Channels vs ecosystems: partner plays, platform economics, and data strategies for 2024

Published on March 15, 2024
Expert advice from Scott Brinker (Hubspot) and Jay McBain (Canalys).

Snapshot

The customer you sell to thinks in terms of integrated experiences, not single-product decisions. These buyers expect a constellation of touchpoints—pre‑sale advice, technical integrations, implementation services, and ongoing optimization—so purchase choices are made against a backdrop of recommendations, bundled solutions, and trusted intermediaries rather than a lone product sheet. This is why marketplaces and platform ecosystems are compressing selling economics: they reduce friction at the point of purchase and aggregate choice, putting pressure on standalone resale margins and forcing vendors to compete on the completeness and coherence of the experience they deliver.

Keep reading to learn how Scott Brinker and Jay McBain break these ideas into concrete plays, tooling recommendations, and pilot experiments you can run this quarter to improve partner attribution, build scalable co‑sell programs, and make partner economics measurable and fair. Their frameworks show how to move from a transactional mindset to a flywheel mindset—reduce friction, make partner value visible, and reward the work that truly grows lifetime customer value.

This is how billionaires get created. This is how the new economy works. – Jay McBain.

Table of Contents

Why channels and ecosystems are different

When you think of channels, think of distribution and transactions. Channels are where the money exchanges hands — resellers, retailers, agents, and marketplaces. When you think of ecosystems, think of the broader set of trusted advisors and integrations that shape buyer decisions before, during, and after the transaction. The difference matters because the levers you pull are different.

If your priority is frictionless buying, channels matter. If your priority is long-term customer value, renewals, and expansion, ecosystems matter. The reality is both matter and they overlap. Your job is to decide which parts of the orchestration you own, which parts partners own, and how to make that value visible.

Seventy-five percent of the world economy moves indirectly. – Jay McBain.

How to frame the problem

Start with the customer. Map who surrounds them. For most B2B buyers today, seven partners show up in the decision process. Only one of them might collect payment. The others influence selection, integration, and long-term value. That means you must plan for:

  • Where your product sits in the customer’s journey.
  • Which partners influence the pre-sale, implementation, and post-sale moments.
  • Where money will be collected — direct, indirect, or via marketplaces.

What matters is that in the customer’s first 28 moments those partners are talking about HubSpot. – Jay McBain.

The five plays shaping partnerships in 2024

Jay lays out five core plays that shift the rules. Treat these as the strategic spine of any partner plan you build this year.

  1. The millennial majority buyer — Buyer psychology has shifted. Younger buyers favor subscription, integration-first experiences, and ecosystems that connect tools and advisors. If you aren’t integration-ready you risk losing large swaths of your market.
  2. The platform economy — Platforms create gravity. When ISVs and service partners line up around a platform, a multiplier effect appears. Expect marketplaces and platform-led commerce to become the dominant route to many categories of customers.
  3. The new economics of partnering — Marketplaces have compressed resale margins. Resale alone will likely be a 1–3% affair in many ecosystems, while services, advisory, and points of value will capture the rest of the economics.
  4. The end of third-party tracking — Cookies are dying. That forces a move to first- and second-party data models and makes partnerships that create context and identity more valuable.
  5. Generative AI acceleration — AI is the accelerant. It creates new product expectations, automates advisory tasks, and creates opportunities for partners to embed differentiated intelligence into solutions.

2024 is shaping up to be an inflection point year. – Jay McBain.

Why data is the new battlefield

Scott frames the single biggest trend as data becoming the center of platform and go-to-market strategy. Historically, platforms locked up data, but that model is breaking down. You now need a universal data layer so you can:

  • Analyze behavior across your product, integrations, and partner contributions.
  • Feed near real-time signals back into apps to trigger partner plays and automation.
  • Power AI models with clean, integrated data so recommendations and personalization scale.

That means a modern partner agenda includes data engineering: extract, transform, model, and activate. The result is measurable partner value and the ability to compensate partners based on what they actually contributed to customer outcomes.

We are in a revolutionary state on data. – Scott Brinker.

Account overlap mapping: a practical playbook

Account overlap mapping is the most tactical place to start using data to drive partner motions. Here’s a playbook you can follow right away.

1. Get the baseline data

Collect account lists from your CRM, marketing automation, and any partner systems. Standardize naming, dedupe, and enrich records where possible. This is the raw material.

