Acme Data

𝗛𝗼𝘄 𝗬𝗼𝘂 𝗖𝗮𝗻 𝗠𝗲𝗮𝘀𝘂𝗿𝗲 𝘁𝗵𝗲 𝗩𝗮𝗹𝘂𝗲 𝗼𝗳 𝗬𝗼𝘂𝗿 𝗗𝗮𝘁𝗮 𝗤𝘂𝗮𝗹𝗶𝘁𝘆 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻

𝗥𝗲𝗮𝗹 𝗪𝗼𝗿𝗹𝗱 𝗗𝗮𝘁𝗮 𝗤𝘂𝗮𝗹𝗶𝘁𝘆 𝗜𝘀𝘀𝘂𝗲𝘀 - #𝟱 𝗶𝗻 𝗧𝗵𝗶𝘀 𝗦𝗲𝗿𝗶𝗲𝘀

Our customers want to know exactly what value they are getting out of Data Studio, Acme Data’s data quality solution. They want specific metrics, nothing vague.

𝗢𝗻𝗲 𝗠𝗲𝘁𝗿𝗶𝗰 𝗧𝗵𝗲𝘆 𝗪𝗲𝗿𝗲𝗻’𝘁 𝗦𝘂𝗿𝗲 𝗢𝗳

• 𝗜𝗻𝗰𝗿𝗲𝗮𝘀𝗲𝗱 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗦𝗮𝘁𝗶𝘀𝗳𝗮𝗰𝘁𝗶𝗼𝗻 – While they could do surveys or measure NPS, or hear anecdotal information from employees, they found it difficult to directly attribute higher customer satisfaction to higher quality data. While that might seem inherently true, it might have limited value when trying to justify a purchase.

𝗠𝗲𝘁𝗿𝗶𝗰𝘀 𝗧𝗵𝗲𝘆 𝗗𝗶𝗱 𝗟𝗶𝗸𝗲

o 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗲 𝗥𝗮𝘁𝗲𝘀: While they found it difficult to attribute more sales to higher quality data, they could definitively measure response rates from campaigns before and after data cleansing.
o 𝗣𝗼𝘀𝘁𝗮𝗹 𝗖𝗼𝘀𝘁𝘀: They were able to measure the money saved on postage and physical mail by not mailing to undeliverable or duplicate records
o 𝗖𝗮𝗹𝗹 𝗛𝗮𝗻𝗱𝗹𝗲 𝗧𝗶𝗺𝗲: One customer measured that our accurate and reliable “search before create” reduced their average customer support call handle time by 45 seconds (at 3 million calls per year)
o 𝗗𝘂𝗽𝗹𝗶𝗰𝗮𝘁𝗲 𝗥𝗲𝗰𝗼𝗿𝗱 𝗦𝘂𝗽𝗽𝗿𝗲𝘀𝘀𝗶𝗼𝗻: The number of “search before create” calls that found an existing record that was selected as opposed to creating a new one
o 𝗥𝗲𝗰𝗼𝗿𝗱𝘀 𝗠𝗲𝗿𝗴𝗲𝗱: The number of duplicate records merged
o 𝗔𝗱𝗱𝗿𝗲𝘀𝘀𝗲𝘀 𝗩𝗮𝗹𝗶𝗱𝗮𝘁𝗲𝗱: The number of addresses validated against the USPS, Canada Post and global address databases
o 𝗗𝗲𝗹𝗶𝘃𝗲𝗿𝘆 𝗣𝗼𝗶𝗻𝘁 𝗩𝗮𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻 (𝗗𝗣𝗩) 𝗥𝗮𝘁𝗲: The number of addresses positively identified as having a mailbox that would accept mail
o 𝗠𝗶𝘀𝘀𝗶𝗻𝗴 𝗔𝗱𝗱𝗿𝗲𝘀𝘀 𝗖𝗼𝗺𝗽𝗼𝗻𝗲𝗻𝘁 𝗙𝗶𝘅 𝗥𝗮𝘁𝗲: The percentage of records where missing data (e.g., apartment numbers, ZIP+4) was appended
o 𝗜𝗻𝘃𝗮𝗹𝗶𝗱 𝗔𝗱𝗱𝗿𝗲𝘀𝘀 %: The number of addresses deemed invalid by postal data
o 𝗨𝗽𝗱𝗮𝘁𝗲𝗱 𝗠𝗼𝘃𝗲𝗿 𝗔𝗱𝗱𝗿𝗲𝘀𝘀 %: The percentage of records that matched against the 48-month NCOA database of moves

That’s a lot of metrics and there are more.

They like being able to see these statistical totals and percentages, the month to month trends (going up or down), as well as the effects on new data being entered.

This information can help you justify an initial data quality purchase or maintain an existing one.

𝗜𝗳 𝘆𝗼𝘂 𝗰𝗼𝘂𝗹𝗱 𝘂𝘀𝗲 𝘀𝗼𝗺𝗲 𝗵𝗲𝗹𝗽 𝘄𝗶𝘁𝗵 𝗱𝗮𝘁𝗮 𝗾𝘂𝗮𝗹𝗶𝘁𝘆, 𝗰𝗼𝗻𝘁𝗮𝗰𝘁 𝘂𝘀. 𝗪𝗲’𝗿𝗲 𝗲𝗮𝘀𝘆.