Run a Pricing and Packaging Refresh

Aim: Grow the Business → Objective: Capture more of the value
you already create → Initiative: Run a disciplined pricing and
packaging cycle, competitive analysis, willingness-to-pay research,
scenario modeling, controlled rollout, post-launch monitoring

Fits well at: $500K–$25M businesses that haven't revisited pricing
in over a year, which is almost all of them. Also critical when
launching a new line of business, where the adjacent offer needs to be
priced correctly relative to the parent without cannibalizing it. Most
businesses leave money on the table because they price once and never
revisit; this initiative treats pricing as a recurring strategic motion,
not a one-off project.

What this is

A repeatable quarterly cycle for evaluating and adjusting your prices
and package shape. Each cycle runs through five phases: competitive
landscape scan, willingness-to-pay research with existing and prospective
customers, financial-model scenario branching to see the revenue and
margin impact of each option, a controlled rollout to a subset of
customers, and post-launch monitoring to confirm the numbers land where
the model predicted.

The goal isn't "raise prices." It's to ensure your packaging reflects
the value customers actually receive, your price band is defensible
against competitors, and your margins support the growth plan. Sometimes
the answer is a packaging restructure with no price increase at all.

What "done" looks like

• A competitive pricing landscape doc, refreshed quarterly, living in
  the Knowledge Base

• 15+ willingness-to-pay interviews synthesized with price sensitivity
  bands identified

• At least three pricing scenarios modeled in the financial model with
  revenue, margin, and churn impact projections

• A rollout plan with a control group and success criteria defined
  before launch

• Post-launch monitoring dashboard tracking adoption, upgrade/downgrade
  rates, and margin impact for 8 weeks

• A written pricing decision log capturing what was changed, why, and
  what the data showed

• A recurring quarterly pricing review on the calendar

The work, decomposed

• Sub-objective: Scan the landscape → competitor pricing, packaging
  shapes, positioning gaps

• Sub-objective: Research willingness to pay → customer interviews,
  survey design, price sensitivity analysis

• Sub-objective: Model the scenarios → revenue impact, margin
  sensitivity, churn risk, cannibalization analysis (for new lines)

• Sub-objective: Roll out controlled → cohort selection, grandfather
  rules, communication plan

• Sub-objective: Monitor and decide → adoption tracking, margin
  confirmation, decision to expand or revert

How it runs in Happee AI

Agents involved

• Research agent. Runs the competitive landscape scan and the
  willingness-to-pay interview program. Maintains the competitive
  pricing doc in the Knowledge Base, synthesizes interview findings
  into price sensitivity bands, and flags shifts between cycles ("three
  competitors raised their mid-tier by 15–20% since last quarter").

• Finance agent (Alex). Builds the pricing scenario models ,
  revenue, margin, and churn projections for each option. Runs
  cannibalization analysis when a new line is being priced alongside
  the core. After rollout, monitors actual vs. projected impact and
  prepares the quarterly pricing review memo.

• Sales agent. Conducts willingness-to-pay conversations during
  existing customer touchpoints. Handles rollout communications ,
  renewal notices, upgrade/downgrade offers, grandfather notifications.
  Reports customer sentiment and objections back to the research agent.

• Marketing agent. Updates pricing page copy, comparison tables,
  and sales collateral when packaging changes. Ensures all
  customer-facing materials reflect the new structure before rollout.

Where the work lives

• Knowledge Base, competitive landscape doc, willingness-to-pay
  synthesis, pricing decision log, rollout playbook, all versioned

• Financial Models, pricing scenarios as named branches (current,
  option A, option B, new-line pricing), each with revenue and margin
  projections

• Analytics time-series, price realization, upgrade/downgrade
  rates, ARPU by cohort, margin by tier, churn by pricing change

• Dashboards (Live Views), post-rollout monitoring dashboard
  tracking adoption, revenue impact, and customer movement between tiers

• Directory, customer segments tagged by current tier, pricing
  cohort (control vs. rollout), and grandfather status

• Tracker, rollout tasks as work items in a "Pricing Cycle"
  workflow (scan → research → model → rollout → monitor → decide)

• Channels, #pricing for cross-functional coordination; quarterly
  review findings posted here

• Recurring meetings, quarterly pricing review, with prepared
  memo from Alex

Rhythms

• Quarterly, full pricing cycle: landscape scan, willingness-to-pay
  refresh, scenario modeling, rollout decision

• Weekly (during rollout), adoption and margin monitoring, customer
  sentiment check

• Monthly (between cycles), competitive landscape watch, price
  realization tracking

Data flows

• Competitor pricing changes → landscape doc → scenario assumptions

• Customer interviews → price sensitivity bands → scenario inputs →
  financial model

• Rollout cohort behavior → time-series metrics → monitoring dashboard
  → expand/revert decision

• Pricing decisions → decision log → next cycle's baseline

Before Happee AI vs. with Happee AI

Day in the life

Monday morning, start of Q3 pricing cycle. The research agent has
already refreshed the competitive landscape doc overnight, two
competitors restructured their packaging last month, one dropped its
entry tier entirely, and the other bundled analytics into mid-tier. In
#pricing, Alex posts a brief: "Current ARPU is $127, up from $118 last
cycle. Three scenarios modeled, A keeps current structure with a 10%
band increase, B restructures mid-tier to match the competitor bundle,
C introduces an annual commitment discount. Margin impact ranges from
+3% to +8%. Recommend we run willingness-to-pay interviews this week
before choosing." The owner reviews the scenarios, approves the
interview guide, and the research agent schedules 15 calls from the
Directory. By Friday, the synthesis is in, customers value the bundle
but resist the annual lock-in. Alex updates the model: option B with
monthly billing wins on both revenue and retention. The owner approves
a controlled rollout to 20% of new customers next month, and the sales
agent drafts the rollout messaging. Alex offers: "Want me to set up the
quarterly pricing review as a recurring cadence? I'll prepare the
landscape scan and scenario memo each quarter so we never go a full year
without looking at this again." The owner says yes. The loop closes.

Related Initiatives

• Customer success and expansion program
• Marketing analytics and attribution
• Financial modeling and scenario planning
• Build an outbound sales motion
• Validate and launch an adjacent product line

Features in play: Knowledge Base · Financial Models · Analytics & Dashboards · Directory · Tracker · Workflows · Channels · Meetings · Brand & Materials · Reminders & Decisions · Agents