{"id":2134,"date":"2023-06-15T15:53:43","date_gmt":"2023-06-15T15:53:43","guid":{"rendered":"https:\/\/solutionsreview.com\/crm\/?p=2134"},"modified":"2023-08-08T21:02:09","modified_gmt":"2023-08-08T21:02:09","slug":"are-your-data-solutions-excluding-key-customers","status":"publish","type":"post","link":"https:\/\/solutionsreview.com\/crm\/2023\/06\/15\/are-your-data-solutions-excluding-key-customers\/","title":{"rendered":"Are Your Data Solutions Excluding Key Customers?"},"content":{"rendered":"

\"Are<\/p>\n

As part of Solutions Review\u2019s\u00a0Contributed Content Series<\/a><\/span><\/span>\u2014a collection of contributed columns written by industry experts in maturing software categories\u2014Olivia Hinkle, the Senior Product Marketing Manager at <\/span><\/span>Validity<\/span><\/span><\/a>, outlines how companies can ensure their data solutions don’t exclude essential customer data.<\/strong><\/em><\/p>\n

Customer data<\/a> is one of the most valuable assets your company possesses. This information helps make vital business decisions, create compelling marketing campaigns, and continuously inform improvements to your product suite. While data solutions will vary based on the size and complexity of your business, best practices surrounding data management should stay the same. <\/span><\/p>\n

Consistency, accuracy, and quality should always be top of mind. Organizations need dedicated individuals and technologies to curate and manage their proprietary data, or they’ll risk legal non-compliance and dissatisfied customers. Excluding key customers isn’t a shortcoming of the data solution you employ but the processes and governance you have in place. <\/span><\/p>\n

In today’s macroeconomic climate, all customers must be considered ‘key.’ But depending on how your organization defines <\/span>its<\/span><\/i> key customers, here are a few things to keep in mind to ensure you’re adequately building data best practices to meet everyone’s needs. <\/span>\u00a0<\/span><\/p>\n

Segment by Customer Demographics\u00a0 <\/span><\/b>\u00a0<\/span><\/h3>\n

Data needs and expectations vary widely based on company size, budget, industry, location, and other factors. Understanding the unique needs of each customer type will catalyze your efforts to build and implement best data practices within your organization. <\/span>\u00a0<\/span><\/p>\n

Larger companies typically have more complex data needs and higher expectations for data accuracy and analysis capabilities. They’ll likely require more advanced data management and analytics tools because they have an expansive volume of data. Secondarily, they also have more to lose if they get data collection, protection, and any resulting actions wrong.<\/span>\u00a0<\/span><\/p>\n

On the other hand, smaller companies often have simpler data needs yet fewer resources to manage them appropriately. These businesses are usually more focused on cost-effectiveness and ease of use rather than sorting through and protecting thousands of customers’ worth of data. <\/span>\u00a0<\/span><\/p>\n

Customers in different regions will also have differing expectations due to local regulations and technological infrastructure. Those in countries with strict data privacy laws may be more concerned about how their data is collected, stored, and used. Even your average consumer is worried about data privacy regarding SMS marketing. For example, <\/span>recent research<\/span><\/a> found that 96 percent of recipients wish companies were more transparent about how their data is used. <\/span>\u00a0<\/span><\/p>\n

Segmenting your data management practices by customer demographics will help you ensure you’re meeting everyone’s individual needs. But remember that ensuring you’re treating each customer equally\u2014regardless of variances in size, location, spending, etc.\u2014is only possible if the personnel responsible for a customer (i.e., Customer Success Managers) have access to clean and accurate data. <\/span>\u00a0<\/span>\u00a0<\/span><\/p>\n

Data Quality is King <\/span><\/b>\u00a0<\/span><\/h3>\n

It’s impossible to execute on the vast majority of business functions without clean, accurate data. Trustworthy CRM data, for example, is vital to the success of any business. Yet <\/span>research<\/span><\/a> shows 95 percent of survey respondents report having data quality issues that seriously impair their ability to leverage their CRM fully. This illuminates a concerning disconnect between the significance we place on data cleanliness and our efforts to maintain it. <\/span>\u00a0<\/span><\/p>\n

Data quality is king. Running a report on the top 50 customers by revenue or the top customers in a given region or industry requires accurate data to run said reports. Attempting to run a promotion or campaign to the top ‘n’ customers in any given sector is impossible if some accounts have missing segmentation attributes like Industry or Company Size. <\/span>\u00a0<\/span><\/p>\n

Deploying data quality tools can help pick up the slack by identifying anomalies and automating their remediation. But technology can only treat the symptoms of poor data management rather than the root cause. Some actionable steps your business should take now to improve data quality include:<\/span>\u00a0<\/span><\/p>\n