Acme Data

𝟴 𝗪𝗮𝘆𝘀 𝗔𝗱𝗱𝗿𝗲𝘀𝘀 𝗩𝗲𝗿𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗣𝗮𝘆𝘀 𝗢𝗳𝗳

𝗥𝗲𝗮𝗹 𝗪𝗼𝗿𝗹𝗱 𝗗𝗮𝘁𝗮 𝗤𝘂𝗮𝗹𝗶𝘁𝘆 𝗜𝘀𝘀𝘂𝗲𝘀 - #𝟴 𝗶𝗻 𝗧𝗵𝗶𝘀 𝗦𝗲𝗿𝗶𝗲𝘀

When discussing data quality challenges with clients, they frequently identify address verification as a top priority. Below is a list of some of the many reasons they give.

• 𝗖𝗼𝘀𝘁 𝗥𝗲𝗱𝘂𝗰𝘁𝗶𝗼𝗻

Returned, lost, or redirected shipments come with a high cost. DPV (Delivery Point Validation), that comes with Data Studio’s address verification, ensures that an address is valid and has a mailbox that will receive mail.

• 𝗜𝗻𝗰𝗿𝗲𝗮𝘀𝗲𝗱 𝗠𝗮𝗿𝗸𝗲𝘁𝗶𝗻𝗴 𝗖𝗮𝗺𝗽𝗮𝗶𝗴𝗻 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗲

Ensuring that materials reach the targeted recipients, higher response rates are achieved as well as higher engagement.

• 𝗠𝗮𝗶𝗹 𝗗𝗶𝘀𝗰𝗼𝘂𝗻𝘁𝘀

CASS Certified, that comes with Data Studio’s address verification, is required to qualify for mail automation and bulk mail discounts.

• 𝗦𝗮𝗹𝗲𝘀 𝗧𝗮𝘅 𝗖𝗮𝗹𝗰𝘂𝗹𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗖𝗼𝗺𝗽𝗹𝗶𝗮𝗻𝗰𝗲

Address verification is crucial for accurate sales tax calculation and compliance. It ensures tax is calculated based on the precise, validated shipping address—required for destination-based taxing—preventing overcharging or undercharging customers and reducing audit risks.

• 𝗧𝗲𝗿𝗿𝗶𝘁𝗼𝗿𝘆 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁

Verified addresses allow for better, more detailed territory analysis and segmentation. It enables CRM systems to automatically route leads and accounts to the correct sales representative, ensuring fair distribution and optimal coverage while preventing ownership disputes between sales reps.

• 𝗞𝗻𝗼𝘄 𝗬𝗼𝘂𝗿 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿 (𝗞𝗬𝗖) 𝗮𝗻𝗱 𝗔𝗻𝘁𝗶-𝗠𝗼𝗻𝗲𝘆 𝗟𝗮𝘂𝗻𝗱𝗲𝗿𝗶𝗻𝗴 (𝗔𝗠𝗟)

KYC and AML are mandatory verification process used by financial institutions and other regulated businesses to prevent crimes like money laundering and terrorist financing. Identity verification, including address verification, is a key step in KYC and AML processes.

• 𝗜𝗻𝗰𝗿𝗲𝗮𝘀𝗲𝗱 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗥𝗲𝗰𝗼𝗿𝗱 𝗠𝗮𝘁𝗰𝗵 𝗮𝗻𝗱 𝗠𝗲𝗿𝗴𝗲 𝗥𝗮𝘁𝗲𝘀

Verified addresses have complete address data and follow a common format. By improving the completeness and consistency of address data, match processes that rely significantly on address data points have much higher match and subsequent merge rates.

• 𝗜𝗺𝗽𝗿𝗼𝘃𝗲𝗱 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 (𝗖𝗫)

CX is improved by eliminating frustration caused by failed deliveries. It creates a smoother, faster purchasing process that increases customer satisfaction and loyalty. It builds brand trust.

𝗗𝗮𝘁𝗮 𝗦𝘁𝘂𝗱𝗶𝗼 𝗯𝘆 𝗔𝗰𝗺𝗲 𝗗𝗮𝘁𝗮

Data Studio from Acme Data provides global address verification including DPV and NCOA, that integrates seamlessly with your enterprise applications and databases.

