Question

What obstacles exist to customer loyalty and how might they be removed?

Answer 1

Too many data collection channels could lead to several disparate customer sources, poor data quality, and an overwhelmed data crew.

To solve for multiple data collection channels, think about centralizing your data collection management methods by appointing a go-to data handler and systematizing your data collection strategy across departments. Your data handler can be the point of contact for data collection, ensuring data quality practices are upheld while focusing on the long-term goal.

Poor contact data

Your first challenge with loyalty programs: Get the customer to sign up. Factors such as the amount of time it takes to enter in their information and how personal the information required is, all impacts the consumer’s willingness to sign up. Not enough customers signing up understandably results in a more difficult time reaching these customers. However, sign ups mean zilch if contact data is inaccurate, as that also results in the inability to reach customers.

Solution: Implement a data quality solution. Our latest Global data management report found that the biggest ways poor data quality impacts retailers are wasted resources (45%), damages the reliability of analytics (39%), and negatively impacts reputation (35%). Whether you want to use data quality for predictive analytics to optimize consumer experience or implement a data cleansing tool, like address or email verification, taking control of your data will equip you with actionable and real-time insights.

3. Not having a data-driven culture

There is a sharp correlation between increased company profits and the amount of data quality solutions that are put in place. Not emphasizing data quality in your business can cost you far-reaching consequences, such as customer engagement, loyalty, and revenue.

Solution: Data quality should be prioritized as a key business focus. Loyalty programs need to be built on a solid foundation of data, but what does a good data foundation look like?

• Cleaning your existing data.
• Consolidating and deduping records.
• Ensuring newly collected data is accurate before it enters into CRM and other systems.

Reliable, clean data represents an opportunity to better understand your customers, drive actionable insights and optimize customer or prospect experience. When loyalty programs are the key to increasing revenue, customer retention, and lifetime value, you want to make sure your data quality initiatives are up to par.