Having spent many years in Martech, I’ve learned a simple truth: pricing models quietly shape marketing behavior. Not strategy decks. Not vendor roadmaps. Pricing.
For years, Martech was priced using a seat‑based model combined with channel consumption (email, SMS, …). You predicted and negotiated your volumes, added a bit extra just to be safe, and you were covered. There was little to no impact from the number of segments, integrations, duplicate lists, or legacy landing pages and emails.
That’s why the shift toward consumption-based pricing in Martech and especially Salesforce Data 360 (formerly Data Cloud) matters far beyond procurement. This isn’t just about how we pay – it’s about how we plan, prioritize, and execute. And it’s forcing some uncomfortable questions we’ve avoided for a decade.
I’m not here to cheerlead for Salesforce or any vendor. I’ve seen the good, the bad, and the ugly, from all-you-can-eat licenses that encouraged “spray and pray,” to CFOs blindsided by cloud bills. My stance: consumption-based pricing can make Martech more accountable, fair, and accessible, if (and only if) we adopt it with discipline, transparency, and guardrails.
The Status Quo: Flat Fees, Flat Thinking
Let’s be honest about flat, fixed fee, “all-you-can-eat” pricing: it feels safe. You can allocate a budget in Q4 and sleep at night. But it also distorts behavior.
- Utilization theater: I’ve watched teams chase usage to “get value” from sunk costs: “We’re paying for unlimited sends, so let’s blast one more segment.” That’s not strategy, that’s buffet psychology.
- Spray and pray becomes a habit: When marginal cost is invisible, precision loses out to volume. We send more, not smarter.
- Mid-market exclusion: Flat enterprise licenses often price out ambitious mid-market brands that could punch above their weight if they could pay as they grow.
Fixed contracts created a comfort zone. But comfort isn’t a strategy.
Why Pay-Per-Consumption Makes Strategic Sense Now
We’re moving into a world of conversational marketing and sales, continuous, context-rich interactions across channels, powered by real-time data. In that world, paying for what you actually use aligns incentives in a way flat fees never did.
- Fairness and accountability: You pay when you ingest data, unify profiles, segment, activate, or run models (i.e. when work happens, and outcomes are possible). That’s closer to value than “seats” or “tiers.”
- Access for more players: Mid-market and scale-ups can adopt enterprise-grade capabilities without swallowing a massive annual fee. Start small, prove value, expand intentionally.
- Better behaviors: When usage has a cost, we design for impact per event, cleaner data pipelines, sharper segmentation, fewer but smarter activations, and proper experimentation design.
- No useless features: One bonus benefit teams love? They stop paying for features that look good in a sales deck but never make it into daily workflows. Instead of buying a giant platform “just in case,” they activate only the capabilities that matter. It reduces waste, improves adoption, and keeps teams honest about what truly drives outcomes.
This isn’t hypothetical. We’ve already normalized consumption in cloud infrastructure (compute, storage, streaming) and paid media (CPC, CPA, tROAS). Martech is late to the party.
The Real Objection Isn’t Budget, It’s Uncertainty
The pushback I hear isn’t “we can’t afford it.” It’s “we can’t predict it.” Fair. But let’s unpack that.
- “We need predictability.” You already forecast email volumes and media spend. The same modeling works for identity resolution calls, segmentation jobs, and activation events, especially once you baseline for two quarters. And when it comes to Data 360, Salesforce even provides you with an easy-to-use calculator.
- “We can’t risk runaway bills.” You can cap it. Set monthly caps, alert thresholds, and kill switches, just as you do for social ad platforms.
- “We don’t know what drives cost.” Then demand transparent meters like the digital wallet: clear unit definitions, per-unit prices, sample calculators, and real-time dashboards. If you can’t see and simulate it, you shouldn’t sign it.
Most resistance is habit and the fear of the unknown. Both are solvable with visibility and governance. Just do your homework in advance and make sure to think about the real “needs”, “wants”, and “nice to haves” because these are the choices that will drive the cost.
The Downsides (Because Yes, This Shift Is Hard)
I’m bullish, but not blind to reality. Moving to a consumption-based model isn’t just a commercial change – for many organizations, it triggers a full rethink of budgeting, forecasting, and internal accountability. That alone can be a major transformation. And the concerns customers raise are valid: shifting from predictable line items to variable usage introduces uncertainty, new processes, and, at times, organizational friction.
Here are the most common pitfalls I see and how to mitigate them:
- Perverse incentives: When every experiment burns credits, teams may play it safe, slowing innovation. The fix: ring-fence an experimentation budget and define SLAs around learning velocity so exploration remains a protected activity.
- Opaque metering: Vague or shifting “credit” definitions erode trust fast. Push vendors for stable unit definitions, transparent SKU catalogs, and versioned pricing documentation.
