Tool Evaluation
Part of Marketing technology procurement
Structuring a marketing software proof of concept
Choose the uncertainty, set acceptance cases and record what a limited marketing software proof of concept establishes.
A marketing software proof of concept answers one purchase-critical question in a limited setting. Before involving a supplier, define the task, expected result, evidence and stop point. The finding states what worked under the conditions used and what remains unknown about production use.
Choose one uncertainty
Start with a requirement that neither a written answer nor a prepared demonstration can settle. A corrected campaign source might need to reach a sales record, for example. State which part remains unproven and which purchase decision the result will inform. If the question is only which edition includes a feature, seek a written answer first.
Set the start and finish, internal owner, participating users, environment, supplier responsibilities and any cost or access approval. Keep the exercise small enough to explain a failed result. A sandbox result does not establish production capacity or resilience unless those conditions are also checked.
Set the acceptance cases
Write the expected result before the exercise begins:
Field / Question to answer
- Starting state
- Which safe records, roles and configuration are available?
- Action
- What does the ordinary user or connected system do?
- Expected result
- What must appear, where and by when?
- Exception
- What happens if a value is missing, corrected or rejected?
- Evidence
- Which screen, record or log will show the result?
- Owner
- Who judges the case and resolves disagreement?
Ask the team receiving the output to check its end of the task. In a sales hand-off, the receiving record matters as much as the marketer's sending screen. Note administrator intervention and manual repair: a possible result may still demand too much work to operate.
Control access and data
Use synthetic or approved sample information where it can answer the question. If real personal information is proposed, have the appropriate privacy and security owners assess its use, supplier access and handling before sharing. Define who can enter the environment, how access ends and what happens to the test data.
Record the edition, enabled components, integrations, roles, sample data and supplier setup. When comparing suppliers, give them the same business outcome and comparable conditions while allowing different technical routes. Note any material difference in preparation or access.
Comparison of Supplier Conditions in a Multi-Vendor Proof of Concept
- Business outcome
- Same target: successful hand-off from marketing to sales system
- Test environment
- Sandbox with identical configurations, roles, and integrations across suppliers
- Data used
- Synthetic customer records approved under privacy guidelines
- Access control
- Time-limited access with automatic deactivation post-test
Pros and Cons of Using Synthetic Data in a Proof of Concept
- Pro: Avoids privacy risks under APPsReduces exposure to breaches of the Australian Privacy Principles (APP 3) when handling solicited personal information.
- Con: May not reflect real-world complexitySynthetic data may lack edge cases present in actual customer records, potentially underestimating operational effort.
- Pro: Enables fair comparison across suppliersEnsures all vendors operate under identical conditions, supporting objective evaluation.
- Con: Requires upfront design effortCreating realistic synthetic datasets demands time and planning, especially for complex integrations.
Report what the proof established
For each case, record met, not met, inconclusive or not run, with the observation and setting. Keep a supplier explanation separate from an observed result. If missing setup caused a failure, record the proposed correction and decide whether to repeat the case. Preserve the original acceptance condition and document any agreed change.
End with the decision supported by the findings: continue to commercial review, request another check, revise the requirement or stop. List production questions separately, including migration, monitoring, support and scale. A limited proof can reduce uncertainty without establishing that the service is ready for live use.
