# Jonathan Bland

Jonathan Bland works on B2B SaaS marketing at Omni Lab, with a focus on paid media, campaign testing, attribution, and driving pipeline.

- Profile: https://b2binfluencer.marketing/creators/jonathan-bland/
- LinkedIn: https://www.linkedin.com/in/jonathan-r-bland
- LinkedIn followers: 30,627
- Topics: paid-ads, marketing-measurement
- Based on 13 dated posts, latest 2026-10-07

## Summary

Useful for B2B SaaS paid media and attribution talks or workshops on incremental testing and multi-touch measurement.

- Best for: A B2B SaaS company wanting a practitioner talk or workshop on incremental testing and multi-touch measurement.
- Not for: Consumer or DTC sponsored creator work with paid posts, video, rate cards, or reach metrics.
- Check first: Confirm prior speaking or workshop examples and recent engagement figures for comparable paid-media topics.

### Takeaways

- B2B buyers rarely convert on one touchpoint, so one attribution model misleads.
- Brand search received credit for 51.4% of pipeline on 7.4% of ad spend.
- Lead quality and lead volume are a trade, not a pairing.

## Main ideas

- **B2B buyers rarely convert on one touchpoint, so one attribution model misleads**: Bland argues that almost nothing in B2B comes from a single ad, blog post or event, making last-touch attribution a weak way to judge performance on its own. They acknowledge the pressure from CEOs, CFOs and budget holders for a black-and-white answer, but say many interactions precede a purchase: events, following an employee on LinkedIn, a Slack community conversation, an ad, a blog post, an SDR email and a pricing-page visit. Their practical recommendation is to run several attribution models at once and treat last-touch as one data point, not the verdict. They also note that most people never click ads, so click data misses much of what moved a buyer. Leading indicators can help when they are defined correctly and explained in language a CFO or CEO accepts.
- **Brand search looks like the best campaign, but much of the credit is not incremental**: Bland argues that branded search often appears to be the strongest performer because buyers already in a sales cycle search the company name, click the ad rather than the organic result below it, and give paid search the credit. Those clicks often would have happened anyway, flattering the channel’s headline metric. They reject the bluntest test — switching brand off for 60 days — because one large deal or a slow month can swamp the result, and propose a staged diagnosis that starts cheap and escalates. They also flag a communication problem inside the business: attributed pipeline in Salesforce or HubSpot will drop when brand spend is pulled back because there are no clicks and no UTMs. The number to watch is total pipeline, and the company has to agree to that before running the test.
- **Repeat a few clear ideas, and keep the list short**: Bland treats repetition as the method, not a failure of originality: if you are not sick of saying something, you probably have not said it enough. The point behind that habit is focus: do a few things well rather than eight things poorly. Simpler campaign structures are easier to manage, maintain and explain to a team. Bland groups the ten repeated claims under three principles: most buyers are not buying yet, so build for them; most of what moves buyers never shows up as a click, so measure accordingly; and fewer, simpler things done well beat complexity. Two claims challenge common B2B habits: audience size matters less than reaching the highest-fit segments on channels those buyers already use, and LinkedIn should not be judged by Google’s standards because paid social is not paid search.
- **Lead quality and lead volume are a trade, not a pairing**: Bland pushes back on campaign goals that demand the same lead volume with higher quality, arguing that becoming more selective means removing options by definition. That means cutting poor-quality traffic, dropping low-intent leads, narrowing targeting and often paying more to reach better prospects. Better conversion rates, creative or more budget could eventually rebuild volume, they allow, but volume cannot remain fixed while the business also demands that unwanted volume be removed. The argument surfaces this conflict before a channel plan or test is built, rather than after the results come in.
- **Ring-fence a budget for marketing that never shows up in a dashboard**: Bland proposes a marketing spend category for work that makes sense for the brand but does not fit a clean ROI report. Many effective marketing moves never appear on dashboards, they argue, and the obstacle is rarely marketer belief. It is an executive team that understands marketing, plus measurement and incentive structures that allow the spend without a heavy approval process. They stress that this is not a hall pass on accountability, making the idea a governance proposal rather than a rejection of measurement: how much budget can be spent without a direct-response justification, who approves it, and how it is reviewed?
- **Staffing and channel scope are marketing priorities**: Bland posts openly about hiring for their team and details what they consider in scope for a performance marketing function. The primary channels are Google Ads, Bing Ads, YouTube and Display, with other social channels a plus. Responsibilities include day-to-day campaign management, budgets, optimisations and impact test creation aimed at driving pipeline, as well as pitching new strategies, bidding approaches, and creative and copy tests rather than running programmes on autopilot. The post also names OmniOS, described as the team’s proprietary AI platform for managing paid media at scale.

