Data Integrity Audit & QA – GA4, Adobe Analytics, Piwik Consulting – Data Analytics Consulting NY Indexable Analytics

Quality Assurance Audit your Analytics Data for Accuracy, Completeness, and Quality, Trust your Data

Second (expert) set of eyes to QA your data
Troubleshoot, problem-solve, document and work through data issues
Work with vendors as a team to ensure data is flowing
Avoid gaps in tracking skew your data and make bad advertising budget decisions

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Google Analytics 4, Adobe Analytics & Piwik Audit Service

Audit of account, property, data stream, conversions, dimensions, etc
Ensure important events and custom attributes are being sent to analytics tool from the tag manager, matching the measurement plan
Product linking validation (BigQuery, Google Ads, Search Console, etc)
Proper currency, data retention, timezone, etc are set correctly
User management and governance
Campaign tracking following a set standard

Google Tag Manager and Adobe Tags Audit and Debugging

Path to completion, funnel step QA
Resolve there are no data gaps
E-commerce cart process testing
Ensure tag presence either site wide tags or specific points of conversion
Check for data leaks (ie former vendor tags still firing or tag piggybacking) as well as inflated counts caused by duplicate tags
Ensure tag and page load times are kept to the minimum

Web Analytics QA Debugging Services New York

Step by step debugging of processes such as add-to-cart all the way to purchase or other conversion funnel steps to ensure all tags and variables are firing as expected

Data Stewardship Audit Case Study

How our data debugging service helped our client determine the results a vendor was delivering where millions of dollars were spent in activation.

The client received a report by a programmatic vendor claiming a relatively large number of conversions to which the client wasn’t sure and called us to run a third party audit as the internal analytics team ran out of ideas to test, also it is a good measure that a second independent set of eyes review, it’s best practice in big corp analytics.

The client needed to confirm to which channel to give attribution, therefore invest marketing dollars and this was a critical moment as the client was about to sign for renewal with this programmatic vendor.

Our Analytics Troubleshooting Process

Established our Role in the Analytics Audit Process

We acted as data steward for the client, we attended all meetings and drove the conversation which included business and technology context, working with internal analytics teams as well as vendors, that involved testing and documenting results.

Tested Analytics Attribution Using Campaign Parameters

We sent test traffic to site using vendor URL and attaching test UTM parameters to identify the test traffic in GA4, landed on the page and performed the specific action such as filling out a contact form

Got Data Count Benchmarks

Since we had vendor pixels in GTM for TTD and DCM on specific events, we asked for a report of counts from the vendor interface both for TTD and DCM Floodlight respectively. We also asked for URLs to test that would not inflate counts.

Shared Analytics Audit Results

The result of our test, 10 out of 10 attempts, the test pass, ruling out GA4 failing to attribute conversions to TTD.

This confirmed that GA4 wasn’t somehow just ignoring or sending TTD traffic to another channel (such as direct or hidden somewhere else). With this test also we gained more confidence that GA4 was tracking correctly helping employees trust more in the data and use it.

Bonus Deep Dive Analytics QA Findings Not Directly Related to Initial Request

When cross inspecting GA4 (client) vs the DCM and TTD (reports shared by the vendor) we noticed that TTD had what it looked like inflated amounts in the purchase dimension that exactly matched what was recorded in GA4 and DCM with a pattern to multiply by 3 therefore inflating purchase counts by a lot.

We also noticed that big ticket purchases in amount ($25K +) were being attributed to referring domains that may not make a lot of sense given the context and there were many of them

What our Analytics QA and Troubleshooting Deliverable Meant to our Client

We delivered documentation showing the discrepancies across tools and with that information empowered the client giving leverage in negotiations as was able to get a significant amount of credits for the dubious conversions. Also after the analytics audit and conversation the vendor showed improvement in the context and site authority where the ads were displayed.

Our work resulted in less false leads, less revenue attributed to the channel and better exposure to relevant websites to show ads.

Need help with analytics audit, QA and troubleshooting?

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