New B2B offers: identify and test opportunities

New B2B offers: identify and test opportunities

To develop a new B2B offer, turn frontline observations into clear hypotheses, then test them with the relevant customers. A repeated request deserves attention. It does not yet establish a large enough market, an acceptable price or the ability to deliver profitably.

To develop a new B2B offer, turn frontline observations into clear hypotheses, then test them with the relevant customers. A repeated request deserves attention. It does not yet establish a large enough market, an acceptable price or the ability to deliver profitably.

To develop a new B2B offer, turn frontline observations into clear hypotheses, then test them with the relevant customers. A repeated request deserves attention. It does not yet establish a large enough market, an acceptable price or the ability to deliver profitably.

This guide helps you select opportunities, prepare an initial test and decide what comes next before committing to substantial development.

Key points

  • Internal listening reveals possibilities; customer conversations and tests examine their commercial reality.

  • A meeting, a letter of intent and a paid order provide different strengths of evidence.

  • Test the need, the buying decision and the economics of delivery.

Where can opportunities appear?

Examine six sources: requests outside the catalogue, workarounds developed by teams, repeated reasons for lost deals, services provided without separate billing, unexpected uses of existing offers and needs that remain poorly served.

Record who expresses the need, the situation and its consequence. Repetition can justify investigation, but an infrequent request with a significant impact can matter too. New regulation, equipment changes or a customer acquisition may reveal an emerging need.

Process mapping can reveal services already provided informally. An organisational assessment can bring together observations dispersed across sales, support and operations.

Distinguish a signal from a validated need

Examine the range of customers, urgency, existing alternatives and the cost of the current situation. Count distinct companies and contexts: ten requests from one account do not equal ten potential customers.

Internal observations are useful but selective. Sales hears from certain contacts, support sees problems and operations sees delivery difficulties. Compare these views with customer conversations and, where available, reasons for lost deals.

Identify users, influencers and budget holders. A technician may advocate an additional service without having purchasing authority. Test the proposition with people able to get it bought.

State an offer hypothesis

Describe the target segment, problem, desired result, proposed solution, delivery resources and economic assumptions. For example: “For maintenance managers responsible for critical spare parts across several sites, periodic stock checks could reduce incidents caused by missing parts. The need, price and delivery cost remain to be tested.”

Steve Blank’s Customer Development approach tests business-model hypotheses against customer behaviour. We apply that principle to offer exploration in an established company. The worksheet below is a Spentia adaptation. See What’s A Startup? First Principles (2010).

Separate observations from assumptions. A received request is a fact to document. Acceptable price, market volume and margin remain hypotheses until examined.

Choose the first opportunities to test

Compare the importance of the need, access to customers, delivery resources, alternatives and the cost of an initial test. Consider the effect on existing offers: does it complement them, replace something already sold or add work that is hard to absorb?

Choose a test that resolves the important uncertainty. More satisfaction interviews will not establish an acceptable price. If delivery capability is uncertain, measure the work required during a paid pilot.

A first customer can help shape the offer. To assess repeatability, approach others in the same segment and track requested changes. Bespoke work can be viable, but its economics differ from a standardised service.

Organisation and assessments

Make organisational decisions with a clear assessment

Our assessments identify practical changes to help your teams and processes work together.

Run an initial customer test

Begin with current practice: how the customer handles the problem, previous attempts, purchase triggers and budget approval. Then present a proposition specific enough to support a decision: scope, expected result, price or pilot terms, timing and responsibilities.

Response

What it tells you

What it does not yet establish

Expressed interest

The topic receives a positive reaction

Available budget or a future purchase

Time and data committed to a test

The customer accepts an exploration effort

Willingness to pay the target price

Letter of intent

An intention is formalised, subject to its terms

Payment or a certain purchase

Paid pilot or order

A purchase is accepted on the proposed terms

Sustained profitability, renewal or a broad market

Set continuation criteria before receiving the answers and record reasons for refusal. A small test supports learning and the next decision; it does not statistically validate the entire market.

An example: from a frontline request to an offer test

This fictional teaching example claims no client outcome. Technicians in an industrial maintenance company report requests to check spare-parts stock during visits. The task is outside the contract.

The potential offer is a documented periodic check of selected critical parts. Before developing it, the company needs to establish the problem with maintenance managers and buyers, understand existing checks, and estimate the additional work and responsibilities.

An initial paid test could cover one site and a defined list of parts. Scope, price and the customer deliverable would be agreed in advance. The company would track commercial responses, actual working time, requested adaptations and margin after directly related costs.

Continuation criteria could combine several purchases in the target segment, delivery cost compatible with price and sufficiently similar needs to repeat the service. Set the expected number of purchases and learning budget for the context. No result is assumed; the next decision depends on the test.

Tool: offer hypothesis worksheet

Field

What to record

Customers and buyers

Segment, users, influencers and budget holder

Need

Specific situation and consequences for the customer

Available evidence

Requests, interviews, lost deals or existing services

Current alternative

The solution used, including leaving things unchanged

Proposed offer

Scope, deliverable and limits

Economics to test

Price, delivery cost, margin and adaptations

Test

Proposition, customers, timing and budget

Decision criteria

Conditions to continue, adjust or stop

Innovation can start with a detailed understanding of work and customer requests. An operational assessment can identify and organise opportunities. Commercial validation then requires dedicated customer conversations and tests.

Frequently asked questions

Can we rely only on sales feedback?

Can we rely only on sales feedback?

