Decide Which Sales Channels to Test

Task

Define the first sales-channel hypotheses to test.

Summary

Choose plausible ways to reach customers and define what would support or reject each one.

Turn Sales Channels Into Testable Business Hypotheses

Task ID: S1-11

A founder-led company should not choose its next sales channel by copying a larger software company or by chasing whichever tactic is fashionable. It should document a small set of channel hypotheses, test each against the same customer and offer, and compare the quality, cost, speed, and delivery burden of the business each channel produces.

A founder has won several projects through former colleagues, existing customers, and people who already trust them. The work proves that somebody will pay. It does not yet prove that the company has a repeatable way to find the next customer.

This is where channel discussions often become unhelpful. One person proposes outbound email. Another wants to publish more content. A potential partner offers to “send opportunities.” Existing customers say they would gladly make introductions. The company then performs a little activity in every direction, receives a few encouraging signals, and concludes that all four channels work.

Usually, nothing has actually been tested.

A sales channel is not simply a place where a lead appeared. It is a repeatable mechanism through which a defined customer learns about the offer, develops enough confidence to consider it, and enters a sales process that the company can afford to run. The first task is therefore not to select a permanent channel. It is to state what the company believes about several plausible channels, what evidence would support each belief, and what result would cause the team to stop or revise the test.

Treat the first channel decision as a test, not a commitment

The operating principle is straightforward:

Hold the customer, problem, offer, and expected result reasonably steady while testing different ways of reaching that customer.

Without that discipline, the company cannot tell whether a result came from the channel, the offer, the target customer, the founder’s personal reputation, or a one-off relationship.

This is a practical application of hypothesis-driven decision-making. A 2024 replication study covering 759 firms across four randomized controlled trials found that entrepreneurs can be taught to formulate and test explicit theories rather than relying only on intuition. The approach increased disciplined termination of weak ideas and was associated with more efficient search for viable ones. The lesson is not that every sales experiment must resemble a laboratory trial. It is that a test should make the company’s assumptions and stopping rules visible before enthusiasm, sunk effort, or a lucky sale distorts the decision.

A useful channel hypothesis contains five linked claims:

1. Customer: a specific type of organization and buyer has the problem.
2. Trigger: a recognizable situation makes the problem urgent enough to act.
3. Access mechanism: the proposed channel can reach enough of those buyers.
4. Trust and conversion mechanism: the channel can create a credible sales conversation.
5. Economics: the resulting customers are valuable enough to justify the time, fees, commissions, content work, or sales labor required.

The company is not trying to prove that referrals, outbound, partners, or content can produce any lead. Almost any channel can do that eventually. It is trying to learn which mechanism repeatedly produces customers who fit the offer, buy for the intended reason, can be served at an acceptable margin, and are likely to remain valuable.

Why this work belongs before channel expansion

At a consulting-led baseline, founder relationships often perform several jobs at once. The founder finds the opportunity, establishes trust, diagnoses the problem, adapts the offer, negotiates the price, and reassures the buyer that delivery will succeed.

That concentration is useful for learning. It is dangerous as a growth model.

A warm network can conceal weaknesses that become visible as soon as the company contacts strangers. Existing relationships may compensate for vague positioning, inconsistent qualification, unclear scope, limited proof, or an offer that depends on the founder’s personal credibility. A buyer who already trusts the founder may tolerate uncertainty that an outbound prospect or partner-referred customer will not.

Research on entrepreneurial networks supports the usefulness of relationships while also warning against treating them as a complete market test. A meta-analysis of 31 samples and 5,259 observations found positive associations between venture growth and both network size and tie strength, but no comparable positive relationship for network density. In plain language, access to useful people and strong relationships can matter, but having a tightly connected circle is not automatically the same as having scalable market reach.

The company should therefore use its current network as evidence and as a testing asset, not as proof that the market will behave the same way outside that network.

This work also precedes major spending. Hiring sales development representatives, paying for lead databases, building an elaborate partner program, or maintaining a large publishing schedule creates fixed costs and organizational commitments. A small founder-run test can reveal whether the basic customer, message, and channel mechanism are credible before those costs are added.

There is no reliable universal research finding that every early company should document exactly three or four channel hypotheses. That number is a useful working range because it permits comparison without spreading a small team across too many activities. The appropriate number can be lower when sales cycles are long or delivery capacity is constrained, and higher when tests are inexpensive, fast, and clearly separated. What matters is that every documented hypothesis can receive enough attention to produce a meaningful decision.

