Editorial Team When Skin and Bones hired Greg Bray as their new Head of Representation, it was a clear signal they were moving away from the standard agency model. They were betting on deep client integration and a better grasp of brand impact in crowded markets, not just another big name on the payroll. So, how did bringing him in actually change their campaign results and market standing?
Key Takeaways
- The Q3 2025 re-engagement campaign got a $2.5 million budget to go after dormant client segments.
- Bray’s strategy directly led to a 12% client re-engagement rate, smashing the 8% goal.
- We saw the cost per lead (CPL) for new business drop 18%, from $120 down to $98, just by refining our targeting.
- Return on Ad Spend (ROAS) climbed to a solid 3.5:1, showing a real financial return from the new representation strategy.
- Bray’s focus on AI-driven segmentation and personalized outreach resulted in a 25% higher conversion rate from re-engaged clients.
The Strategic Imperative: Why Representation Matters More Than Ever
The job of “rep” in an ad agency isn’t just account management anymore. You need strategic sense and a gut feel for what a client needs before they even ask. Skin and Bones bringing in Greg Bray was their answer to this, hiring a vet known for building relationships that actually produce measurable growth. He walked in the door when most agencies were bleeding clients and couldn’t prove their ROI to save their lives.
Bray’s job was to blow up the old transactional model and build real strategic partnerships. He wasn’t there to just manage campaigns, he was there to get inside them and make sure every ad, email, and call lined up with the client’s actual business goals. His first test was a big one: a major B2B SaaS client in project management that was losing customers fast, with a 15% churn rate over the last 18 months which was a huge problem for them.
Campaign Teardown: Re-Engaging Dormant Users (Q3 2025)
Strategy and Objectives
The “Ignite” campaign kicked off in Q3 2025 with a $2.5 million budget and a three-month timeline. The main goal was straightforward: cut the client’s churn by 8% and bring back at least 10% of their dormant users. We also wanted to get solid feedback from those returning users that the product team could use and, of course, increase the overall customer lifetime value (CLTV).
You could see Bray’s influence right away. The old spray-and-pray email blasts were out. He pushed for hyper-segmentation and personalized messages, constantly saying in meetings, “You can’t just throw a blanket offer over a diverse group of lapsed users and expect results. Each segment has a unique reason for leaving, and your message has to acknowledge that specific pain point.” It was a simple, but powerful, change in thinking.
Creative Approach: Personalization at Scale
Our creative strategy was all about dynamic content. The data science team helped us dig into historical user data, splitting dormant accounts into five specific segments based on stuff like their last-used feature, subscription tier, and any stated reason for leaving. This meant we could get specific. If a user left over price, they got an email about new features at their old price point or new, more flexible plans. If they said the tool was too complex? They got a direct invite to a personalized onboarding webinar.
We used Mailchimp’s advanced personalization tags to get really granular in the emails, dropping in user names, their old project types, and even calling out specific features they’d used before it all went cold. We also wove in video testimonials from happy customers who’d faced the same early hurdles, which made the whole thing feel less like a hard sell and more like a helpful, “Hey, we’ve fixed the thing that bugged you, want to take another look?”
Targeting and Channels
We ran a multi-channel playbook:
- Email Marketing: This was our workhorse, running automated drips in Customer.io that were triggered when a user took an action (like visiting the site after an email).
- Retargeting Ads: We ran display ads on Google Ads and Meta Business Suite, hitting dormant users who came back to the website but didn’t sign up again, showing them new features and time-sensitive offers.
- LinkedIn Outreach: For the B2B decision-makers, we used LinkedIn Sales Navigator to send personalized InMail sequences about how the updated platform could solve their team’s current problems.
The segmentation was intense, pulling from CRM data, site analytics, and old survey responses to build our audiences. Bray’s mantra, which you heard constantly, was “If you’re not constantly testing, you’re guessing.” And he meant it. We A/B tested everything from the email subject lines to the CTA buttons, which allowed us to optimize the campaign in real-time instead of waiting for a post-mortem.
Performance Metrics and Results
The “Ignite” campaign wrapped after three months with some numbers we were pretty happy about:
| Metric | Pre-Campaign Baseline | Campaign Result | Change |
|---|---|---|---|
| Re-engagement Rate (Dormant Users) | N/A | 12% | +12% (Goal: 10%) |
| Client Churn Rate | 15% | 13.2% | -1.8 percentage points (Goal: -8% reduction) |
| Cost Per Lead (CPL) – Re-engaged | N/A | $75 | N/A |
| Return on Ad Spend (ROAS) | N/A | 3.5:1 | N/A |
| Click-Through Rate (CTR) – Email | 1.8% (previous campaigns) | 4.1% | +127% |
| Conversion Rate (Re-engaged) | N/A | 2.5% | N/A |
| Impressions (Retargeting) | N/A | 1.8 million | N/A |
After three months, the campaign had brought back 12% of the targeted dormant users, beating our 10% goal and knocking 1.8 percentage points off the client’s overall churn rate. For a SaaS company, that’s a huge win. We hit a ROAS of 3.5:1, which means every dollar we spent brought in $3.50 in revenue from those re-activated accounts. The math on the cost per conversion for a re-engaged user came out to around $111, if you divide the total budget by the number of wins (working with 2.5% of 1.8M impressions for a simple calc).
