CASE STUDY

OPTIMIZING PRICING STRATEGY for a PRODUCT PORTFOLIO

METHODOLOGIES USED: 1. Qualitative Interviews 2. Adaptive Conjoint Analysis (ACBC)

o simPRO™ Preference Simulator

o Reactor™ Market Modeling & Forecasting

The following case study and data is from an actual CLIENT project, however the data has been de-identified to avoid sharing any sensitive client or confidential information and is intended for general information only.

First….let’s meet the CLIENT

LOOKING TO LAUNCH A NEW PRODUCT TO REPLACE AN EXISTING PRODUCT

Dominant market leader in…..

1

2 LOOKING TO MAXIMIZE PROFITS FOR ITS PRODUCT PORTFOLIO

3 SEEKING TO AVOID CANNIBALIZING EXISTING PRODUCT SALES

NETWORKED HOSPITAL EQUIPMENT

The CLIENT wanted to know…..

Research Objectives CENTRAL RESEARCH QUESTION: What impact will different pricing models and timing of our product launch have on our revenues and profits?

Research Objectives CENTRAL RESEARCH QUESTION: What impact will different pricing models and timing of our product launch have on our revenues and profits?

1. What is the purchasing process and who are the key

decision makers and influencers?

Research Objectives CENTRAL RESEARCH QUESTION: What impact will different pricing models and timing of our product launch have on our revenues and profits?

2.

1. What is the purchasing process and who are the key decision makers and influencers?

What is the preference for different product and non-product features and pricing models?

Research Objectives CENTRAL RESEARCH QUESTION: What impact will different pricing models and timing of our product launch have on our revenues and profits?

2.

1. What is the purchasing process and who are the key decision makers and influencers?

3. How do we maximize our 5 year profits?

What is the preference for different product and non-product features and pricing models?

P hases

23 IN-DEPTH INTERVIEWS Hospital C-Level Executives

Hospital Managers and Directors

GOALS Identify key decision makers Understand the decision-making process

PHASE Qualitative Analysis

1

2

We IDENTIFIED DOPs and CFOs as the DECISION MAKERS that should be the key TARGETS for sales and marketing.

In-Depth Interviews Key Findings 1

Identify key decision makers

GOALS 1

Risk Managers are not the decision makers CNOs and CIOs are potential influencers

In-Depth Interviews Key Findings 2

Understand the decision- making process

GOALS 2

Incremental changes or expansions to these networked hospital equipment typically fall under the operational & financial authority of DOPs…

In-Depth Interviews Key Findings 2

Understand the decision- making process

GOALS 2

…while larger additions or entire system upgrades require C-level approval.

Incremental changes or expansions to these networked hospital equipment typically fall under the operational & financial authority of DOPs…

In-Depth Interviews Key Findings 2

Understand the decision- making process

GOALS 2

Decision-making is based on:

…while larger additions or entire system upgrades require C-level approval.

Incremental changes or expansions to these networked hospital equipment typically fall under the operational & financial authority of DOPs…

→ Overall Cost of Ownership → Brand → System IT Architecture → Product Usability Features → Time to Market

442 WEB-BASED SURVEYS DOP, CFO, CEO, CIO, COO, CNO,

IT Director, VP Nursing

Determine intention of upgrading or replacing existing product Statistically validate preference for different pricing models

1

2

GOALS

PHASE Quantitative Analysis

Key Findings 1

Half of customers plan to upgrade within 2 years...

PLAN TO

UPGRADE/REPLACE

WITHIN 2 YEARS

53% PLAN A REPLACEMENT

28%

Surveys

Determine intention of upgrading or replacing existing product

GOALS 1

Key Findings 1 Surveys

…because of the following 5 reasons:

Product Lease Expires 60%...

Significant New Product Benefits Offered 61%...

Current Products No Longer Supported 46%...

Equipment No Longer Functions Properly &

Too Costly To Maintain 46%...

The Price Declines 16%...

To DETERMINE the most important PURCHASING DRIVERS, respondents were asked to select their most preferred product configuration in a conjoint exercise.

