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Cost-benefit analysis

As explained in Effective Conversational AI

Cost-benefit analysis is a comparison of the expected advantages of a change with the resources and expenses required to implement it.

A chatbot improvement can reduce user frustration yet demand substantial time, coordination, and technical complexity. Cost-benefit analysis compares those investments with expected direct and indirect gains. section 3.4.2 section 8.2.5

Assess a proposed change by considering:

  • Benefits, including improved containment and user experience. section 3.4.2
  • Costs, including implementation time, resources, complexity, and coordination across departments. section 3.4.2
  • Expected return, scaled by the volume of affected conversations. section 3.4.2
  • Operational risk, because added complexity creates more potential failure points. section 8.2.5

Simplifying an error-prone input

Suppose users must provide an alphanumeric membership number and frequently confuse letters with digits. A backend process can detect nine digits and add the shared alpha character, allowing a simpler question. Compare the implementation expense with reduced failures, lower user effort, and fewer agent handoffs; preserve retries, alternate paths, or escalation when the process fails. section 8.2.5

Figure 3.17 An effect-effort matrix visualizes the relationship between the effort required and the potential effect of a proposed change.
figure

Use the effect-effort matrix to compare the potential effect of a proposed change with the effort required to implement it. section 3.4.2

How Effective Conversational AI covers it

How deep it goes
Explains benefits, costs, volume, financial effect, and effort, but does not provide a formal accounting method.
Examples
Uses agent-transfer costs, an effect-effort matrix, and a backend simplification for confusing membership-number input.
What it assumes
Assumes a documented problem, proposed remedy, conversation-volume data, and metrics for user or operational effects.
What you can do after
Evaluate chatbot changes by estimating value, implementation effort, affected volume, and operational risk.
How it connects
Connects prioritization with containment, user experience, conversation volume, implementation effort, and escalation.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Effective Conversational AI. The section links point to the parts of the book it draws on.