2. Use an overlap tool

Tools like Crossbeam (mentioned by Scott) or other account mapping platforms let you see overlaps across partner ecosystems and prospects. The goal is to surface:

  • Shared accounts where you and a partner both have presence.
  • Accounts where a partner has relationships but you don’t.
  • Whitespace where co-marketing or APP-led expansion could unlock net-new opportunities.

3. Frame the plays per quadrant

Use a 3×3 matrix (your customers, opportunities, prospects vs partner customers, partner opportunities, partner prospects). For each quadrant define a play: co-sell, co-market, referral agreements, technical integration, or joint solution design.

4. Operationalize and measure

Make these plays programmatic. Create templates for outreach, landing pages for co-marketing, and defined KPIs for trackable outcomes. Feed these KPIs into your universal data layer so performance is visible.

5. Expand into 3D thinking

Scott describes an evolution from a 3×3 grid to a 3x3x3 cube — adding a third dimension such as product, region, or vertical. As you scale account mapping, think about intersecting multiple planes of data to discover high-value partner plays.

Rewriting partner economics for value-based pay

Marketplaces have drastically reduced the ceiling on traditional resale margins. That forces a rethink: instead of paying for the transaction only, pay for outcomes and point-of-value contributions.

Define what “point of value” means for your business. Examples include:

  • Customer acquisition credit from partner-led demand generation.
  • Implementation success metrics (time to value, milestone completions).
  • Renewal and expansion signals attributable to partner-led services.

Once defined, instrument these activities in your data stack so you can measure and pay partners accordingly. If a partner authored the ebook that shortened sales cycles, compensate them for that saved SG&A. If another partner built the integration that unlocked a $1M account, pay them for demonstrated technical value.

If you did the ebook, I want to pay you for that. – Jay McBain.

Designing routes to market: cash registers and friction

Jay uses the metaphor of cash registers: depending on what you sell, you need cash registers where your customers expect to buy. Donuts or coffee need registers on every corner. Complex B2B software needs a mix of direct, indirect, and marketplaces, depending on buyer preference.

Ask yourself these three questions:

  1. How does my buyer prefer to buy?
  2. Which partners reduce friction and create trust before the sale?
  3. Where does it make sense to let a marketplace collect payment to reduce friction but maintain brand and lifecycle control?

Answering these helps you decide where to invest in partner enablement, where to simplify procurement, and where to build marketplace integrations.

Getting the customer to the dance is as important as keeping them dancing all night long. – Jay McBain.

Program changes you can make right now

Short list of tactical moves you can implement immediately to align with the new plays:

  • Start account overlap mapping on a pilot set of top 50 partners and 500 target accounts.
  • Create a point-of-value taxonomy (marketing contribution, engineering delivery, customer success, integration work).
  • Instrument basic partner attribution events into your CDP or data warehouse.
  • Build co-marketing templates and clear co-sell playbooks for the most common quadrants in your overlap matrix.
  • Run a compensation experiment: pay a portion of partner fees on measured outcomes instead of pure resale.
  • Prioritize first-party data capture touchpoints in your product and onboarding flow to offset cookie loss.
  • Prototype one AI-assisted play: partner-sourced lead enrichment or partner-guided product recommendations.

How is the data going to inform generative AI and just regular human intelligence? – Justin Zimmerman.

As you rebuild partner programs for 2024, the underlying tech stack becomes critical. Tools fall into several categories:

  • Account mapping and partner analytics: Reveal, partner overlap mapping tools.
  • Data ingestion and warehousing: Fivetran, Stitch, Snowflake, BigQuery.
  • Data modeling: dbt to create reusable, versioned models for partner KPIs.
  • Activation and reverse ETL: Hightouch, Census to push enriched data back into CRMs and partner systems.
  • Partner relationship platforms: modern PRMs that support more than portals — partner enablement, deal registration, and API-first models.
  • Attribution and lead-to-revenue: platforms that map marketing and partner touchpoints to revenue.
  • Generative AI tooling: embeddings, LLM orchestration for partner recommendations and contextual playbooks.
  • Integration and marketplace infrastructure: API gateways, SDKs, and marketplace listing services.

Examples from the discussion: HubSpot (platform), Reveal (account overlap), Fluency (referral discovery), PRM solutions discussed by Greg, and marketplace platforms from cloud vendors. Mix enterprise-grade data tools with partner-centric activation tech to get the flywheel spinning.

We’re seeing solutions partners bring in app partner solutions as part of the complete offering. – Scott Brinker.

