Airport PPC: SAV Shuttle’s Q4 2025 Wins & Pitfalls

Running geographic PPC for a specialized service like an airport shuttle is all about careful planning, especially when your audience is just passing through. We’re breaking down a campaign we ran for a regional airport shuttle at Savannah/Hilton Head International (SAV) in Q4 2025. It’s a solid case study in how tight local targeting can really pay off in a crowded travel market, and it also shows exactly what happens when you underestimate seasonality and don’t read keyword intent correctly.

Campaign Teardown: Savannah Airport Shuttle Service, Q4 2025

Our client was “Coastal Ride,” a shuttle service doing transfers between SAV and spots around Savannah, Hilton Head Island, and Bluffton. They brought us in to run a geographic PPC campaign for Q4 2025. The mission was simple: get more direct bookings for airport rides, specifically from leisure and business travelers coming in and out of SAV. This timeframe, covering Thanksgiving and the December holidays, is always a surge period for travel in the region.

We ran the campaign for a straight 90 days, from Oct 1 to Dec 31, 2025. The total ad spend was $18,000, which broke down to about $200 a day. The goals were aggressive: a Cost Per Lead (CPL) under $25 and a Return On Ad Spend (ROAS) of at least 300%, based on some historical conversion data they had from organic traffic.

Strategy and Targeting: Precision in Proximity

The whole game plan was built on hyper-local targeting using Google Ads’ advanced location settings. We started with a primary 25-mile service radius around SAV, which covered downtown Savannah, Tybee Island, Hilton Head, and Bluffton. But the real work was in the specific geo-fences we set up:

• SAV Arrivals/Departures: We drew a tight 1-mile circle around the airport terminals and slapped a +25% bid adjustment on it. This was to catch people literally standing there, phone in hand, looking for a ride.
• Major Hotel Districts: We put smaller fences (0.5 to 1 mile) around hotel clusters in downtown Savannah, think Ellis Square and River Street, and the big resorts on Hilton Head. These got a +15% bid adjustment.
• Competitor Locations: We even fenced off our competitors’ main pickup points. We kept the bid adjustment low here (+5%) because the goal wasn’t to get into a bidding war, but to monitor their presence and maybe poach a few high-value searches when the price was right.

We then layered on demographic targeting for adults 25-65 who showed interest in travel and business. We also targeted the top 30% of household income brackets, since a private shuttle is a premium service compared to an Uber. We didn’t totally exclude lower-income brackets, because some travelers will always pay for convenience, but we did bid 10% lower for those segments.

Our keyword strategy was a standard mix of match types. We had exact match like “savannah airport shuttle,” phrase match like “hilton head airport transport,” and some broad match modified (back when it was a thing) like “+airport +car +service +sav.” The negative keyword list was our shield, and we managed it aggressively. Terms like “free shuttle,” “bus schedule,” “rental car,” and “public transportation” were blocked from day one to protect the budget. Honestly, managing negatives is probably the most overlooked part of local PPC, but it has a direct impact on your efficiency.

Creative Approach: Clarity and Call-to-Action

For ad copy, we went for pure clarity and convenience. Headlines like “Stress-Free SAV Transfers,” “Reliable Airport Shuttle,” and “Book Coastal Ride Now” did the heavy lifting. In the descriptions, we spelled out the features: “Professional Drivers,” “On-Time Guarantee,” and “Luxury Sedans & SUVs.” We also used call extensions and structured snippets to show phone numbers and service areas, and to be transparent with things like “Flat Rates to Hilton Head.”

In each ad group, we ran four different ad variations to see what would stick. It was a classic A/B test. For example, we pitted a speed-focused ad (“Fastest SAV Transfers”) against a comfort-focused one (“Relaxing Ride to Hilton Head”). We just needed to find out what travelers actually cared about when they were booking.

What Worked and What Didn’t: A Data-Driven Retrospective

The campaign’s performance was a mixed bag, we crushed some goals and missed others. Here’s the data:

What worked:

• High Impressions and CTR: Our tight geographic targeting paid off. The bid adjustments around the airport and hotels generated a ton of relevant eyeballs and clicks. Our 4.16% CTR was solid, beating the typical 3.5% industry average for travel services that Statista reported for 2025.
• Ad Copy Performance: The ads that focused on “Stress-Free” and “Reliable” messaging consistently beat the ones pushing “Fastest.” The data showed this pretty clearly: during the hectic holidays, travelers were looking for dependability, not a slightly shorter car ride.
• Negative Keyword Management: All that work on the negative keyword list probably saved us 12-15% of the budget that would have been wasted on irrelevant searches, especially with all the weird queries that pop up during the holidays. This ongoing task is non-negotiable for anyone who wants to run an efficient campaign.