Key Findings 2 Conjoint Analysis

Statistically validate preference for different pricing models

GOALS

2

Brand Brand A Brand B Brand C

Upgrade Guarantee Plan S/W only Not Included S/W & H/W

Time to Commercial Availability 6 months 6 months Available Now

Service Levels Service Only Service with Parts None

Product Feature #1 Fast Slow Fastest

Product Feature #2 High Low Low

IT Architecture Hardware Hardware Web-based

Payment Model Purchase Lease Lease

Total Networked Equipment Price $160K for all units ($40K per unit)

$2.3K per month ($30K per unit purchase price

equivalent for 5 years of operation at 6% discount rate)

$3.9K per month ($50K per unit purchase

price equivalent for 5 years of operation at 6% discount

rate)

Total Price of Service Plan $6K for all units ($1K per unit)

$4K per month ($900 per unit)

$5K per month ($1.2K per unit)

⃝ ⃝ ⃝

Please select the product that you most prefer. Assume everything about the 3 products is identical EXCEPT for those differences presented in each scenario.

Choose the product you most prefer by clicking on of the buttons below.

By forcing respondents to make various trade-offs between features and price, it becomes possible to measure which product features are more likely to drive product selection.

Key Findings 2

0%

5%

10%

15%

20%

25%

30%

Total

Monthly Service Plan PriceBrandService LevelsUpgrade GuaranteePayment PlansPrice per UnitIT ArchitectureProduct Feature #1Time to MarketProduct Feature #2

Imp

ort

ance

27%

MONTHLY SERVICE PLAN PRICE is validated to be the MOST IMPORTANT purchase decision driver. 12% 13% 13% 12%

9% 6%

5% 4% 3%

Conjoint Analysis

Next, we used our proprietary market forecasting simulator, ™, to assess how the Client could maximize profits based on the survey and market data.

Revenue

Market Share Profitability

Conjoint Analysis

Historical Market Data

INPUT FORECAST FOR:

Combine survey findings with historical market data to model various strategic options

Determine impact of product and non-product features on:

Revenue Market Share Profitability

Assess likelihood of adoption of the new product

1

GOAL

PHASE Market Forecasting

2

Using Reactor™ Market Model, we TESTED alternative business decisions…

Market Model Scenario Modeling

CLIENT PROJECT System

Price

Monthly

Lease*

Service

Price

Months to

Launch

Unit cost

System

Unit Cost

Service

Long-Run

Annual

Units

Long-Run

Unit Share

Long-Run

Brand Unit

Sales

Long-Run Brand

Unit Share Year 1 Revenue** Year 2 Revenue** Year 3 Revenue** Year 1 Profit** Year 2 Profit** Year 3 Profit**

Discounted

3-Year Profit

Discounted

5-Year Profit

New Red Lease $55,000 $700 $300 0 $12,000 $50 1,914 10.46%

New Blue Purchase $55,000 $300 0 $12,000 $50 302 1.65%

New Red Purchase $55,000 $300 0 $12,000 $50 344 1.88%

New White Purchase $55,000 $300 0 $12,000 $50 158 0.86% 2,718 14.85% $116,240,492 $185,984,786 $185,984,786 $92,196,643 $147,514,629 $147,514,629 $348,420,503 $579,322,702

Legacy Red Lease $45,000 $677 $275 $10,400 $50 6,809 37.20%

Legacy Blue Purchase $45,000 $275 $10,400 $50 886 4.84%

Legacy Red Purchase $45,000 $275 $10,400 $250 1,161 6.34%

Legacy White Purchase $45,000 $275 $10,400 $250 585 3.20% 9,440 51.58% $530,815,537 $530,815,537 $530,815,537 $382,195,592 $382,195,592 $382,195,592 $1,042,200,103 $1,640,444,516

Client Total 12,158 66.43% $647,056,029 $716,800,324 $716,800,324 $474,392,235 $529,710,221 $529,710,221 $1,390,620,605 $2,219,767,218