It is a starting point. Compare it with support, operations and direct conversations with the customers concerned. Where possible, include accounts that do not buy or have chosen an alternative.

How can we test before developing at scale?

How can we test before developing at scale?

Offer a limited scope, potentially delivered manually, on clear terms. Depending on the uncertainty, a prototype or demonstration may be needed before a first sale. Keep investment proportionate to what the test can establish.

How do we distinguish a one-off request from a repeatable offer?

How do we distinguish a one-off request from a repeatable offer?

Look for a common need, comparable result and reusable delivery approach. Measure adaptation costs. Some customisation can work if pricing and organisation support it; repeatability does not require an identical service every time.

What role can AI play in analysing needs?

What role can AI play in analysing needs?

It can help classify requests, compare customer comments and retrieve similar situations from authorised data. Check the groupings and preserve access to sources. An automated summary or simulated customer does not replace a response from a real customer.

Sources

  • Steve Blank, What’s A Startup? First Principles, 25 January 2010.

  • The worksheet and example are Spentia methodological adaptations for B2B offer exploration. No launch results are claimed.

What sets us apart.

Five choices in our method that set Spentia apart from traditional consulting.

1. Organisation-wide interviews in 3 days.

No sampling. Aria interviews everyone within the agreed scope in 3 days, whether that means 20 people or 5,000.

1. Organisation-wide interviews in 3 days.

No sampling. Aria interviews everyone within the agreed scope in 3 days, whether that means 20 people or 5,000.

2. Senior human analysis, using B-ADSc.

2. Senior human analysis, using B-ADSc.

Demonstrated causal relationships, not correlations. Our experts use decision algebra to distinguish root causes from symptoms.

3. Control over your technology and data.

3. Control over your technology and data.

Data hosted in France. Strict compliance with the EU AI Act and GDPR.

4. A guaranteed four-week turnaround.

4. A guaranteed four-week turnaround.

Your action plan delivered in 4 weeks. Recommendations with estimated costs and benefits, priorities agreed with you, and a clear schedule.

5. Full traceability.

5. Full traceability.

Evidence, not assertions. Each conclusion is weighted according to how often it appears in the interview responses that support it.

What sets us apart.

Five choices in our method that set Spentia apart from traditional consulting.

1. Organisation-wide interviews in 3 days.

No sampling. Aria interviews everyone within the agreed scope in 3 days, whether that means 20 people or 5,000.

1. Organisation-wide interviews in 3 days.

No sampling. Aria interviews everyone within the agreed scope in 3 days, whether that means 20 people or 5,000.

2. Senior human analysis, using B-ADSc.

2. Senior human analysis, using B-ADSc.

Demonstrated causal relationships, not correlations. Our experts use decision algebra to distinguish root causes from symptoms.

3. Control over your technology and data.

3. Control over your technology and data.

Data hosted in France. Strict compliance with the EU AI Act and GDPR.

4. A guaranteed four-week turnaround.

4. A guaranteed four-week turnaround.

Your action plan delivered in 4 weeks. Recommendations with estimated costs and benefits, priorities agreed with you, and a clear schedule.

5. Full traceability.

5. Full traceability.

Evidence, not assertions. Each conclusion is weighted according to how often it appears in the interview responses that support it.

What sets us apart.

Five choices in our method that set Spentia apart from traditional consulting.

1. Organisation-wide interviews in 3 days.

No sampling. Aria interviews everyone within the agreed scope in 3 days, whether that means 20 people or 5,000.

1. Organisation-wide interviews in 3 days.

No sampling. Aria interviews everyone within the agreed scope in 3 days, whether that means 20 people or 5,000.

2. Senior human analysis, using B-ADSc.

2. Senior human analysis, using B-ADSc.

Demonstrated causal relationships, not correlations. Our experts use decision algebra to distinguish root causes from symptoms.

3. Control over your technology and data.

3. Control over your technology and data.

Data hosted in France. Strict compliance with the EU AI Act and GDPR.

4. A guaranteed four-week turnaround.

4. A guaranteed four-week turnaround.

Your action plan delivered in 4 weeks. Recommendations with estimated costs and benefits, priorities agreed with you, and a clear schedule.

5. Full traceability.

5. Full traceability.

Evidence, not assertions. Each conclusion is weighted according to how often it appears in the interview responses that support it.

ARTICLE

Successful AI transformation starts with how work gets done

Businesses that turn AI into lasting change start with the work, the tools people actually use and the organisation’s ability to make decisions.

ARTICLE

Successful AI transformation starts with how work gets done

Businesses that turn AI into lasting change start with the work, the tools people actually use and the organisation’s ability to make decisions.

ARTICLE

Successful AI transformation starts with how work gets done

Businesses that turn AI into lasting change start with the work, the tools people actually use and the organisation’s ability to make decisions.

Subscribe to our newsletter

Subscribe to our newsletter

Le signal Spentia: practical insights on AI, transformation and talent.

Each edition covers developments in organisational transformation: tools, methods, lessons from practice and the people involved.

Le signal Spentia: practical insights on AI, transformation and talent.

Each edition covers developments in organisational transformation: tools, methods, lessons from practice and the people involved.

Our newsletter is in French. You can unsubscribe at any time using the link in each issue.

Our newsletter is in French. You can unsubscribe at any time using the link in each issue.

Spentia SAS - 1 rue de Stockholm, FR-75008 Paris

Spentia SAS - 1 rue de Stockholm, FR-75008 Paris