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Are you data fit?

February 9, 2016

Bad data is no better than no data’ - Duda, M.D, & Nobile, J.L., "The Fallacy of Online Surveys: No Data Are Better Than Bad Data," Human Dimensions of Wildlife 15(1): 55-64.

 

Your company collects a huge amount of data, of varying types, spread across various systems and locations, stored in many different formats. This is a problem facing many organisations who are recognizing the ever increasing need to consolidate all their data, making it available, connected and usable to everyone who needs it. Whilst it may sound like a daunting task, there are actually people who are passionate about this process and are available to consult and help in its implementation!

 

Step 1- Establishing your data’s ‘cleanliness’

Prior to utilising your data, or even before cleaning it, you need to understand its current state- essentially asking how ‘dirty’ it is. Aspects to look for include duplicate records, missing and misaligned fields, for instance mobile numbers in the post code field. Once this has been established, you can make more informed decisions when beginning the cleaning process.

 

 

Step 2- Cleaning your data

 

Bad data identified you can now begin cleaning your database. There are various methods that can be used to do this, which one to use is dependent on the issue at hand, here are a few of the most common processes;

  • Data Standardization refers to the process of implementing best practice policies internally ensuring that all data is ‘clean’ at source. Crucial to this is the implementation of an organised and consistent environment for data entering into your CRM system.
     

  • Perhaps the most critical method when ensuring clean data, and a must when creating or upholding an efficient Single Customer View, is the process of data de-duplication. This involves ensuring that there are no duplicate entries in your data and, if there are, matching them into one entity.
     

  • To maximise your CRM, it is important that your data is constantly validated. Therefore prior to utilising it within a CRM system, a data validation processes must be decided. This involves agreeing constraints, rules and routines which are applied throughout your business ensuring that all data is useable and if not, it does not go unnoticed.
     

  • It is also important to complete missing data. This can often be done using calculated assumptions, for instance a client working in the hospitality sector had a group of contacts, all working for the same organisation and using the same email domain, however some were missing the ‘.co.uk’. You can safely assume that this domain should be added.

Step 3- Keeping your data up to date

 

Achieving ‘the right message, to the right customer at the right time’ is not possible with data which is obsolete. Whilst the measures outlined above will aim to keep your data clean it important that they are continually undertaken to keep your database as up to date as possible. As mobile numbers, addresses and, to a lesser extents, names change it is important to employ ongoing data standardization

 

(particularly to iron out human error). Similarly, as your employees may enter the same customer into your CRM system at different times, it is important to undertake ongoing de-duplication. All these processes can be automated on a daily basis to reduce human input.

 

Step 4- Enriching your data

 

Your data has now been consolidated into one system from its various locations, undergone cleaning, presented as a Single Customer View and is now ready to be used to drive engagement and sales. Its potential can then be enhanced through continued efforts to enrich it, either through internal measures (the integration of further data feeds) or through the use of external sources, for example 3rd party data sets or open source data. For example, in order to gain a 360-degree view of each customer, one of client of integrated their SCV with their customer relations database. As a result when dealing with customer enquiries, they now have all the info they need in the one place resulting in a quick and efficient response process. SiriusDecisions estimate that 30 % of an employee’s time is wasted on contact research when dealing with such matters. An example of a 3rd party data sources used to enrich your data would be ACORN which provides demographics, social and consumer behaviour data based on a customer’s postcode.

 

If you are thinking about using your data more effectively, whatever state it is in, get in touch and our team can advise on the process!

 

 

 

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