Sales wants lower prices; Product Marketing wants to defend the value of its products. When each side mainly questions the other's position, additional numbers alone achieve little. During an earlier role as an employee, Reiner drove an initiative that connected data preparation with joint pricing discussions. This experience belongs to his role within that company, not to a Corvendor client engagement.
Different perspectives stood behind the price proposal
Two perceptions met in the discussions. From Product Marketing's perspective, Sales mainly wanted lower prices to make selling easier. Sales, in turn, saw too little understanding of market dynamics in Product Marketing. These perceptions made it harder to assess a proposal against the particular situation.
The task was therefore larger than assembling another price list. Competitor information and inventory needed to be brought together for regular pricing discussions. Both teams needed a basis for examining when a pricing argument matched market conditions and when it did not.
Shared information first had to become usable
The work included gathering and cleaning competitor price lists alongside information about channel inventory and the company's own stock. This information was brought together for weekly pricing discussions. Reiner drove the initiative, connecting the data work with collaboration between Sales and Product Marketing.
An overview like this needs more than values placed side by side. A price comparison needs comparable products and terms; an inventory figure needs an identifiable date and scope. Incomplete or mismatched information must be treated accordingly. These are requirements for a useful shared basis, not a reconstructed technical specification of the historical system.
The important change appeared in the discussion
As the collaboration developed, the discussion changed. Sales also proposed price increases when products were scarce or the reputation of competing products was in question. Its starting position was no longer automatically a request for a lower price.
The point is not that higher prices would always have been better. A proposal could now be examined against the shared information. A discussion can then be organized around questions such as:
- Market: Which comparable offers and conditions support or challenge the proposed price?
- Availability: How do channel inventory and the company's own stock relate to the product's situation?
- Reasoning: Which observation supports the proposal, and what remains an assumption?
These questions illustrate the approach; they are not a transcript of a historical meeting. Shared data does not remove every conflict of interest. It does help teams examine arguments concretely rather than judge them only by the department they came from.
The achievement combined data work and collaboration
In Reiner's account, a significant achievement was bringing Sales and Product Marketing to a shared view of the situation. Opposing assumptions about departmental roles could give way to proposals based on the circumstances. That came from combining prepared information with regular discussion among domain experts.
This does not establish a measured increase in revenue or margin. A proposed higher price is not itself proof of business success. The experience described here concerns the improved basis and changed collaboration around the decision.
What could be added today
The historical initiative relied on data work and collaboration, not an AI solution. In a project today, analysis or machine learning could additionally examine relationships among inventory, sales patterns, price levels, and competition. That would be an extension requiring its own development and evaluation.
A model recommendation would provide another input to the discussion. It would not replace market knowledge or responsibility for a pricing decision. Observed relationships alone also do not establish what a particular price change would cause. The appropriate method depends on the available data and the specific question.
Begin with one product group and a shared question
For a comparable project, a pilot can focus on one product group and preparation for a regular pricing discussion. The teams agree on the information needed, who interprets it, and which decisions the overview should support. Corvendor can connect data preparation and software with that coordination among domain experts.
Several checks can establish whether the solution helps in daily work:
- Preparation: How much work does it take to assemble the required information in time?
- Shared basis: How often must inconsistent data or unclear definitions be resolved during the meeting?
- Decision: Are proposals and open assumptions reviewable, and do the teams reach an actionable decision?
- Follow-up: Can later outcomes be compared with the original reasoning and inform the next discussion?
These are possible checks for a new project, not retrospectively claimed measurements. Their value is in making improvements to the data and shared workflow visible before deciding on expansion.
A shared data foundation can change more than a report: it can change how teams examine their own assumptions. That requires data work, domain understanding, and collaboration to come together.
