Bad Data Is Bad For Business
Customer data is used to create customer profiles, which can then be used to drive advertising, marketing, growth initiatives – even store locations, and in customer initiatives, to improve customer service or the overall customer experience. Customer data is gathered internally, or purchased from third-party providers. If bad data is used in the algorithm, insights generated are unreliable, and any actions taken based on that data can negatively impact the customer experience.
Data needs to be consistent, relevant, and have both accuracy and integrity. Data that fails on any of these measures can be considered bad data, and impact the methods by which enterprises create customer profiles – making those profiles at best, skewed and at worst, completely invalid.
Bad data impacts customer experience with brand interactions, including:
Poor Customer Service:
Bad data used for customer service may result in frustrating experiences for both the customer, who may be asked to provide information more than once and the customer service representative that is attempting to provide an individualized, responsive customer experience. It is unlikely that the customer will be satisfied at the end if they have to constantly correct the erroneous demographic, personal, or prior purchase information in the course of a customer service interaction.
A recent survey of marketers showed that 21% of their budget was wasted on insights generated from bad data. This affects the customer experience, as brand interactions that are deemed irrelevant, or just plain wrong, erode the consumer-brand relationship. Personalized customer service, when accurate and timely, can boost sales, engagement, and customer retention. Inaccurate personalization can negate those results just as easily.
How to ensure data quality
To ensure that data used in analytics is of good quality – and therefore the customer insights drawn from it are good as well – a company should dedicate resources, including employee time and equipment, to ensure that data is accurate before being used in analytics.
Purchase Clean Data
To ensure that the data purchased from an outside party is high-quality, you should know the following:
- Data methodology: How was the data collected?
- Data source(s): Where did it come from?
- Data scale: How large is the raw data set?
- Data parameters: What are the guidelines for data verification and accuracy?
- Data freshness: What is the lag time between occurrence and reporting?
- Data type: Is it factual, or inferred?
- Data privacy and security: Does the provider follow strict guidelines for protecting the security and privacy of personal information?
When this consumer data is inaccurate, inconsistent, or lacks integrity across data sets, the insights that are drawn from the data will be inaccurate as well. This negatively impacts business outcomes, including providing a positive, unified customer experience. To optimize the customer experience and ensure customer satisfaction, and strong brand relationships, consumer data must be high-quality, accurate, and cleansed.
With 9 out of 10 businesses competing mainly on customer experience, it’s the organizations that take customer experience seriously that will stand out from the noise and win loyal customers over.
One thing is for sure, to deliver a positive experience, you have to know your customers better than ever before. This means creating complete customer profiles that help you understand and measure your customers’ behaviour at every touchpoint, and across multiple channels. Once you know your customers well enough, you can use that knowledge to personalize every interaction. Customers these days have more power and choices than ever before. Thus, you are responsible for understanding and acknowledging their needs.
If you make sure their interaction with your company is smooth, pleasant and continuously improving, you will drive brand loyalty. If not, you’ll give your competitors the best gift you can – your customers.