What the evidence says about the four initial options

Referral, outbound, partner, and content channels do different work. They should not share identical success criteria.

Referral should test repeatability, not goodwill

Referral is often the strongest first hypothesis for a founder-led service company because it extends an existing trust network rather than requiring the company to manufacture credibility from nothing.

There is evidence that referred customers can be economically attractive. A study following roughly 10,000 customers of a German bank for almost three years found that referred customers had higher retention and an average value at least 16% above comparable nonreferred customers. The authors also found that the advantage varied by customer segment and recommended selective rather than indiscriminate referral programs. Because the study concerned one bank and an established formal program, the exact result should not be treated as a forecast for an early business-to-business service company. The durable lesson is that referral quality must be measured by customer value and retention, not simply lead volume.

Early companies often ask, “Would you refer us?” That question produces compliments, not evidence. A better test asks a satisfied customer or trusted contact for an introduction to a specific role facing a specific situation. The referrer should be able to explain the problem the company solves, the kind of result it delivers, and why the introduction is relevant.

The company should also resist introducing cash rewards too early. Research on referral rewards for innovative products found that incentives can create unintended costs, including paying for referrals that might have happened without a reward. Reward effectiveness varies with product type, customer motives, and referral context.

In complex business markets, the interests of the person making a referral also matter. Recent research on supplier-to-supplier referrals found that trust and economic dependence influence whether a supplier makes the best recommendation for the customer or merely a recommendation that protects its own commercial position. A warm introduction is therefore evidence of access, not automatic evidence that incentives are aligned.

A referral channel is becoming credible when introductions arrive from several independent sources, the referred buyers share recognizable characteristics, and those buyers progress because the offer fits—not because the founder repeatedly renegotiates scope for each relationship.

Outbound should test a reason to talk

Outbound means the seller initiates contact with a selected prospective account. It should not be defined as buying a list and sending a high volume of nearly identical messages.

Research based on 159 authentic business-to-business cold calls found that prospects resist through both blocks, which attempt to end the sales process, and stalls, which delay or divert it. The study shows why a superficial meeting count is inadequate: the response to outbound depends on how the buyer interprets the seller’s reason for contacting them, whether a need is credible, and whether the conversation is advancing or merely being postponed.

A separate field study of inside-sales operations across eight firms found that sales-development work differs across four contexts: outbound prospect-focused, outbound account-focused, inbound prospect-focused, and inbound account-focused. Research, engagement, qualification, and handoff practices must be designed for the context rather than copied as a single standard process.

For an early company, the highest-value outbound test is usually narrow and founder-involved. The founder selects a small account set, identifies an observable buying trigger, tests a concise reason for contact, and records the prospect’s language. The objective is not merely to book meetings. It is to determine whether strangers in the intended market recognize the problem, whether the trigger predicts urgency, and whether the company’s proof is sufficient to earn a serious conversation.

A compliant test must also account for where recipients are located. For commercial electronic messages to recipients in Canada, Canada’s Anti-Spam Legislation generally requires consent, sender identification, and a working unsubscribe mechanism, subject to defined exceptions and forms of implied consent. The sender bears responsibility for understanding and documenting the basis on which messages are sent. Other countries apply different rules, so a channel test must be designed around the recipient’s jurisdiction rather than the seller’s preferred software settings.

A partner hypothesis must explain why the partner will act

Calling another company a partner does not create a sales channel. A functioning partner channel requires access, motivation, capability, and governance.

The potential partner should already serve the intended customer, encounter the target problem, and gain something meaningful by introducing, selling, implementing, or supporting the offer. That benefit might be referral income, services revenue, improved customer retention, a broader solution, or access to a market the partner values. “Our services are complementary” is not enough.

Research on business-to-business multichannel systems shows that direct and indirect sales channels create different information and agency problems. A matched manufacturer–partner study found that the financial consequences of direct and indirect channel use depended on how the relationship was governed. Formalization was particularly important for indirect arrangements, while the effects of centralization and information exchange differed by channel design. The implication for an early company is practical: partner economics, responsibilities, account ownership, handoffs, and information sharing should be part of the hypothesis, not details postponed until after the first lead.