## Work to read

- [Ten positions Jonathan Bland says they have repeated for nearly four years](https://www.linkedin.com/posts/jonathan-r-bland_if-you-arent-sick-and-tired-of-saying-it-activity-7512860071182151681-9pim)
- [A first-person buying story used to challenge last-touch attribution](https://www.linkedin.com/posts/jonathan-r-bland_b2b-buyers-do-not-buy-after-seeing-one-ad-activity-7513586718990802944-_1Z9)
- [Auditing brand search: 51.4% of pipeline on 7.4% of spend](https://www.linkedin.com/posts/jonathan-r-bland_ummmm-not-sure-this-is-a-surprise-butttttt-activity-7511056952467054592-_iY6)
- [Why lead volume and lead quality are a trade, not a pairing](https://www.linkedin.com/posts/jonathan-r-bland_we-want-the-volume-of-leads-to-stay-the-activity-7508878693088436224-nAri)
- [A budget line for marketing that does not show up in a dashboard](https://www.linkedin.com/posts/jonathan-r-bland_we-need-a-marketing-spend-category-called-activity-7510685747289432065-1rie)
- [Hiring a senior performance marketing manager at Omni Lab](https://www.linkedin.com/posts/jonathan-r-bland_im-looking-for-another-sr-performance-marketing-activity-7511413505040945153-EPeP)

## Brand relationships

- **Omni Lab** (employment)

## Partnerships

Jonathan Bland's posts do not list a published sponsorship program: no rate card, media kit, audience demographic sheet, stated content-format menu, or partnership inquiry route. They do show a working context that shapes any commercial conversation. They recruit for Omni Lab, a B2B SaaS marketing agency, and describe its in-house paid media platform, OmniOS, as something the team uses when managing spend at scale. That points to an agency-side practitioner arrangement rather than the creator-side sponsorship packages a brand would normally price and book. A brand approaching them should expect to negotiate from scratch, not select from a menu. Useful questions to open with: whether they take sponsored posts or paid collaborations at all, whether work would run through Omni Lab or personally, which channels are available, and whether any deliverable would involve OmniOS.

## Alternatives

- Tom Casano: Pick Tom Casano when the problem is LinkedIn Ads execution and lead capture, not attribution design. His posts walk through the friction of sending mobile LinkedIn users to a website form: see the ad, click, wait for the page to load, navigate, find the form, and type details with a thumb. His fix is LinkedIn Lead Gen Forms, which pre-fill name, email, job title, company and phone. The numbers he gives are concrete: gated mid-funnel content at 10–30% conversion, bottom-of-funnel demos at 1–5%, a website landing page at about 1%, and a $2,000 cost per lead becoming $400. In his second post, Casano argues that last-touch attribution was built for banner ads in 2003, not a nine-month, seven-stakeholder B2B deal. He points to influenced pipeline and influenced revenue, LinkedIn's Revenue Attribution Report, and tools such as Fibbler, Dreamdata and HockeyStack. If the team already agrees attribution is the problem and needs the LinkedIn program fixed at the point of capture, Casano is the closer match for that half of the job.
- Nick Jordan: Choose Nick Jordan when the channel being defended is organic or AI-search visibility and the CFO already tracks paid cost per click every week. Jordan puts LLM visibility data on the same slide as paid and affiliate, using the same format and metrics so the comparison needs no explanation. They report one campaign where non-branded traffic from organic plus AI search converted at 8%, matching the paid channels and people who already knew the brand, and describe the proxies to watch: when LLM visibility rises, branded search and direct traffic spike. The second post makes the cost argument directly: high-intent keywords run $3.50–$8.50 per click on paid, while the same keywords sourced organically come in under $0.50 by the end of year one, calculated by dividing total organic clicks over twelve months by total retainer spend. That's a ten-minute spreadsheet exercise. If the client's question is why the organic retainer should survive next quarter, Jordan answers in the same language the paid team uses.
- Will O'Brien: Choose Will O'Brien when the incrementality question concerns affiliate spend or the buyer works in retail, apparel, CPG or D2C rather than B2B SaaS. The affiliate post is the most directly transferable: a performance lead at a $400M+ apparel brand called the channel's 12x blended ROAS fake, and an incrementality test put the lift within a margin of error. O'Brien lays out the mechanics (last-click platforms hand credit to the affiliate because the affiliate link is usually the last touch, networks self-report attribution, and nobody in the chain has an incentive to question it), the structural cause (affiliate and measurement teams are run separately), the deepest loss (brand-loyal repeat buyers using coupon sites, where the brand pays full commission to retain a customer it already had), and the reported outcome of switching to an incremental metric (20% to 50% of previous affiliate spend not generating incremental revenue). If the client wants the same question asked of affiliate instead of brand search, or a consumer-commerce analogue to persuade a skeptical finance lead, O'Brien's material is more relevant. The AI-discovery post adds another entry point for consumer brands watching direct traffic behave oddly.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/