𝗜𝗳 𝘆𝗼𝘂 𝗰𝗼𝘂𝗹𝗱 𝘂𝘀𝗲 𝘀𝗼𝗺𝗲 𝗵𝗲𝗹𝗽 𝘄𝗶𝘁𝗵 𝗮𝗱𝗱𝗿𝗲𝘀𝘀 𝘃𝗲𝗿𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻, 𝗰𝗼𝗻𝘁𝗮𝗰𝘁 𝘂𝘀. 𝗪𝗲’𝗿𝗲 𝗲𝗮𝘀𝘆.

𝗜𝗻𝘁𝗲𝗿𝗽𝗿𝗲𝘁𝗮𝗯𝗹𝗲 𝘃𝘀. 𝗘𝘅𝗽𝗹𝗮𝗶𝗻𝗮𝗯𝗹𝗲 𝗔𝗜: 𝗪𝗵𝗼 𝗦𝗵𝗼𝘂𝗹𝗱 𝗬𝗼𝘂 𝗧𝗿𝘂𝘀𝘁 𝗳𝗼𝗿 𝗠𝗮𝘁𝗰𝗵𝗶𝗻𝗴?

𝗥𝗲𝗮𝗹 𝗪𝗼𝗿𝗹𝗱 𝗗𝗮𝘁𝗮 𝗤𝘂𝗮𝗹𝗶𝘁𝘆 𝗜𝘀𝘀𝘂𝗲𝘀 - #𝟲 𝗶𝗻 𝗧𝗵𝗶𝘀 𝗦𝗲𝗿𝗶𝗲𝘀

Many of our clients are large enterprises that deal with significant volumes of customer records, often millions. If you have a million customer records and a duplicate rate of 20%, that means 200,000 of your customer records are duplicates. Some simple math quickly informs you that it is cost prohibitive to match and merge that volume using only manual efforts.

What is needed, and what our customers require, is a system that can positively identify and automatically merge the largest number of duplicate records without user intervention. That is where AI comes in. We can use AI to positively identify the largest number of duplicate records that can then be automatically merged.

That takes a lot of trust. If the AI positively identifies 3/4 of the duplicates, and you trust the AI, that means that it will merge 3/4 of your duplicate records without any human supervision. In the case where the customer has 1,000,000 records and a 20% duplicate rate, and assuming they are all pairs, 150,000 of the 200,000 duplicate records will automatically be merged as non-survivors. 150,000 records will no longer exist. Get that wrong and there will be trouble.

𝗜𝗻𝘁𝗲𝗿𝗽𝗿𝗲𝘁𝗮𝗯𝗹𝗲 𝗔𝗜

In the world of AI, the concept of interpretability is a big deal. It means that users inherently understand a model's internal mechanics, that they comprehend the logic beforehand. Interpretable AI is built to be transparent from the start.

𝗘𝘅𝗽𝗹𝗮𝗶𝗻𝗮𝗯𝗹𝗲 𝗔𝗜

Explainable AI involves post-hoc techniques to explain black box model decisions after decisions have been made, after it merged your records. Black box is the opposite of transparent.

𝗟𝗮𝗯𝗼𝗿𝗶𝗻𝗴 𝗧𝗵𝗲 𝗣𝗼𝗶𝗻𝘁

• Interpretable = Transparency
• Explainable = Justification

Our customers do not want to have to justify their actions.

𝗖𝗮𝘀𝗲 𝗜𝗻 𝗣𝗼𝗶𝗻𝘁

A very large retailer built a duplicate detection engine using an AI algorithm provided by one of the “Big Three” cloud providers. This algorithm was purpose built for duplicate detection. They trained the model and ran the model against their database and found that the results were unusable. The algorithm matched many, many records that were not duplicates.

There were discussions about how the model would probably do better given higher volumes of data. Those discussions didn’t sway anyone and the company abandoned the model.

That’s when they called us.