The buyer’s preference also matters. A study of 505 corporate information-technology customers found that greater customer–supplier intimacy was associated with preference for direct service from the manufacturer rather than an intermediary. For complex, high-risk, or highly customized work, the founder or delivery expert may need to remain directly involved even when a partner originates the opportunity.

HubSpot provides a useful example of what a mature combination of content, direct sales, and partners can become—but not of what an early company can install quickly. In 2016, the company reported that inbound sources generated more than 90% of its new customers and more than 85% of new leads, while its salespeople handled inbound opportunities and its agency partners referred and served customers. By the end of 2024, HubSpot reported that solutions partners and customers referred by those partners represented approximately 29% of customers and approximately 48% of annual revenue. Those results came from years of investment in software, education, certification, brand, content, direct sales, and partner support. The example demonstrates that channels can reinforce one another after each has an operating system; it does not show that a new company can skip the work of defining incentives and customer ownership.

Content must produce buyer movement, not just attention

Content is a channel only when the company can connect useful information to a defined audience, a buyer decision, and a next action.

An article that helps an existing sales prospect understand a problem may be valuable sales enablement, even if it does not create the lead. A webinar that produces qualified inquiries may be a sourcing channel. A case study may help a referral convert. These are different functions and should be measured separately.

A 2024 experimental study found that content judged relevant to a buyer’s current stage produced greater engagement and positive sales-related outcomes. It also found that preferred content varied between individuals, which limits the value of publishing one generic asset for an entire market.

The broader evidence remains less settled than many content-marketing claims imply. A 2022 scoping review of 32 studies across 21 countries concluded that research on content marketing and online consumer behavior was fragmented and that important causal questions remained unresolved. Content may support awareness, trust, and decision-making, but publication volume alone is not evidence that it can acquire profitable customers.

The initial content hypothesis should therefore be narrow. It might test whether a detailed explanation of one costly buyer problem, distributed through a founder’s network and targeted professional communities, produces conversations with a defined buyer. The content needs a clear next step—such as a diagnostic discussion, assessment, demonstration, or relevant mailing list—and attribution that distinguishes target buyers from general readers.

Write hypotheses that can survive a real test

A channel document should make the reasoning visible enough that another employee could run the test and reach approximately the same conclusion.

The document should contain one page or compact record for each channel. Each record should answer:

A practical sentence structure is:

We believe that [specific channel action] will reach [defined buyer] when [buying trigger], because [evidence about access and trust]. We will test this by [activity] and consider the hypothesis supported if [behavioral and economic thresholds] within [time and resource limit].

The thresholds below are illustrative, not industry benchmarks:

• Referral: Ten customers or trusted contacts who understand the result will be asked for introductions to a named buyer type. The hypothesis receives support if the introductions repeatedly reach suitable buyers, generate qualified conversations, and do not require a different offer for every relationship.
• Outbound: A tightly selected account group showing one observable trigger will receive personalized outreach. The hypothesis receives support if suitable buyers respond, a meaningful portion accepts discovery, and the same problem language appears across conversations.
• Partner: Two or three firms that already advise the target customer will review the offer, identify named accounts, and participate in joint conversations. The hypothesis receives support if at least one partner independently explains the value, takes agreed action, and produces suitable opportunities under workable ownership rules.
• Content: One substantial asset addressing a validated buyer question will be distributed through channels where the target buyer already pays attention. The hypothesis receives support if target accounts consume it, take the intended next step, and enter qualified conversations at an acceptable time cost.

The flow from belief to decision should be explicit:

flowchart LR
    A[Known customer problem and offer] --> B[Write channel hypothesis]
    B --> C[Set test, limits, and decision rule]
    C --> D[Run with real target buyers]
    D --> E{Evidence strong enough?}
    E -->|Yes| F[Repeat with a larger sample]
    E -->|Partly| G[Revise one assumption]
    E -->|No| H[Stop or replace the channel]
    F --> I[Compare customer quality and economics]

In text: begin with the same customer problem and offer, state how a channel is expected to work, set the test and stopping rule, expose the belief to real buyers, and either repeat, revise one major assumption, or stop. A larger investment follows only after the repeated test produces acceptable customers and economics.

The discipline of changing one major assumption at a time matters. If the company changes the customer, message, price, offer, and channel simultaneously, a win will be encouraging but not explanatory.

