Quality data is a challenge for most businesses and becomes only more challenging the more data that you have. The first question that we should ask ourselves is why good quality data is important? To examine this question, let’s consider the following scenario.
Consider a large business to consumer (B2C) business that has over 100,000 customers across multiple locations and manages large scale events and facilities.
In order to be able to effectively communicate with those customers, as well as market to them and take advantage of upsell opportunities, the first step is to first remove duplicates from the data - not an easy task in a large data set as customer data is entered with different spelling, different phone numbers and often with different email addresses or completely missing data.
If we don’t solve the problem of bad data, we end up with the following challenges:
- Customers and prospects are communicated with multiple times for the same messages - this is a waste of money and also creates a bad impression on the customer,
- If data is entered with invalid data in the first place, this can result in important messages not being communicated to customers (such as customers missing out on the announcement of a new service or product),
- It becomes impossible to fully understand a customer and to get a 360 degree view of those customers. Without this, cross selling becomes impossible.
So, how do we solve these challenges?
The first step is connecting your systems.
In this particular example, Datamagic helped the organisation by connecting the following systems:
- Customer Relationship Management
- Email & SMS Marketing Systems
- Venue management software
- Events management software
Across these various systems, there was the possibility that a single contact was entered multiple times across the organisation. In order to identify these duplicates and ensure that they weren’t duplicate across each system, we chose to leverage Master Data Management (MDM) as part of the data quality strategy.
This means that each time a new company or contact record was created in each system, is was first passed into the MDH platform, which checked the data against a set of business rules and also for potential duplicates. Records flagged as a potential duplicates or those that failed any business rules were put into quarantine for review by the organisation's data stewards. Once the data was corrected, the records flowed into each system.
This had the following benefits:
- Duplicate records were removed and continue to be removed across the business,
- Customer data, such as stadium visits and event attendance were integrated into the customer record in the CRM. Providing the sales and customer service teams the desired 360 degree view of the customer record,
- The marketing teams are now able to leverage accurate customer data to effectively market to the customers across the business units.
An example of how this particular solution is provided is shown below.
What are some of the benefits of improved data quality?
Some of the benefits of improved data quality include:
- Minimises the risk of errors, assumptions, and biases in decision-making processes,
- Empower your customers with products and services, leading to increased customer satisfaction and loyalty,
- Mitigate losses and ensure business continuity by proactively identifying potential risks,
- Gain a competitive edge and eye for new opportunities.