- Complex procurement: Not every buyer can embrace pure consumption. Government and regulated industries often require fixed or predictable pricing. These customers will still need committed-use agreements, prepaid bundles, or reserved tiers.
- Data gravity and vendor lock-in: The deeper your architecture leans on one vendor’s meters, the harder it becomes to switch. Mitigate lock‑in with portable data schemas, open APIs, and message buses that allow you to decouple core logic from any single platform.
What I Expect From Salesforce (and Any Other Vendor)
If vendors want customers to truly embrace consumption, they have to earn trust first. That means real transparency, real control, and clear, long-term commitments about how their pricing works and how usage is measured. No amount of persuasion beats clarity. Give me a model I can understand and stick to, and I’ll lean in.
Here’s what that looks like in practice:
- Clear, stable meters: Define units plainly (e.g., “X per 1,000 profiles unified,” “Y per 1M events processed”), and don’t quietly redefine them mid-year.
- Real-time usage dashboards beyond the digital wallet possibilities: Per product, per workspace, per campaign, with alerts when thresholds are hit.
- Hard caps and tiered protections. Let customers set caps, pausing non-critical jobs while allowing critical flows to continue.
- Predictive cost simulators. Let us plug in volume assumptions and see modeled monthly spend before we ship a pipeline.
- Hybrid options: Pre-made packages with included consumption and preferred rates (like telco bundles or cloud reserved instances), backed by transparent overage meters.
- Sandbox allowances. Include non-production credits or discounted dev/test rates so teams can learn without fear-taxing innovation.
- Unified billing language. Cross-cloud consistency: one set of concepts, one glossary, one invoice.
If Salesforce does this well for Data 360, alongside Marketing, Sales, and Activation workloads, it will feel less like a black hole and more like a fair market.
How Consumption Pricing Changes Strategy (for the Better)
- Fewer, better events: One of the biggest shifts I see is teams moving away from capturing everything and instead focusing on the events that genuinely reflect customer intent.
A retail client I worked with cut their event schema from 100+ fields to just 27 core behaviors. Suddenly, dashboards became clearer, activation became faster, and engineering stopped drowning in noise. Instead of tracking “hovered on hero image,” they aligned around moments that matter: add‑to‑cart, low‑inventory views, checkout starts. The result? Better predictive models, lower data-processing costs, and fewer credit surprises.
- Identity with intent: Identity resolution is powerful, but it’s not free and not always necessary. High-performing teams have learned to apply it where it moves revenue, not everywhere by default.
One business I supported, limited identity stitching to high-value journeys: checkout recovery, churn prevention, and premium upsell flows. Low-signal behaviors (like casual browsing) no longer triggered heavy identity workflows. This kept their consumption predictable while actually improving match quality where it counted.
- Right-time activation: Instead of defaulting to weekly “just because” campaigns, teams are adopting triggers based on meaningful customer milestones.
A travel brand shifted from scheduled promotional sends to lifecycle-based programs; search abandonment, trip countdowns, loyalty tier progress. Conversion rates went up double digits, and message volume dropped by a third. When credits are on the line, teams finally stop sending mail for the sake of filling the calendar.
- Experimentation discipline: Teams also tell me that consumption nudges them into better testing habits.
One team I worked with used to let A/B tests run for weeks because “it couldn’t hurt.” Once credits came into play, they tightened things up: write down the goal, decide what “good” looks like, and stop the test as soon as a variant clearly isn’t working. Nothing fancy, just cleaner decisions, faster learnings, and fewer wasted runs.
- Data minimization with purpose: Companies are also becoming more thoughtful about what they collect and how long they keep it.
A global retailer realized they were retaining every customer action indefinitely, even though most of it had no predictive value after 30 days. By implementing tiered retention (hot data for 30 days, warm for 180, aggregated thereafter), they reduced data volume by 60% and compliance risk along with it. Cost savings were a side effect; clarity and simplicity were the real gains.
My Bottom Line
I don’t believe pay-per-consumption is a temporary pricing experiment. I believe it’s the logical pricing model for the next era of Martech, one defined by real-time data, AI-assisted orchestration, and tight feedback loops. It rewards precision, opens doors for mid-market innovators, and aligns cost with value.
But it only works if vendors provide transparency and customers build governance. No black boxes. No gotchas. No mystery credits that change names every quarter.
Pay-per-consumption isn’t just a commercial change; it’s a design choice. Make it well, and the technology starts working for the strategy – not the other way around.
One Last Thought
We’ve spent a decade talking about “customer-centricity.” Consumption-based pricing quietly asks us to be business-centric too, pay for what matters, measure what works, and stop what doesn’t. If that makes us a little uncomfortable, good. Discomfort is where better marketing begins.
