Jeff was the first Manager of Paid Search at Byte.com, a D2C telehealth competitor to Invisalign and Smile Direct Club. Byte used this multi-step sales process: 1) After seeing a Google ad, take eligibility quiz; 2) Buy $17.95 Impression Kit; 3) Return kit and see 3-D image of straightened teeth; 4) Purchase $2,100 aligner system from outbound sales rep.

When Jeff took over the account he inherited multiple Google campaigns that lost $4.5 million the prior year. In the Google ads platform he found the usual KPIs (CTR, CVR, CAC and ROAS), but he didn’t have back-end ROI data to inform profitability decisions.

Jeff’s first step was to audit the campaign structure. There he found reporting, tracking and attribution issues. He found duplicate keywords spread across multiple campaigns. He found targeting settings that were losing money.

To turn things around Jeff worked with the Analytics team and created a new campaign naming structure that flowed into new tools (MTA with Rockerbox and reporting via Tableau) that eventually reported ROI.

The new structure had three primary campaign criteria: Brand, Competitor and Product. Secondary criteria included campaign type (search, display, video), keyword match type, and country. Eventually he created and managed 30+ campaigns.

While the new naming structure was being tested, existing campaigns, ad groups, keywords, match types, ad copy and landing pages were analyzed. Those not returning positive ROAS were paused.

Jeff then created new campaigns, started A/B testing new copy, and created Excel spreadsheets to report on progress and spot anomalies. Seven months after taking over campaigns that lost $4.5 million in the prior year, Jeff’s new campaign structure generated $800K in revenue.

Over the next two years the paid search campaigns Jeff created and managed accounted for 27% of Byte’s total aligner sales. He generated 860,000 leads,166,340 impression kits sales, 50,439 aligner system sales, $120 million in revenue and $22 million in profit at ROI of 23%.

Jeff joined one of the country’s largest mortgage lenders and took over an inefficient paid search program. Over four years he grew monthly spend to $2M from $100K.

His success with one division led him to working with two more divisions. The workload on the subprime mortgage lending group required more eyeballs so the division staffed up and Jeff worked alongside the new team.

When Jeff managed the account the most expensive keywords bounced from positions 2-4. That enabled the team to maintain high lead volume at acceptable CPL levels.

Time on page data showed that ads in the first position had high abandon rates, compared to ads that appeared lower in the paid search results. Jeff surmised that people clicking on top position ads didn’t really know what they wanted when they hit the landing page and quickly returned to the search results.

One summer the subprime team managing the account noticed some weakness from our main competitor -- they were no longer in the top position on a high volume keyword.

Against Jeff’s advice, the team decided to hike bids and get to first position, where they stayed for the next three weeks. Compared to the prior month spend increased by 50%, quality lead volume only went up 10%, and cost per funded loan increased 66%, making that month highly unprofitable for the company.

Jeff worked briefly for an agency that had an international travel client. Upon taking over the account he audited the campaign structure, keywords, match types, ad groups and ad copy to learn what (or wasn’t) working.

To attain success Jeff has always followed the waterfall and tracked leads from inception to final sale. Unfortunately, the travel client had a 12-month lag to final sale, so he could only optimize based on CPL goals and platform KPIs visible in Google and Bing.

Once he cleaned up the existing campaigns and created efficient new ones, he started testing new campaign types and audiences. He began with display and then tested YouTube ads (versions of their DRTV spots). In past years with the old campaign structure, the client advertised from January to June because lead volume from July to December was too low and CPL too high.

With the new campaign structure and mix of paid search, display and YouTube, the Winter/Spring mix had generated higher lead volume at lower CPL than past years.

The client loved the Winter/Spring results and wanted to test in Summer/Fall, but didn’t want to commit to high spend levels.

Jeff then audited the campaigns again and developed a plan. Marginal campaigns, ad groups, and keywords would be paused. Only those that met a lower CPL threshold would stay live. With the new mix and a lower spend level in place, the Summer/Fall campaigns generated 2,500/month leads at 20% lower CPA than the Winter/Spring campaigns.