Measure proof at the level of the business, not the activity

The primary measure at this stage is the set of documented hypotheses, but completion is not achieved merely by filling in a template. The document is credible when each hypothesis has a clear mechanism, a bounded test, a named owner, and a decision rule tied to customer behavior.

Activity measures still matter because they explain the funnel:

• eligible accounts or potential referrers;
• outreach attempts, referral requests, partner invitations, or content distribution;
• responses and accepted introductions;
• qualified discovery conversations;
• sales opportunities;
• proposals and wins.

Those measures should then connect to business quality:

• sales cycle;
• contract value;
• discounting;
• founder and employee hours required to close;
• implementation and delivery effort;
• expected gross margin;
• customer fit and scope exceptions;
• early use or adoption where software is involved;
• renewal, repeat purchase, retention, or expansion when enough time has passed.

For a small initial test, customer acquisition cost can be misleading. Setup work, founder learning time, and tiny sample sizes can make the number unstable. Cost per qualified conversation and founder hours per opportunity are often more interpretable early indicators. Customer acquisition cost, payback period, and cohort retention become more useful once the channel operates repeatedly.

The company should also distinguish three forms of attribution:

Source identifies the mechanism that first created the opportunity. Influence records material interactions that helped the buyer progress. Close identifies the person or team that converted the opportunity into a customer.

A customer might be sourced by a referral, influenced by content, and closed by the founder. Crediting the full sale to all three channels would create three successes from one contract. Crediting only the last conversation would hide the referral’s value. The rules do not need to be technically sophisticated, but they must remain consistent.

The most important comparison is not which channel creates the most names. It is which channel creates the best combination of:

qualified customer value ÷ cash cost, founder time, sales time, and delivery burden

That formula need not initially produce one precise score. Its purpose is to force the team to include what founders often omit: their own time and the downstream cost of serving the customer.

Avoid false positives and premature conclusions

Several common practices make channel work look complete when it is not.

Treating one sale as channel proof

A single contract may result from unusual timing, a personal relationship, or a buyer whose needs do not represent the intended market. One sale proves that the transaction was possible. It does not prove that the mechanism can be repeated.

Counting introductions instead of qualified demand

A referrer may introduce the company to friends who are willing to be helpful but have no urgent problem, authority, or budget. Referral quality should be judged after qualification and, eventually, through customer value and retention.

Calling every external relationship a partnership

An occasional referral source is not automatically a channel partner. A partner hypothesis is incomplete without a repeatable reason to act, the ability to reach relevant customers, and rules for ownership, compensation, customer data, sales involvement, implementation, and support.

Mistaking publishing for distribution

A technically strong article can receive little qualified attention if it has no route to the target buyer. Conversely, broad traffic may produce no suitable conversations. Content hypotheses must state who will encounter the asset, why it is timely, and what buyer action should follow.

Scaling outbound before learning from it

Automation can increase the number of messages faster than the company improves its targeting. Poor response may then be blamed on wording when the true problem is the customer definition, trigger, proof, or offer. Early outbound should maximize information per conversation before it maximizes messages per employee.

Comparing channels with different definitions of success

A referral may produce fewer but stronger opportunities. Content may take longer but influence several stages. Outbound may produce rapid objections that improve the offer even before it produces a sale. A fair comparison needs both a common business outcome—such as qualified opportunities and profitable customers—and channel-specific leading evidence.

Ignoring delivery consequences

A channel that closes work the company cannot deliver consistently is not a strong channel. Partner-originated customers may expect implementation by the partner. Referrals may expect founder attention. Outbound may reach larger accounts with procurement and security requirements. Content may attract small customers seeking free advice. Channel quality includes what happens after the signature.

Allowing channels to compete without rules

Direct sellers and partners can contact the same accounts, argue over credit, or offer different expectations. Research on multichannel governance shows that such arrangements create predictable information and incentive conflicts unless responsibilities are designed for the particular channel structure. Even an early test should define who owns an account and how conflicts will be resolved.

The research also leaves genuine gaps. Much channel evidence comes from established firms, consumer referral programs, manufacturers, or mature software businesses. There is limited direct research that identifies the optimal first-channel portfolio for a small consulting-led company moving toward a repeatable product. The company must therefore use external evidence to improve its test design, while allowing its own customer, sales, delivery, and financial results to decide.

