Getting to a better customer on-boarding experience. An Experian Data Quality White Paper
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1 Getting to a better customer on-boarding experience An Experian Data Quality White Paper
2 Introduction Successful customer on-boarding is a critical task for all energy providers. While there are numerous steps as well as state regulations to consider in the process, certain components are consistent across the country. Regardless of location, all energy providers capture three critical elements of contact data: 1. The service address where the customer has or wants service 2. The mailing address for billing, voluntary disconnects and other communications 3. The address for e-billing and e-communication initiatives Finding a service address Energy companies are challenged with determining if a potential customer s address falls within their footprint. Whether the customer enters their address directly via self-service or provides the information to a care agent, one of two things occurs: 1. The customer s address is determined to be within the utility s footprint 2. The customer s address does not appear to fall within their footprint Small errors when an address is entered can mean big problems during customer on-boarding. In fact, human errors are behind a significant percentage of instances where a customer or care agent runs into a failure to locate. An example would be mis-hearing a customer over the phone or mis-keying a street name. The overall quality of service address data can reduce the likelihood that you will find the address needed for the transaction at hand, impacting conversionrates. Additionally, the delay in searching or re-querying service address data increases average handle time, which significantly impacts customer satisfaction. Example 1: Example 2: Example of abbreviation errors that derail on-boarding efforts: Str versus Street versus ST. Example of mistyping errors that derail onboarding efforts: Whichwood Rd versus Wychwood Rd
3 Industry benchmarks According to my clients, up to 50% of their customers fail at starting service via self-service. They also find that up to 70% of those failures are due to the customer not being able to find their service address. Without a robust search-and-match tool in place, energy providers cannot expect to find the right match within their footprint. Ultimately, an individual will only attempt to input an address a few times before giving up, meaning human error plays a critical role. Overall data quality is an increasing priority for almost all utilities I interact with. Whether it s the incorrect capture of and USPS mailing address during the on-boarding process or simple account updates--bad data leads to numerous operational inefficiencies. Some examples of these inefficiencies include failed or delayed truck rolls, returned mail, increased call center volumes, increased average handle time and a generally poor customer experience. The actual dollar cost of these issues can be significant. Consider USPS mailing address errors as an example. We find that on average 3-5% of all mail being sent monthly is somehow inaccurate. A simple calculation below highlights the average cost associated with address errors. The operational costs associated with on-boarding 1,500,000 customers x 3% incorrect mailing addresses = 45,000 x 20 average communications per year = 900,000 x.40 avg. print and post cost = $360,000 in operational costs Our clients also cite significant revenue implications through voluntary disconnects. In this instance, the rate of error compounds because the agent or customer could be entering an address for an area of the country with which they are not familiar. Clients have reported as high as 12% of their final billing addresses are inaccurately captured. These customers represent low-hanging fruit within the collections space. They call to provide a forwarding address, showing a desire to pay off any final fees. However, address errors collected during these interactions lead to a loss or delay in revenue collection. The chart below highlights one such example. The revenue loss associated with address errors 1,500,000 customers x 15% average churn = 225,000 x 8% of final addresses incorrectly captured = 18,000 final bills with incorrect addresses x $200 average final bill = $3,600,000 lost or delayed revenue x 5% minimum impact from data quality = minimum of $180,000 in lost revenues
4 There is a solution Traditionally, utilities believed that these challenges were simply a cost of doing business. But they no longer need to be. My clients utilize a suite of products that support a comprehensive customer on-boarding and off-boarding solution. The list below highlights how they have significantly surpassed return on investment goals. Enable more customers to find their service address faster and on the initial search via self-service Enable care agents to more efficiently search service address data and find what they need, when they need it Significantly reduce call center volumes related to customers who cannot locate their serviceable address Significantly reduce handle time by allowing care agents to instantly find relevant information they need for the call they are currently trying to complete (they should be able to find every address in a footprint in less than 15 keystrokes, even with minimal information from a customer) Improve the customer experience by driving first-contact resolution, through accurate contact data capture including significantly fewer issues with service address lookups, increased success rates of initial on-boarding communications and first bill delivery Increased revenue through more accurate final bill data capture during voluntary disconnects
5 Making an impact Experian Data Quality software matches against an energy providers existing service address database in real time, allowing fast identification of existing premise addresses by a customer or care agent during on-boarding. Additionally, the software quickly validates and standardizes and USPS postal mailing addresses at the point of capture. To ensure the correct and efficient entry of customer information, I recommend the following functionality: Search and match Address validation validation As each customer or care agent enters a service address into a.com or CIS application, search-and-match functionality will help to query the energy provider s own local service address database using fuzzy matching. This type of matching is outside of normal searching capabilities, allowing for typos, phonetic matching, misheard or misspelled words, discrepancies between street abbreviations and much more. The tool will instantly begin returning results from the service address database which match what the customer/agent is typing. Only matches from the energy provider s footprint will be surfaced during the search.
6 Once a single premise address selection is made, Experian Data Quality s solutions ensure that the premise address is valid according to the USPS. If there is a discrepancy, we will either automatically fix the error for mailing purposes or flag the issue to the end user for resolution (in cases where interaction is required.) When the customer or care agent enters their address, we immediately invoke real-time validation and determine the validity of the , fixing typographical errors and ensuring the inbox is active. Within this process, we use a proprietary method to perform an SMTP check with that actual mailbox to determine deliverability. Finally, in the event that a customer or agent selects to enter new billing address, or in the case of a voluntary disconnect, Experian Data Quality s tools validate the customer s address as it is typed. This functionality uses our type-ahead technology while searching the USPS database. Once the customer or agent selects an address, the validated address will populate into the correct address form fields.
7 About Experian Data Quality Experian Data Quality is a global leader in providing data quality software and services to organizations of all sizes. We help our clients to proactively manage the quality of their data through world-class validation, matching, enrichment and profiling capabilities. With flexible software-as-a-service and on-premise deployment models, Experian Data Quality software allows organizations around the world to truly connect with their customers by delivering intelligent interactions, every time. Established in 1990 with offices throughout the United States, Europe and Asia Pacific, Experian Data Quality has more than 13,500 clients worldwide in retail, finance, education, insurance, government, healthcare and other sectors. For more information, visit edq.com, or call (888)
8 Experian Data Quality 125 Summer Street, Suite 1910 Boston, MA edq.com Intelligent interactions. Every time Experian Information Solutions, Inc. All rights reserved. Experian and the Experian marks used herein are trademarks or registered trademarks of Experian Information Solutions, Inc. Other product and company names mentioned herein are the property of their respective owners. Month 2014
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