Poor data quality is frequently the cause of negative experiences for customers, leads and employees!
What Defines Bad Data?
Consumers produce vast amounts of data every day through their interactions with brands’ websites, apps, service centres and chat servers. Recent research has revealed that every single person creates 1.7MB of data every second, and humanity produces 2.5 quintillion bytes of data every day!
With so much information being produced, how can brands ensure they’re not collecting bad data?
Note: bad data is not only a problem for brands interested in improving their CX, it also directly influences ROI and in 2017, Gartner estimated that inferior data costs brands $9.7 million per year.
So what exactly is “bad data”? It is any and all data that is unstructured, inaccurate, inconsistent, incomplete or contains duplicate information. Ultimately, all data that brands collect comes from various channels, many of which are siloed, and much of the data comes in varying formats or from different databases. Alternatively, we also have data that is more random and not formatted, with no consistency, and which must be collected in a structured, consistent way for it to ever be useful.
As humans, we personally collect data everyday through our feelings, memories and impressions but for businesses this “worldview” exists through data and the insights and intelligence derived from it. However, the challenge is that raw data is often a transient resource and can be extremely messy without the proper expertise to understand and interpret it into actionable insights (i.e. turning “bad data” into “good data”.)
What is the Problem with Outdated Data?
Although it may seem trifling, data that is old/outdated is often worse than bad data and businesses that try to utilise outdated data to inform their decisions will be doing themselves and their customers a disservice.
For Example: Consider what consumer behaviour would have looked like in 2018 and then flash-forward to 2022, the market (especially post-COVID-19) looks quite different.
For instance, many shoppers today purchase their products online and utilise click and collect services — or have them delivered directly to their door. Additionally, customer demographics are forever and quickly changing (e.g. people change their name, address, age, marry, have children, switch jobs, get promotions, adjust their income level, education level) and inherently, all of these factors will change consumer behaviours.
This is why it is so important to frequently gather consumer insights, as it directly enables businesses to have data that will help to diversify and grow their business and income streams.
Costs of poor-quality data:
- Reputational damage: This can range from small, everyday damage to large public relations disasters.
- Missed opportunities: A company may miss a critical opportunity for new product development or customer need that a competitor with a more mature understanding of data may capitalise upon.
- Lost revenue: Poor data can lead to lost revenue in many ways (e.g. communications that fail to convert to sales because the underlying customer data is incorrect)
What is the Solution?
Obtaining actionable insights is one of the primary goals of collecting and utilising “good data”.
However, keep in mind, it was found that the annual cost of poor-quality data is over $3.1 trillion dollars in the US alone (IBM).
Why? We find that fragmentation typically occurs because most businesses are sifting through all their data without professional assistance, which can be extremely difficult, and key information is often missed.
Here at HOED Research, we have the expertise and advanced technology combined, which ensures that we’re only gathering the best information that can be reported on and seamlessly transformed into actionable insights. Providing you, the client, with everything you need to action change that will contribute to the improvement of products and services to enhance sales, achieve KPI’s and deliver a greater ROI.