Most AR/VR and metaverse companies burn ad budgets on broad interest targeting because no one has built a real audience model for them yet. Winston Francois embeds with your team to build programmatic infrastructure that finds the buyers who actually convert – not just the curious. We have operated inside fast-moving immersive tech companies and know what separates campaigns that scale from ones that stall.
The Problem
Standard audience segments don't map to your buyers
Programmatic platforms were built for categories like travel, finance, and consumer packaged goods. AR/VR and metaverse products don't fit cleanly into any of those buckets. Broad 'tech enthusiast' or 'early adopter' segments pull in millions of people who have no budget, no use case, and no intent to buy. You end up with high impression volume and a cost-per-acquisition that makes the channel look broken when the real problem is the targeting architecture.
Platform attribution is unreliable for immersive product categories
AR/VR purchases often involve a longer consideration window than standard SaaS or e-commerce. A user might see a display ad, watch a YouTube walkthrough, attend a virtual demo, and convert two weeks later. Standard last-click attribution on DSPs misses most of that path. Without a coherent attribution model, you can't tell which programmatic channels are actually driving pipeline and which are collecting credit for organic conversions.
Creative requirements for immersive tech are operationally harder than most teams expect
Effective programmatic creative for AR/VR products needs to demonstrate spatial or experiential value in a flat 2D ad format – which is a real creative constraint most ad teams aren't equipped for. If your creative isn't demonstrating the product in motion or showing a before/after that resonates with a specific use case, click-through rates will be low and your DSP algorithms will deprioritize your inventory. Low-quality creative tanks your entire programmatic program, not just the individual placements.
You're competing for attention against well-funded incumbents with mature data assets
Established consumer tech players have years of first-party data, retargeting pools, and lookalike audiences built from millions of purchasers. When you enter programmatic channels as an AR/VR startup or growth-stage company, you're bidding against competitors whose algorithms already know what a high-intent buyer looks like. Without a deliberate strategy to build your own data infrastructure – pixel coverage, CRM sync, seed audience construction – you will consistently overpay for the same impressions.
How We Help
The first thing we do is audit what you're already running. That means pulling raw data from every active DSP, reviewing pixel implementation, checking attribution setup, and mapping your current audience segments against actual conversion data. Most AR/VR companies at this stage have at least one major structural problem – incomplete pixel coverage, mismatched attribution windows, or audience segments that sound logical but don't reflect actual buyers. We document what we find and prioritize fixes by revenue impact, not complexity.
From there, we build an audience strategy that's specific to your product and buyer. For enterprise AR/VR platforms, that might mean building B2B segments from first-party CRM data and syncing them to DSPs via clean room integrations. For consumer metaverse products, it might mean constructing high-intent lookalike audiences from your best-LTV cohort and suppressing low-value segments that inflate spend without driving purchases. The strategy is grounded in your data, not in what worked for a different category.
Execution means we are inside your ad accounts, not advising from the outside. We set up campaigns, manage bids, iterate on creative briefs with your design team, and adjust targeting in real time as performance data comes in. We operate with the mentality of an internal growth team – if something isn't working, we change it that week, not at the next monthly review. Our team has operating experience inside immersive tech companies and understands the product and sales cycles well enough to make fast, accurate decisions.
Measurement is where most programmatic engagements fall apart, and we build it in from the start. We establish a measurement framework before the first dollar is spent – defining which signals map to downstream revenue, setting attribution windows that match your actual sales cycle, and building dashboards that connect ad spend to business outcomes rather than just platform metrics. We report on cost-per-pipeline, cost-per-demo, and cost-per-close alongside standard channel metrics so you always know what the program is actually worth.
We also work on the internal capability transfer. By the end of an engagement, your team should understand how to read programmatic data, what to optimize when performance shifts, and how to brief creative that actually performs in these formats. We are not trying to create dependency – we are trying to build something that works without us.
What we deliver
- DSP audit and attribution framework – full review of current ad accounts, pixel implementation, and measurement setup with documented recommendations
- Audience architecture – first-party data integration, lookalike model construction, suppression lists, and segment refresh cadence
- Creative brief system – structured templates and feedback loops that produce ad creative calibrated to AR/VR product demonstration
- Campaign build and management – live management of programmatic campaigns across relevant DSPs with weekly performance reviews
- Revenue-linked reporting – custom dashboards connecting ad spend to pipeline, demo volume, and closed revenue
AR/VR companies that win in programmatic don't start with creative – they start with data infrastructure. If your first-party signals aren't feeding your DSP algorithms, you're paying platform rates to reach someone else's audience.
