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A-Team Insight Blogs

The Perils of Inaccurate Data Capture

By Russell Jones, CEO, Fetchify (specialising in SaaS address lookup and data validation solutions).

Inaccurate data can be damaging to all aspects of a business. In a 2018 survey, Gartner reported that organisations are negatively impacted by poor quality data, resulting in wasted resources and unnecessary costs to the tune of $15 million annually.

Poorly captured and managed customer data impacts the entire lifecycle of the online user experience, filtering through marketing, customer registrations, ordering, payment completion, shipping, and ultimately customer service. For the business, it has a negative impact on resources and budgets, as well as leading to a whole host of regulatory implications. The 2018 Data Protection Act and Consumer Protection legislation now dictates that businesses must not only capture but manage, store, retrieve and routinely cleanse their customer data. This adds to a compelling and growing list of reasons for businesses to invest in high quality data capture technology; as not only does failure to do so lead to loss of customers, but a breach of legislation can carry fines of up to 4% of an organisation’s annual turnover.

A concerning perception remains that the Information Commissioner’s Office (ICO), will only target large companies for breaches of compliance, a perception which often prejudices the decision for smaller companies to act swiftly. Larger companies may also find that the uncertainty around the exact requirements and the potential scope and implementation costs of solutions can seem a greater expense than the penalties of non-compliance. Unfortunately for such businesses, money is not the only cost of falling foul of the ICO.

The size, structure and developmental ethics of a company will greatly affect the adoption of any new technology or process. Smaller companies with fewer employees will tend to prioritise marginal gains and efficiencies using tools like auto address lookup to minimise the time cost of poor address data in areas such as customer service and redeliveries. These companies are also more likely to have lower proportional spends on marketing and tech development, as well as a more agile decision-making hierarchy. This means they can condense a MoSCoW (Must have, should have, could have, would have) analysis into a single conversation and implement a solution like Fetchify using internal resources in as little as half an hour.

Larger companies, on the other hand, where any new process or technological implementation requires a proposal, solid business case and perhaps even external resources, such as a web development agency, can take exponentially longer to adopt new solutions, assuming the proposal is successfully allocated budget. Even in those companies where development strategy works on an Agile methodology, initial approvals can run into months. All the while more and more poor-quality data is accumulated, customer service teams defend the walls from an onslaught of annoyed customers and marketeers labour to increase their email deliverability stats and maintain their 4 stars on TrustPilot. How then do companies protect themselves effectively, within a budget?

Whilst implementing new technology might be overwhelming, businesses can start out simply by mapping all the ways in which they capture, store and use customer data, as well as all the types of data they hold and how that data is then deployed. This process will highlight how and where poor data is impacting the business and its customers. In our experience, the most common point of failure is where the data is initially recorded. This is why data validation solutions, which do not cost a company as much as they might think, not only save time and money, but add significant long-term value to the customer journey.

With virtually immediate effect, businesses can expect to see fewer failed deliveries and customer complaints and a reduction in associated costs. In the longer term, greater engagement, legal compliance and the potential for better data analysis should follow and can lead to more targeted activities such as expansions, events or marketing into new territories. Ultimately, better data leads to better services and greater growth opportunities. No business should turn their nose up at that.

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