppliers offer you your data at a premium price. It can easily cost thousands of euros to setup something as simple as an excel export per day/month/year.
When selecting a new third-party tool: such as tracking tools or CRM tool, make sure that you have the possibility to download your raw data. Some providers merely give you the opportunity to download their standard reports.
These reports need to be in a format with which you can work with the data. A PDF download of a single CRM campaign that includes click through rates, sales conversion rates, opening rates and possibly more, is only useful when you would like to take a snapshot of your campaign.
The goal of working with data is that you can create actionable learnings. Thus the element of time is critical to understanding customer behavior.
Snapshot can be useful sometimes but you only really learn something if you can look at the development of your campaigns. And looking at aggregated views per month or year can be misleading. Especially when goal is to understand whether you have gotten better or worse over time.
Be consistent and have a <data integrity> plan
Consistency is one of the keywords when it comes to data integrity. A consistent use of dates, numbers, prices, and social demographic information is an absolute prerequisite to working with your data.
A simple example, when working with revenue numbers use Net Revenue Values (excluding VAT) at all times. Especially in an international company, the VAT-percentages can vary tremendously. This even holds true within the European Union. Next to that, it often happens that various currencies are used in the database. Tip: add one data field with a single consolidated currency (CHF, EUR or USD for example). This will enable you to compare revenues and costs across geographic areas more easily.
Cleaning up data can take up a lot of your time. It is usually best to make a plan before you start to collect your data instead of having to clean it up afterwards. When working with large numbers of data it is hard to fix your problems after a long period time.
If you would like to find out more about data integrity and how to work most efficiently with large sets of data, please do not hesitate to contact us.
