competitive-response-modeler

name	competitive-response-modeler
description	Models multi-round competitive interactions: who reacts, how fast, with what move, and what payoff outcome - using reaction functions, commitment value, and signaling theory. Use when planning a pricing change, market entry, product launch, capacity addition, or any move where competitor reaction will determine whether the move pays off.

Competitive Response Modeler

The move only matters if you correctly predict the reaction.

What this skill is

A workflow for simulating competitive interactions across multiple rounds: identify likely respondents, characterize each competitor's profile and capacity to respond, model the reaction function, compute the post-reaction payoff, and stress-test commitment moves (capacity, contracts, public statements) that change the game. Built on the Industrial Organization (IO) economics of strategic moves - entry deterrence, predation, accommodation, and signaling.

What it solves

• One-period payoff thinking ignoring the rival's response
• "We'll just match" assumptions that miss asymmetric capacity to respond
• Underestimating the value (or cost) of public commitment
• Mistaking accommodation for cooperation in repeated interactions
• Pricing or capacity moves that triggered a price war the analysis didn't foresee

When to invoke

• Pricing changes (cut, raise, repackage)
• New market entry - anticipating incumbent response
• Product launch in a category with strong rivals
• Capacity additions (manufacturing, sales force, channel)
• Major Mergers and Acquisitions (M&A) move that re-orders the competitive set
• Public strategic announcements where signaling effect matters

Phase 1: Identify the competitive set

List every competitor whose response could materially affect the move's payoff. For each:

• Market share
• Cost position (low-cost, mid, premium)
• Strategic focus (where this product or segment sits in their priorities)
• Recent moves (last 12 months)
• Public posture (aggressive, accommodating, niche)

Cut the list to 3-5 material respondents. Modeling all isn't useful.

Phase 2: Profile each competitor's response capacity

For each:

• Means - can they technically and financially respond? (capacity, capability, capital)
• Motive - do they care about this move? Is it a core market or peripheral?
• Opportunity - internal alignment, leadership focus, organizational bandwidth
• Speed - how fast can they move? days, weeks, quarters?
• History - what did they do the last 3 times something like this happened?

A competitor with means but no motive may not respond. A competitor with motive but no means is loud but harmless. The dangerous response comes from competitors with all three.

Phase 3: Build reaction functions

For each competitor, hypothesize the reaction function: action → reaction.

Examples:

• If we cut price 10% in segment X → competitor Y likely cuts 8% within 30 days because their Chief Executive Officer (CEO) has publicly committed to share leadership
• If we add capacity Z → competitor W likely waits and adds capacity only after observing demand absorption
• If we announce feature F → competitor V probably announces vaporware within 60 days

For each reaction:

• Probability (low / medium / high)
• Magnitude
• Timing
• Reasoning chain

Phase 4: Multi-round payoff matrix

Build a tree of plausible action-reaction sequences:

Round 0: We move
Round 1: Each competitor reacts (or not)
Round 2: We respond to their response
Round 3: New equilibrium or further escalation

At each terminal node, compute payoff (share × margin × volume, or Net Present Value (NPV)).

The headline question is not "is round 0 profitable?" but "is the terminal equilibrium profitable?" A 10% price cut that captures share but settles into a permanently lower-margin equilibrium can destroy value even if round 0 looks like a win.

Phase 5: Commitment moves

Standard game theory: making yourself less flexible can improve outcomes if it changes the rival's calculation.

Commitment types:

• Capacity commitment - invest in capacity that only pays back at high volume, signaling commitment to compete hard
• Long-term contracts - lock customers, raise rival's cost of poaching
• Public statements - CEO commitment publicly disclosed, harder to walk back
• Most-Favored-Nation (MFN) clauses - make discounting expensive (price war deterrent or cartel facilitator)
• Burning bridges - exit an alternative market to focus, signaling commitment

Commitment cuts both ways: it strengthens you when credible but boxes you in when wrong. Score each commitment for credibility (1-5) and reversibility cost.

Phase 6: Signaling

Moves carry information about your type, intentions, and capacity. Consider what each move signals:

• Tough type - willingness to absorb short-term loss to discipline rivals
• Accommodating type - willingness to share the market
• Limited capacity - easier to enter against
• Unlimited capacity - entry deterrence

Test the signal:

• What inference would a rational competitor draw from this move?
• Could you signal the same thing more cheaply with a different move?
• Is there a counter-signal you should send to override an unwanted inference?

Phase 7: Game-theoretic check - repeated versus one-shot

Most real competitive interactions are repeated. Apply the folk-theorem intuition:

Interaction	Likely equilibrium
One-shot, no future	Prisoner's-dilemma defection - undercut, take share
Repeated, infinite horizon, observable actions	Cooperation sustainable via grim trigger or tit-for-tat
Repeated, finite horizon	Unravels to defection (unless reputation effects with asymmetric information)
Many small rivals	Coordination collapses; act like one-shot
Few large rivals	Implicit coordination is possible (legal and dangerous areas - flag)

The recommendation must be consistent with the time horizon of the interaction.

Phase 8: Recommendation

Synthesize:

• The move
• Expected reactions per competitor with probability and magnitude
• Terminal equilibrium with payoff versus status quo
• Commitment moves to deploy (or avoid)
• Signals being sent (intended and inadvertent)
• Triggers that would cause us to retreat or escalate
• One unilateral move that improves our position even if no one reacts (insurance)

Output

• Competitor profile sheet (means, motive, opportunity, speed, history)
• Reaction function per competitor with probability and reasoning
• Multi-round action-reaction tree with payoffs
• Commitment-moves shortlist with credibility scoring
• Signaling matrix (signal sent → likely competitor inference)
• Equilibrium projection with payoff versus status quo
• Trigger conditions for retreat or escalation
• One robust move that improves position regardless of reaction

Operating rules

Always

• Identify 3-5 material respondents, not the whole market
• Score each on means, motive, opportunity, and speed
• Compute payoff at terminal equilibrium, not just round 0
• Match the equilibrium concept to the time horizon
• Test commitment moves for credibility

Never

• Assume rivals will accommodate
• Use one-shot logic in a clearly repeated interaction
• Make commitments you can't sustain
• Move first without a contingency for retaliation
• Skip the signal check on any public action