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64 Cards in this Set

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Salesforce Models: Personal Selling -- Selectivity
Company can selectively target its marketing effort
e.g., High-value accounts only
Salesforce Models: Personal Selling -- Interactive
Salespeople can tweak messages based on feedback
Relay field knowledge to improve product and/or service
Salesforce Models: Personal Selling -- People
Recruiting, Training, Motivating, Rewarding, Retaining
More complex than placing ads
Salesforce Models: Personal Selling -- Costly
Cost per sales contact (2000): $169-500 per sales call
Compare with magazine ad insertion: $500K for 20M viewers
Salespeople Functions
Prospecting Finding & cultivating new customers
Presenting Providing information to existing and prospective customers
Selling Closing the sale
Problems Problem Solving: Determining how to address problems
Servicing Rendering technical assistance
Relationships Establish long-term partnerships with customers
Information Gathering info about customers and competitors
Analyzing Assessing sales potential
Allocating Directing sales effort to different resources
Model: GEOLINE
Organization Decisions
-Salesforce structure
-Salesforce sizing
-Territory design
Model: SYNTEX
Model: CALLPLAN
Allocation Decisions
-Deploy resources
-Products, Prospects
-Call planning
Model: MSZ
Control Decisions
-Compensation
-Evaluation
-Motivation
Salesforce Sizing & Allocation: Intuitive Methods -- Afford
“What we can afford”
Salesforce Sizing & Allocation: Intuitive Methods -- % Sales
Salesforce expenditure = percentage of sales, e.g., 5%-8%
Similar: Historical norms or competitor spending
Size = (5% of Sales) / (Average cost of salesperson)
Salesforce Sizing & Allocation: Intuitive Methods -- Breakdown
Breakdown of sales forecast to number of salespeople
Number = (Forecasted Sales) / (Ave. Rev./ Salesperson)
Salesforce Sizing & Allocation: Intuitive Methods -- Problems
Individual accounts can differ from average
Can not know optimal size before calculating allocation
Salesforce Sizing & Allocation: Market-Response -- Sales Entity
Anything associated with potential sales
Customer, Prospect, Segment, Product, Geography
Salesforce Sizing & Allocation: Market-Response -- Function
Determine response function: Sales = f(sales in new entity)
Salesforce Sizing & Allocation: Market-Response -- Allocate
Deploy certain level of resources to each entity to max. profit
Salesforce Sizing & Allocation: Market-Response -- SYNTEX
Pharmaceutical sales firm, with field salesforce
7 drugs (eg, Naprosyn), 9 physician specialties (dermatology)
Considering increasing size of salesforce: 433  473 (background for developing SYNTEX model)
Salesforce Sizing & Allocation: Market-Response -- Sum
Add up all entities to arrive at total Sales
Salesforce Sizing & Allocation: Market-Response -- Goal
Allocate sales efforts to maximize total profits
SYNTEX: Steps for Sales Allocation Model
see slide 7
SYNTEX Model Examples -- C-Tek
Industrial materials supplier
US sales = $100M, 78 salespeople, 14 branches
SYNTEX Model Examples -- Managers
90 minute training sessions with managers
**Estimate sales in 3 years with varying salesforce allocations**
SYNTEX Model Examples -- Results
2 of 14 branches over-staffed; 3 under-staffed
**Profits increased 4% just by re-allocation**
Profits increased additional 7% by adding 25-30 new people
SYNTEX Model Examples -- S&Z
Sinha and Zoltners (S&Z) (2001) studied 50 projects
Average improvement through re-allocation: 4.5%
28% from size change; 72% from re-allocation
Extending the SYNTEX Model: Re-Allocation -- Limitations
SYNTEX Limitations: Static, Sales effort only
**Big limit: Assumes no interactions between segments/ products**
Sales entities = Territories: Little impact
Sales entities = Products: Potential big impact (one product may be considered sub for another)
Extending the SYNTEX Model: Re-Allocation -- ReAllocator
ReAllocator = SYNTEX + Interaction Effects
Extending the SYNTEX Model: Re-Allocation -- ReAllocator Advantages
Incorporates interaction effects
Extending the SYNTEX Model: Re-Allocation -- Disadvantages
Best suited for repetitive buying (hospital supplies)
Sales Territory Design -- Territory
Physical area assigned to salesperson
Territory carved out of total market
Sales Territory Design -- Balance
Opportunities & workload equal across territories
Important for “fairness” of commission
Sales Territory Design -- Imbalance
Most companies (up to 80%) imbalanced