Our Methodology
Every engagement starts with a 90-day sprint structure. The first 30 days are diagnostic: we audit existing accounts, establish clean attribution, and define the audience segments we'll test. No spend changes until we know what the baseline actually is. Days 31 through 60 are execution: campaigns are live, creative is in rotation, and we're iterating based on real data. By day 60, we have a clear read on which channels and audiences are performing. Days 61 through 90 are scale and systematize: we increase spend on what's working, cut what isn't, and document the playbook your team can run.
What makes this different from a typical agency relationship is the operating model. We are not writing strategy decks and handing them off. We are in the accounts, on the weekly calls with your team, and making tactical decisions alongside whoever owns growth internally. We treat your budget like it's ours. That means we will tell you when a channel isn't ready to scale even if scaling it would mean more work for us.
The measurement layer is non-negotiable. We set up attribution, define success metrics, and build dashboards before any campaign goes live. For AR/VR companies specifically, we pay close attention to the gap between platform-reported conversions and actual downstream revenue – that gap is usually where the real decisions live.
How We Work
The first 30 days are structured around discovery and infrastructure. We pull access to every active ad account, audit pixel and tracking setup, review historical performance data, and meet with whoever owns revenue, product, and sales on your side. We come out of that month with a documented baseline, a prioritized fix list, and a campaign plan that both teams have aligned on.
From day 31 through 60, campaigns are running and we are managing them daily. Your team's involvement in this phase is lighter – we are executing, not asking for approvals on every line item. We send a weekly performance brief and flag any decision that needs your input. We are looking for early signals on which audiences and formats are showing cost-efficient conversion before we commit more budget.
Days 61 through 90 focus on scaling what worked and systematizing the process. We document audience models, creative briefs, and reporting frameworks so your team can operate them independently. Most clients move to a retained operating model after the initial sprint, with Winston Francois embedded at 20-30 hours per week to manage ongoing execution and strategy as the market and product evolve.
Typical engagements run six to twelve months. AR/VR programmatic programs take time to build meaningful first-party data assets and optimize DSP algorithms. Companies that see the most durable results are the ones that commit to the full build, not a 90-day test.
- Reduced cost-per-acquisition as audience models mature and DSP algorithms optimize on higher-quality signals
- Attributable pipeline from programmatic channels connected to CRM data, not just platform-reported conversions
- Internal team capability to brief, evaluate, and adjust programmatic campaigns without full external dependency
If your ar / vr / metaverse company needs programmatic advertising leadership, we should talk.
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Frequently asked questions
How much does a Programmatic Advertising engagement cost for AR / VR / Metaverse companies?
Most engagements run between $15,000 and $35,000 per month, depending on the number of active DSPs, the volume of creative production involved, and how much of the analytical infrastructure needs to be built from scratch. That range does not include media spend, which we manage but do not mark up.
How long before we see results from Programmatic Advertising?
Early indicators – click-through rates, cost-per-click, initial conversion signals – are visible within the first 30 days. Meaningful cost-per-acquisition data takes 60 to 90 days because AR/VR purchase cycles are longer than standard consumer categories and DSP algorithms need volume to optimize.
How does the Programmatic Advertising team integrate with our existing staff?
We work directly inside your Slack, your ad accounts, and your weekly growth reviews – not through account manager layers or project management portals. We identify one primary point of contact on your side, typically your head of growth or marketing, and operate as an extension of that person's team.
What makes Winston Francois different from a traditional Programmatic Advertising agency?
Traditional agencies optimize for retained spend because their revenue is tied to media commissions or percentage-of-spend fees. Our model is a flat retainer with no media markup, which means our incentive is program performance, not budget size.
How do you measure ROI from Programmatic Advertising for AR / VR / Metaverse?
We measure at three levels: channel efficiency (cost-per-click, cost-per-landing-page-visit), conversion efficiency (cost-per-demo, cost-per-trial, cost-per-qualified-lead), and revenue efficiency (cost-per-pipeline, cost-per-closed-deal). The third level requires CRM integration, which we set up in the first 30 days.
What type of AR / VR / Metaverse company is the right fit?
The best-fit clients are AR/VR or metaverse companies that have found initial product-market fit, have a defined ICP, and are ready to invest in building a scalable acquisition channel rather than running one-off campaign experiments. That typically means Series A or later for venture-backed companies, or $2 million or more in ARR for bootstrapped businesses. Companies that don't yet know who their buyer is will get more value from a strategy engagement first – programmatic amplifies a working message, it doesn't create one.
