There’s no question that these are difficult times for businesses — especially when it comes to communicating with customers and prospects against a backdrop of disruption to personal and professional lives brought about by the COVID-19 pandemic.
With many businesses forecasting profit losses and bleak third and fourth quarters for the year, what can they do to try to mitigate against customer churn and maintain good client relationships? A data-driven solution to this customer relationship dilemma is one option that businesses have at their disposal.
A data improvement strategy for your CRM
According to research by Forrester, businesses that have developed a data-driven strategy to gather insights on customers are collectively on target to earn $1.8 trillion by 2021, so it clearly pays to get your data maintenance strategy right.
It’s only with the right data that businesses can target and communicate effectively with clients and customers in a way that’s relevant to them. After all, good data is the foundation of great customer experience.
It is a common misunderstanding among many businesses that data management is something that can be done periodically — like a once-a-year spring clean or an occasional spruce before an event. In reality, good data management is an ongoing activity that requires daily attention.
Who is in charge of data?
The onus of good data management is not something that falls on a select few people within an organisation. As great volumes of data are generated from every department, data governance teams should be made up of stakeholders from each area of the business. This way, decisions can be made with the input of subject matter experts across departments.
This cross-functional approach will ensure that the business is complying with all relevant regulations and industry standards, minimising the possibility of blind spots that can lead to business risks.
Make data management simple
Successful data management need not be complicated. Making it as simple as possible for your end-users to input and edit data will lead to better quality and integrity of your data. Simplifying the process also makes it more likely that best data practices will be adhered to.
As well as making the process easier, educating end users so they share an understanding of why these processes are critical to follow (and the implications of not following them) will encourage greater investment in achieving high quality data. This in turn will contribute to improved customer communications.
Using technology to automate data maintenance
Validity and Demand Metric’s State of CRM Data Management 2020 report found that 63% of the companies surveyed were using manual processes for CRM data maintenance. Instead of using these unreliable and time-consuming methods, businesses should make the most of the technologies that are now readily available to automate data maintenance processes efficiently and effectively.
Businesses should be wary though of leaving data maintenance processes entirely up to technology — it’s still necessary to train your teams to use these technologies to achieve the highest quality data and every employee should be invested in this outcome. Unfortunately, the DMA’s latest Marketer Email Tracker report found that 30% of organisations are not currently providing ongoing training for their teams — a figure that needs urgent redress if businesses are to genuinely improve their data management and quality.
Five steps to quality data
While technology is a necessary investment in order to improve customer communications, businesses should steer clear of products that claim to offer a single solution to all your data quality needs — such products do not exist. There are however various tools and technologies available that can be combined to get the results you want such as Validity Inc’s Demand Tools which manages duplicates, standardisation and record reassignments, alongside Validity Inc.’s DupeBlocker which prevents duplicates at the source.
Data governance teams should focus on five key steps to achieve the best data quality solution for the business.
When it comes to profiling, the data team can look for accuracy, whether the data is complete, and any inconsistencies in the data that may question whether the data is stored in the right location and if it is up to date.
Profiling is likely to have identified any areas that require standardisation, which is a process that allows the data to flow through the company and into the analytics in a logical sequence, where it can inform critical business decisions.
Without consistent management and prevention, duplicates will find their way into every CRM. Governance teams can help the business to define the parameters for what it considers to be duplicate records, and seek a flexible third-party tool that can be customised to merge duplicates according to these parameters.
Verification and enrichment
As data is constantly changing, businesses should entrust external sources to verify their customer data. Following a verification process, the customer data can be enriched with other key data points so the business has a better understanding of the customer needs in order to improve service and drive revenue.
Once the previous four steps are taken, monitoring is the final and the easiest step in a successful data-driven CRM strategy. Tools that automate the process of cleansing data can also be enlisted – providing dashboards and alerts that can help the business to track data anomalies.
If a business is truly committed to high quality data, it will ensure that it has a cross-functional data governance team that values and seeks out the best tools and technologies to achieve the goal of quality data. It will also ensure that these tools and technologies are supplemented by training and rigorous processes. With these robust systems in place, the business can expect to reap the benefits of more successful customer communications, and the prospect of improved revenue.By Tunc Bolluk, VP APAC at Validity