What didn’t work as expected:

• Conversion Rate and ROAS: Even with all those clicks, our conversion rate of 2.03% missed the 2.4% target, which dragged down the final ROAS. My theory is that lots of people clicked our ad, got a price, and then went to compare it on aggregator sites or just called a competitor. It’s a classic example of factors outside the ad campaign itself influencing the final sale.
• Peak Season Competition: The last two weeks of December got brutal. Cost Per Click (CPC) for our money keywords like “savannah airport private car” shot up by almost 30%. That spike was pure competition from other shuttles and ride-sharing apps flooding the auction, and it pushed our CPL higher than we wanted. The market can shift fast in an auction, no matter how well you plan.
• Mobile Conversion Discrepancies: Mobile brought in over 70% of the clicks, but the conversion rate was a disappointing 1.8%, while desktop converted at a healthier 2.5%. The client’s mobile booking form was technically responsive, but it had too many steps, and we’m sure that’s where people were dropping off.

Optimization Steps Taken

We didn’t just sit there and watch the numbers. Mid-campaign, especially when those late-December CPCs went crazy, we started making changes:

1. Landing Page Optimization: We pushed the client to simplify their mobile booking form, helping them cut it from five steps down to three and get the main call-to-action above the fold. This was a huge deal. Your ad copy can be perfect, but it’s useless without a smooth path to conversion.
2. Bid Strategy Adjustment: In the final month, we switched the main ad groups from “Maximize Clicks” to “Target CPA.” We had enough conversion data by then for the system to effectively hunt for conversions at our target cost instead of just chasing cheap traffic.
3. Expanded Negative Keyword List: We found another 20 negative keywords to add to the list, mostly related to “cheap,” “discount,” and a few competitor names that kept showing up in search queries without ever converting.
4. Ad Schedule Adjustments: We looked at the data and saw that late-night searches between 1 AM and 5 AM almost never converted. So we cut bids by 10% during those hours and moved that budget to the peak morning and evening travel times.
5. Refined Audience Segments: We built a “Remarketing Lists for Search Ads” (RLSA) audience targeting people who hit the booking page but didn’t finish. We bid up 20% for this group and showed them a new ad with a little urgency, which was pretty effective at winning back some of those lost prospects.
6. Geographic Bid Refinement: As the holidays got closer, we doubled down on what was working. We bumped the bid adjustment for the 1-mile SAV radius to +30% and the hotel zones to +20% to capture as many of those high-intent searches as possible.

So, while the campaign didn’t hit every single KPI, it gave us a ton of real-world data on running geographic PPC for airport services. The whole thing was a lesson in how fast you need to react to data, tweak bids, and even push your client to fix their website. That crazy CPL during Christmas week is a clear warning for next time: you have to budget for a bidding war and maybe even think about dynamic pricing.

Advanced Insights for Local Campaign Analysis

When we analyze local campaigns, we go deeper than the high-level numbers. It’s not uncommon for us to look at performance by zip code, even inside a small radius. For this campaign, we found that searches coming from the 31401 zip code (Downtown Savannah) converted 15% better than searches from 31322 (Pooler, right by the airport). What do you do with that information? You create even more specific bid adjustments and maybe write ad copy for the next campaign that speaks directly to downtown travelers. You can’t just draw a circle on a map. Knowing the behavioral patterns inside that circle is how you go from a good campaign to a great one.

Another thing we live and die by is Google Ads’ Impression Share (IS) metrics. For Coastal Ride, we saw our IS for “savannah airport shuttle” keywords inside the SAV geo-fence fall from 85% in early November to 68% by mid-December. That told us that even though we were raising our bids, competitors were getting even more aggressive and squeezing us out of valuable auctions. This metric is your early warning system. Ignoring impression share in a competitive local market is basically letting your competitors eat your lunch, no matter how good your ad copy is.

Finally, we always push clients to connect their PPC data to their CRM. That’s how you get true closed-loop reporting. It lets you attribute actual revenue to a specific keyword, not just a “conversion” event on the site. For Coastal Ride, this would have shown us that even though certain keywords had a higher CPL, they brought in higher-value bookings like multi-passenger vans, making their ROAS much better in the long run. This kind of integration isn’t a luxury anymore. In my opinion, it’s what separates professional marketing from just guessing.

The Coastal Ride campaign shows that even with super-precise geographic PPC, you have to constantly monitor and optimize to get the best results, especially in a fast-moving market like airport services. The next time we run a campaign like this, we’ll build on what we learned, probably by testing dynamic creative and getting even more granular with audience segments based on their travel intent.