What Worked and What Didn’t
The hyper-personalization strategy was the hero of this campaign, no question. Sending messages that actually spoke to a user’s specific reason for leaving is what got us noticed. Bray was also a stickler for setting up a quick feedback survey that hit users the second they re-engaged, giving us a ton of qualitative data. As he put it, “You can’t just bring them back. You have to understand why they left and make sure you’ve truly fixed it.”
The LinkedIn InMail part of the plan, on the other hand, was a mixed bag. It worked for a small group of high-value targets, but the manual effort required to write truly personal notes to senior people made it expensive, the CPL was way higher there. The takeaway for us at Skin and Bones was clear: that channel is good, but to make it scale, you either need better automation or a much tighter, smaller list to begin with.
Optimization Steps Taken
We made changes on the fly. Our A/B tests showed that emails with embedded video testimonials got a 1.5x higher CTR than ones with static images, so the creative team immediately started cranking out more short, mobile-friendly videos. We also heard from some users that our retargeting felt a bit spammy, so we dialed back the ad frequency from 5 to 3 impressions per user per week, which cut our ad fatigue metrics by 15%.
To sharpen our targeting even more, Bray brought in a third-party data enrichment service to flesh out user profiles that were thin on info. This let us personalize outreach even when we didn’t have much history on a user, which is a massive advantage. It’s no surprise the data enrichment market is growing so fast, as that Statista report shows. Getting that extra layer of data is often the difference between a hit and a miss.
The Impact of Representation on Client Success
The success of “Ignite” came directly from Greg Bray’s new model for representation. He cared more about understanding the client’s actual business than just hitting abstract campaign metrics, and he forced that thinking on the whole team. By setting up bi-weekly deep-dives with the client’s product and sales people, he unearthed small details about their challenges that completely changed our messaging. Skin and Bones became an extension of their growth team, a real partner.
We applied the same thinking to winning new clients. Bray’s team built a tough onboarding process with workshops to hammer out alignment on KPIs, audience psychographics, and the competitive reality before a single dollar was spent. This up-front work killed a lot of the usual misunderstandings and set clear expectations, which is why our initial campaign numbers were stronger and client sat scores went up. I think this is where a lot of agencies fail, rushing to launch without truly understanding the client’s internal pressures and market realities.
This paid off for our own agency’s reputation, too. The “Ignite” campaign became a killer case study that helped us land new business and proved Bray’s strategy wasn’t just talk. His insistence on transparent reporting and constant tweaking built a level of trust where clients felt like we were truly in their corner. It created lasting relationships that went beyond the numbers on a dashboard.
The market is flooded with agencies promising results. An agency separates itself by truly understanding and advocating for its clients’ business. Bray’s arrival at Skin and Bones was a commitment to that principle, and the “Ignite” campaign is the proof: invest in real representation, and you get returns that are foundational, not just financial.
In the end, it was the combination of deep client knowledge and data-driven personalization, all pushed by Greg Bray, that improved the campaign results and cemented Skin and Bones’ reputation. It showed that real representation is what makes client relationships last.
What was the main goal of the “Ignite” campaign?
The main goal was to cut the SaaS client’s churn rate by 8% and win back at least 10% of their inactive users.
How was Greg Bray’s approach different?
He ditched the standard account management model for a real strategic partnership. This meant getting deep inside the client’s business, using hyper-segmentation and personalized messaging based on their actual challenges.
What channels did the campaign use?
It was a mix of email marketing using Customer.io, retargeting on Google Ads and Meta Business Suite, and personalized InMail on LinkedIn Sales Navigator.
What was the campaign’s ROAS?
The “Ignite” campaign hit a 3.5:1 Return on Ad Spend (ROAS). For every $1 spent, it brought back $3.50 in revenue from the users who re-engaged.
What was a key takeaway from how the campaign was run?
A big lesson was about LinkedIn InMail. It worked well for hitting high-value targets, but it was too manual and expensive to scale easily. For future campaigns, we’d need to either automate it more or use it on a much smaller, more focused list.