Comp#1 Legacy Lease $35,000 $677 $200 1,332 7.27%

Comp#1 Legacy Purchase $35,000 $200 1,515 8.28% 2,847 15.55%

Comp#1 New Lease $40,000 $773 $200 0 444 2.43%

Comp#1 New Purchase $40,000 $200 0 569 3.11% 1,013 5.53%

Comp#1 Total 3,859 21.08%

Comp#2 Legacy Lease $55,000 $850 $250 354 1.94%

Comp#2 Legacy Purchase $55,000 $250 1,258 6.87% 1,612 8.81%

Comp#2 New Lease $55,000 $850 $250 0 183 1.00%

Comp#2 New Purchase $55,000 $250 0 491 2.68% 674 3.68%

*Assumes 5 Year lease with a 6% annual discount rate compounded monthly Comp#2 Total 18,304 2,286 12.49%

**Undiscounted

14.9%

51.6%

15.6%

5.5%

8.8%

3.7%

Long Run Unit Share

New

Legacy

Comp#1 Legacy

Comp#1 New

Comp#2 Legacy

Comp#2 New

Market Model Scenario Modeling

CLIENT PROJECT

…an iterative process…

… to QUANTIFY the SALES effects of alternative business decisions:

Market Model Key Findings:

Sales Team Guidance

A moderate software upgrade plan with specific features & limited hardware upgrade guarantees is most highly valued option… and leads to increased share, revenue, and profits

The different needs of buying & leasing customers was identified…

o …and those leasers that are potential brand switchers can be captured (or retained) with a specific combination of service and pricing plans

Switching costs are worth a 5% price premium for an incumbent product

Market Model Key Findings:

Product Portfolio Opportunity

If the existing product is taken off the market the new product can achieve

68.0%

14.4%

5.6%

9.6%

2.5%

Long Run Unit Share – NEW PRODUCT ONLY

New Client Product

Competitor #1 Legacy Product

Competitor #1 New Product

Competitor #2 Legacy Product

Competitor #2 New Product

68% market share.

Market Model

Because many customers preferred the legacy product, and really wanted an improved service plan, rather than an improved product…

However, we IDENTIFIED that the Client’s upgraded PRODUCT plan was NOT the OPTIMAL product strategy.

Key Findings: Product Portfolio Opportunity

…by leaving its existing product on the market the Client can achieve

32.8%

41.1%

10.4%

4.0%

9.3% 2.4%

Long Run Unit Share - OPTIMIZED PRODUCT PORTFOLIO

Client New Product

Client Legacy Product

Competitor #1 Legacy Product

Competitor #1 New Product

Competitor #2 Legacy Product

Competitor #2 New Product

Market Model Key Findings:

Product Portfolio Opportunity

Therefore we RECOMMENDED the Client introduce the new product at a premium price and retain the existing product as a value product.

(instead of 68%) market share...

…and an overall increase in profitability

74%

74%

$-

$100

$200

$300

$400

$500

$600

$700

Y1 Profit Y2 Profit Y3 Profit

Scheduled Launch

12-mo Pre-Announce

Market Model

Long-Run Brand Unit

Sales Long-Run Brand

Unit Share Year 1

Revenue** Year 2 Revenue** Year 3

Revenue** Year 1

Profit** Year 2

Profit** Year 3

Profit** Discounted

3-Year Profit Discounted

5-Year Profit

6K 33% $228M $364M $364M $174M $278M $278M $658M $1.1B

7.5K 41% $394M $394M $394M $275M $275M $275M $750M $1.2B

13.5K 74% $623M $758M $758M $449M $553M $553M $1.4B $2.3B

We DISCOVERED that the Client could see a 36% drop in PROFIT because of delayed purchases if a new product is pre-announced.

Key Findings: Pre-Announcement

64%

SAMPLE OUTPUT

Without the pre-announcement, customers will continue to purchase the current product, especially if they can also purchase a S/W upgrade plan.

FINDINGS and RECOMMENDATIONS

We provided guidance on product roll-out management, pricing strategies, product line management, including:

FINAL RECOMMENDATIONS

1

2

3

Schedule new product announcements very close to actual launch dates Minimizes short-term revenue reductions and optimizes financial returns.

Target DOPs and CFOs DOPs and CFOs are the primary decision-makers and should be the primary target for sales and marketing strategy.

Create a two-tiered product portfolio by keeping existing (legacy) product Profits are maximized when both the legacy and new products are available on the market.

Price the new product at a premium Customers who value the new product’s features are willing to pay a higher price. Price-sensitive customers will have a satisfactory value-priced alternative in the client’s portfolio.

4

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