Measuring partner value: KPIs that matter

Move beyond classic vanity metrics. The new KPIs should reflect the ecosystem’s contribution to customer lifetime value.

  • Influence-based metrics: Number of qualified deals influenced, closed deals with partner involvement, average time-to-close when partner is involved.
  • Value-delivered metrics: Post-implementation time-to-value, reduction in churn attributable to partner-led onboarding, upsell rate on partner-instrumented customers.
  • Platform engagement metrics: Number of integrations adopted, active weave between platform and partner solutions.
  • Revenue split metrics: Marketplace revenue vs direct revenue, services revenue tied to partner activities.

Common implementation pitfalls

Expect friction. These are the things that break most programs when you try to adopt the new plays:

  1. Poor data hygiene. If you can’t dedupe and unify accounts, overlap mapping is garbage in, garbage out.
  2. Overly rigid partner tiers that reward legacy resale at the expense of advisory value.
  3. Ignoring the buyer. You can build brilliant partner programs, but if the buyer prefers marketplace purchasing, you’ll lose conversion.
  4. Under-investing in measurement. If you can’t measure partner contribution, you’ll default to paying the easiest-to-track party — usually the reseller — rather than the most valuable.

Make sure this becomes that flywheel and reduce friction in this flywheel. – Jay McBain.

FAQs

How do I decide between building a resell channel, marketplace listing, or encouraging an ecosystem of advisors?

Start with customer preference and deal complexity. If your buyer wants fast procurement and the product is commodity-like, marketplaces reduce friction. If the buyer requires advisory and integration, invest in an ecosystem of service partners. Often you need a hybrid: let marketplaces handle frictionless purchases while partners deliver integration and long-term value.

What are the first data investments I should make to support partner attribution?

Begin with a canonical customer table in a data warehouse and automate ingestion of CRM, partner, and billing data. Implement a small set of partner attribution events (first-touch partner campaign, partner-influenced opportunity, partner-logged implementation). Use dbt models to standardize and compute partner-level KPIs.

How do you pay partners when marketplaces limit resale margins to 1–3%?

Shift compensation to measured outcomes: pay for documented marketing influence, successful implementations, renewals, or expansions driven by partners. Create explicit micro-contracts that define milestones and payouts tied to data you capture in your systems.

What’s a simple pilot to prove account overlap value?

Pick 3 strategic partners and 200 target accounts. Map overlaps, define three plays (co-marketing ebook, co-sell workshop, joint demo), run the plays for 60–90 days, and measure pipeline created, conversion lift, and time-to-close. Use the results to justify tooling investment.

How should I adapt partner programs for generative AI?

Use AI to augment partner workflows: automate lead enrichment, generate personalized co-marketing content, and recommend partner solutions within product UX. Ensure data quality so AI models can generate reliable outputs and set up guardrails for model transparency.

Conclusion

You are building in a new era where platforms, data, and ecosystems determine your company’s long-term valuation. Create a clear routes-to-market map, instrument the data that measures partner contribution, and redesign economics to reward points of real value. The combined effect of marketplaces, first-party data, and generative AI is not incremental — it changes how you must design partner ecosystems. Move from a transactional mindset to a flywheel mindset: reduce friction, make value visible, and reward partners for the work that actually grows lifetime customer value.

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Announcing a new playbook for partnership leaders, head of partnerships, and partner ops leads…

Introducing Channels vs ecosystems: partner plays, platform economics, and data strategies for 2024!

Inside it you will find a strategic framework and practical plays you can use to rewire partner motion, increase measurable partner value, and adapt to the platform-and-AI era. You will see why the buyer shift, marketplace economics, the end of cookies, and data-first architectures change how you reward partners and design go-to-market routes.

  • How to map account overlap and prioritize partner plays.
  • What KPIs move the needle for renewals and expansion.
  • How to compensate partners for point-of-value contributions.
  • Which data stack components you need to make partner attribution reliable.
  • How to balance marketplace, direct, and partner routes to market.
  • Practical steps to pilot generative AI in partner workflows.
  • Common pitfalls that stall transformation and how to avoid them.

Get this playbook if you are a partnership leader and want to learn what Scott Brinker and Jay McBain do, so you can achieve better partner attribution, scalable co-sell execution, and data-driven partner economics. This playbook is free, no form-fill required, no optin required.

When you start with the buyer and instrument the data, you create a flywheel that scales. – Scott Brinker.

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