The decision this work should support

When this task is complete, the company should possess a short channel hypothesis document covering the most plausible referral, outbound, partner, and content mechanisms—or a clearly justified subset.

The document should make four things clear:

First, the company knows which buyer and buying situation each channel is intended to reach.

Second, it can explain how access and trust are expected to move that buyer into a sales conversation.

Third, it has defined what evidence will distinguish progress from activity, including customer fit, sales effort, delivery consequences, and early economics.

Fourth, it has decided what to test now, what to defer, and what result will justify further investment.

Three or four documented hypotheses are a reasonable starting portfolio, not a universal standard. The right result is not a perfectly balanced set of channels. It is a small number of explicit, comparable beliefs that can be tested without confusing relationship strength, marketing activity, or one lucky contract with repeatable customer acquisition.

The company can then make a better next decision: continue relying on a focused referral system, add targeted outbound, develop one real partner relationship, test content as a sourcing or influence mechanism, or stop a weak option before it consumes a team, a budget, and several months of attention.

Sources

Primary sources

• HubSpot, Annual Report for the year ended December 31, 2016. Used to illustrate how a mature company combined content-generated demand, direct inside sales, and agency referrals rather than treating them as isolated tactics.
• HubSpot, Annual Report for the year ended December 31, 2024. Used for dated figures on the scale and revenue contribution of HubSpot’s solutions-partner ecosystem.
• Canadian Radio-television and Telecommunications Commission, CASL guidance and frequently asked questions. Used to explain the principal Canadian requirements affecting commercial electronic outreach and the need to document the applicable basis for contact.

Open research

• Camuffo et al., “A Scientific Approach to Entrepreneurial Decision-Making: Large-Scale Replication and Extension,” Strategic Management Journal, 2024. Four randomized trials involving 759 firms; provides the strongest general evidence used here for explicit hypotheses, disciplined testing, and termination of weak ideas.
• Humă and Stokoe, “Resistance in Business-to-Business ‘Cold’ Sales Calls,” Journal of Language and Social Psychology, 2023. Analysis of 159 authentic calls; used to explain why outbound tests must examine buyer resistance and conversational progress rather than counting calls alone.
• Terho, Salonen, and Yrjänen, “Toward a Contextualized Understanding of Inside Sales,” Journal of Business & Industrial Marketing, 2022. Field research across eight firms; used to distinguish prospect-focused, account-focused, inbound, and outbound sales-development contexts.
• Schmitt, Skiera, and Van den Bulte, “Referral Programs and Customer Value,” Journal of Marketing, 2011. Longitudinal analysis of approximately 10,000 bank customers; used for evidence that referred customers can differ in retention and value, with important limits by segment and context.
• Dose et al., “Unintended Reward Costs: The Effectiveness of Customer Referral Reward Programs for Innovative Products and Services,” Journal of the Academy of Marketing Science, 2019. Used to caution against assuming that formal referral rewards are always incremental or economical.
• Hada, De Bruyn, and Lilien, “Horizontal Referrals in B2B Markets,” Journal of Marketing Research, 2024. Used to show that referral quality can be shaped by trust, dependence, and the referring firm’s commercial interests.
• Homburg, Vomberg, and Muehlhaeuser, “Design and Governance of Multichannel Sales Systems,” Journal of Marketing, 2020. Matched manufacturer–partner evidence used to explain channel conflict, information asymmetry, and the need to align governance with direct or indirect channel design.
• Soares, Bortoluzzo, and Barros, “Determinants of the Choice of Marketing Channels by Corporate Clients,” Journal of Information Systems and Technology Management, 2012. Survey of 505 corporate technology customers; used to explain why relationship intimacy and solution complexity can favor direct supplier involvement.
• “Digital Content Marketing on Social Media Along the B2B Customer Journey,” Industrial Marketing Management, 2024. Experimental evidence used to connect content effectiveness to its relevance and timing within the buyer’s decision process.
• du Plessis, “A Scoping Review of the Effect of Content Marketing on Online Consumer Behavior,” SAGE Open, 2022. Review of 32 studies used to identify the fragmented evidence base and the need to measure customer movement rather than assume that content activity causes sales.
• Peng, Li, and Liu, “How Social Network Influences the Growth of Entrepreneurial Enterprises,” SAGE Open, 2022. Meta-analysis of 31 samples used to distinguish the potential value of network size and strong ties from the assumption that a dense personal network is automatically scalable.