𝗗𝗮𝘁𝗮 𝗦𝘁𝘂𝗱𝗶𝗼 𝗯𝘆 𝗔𝗰𝗺𝗲 𝗗𝗮𝘁𝗮

Our customers want to know why records are merged and they want to know before it happens. They want clarity around what the AI is doing, what decisions it is making and how the AI is making those decisions. Only then can they trust.

Data Studio’s AI is interpretable. It puts you in control.

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

𝗛𝗼𝘄 𝗮 𝗠𝗲𝗱𝗶𝗰𝗮𝗹 𝗖𝗼𝗺𝗽𝗮𝗻𝘆 𝗨𝘀𝗲𝘀 𝗔𝗱𝗱𝗿𝗲𝘀𝘀 𝗩𝗲𝗿𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝘁𝗼 𝗘𝗹𝗶𝗺𝗶𝗻𝗮𝘁𝗲 𝗥𝗲𝘁𝘂𝗿𝗻𝗲𝗱 𝗠𝗮𝗶𝗹 & 𝗕𝗼𝗼𝘀𝘁 𝗥𝗢𝗜

𝗥𝗲𝗮𝗹 𝗪𝗼𝗿𝗹𝗱 𝗗𝗮𝘁𝗮 𝗤𝘂𝗮𝗹𝗶𝘁𝘆 𝗜𝘀𝘀𝘂𝗲𝘀 - #𝟮 𝗶𝗻 𝗧𝗵𝗶𝘀 𝗦𝗲𝗿𝗶𝗲𝘀

One of our clients, a well known company in the medical space, had two rooms full of returned mailers. This was back when companies would send DVDs in the mail. People would call to inquire about the company’s specialized offerings, and the company would mail them a DVD. The DVD mailers cost about $8 each. The company did a good volume of business (they are global and number one in their space) and too often the packages were returned by the post office. This was because the “send to” addresses had problems.

The packages accumulated because reprocessing them took time and effort. They were stored in these rooms with the idea that the company would eventually reprocess them, but they didn’t like having rooms full of returned mailers.

That’s when they called us.

𝗦𝗼𝗹𝘃𝗶𝗻𝗴 𝘁𝗵𝗲 𝗣𝗿𝗼𝗯𝗹𝗲𝗺

The address information was entered by potential customers on the company website or taken over the phone by the company’s support reps. The data that was entered often had problems.

The solution was to implement Data Studio’s address verification in a way that addressed the whole problem. Working closely with the client, this is what we did:

• Implemented batch address verification to clean all the records in their CRM system (Salesforce)
• Implemented incremental address verification (running every minute) to keep them clean
• Configured real time address auto complete in their Salesforce screens and on their website

This multi-point plan ensured that every address was scrutinized for accuracy. Addresses are not only verified for accuracy, they are often corrected or enriched with accurate data.

And the address verification has additional features.

𝗗𝗲𝗹𝗶𝘃𝗲𝗿𝘆 𝗣𝗼𝗶𝗻𝘁 𝗩𝗮𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻 (𝗗𝗣𝗩)

This not only verifies that an address is correct, it also flags if the address has a mailbox that can receive a package. This was key to eliminating returned mail.

𝗡𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗖𝗵𝗮𝗻𝗴𝗲 𝗼𝗳 𝗔𝗱𝗱𝗿𝗲𝘀𝘀 (𝗡𝗖𝗢𝗔)

This automatically updates addresses for people and business that have moved.

𝗧𝗵𝗲 𝗥𝗲𝘀𝘂𝗹𝘁

The returned mail issue and the associated costs were entirely eliminated. And they converted more prospects into paying customers because virtually all of the prospects now received the promotional mailer.

𝗔𝗰𝗰𝘂𝗿𝗮𝘁𝗲 𝗔𝗱𝗱𝗿𝗲𝘀𝘀 𝗗𝗮𝘁𝗮 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗲𝘀 𝗛𝗶𝗴𝗵𝗲𝗿 𝗥𝗢𝗜

Data Studio, Acme Data’s data quality solution, provides global address verification that maximizes the value of your data. And it is implemented in minutes.

If the end users of your CRM, Analytics and AI systems rave about the quality of your data, you should stick with it. If not, contact us. We’re easy.