Contact Data Services
Dirty Data: what it means for CSPs digital transformation strategy
Dirty data affects data quality, and ultimately your bottom line. Find out how to create a data quality management plan!
What is dirty data?
Dirty data, rogue data, incomplete or inconsistent data. All these terms refer to the same thing and can cover any of these situations:
- Data that hasn’t been updated for years & subsequently has become obsolete
- Information or data silos as a result of data spread over different systems & in different formats
- Data that has become lost within a system and is therefore useless
- Duplicate information, which can lead to customer service or GDPR problems
- Incomplete or inaccurate data
Why is clean data so important?
Data can often be overlooked as a key element of digital transformation. Tools, technologies & processes are often the focus, but equally important to the success of any digital transformation is clean data!
Data is the fuel for sales and marketing campaigns. It is also the cornerstone of business analysis and personalising the customer experience & marketing plan. According to Experian, it is estimated that dirty data can cost businesses up to 12% in missed revenue, mainly through reductions in productivity, wasted resources and crucially, missed sales opportunities.
Dirty data can have an impact on reputation too. Marketing departments using inaccurate data cannot properly target prospects. Using erroneous data can lead to a poor customer experience. You absolutely must get data right before creating a personalised experience for the customer.
How does dirty data affect data quality?
Study after study all point to the same problems. It is clear that a database decays extremely quickly, and most companies do not have a solid data quality management plan or rigorous data governance plan in place to deal with it. Let’s look at some statistics on data quality:
- 30% of an organisation’s data is redundant, obsolete or trivial
- 1 in 3 business leaders don’t trust the information they use to make decisions
- Email marketing databases naturally degrade by around 22.5% every year
Every business must be able to trust their data, but the statistics point heavily in the other direction.
How to create a Data Quality Management Plan
Since 2005 we have been creating and updating contact lists for Telecom & Broadcast Vendors. We can also use our expertise to help clients have a better, more accurate and up to date database through our 4-point plan.
- Database Audit & Analysis: we audit your database(s) to understand what data you hold through segmenting and analysing all the fields for each contact. We will also analyse missing or invalid fields. Our clients will then receive an extremely detailed report to understand the exact situation of their database.
- Data update, clean-up, and completion: once we have audited the database, we are in the position to look at what improvements can be made. We decide which fields we can quickly and cost-efficiently update and/or complete. We homogenise duplicate entries to get a single source of truth. For example, this applies equally to duplicate company entries with slightly different names & duplicate contact details.
- Identification of missing Telcos & Broadcasters: since we hold the most complete database of Telcos & Broadcasters (with 250,000 executive profiles), we can easily identify gaps in your database. We benchmark your list of accounts with our own database and suggest which ones are could be added to make your own database more complete.
- Acquisition of missing contacts: we offer this service to allow you to reach out to acquire new decision makers contact details.
If you want to find out how we can help you address the issue of dirty data, please get in touch today.