--- title: BluePoint Q1 Ad Campaign — LinkedIn & Google Ads Strategy type: article created: '2026-04-05' updated: '2026-04-05' source_docs: - raw/2026-01-07-impromptu-zoom-meeting-112532796.md tags: - paid-social - google-ads - linkedin-ads - bluepoint-atm - q1-2026 - geographic-targeting - reverse-atm layer: 2 client_source: null industry_context: null transferable: true --- # BluePoint Q1 Ad Campaign — LinkedIn & Google Ads Strategy ## Overview In the Q1 2026 planning session, BluePoint ATM and the Asymmetric team aligned on a targeted digital advertising campaign spanning **12 distinct geographies** (a mix of cities and states). The campaign uses two platforms with complementary strengths: LinkedIn for B2B audience filtering and Google Ads for intent-based and geographic targeting. A dual-bid strategy separates low-intent traditional ATM searches from high-intent reverse ATM searches. This campaign also incorporates a time-sensitive opportunity: the [[wiki/knowledge/regulatory/ny-cashless-ban-march-2026|New York statewide cashless ban]], effective March 20, 2026. --- ## Platform Strategy ### LinkedIn Ads LinkedIn is the primary B2B targeting vehicle for this campaign. Available targeting dimensions include: - **Location** — city or state level - **Job title** — e.g., Director of Operations, Facilities Manager - **Industry** — e.g., hospitality, entertainment, retail - **Company size** *(available but not confirmed as a priority filter)* > **Trade-off:** Granular targeting reduces audience size but increases relevance. The team agreed to avoid going too narrow in the initial phase to preserve learning signal. LinkedIn does **not** support interest-based targeting the way Meta does, but the job title + industry combination is sufficient for reaching B2B decision-makers at venues likely to need reverse ATMs. ### Google Ads Google Ads is used primarily for **geographic and intent-based** targeting. Key characteristics: - Strong geographic targeting (city, state, radius) - B2B in-market audiences are available but considered **less effective** for this use case — Google treats users as consumers, not by job title or industry - Semantic search matching handles misspellings and variant phrasings (e.g., "cash to card kiosk," "cashless machine") A **search query report** pulled from Search Console will be shared with the client to surface actual organic search terms, which will inform keyword selection and negative keyword lists. --- ## Dual-Bid Strategy A tiered bidding approach separates traffic by intent level: | Search Type | Example Terms | Bid Target | Rationale | |---|---|---|---| | Traditional ATM searches | "ATM machine," "ATM for my business" | ~$1/click | Low intent; use to educate on reverse ATMs | | Reverse ATM searches | "reverse ATM," "cash to card kiosk" | ~$10/click | High intent; user already knows the product | For traditional ATM clicks, the recommended landing page strategy is to redirect users to content explaining what a reverse ATM is — capturing prospects who have the right *type* of business but haven't yet discovered the product category. > **Note from Mark Hope:** "If somebody's actually searching for reverse ATM, we want to bid big because this is somebody who knows what they're talking about. You might bid $1 a click for the other guy." --- ## Geographic Targeting The campaign targets **12 geographies** — a combination of high-priority cities and states. Specific markets were not finalized in this session; Wade and Mike are reviewing a targeting spreadsheet sent by the Asymmetric team and will return it with confirmed geographies and a budget allocation. **Priority market flagged:** New York State, due to the March 20 cashless ban. See [[wiki/knowledge/regulatory/ny-cashless-ban-march-2026|NY Cashless Ban — Content & Ad Opportunity]]. --- ## Targeting Philosophy Mark Hope outlined two approaches to audience scoping: - **Start tight, then expand** — Begin with narrow filters; open up when traffic volume is insufficient. - **Start wide, then tighten** — Begin broad; prune based on performance data. The recommendation for BluePoint's Q1 campaign is a **middle path**: avoid extremes in either direction. Too narrow yields too little data to optimize; too wide dilutes spend on irrelevant audiences. > "Don't go too wide, but don't go too narrow. Try to have some breadth because you're going to learn from this traffic." — Mark Hope --- ## Conversion Tracking Considerations BluePoint's conversion model differs from e-commerce. A "conversion" is defined as a **form fill** (contact/inquiry submission), not a direct purchase. The team discussed how to assign value to form fills: 1. Track total form fills 2. Estimate the percentage that are qualified leads 3. Estimate the close rate from qualified leads 4. Back-calculate an acceptable cost-per-click based on average customer value This framework will inform bid strategy adjustments as campaign data accumulates. --- ## Action Items | Owner | Action | |---|---| | Wade Zirkle | Return Google Ads targeting spreadsheet with confirmed geographies and budget | | Asymmetric (Karly) | Send LinkedIn and Google Ads targeting options spreadsheet to Wade & Mike | | Asymmetric (Karly) | Send Search Console search query report to client | | Asymmetric team | Begin NY cashless ban content and ad targeting | --- ## Related - [[wiki/clients/bluepoint-atm/_index|BluePoint ATM — Client Overview]] - [[wiki/knowledge/regulatory/ny-cashless-ban-march-2026|NY Cashless Ban — Content & Ad Opportunity]] - [[wiki/knowledge/seo/bluepoint-blog-seo-strategy|BluePoint Blog & SEO Strategy]] - [[wiki/knowledge/direct-mail/bluepoint-integra-list-reverse-append|Integra List — Reverse Append Experiment]]