Billing. Marketing. Sales. Support. What do these enterprise-wide operating segments have in common? To be effective, they must be built upon accurate, complete and integrated data – the foundation of data quality.
With the increase in the ways customers and vendors want to communicate with the enterprise and the continuing globalization of commerce, organizations must manage a growing number of data sources. Companies are in the unenviable position of needing to ensure the accuracy of customer, prospect, partner, supplier and vendor information while having to integrate this data from different touch points.
Businesses have access to variables such as purchase history, inventory availability and lifetime value, offering them better information about their relationships. However, these measures are useful only if they are obtained from reliable and integrated data. For example, if a business is not merging customer purchase history from sales channels such as retail outlets, call centers and Web sites, these measures are of little use and can hurt future business decisions based on this information.
How does a business consolidate customer data from numerous operations? Take a clothing retailer. Whether a consumer buys goods via a physical store, the Web, mail order or call center, good data quality and integration practices enable the enterprise to cleanse and consolidate that data using name and address data or credit card information. It could also establish a positive buying experience for the customer by communicating not only that the items purchased are in stock, but that they will be delivered on a specific day or could be held at the nearest retail store for pickup later that day.
Since businesses understand that it costs more to acquire new customers than to retain existing ones, they like to introduce existing customers to additional products and services. Data quality makes the transformation from new customer to best customer much easier by, among other things, consolidating purchase history.
If a consumer buys a new suit in a company’s store, ties from its Web site and Italian wingtips via mail order, an offer for dress shirts is likely to generate a higher response rate than one for bermuda shorts. Retention, loyalty and satisfaction rates rise when offers are generated for goods and services that resonate with customers.
The previous example underscores the value of the accurate, single customer view. With a complete picture of the availability of products and services customers use across the enterprise, organizations can develop targeted marketing initiatives. This information is also valuable for informing your business partners and vendors when buying trends are detected, allowing for adjustments to maintain appropriate inventory levels.
By knowing where the customer is geographically as well as trends related to sales of goods from the stores near the customer, it would be easier for the business to direct that individual to the correct store. If the item the customer wanted to buy was unavailable in the nearest store, then by knowing the delivery schedule of your shipping vendor, you could estimate or even track where the goods are currently and accurately estimate a delivery time.
Data quality also reduces operational costs. Practices such as verifying address data ensure that goods and services are delivered quickly and accurately. Incorrectly addressed packages also are penalized by major carriers and have a costly effect on inventory and supply chain management.
Not only should businesses verify and consolidate customer data, they should enrich that information. In addition to comprehensive firmagraphic data, such as number of employees and revenue for business-to-business marketing, there is a variety of demographic and lifestyle intelligence that can provide greater insight into a customer or prospect. This information provides economic and socioeconomic details about the person’s household or neighborhood, such as age, income, occupation, education and household size. Developing marketing offers based on this intelligence leverages the business’s understanding of this customer.
Though these concepts seem straightforward, implementation of data quality strategies always appears easier than it actually is. However, qualified vendors can help you identify and maximize the quality and value of your enterprise-wide data.