Source Ortho’s Challenge: Paid Search Data Mining

Does this sound familiar:

1. You  have cost of goods that varies widely by SKU
2. You have healthy growth that is dependent on paid marketing acquisition (AdWords, social)
3. You have a mix of online and offline customer acquisition/sales (e.g. orders taken over live chat, phone etc)

Ortho was in search of a highly customized report for managing marketing campaigns by SKU and enlisted Elevar to help.

Google Analytics Audit

A Google Analytics audit allows Elevar to move quickly in implementing data foundation fixes along with our advanced analytics and reporting improvements.

Attribution is key when making profit-driven marketing decisions. We quickly diagnosed referral issues that were causing inaccurate attribution.

Some referrals were from third party payment systems – Affirm and PayPal – but we also discovered an out of place AdRoll referrer that was affecting AdRoll and our client’s attribution paths.

These issues were quickly resolved by updating the Referral Exclusion list in Google Analytics.

Trust Your Data

When first approaching us, the team at Source Ortho didn’t fully trust their Google Analytics data, but understood the importance of accurate data. Especially if we were going to move in the direction of net profit margin by SKU driving paid search spend decisions.

Once again, we used Elevar to automate the analysis of common reporting discrepancies for channel reporting in Google Analytics.

Specifically we found:

• Blog traffic (i.e. organic) was not recording accurate pageviews
• Email traffic was not tagged with medium & source parameters so they were being bucketed into “Direct”
• The dreaded (Other) default channel was loaded with traffic and revenue that belonged elsewhere

Once we cleaned up our channel attribution reporting then we were able to surface conversion optimization opportunities and A/B test improvements within specific channels.

Data Mining and Custom Reporting

Our challenge was to find a way to:

1. Fetch transaction data from BigCommerce to act as our master revenue source (due to the amount of offline orders placed without being pushed into Google Analytics)
2. Fetch cost of goods data per SKU
3. Fetch paid search cost by keyword
4. Merge these together to provide a row by row net margin % report by SKU

Not an easy task when we had to match unique product IDs used in AdWords to SKUs from Google Analytics and BigCommerce – all of which used different product identifiers.

What made this challenge unique was a set of products and customer types that deferred to placing orders via phone or email instead of online.

This is why looking at just AdWords and Google Analytics reports didn’t tell the whole story.

Ultimately we were able to compile all of the data sources into a single Elevar report that contained:

1. Product Parent Name
2. SKU
3. Product ID (from AdWords)
4. Qty Sold
5. Product Revenue
6. Total Product COGS
7. AdWords cost by SKU
8. 3% operating cost
9. Net Profit
10. Profit Margin
11. % of Search Impressions

This unlocked a plethora of actionable insights that were implemented across marketing campaigns. Spend was cut on poor performing products while budgets and bids increased on those that had more opportunity.

Now that we have a key reporting process setup for managing effective marketing campaigns, we’ve moved on to landing page optimization testing using Google Optimize to further our return on ad spend (ROAS) gains.

Interested in learning more about Elevar’s solutions? Book a call with us today!