Too many salespeople in some areas; not enough in others
Could reduce travel time by 10-15% with balance
Sales Territory Design -- Dynamic
Territories tend to become unbalanced over time
Sales Territory Design -- Goals
Easy to administer: By ZIP code or county
Easy to estimate: Known number of targets (ie 5 hospitals in area)
Easy to travel: No/ few geographic boundaries
Sales Territory Design: GEOLINE -- Objectives
Equalize workload/ potential over territories
Create physically contiguous (touching) territories
Minimize travel time across territory 9on exam ... adjust bourndary between territory to accomodate sales people travel)
Sales Territory Design: GEOLINE -- breakdown
Breakdown Breaks down entire market into SGUs
SGU Standard Geographic Unit: ZIP code, County
Sales Territory Design: GEOLINE -- COSTA
Adds profit influence; Allocate over Sales Coverage Units SCU
Salesforce Compensation -- Objectives
Compensation: Reward for performance
Motivation: Encourage to work harder (quota + bonus)
Direction: Emphasize certain products/activities
Example: Higher commission % for featured product
Salesforce Compensation -- Monetary
Salary: Money for time worked
Commission: % of Sales generated
Bonus: Money for attaining quota (company-set goal)
Salesforce Compensation -- Non-monetary
Recognition: Salesperson of the month
Contests: Highest sales per quarter
Awards: All-expenses paid trip
Salesforce Compensation -- Combination
Most popular compensation plan (70%)
Salary + Commission (+maybe bonus)
Salesforce Compensation -- Evaluation
Plot out pay vs. performance for each salesperson
Salesforce Compensation: MSZ Model -- Conjoint
Uses conjoint analysis to design a bonus plan (on exam)
Salesforce Compensation: MSZ Model -- Purpose
Set individual sales quotas reflecting territory differences
Design common bonus plan awarding same pay for perform.
Example: Territory A: 10 big accounts, Terr. B: 20 small accts.
Can not do bonus based on number of accounts
Salesforce Compensation: MSZ Model -- Inputs
Sales potential per territory (secondary info available)
Salespeople’s assessments on their projected sales impact
**(i.e. individual sales response functions)**
+ personal worth of leisure time: “Utility” of bonus vs. leisure
Salesforce Compensation: MSZ Model -- Trade-Off
c influenced by salesperson desires: Utility of bonus vs. leisure

c = rate at which sales approaches max with increasing effort
Salesforce Compensation: MSZ Model -- Profit
Maximizes profits, incorporating idiosyncracies of salesforce
Improving Efficiency & Effectiveness of Sales Calls -- Sales Call
Physical visit by salesperson to account
Average 3.4 calls/day, 750 calls/year
Improving Efficiency & Effectiveness of Sales Calls -- Varies
Some calls routine; Existing long-term relationship
Some calls difficult; Prospects need a lot of convincing
Improving Efficiency & Effectiveness of Sales Calls -- Ideal
Spend more effort where likely response is high
Improving Efficiency & Effectiveness of Sales Calls -- Human
Salesperson tendency to “win” a sale, even at low likelihood
Improving Effectiveness of Sales Calls: CALLPLAN -- CALLPLAN
Interactive system to maximize return on sales efforts
Number of calls to make to each client & prospect per period (exam q ... what is call plan)
Improving Effectiveness of Sales Calls: CALLPLAN -- Period
Effort period = Planning period of salesperson (Quarter)
Response period = Planning period of firm (Year)
Improving Effectiveness of Sales Calls: CALLPLAN -- Allocation
Allocate effort across different accounts to maximize results
Marketing Channel Decisions -- Strategy
High-level decision: How to sell to target market
Directly to customers: Direct mail, Internet
Intermediary: Agents, Brokers, Wholesaler, Retailer
Contractual: Ownership of channel (Apple stores)Brokers
Marketing Channel Decisions -- Location
Number of outlets
Location of outlets
Owned by company (Wal-Mart)
Owned by intermediary, influenced by company (McDonald’s)
Marketing Channel Decisions -- Logistics
Physical distribution
Inventory
Efficiency of channel operations; high service, low costs
Marketing Channel Decisions: GRAVITY Model -- GRAVITY
Model to support location decisions
Marketing Channel Decisions: GRAVITY Model -- Factors
Customer profiles, Store image, Drive times, Competitors
Marketing Channel Decisions: GRAVITY Model -- Attractive
Size of store: Bigger = Better; selection, prices
Distance to store: Closer = Better (thing to know)
Marketing Channel Decisions: GRAVITY Model -- Gravity
Shoppers “pulled” to high-probability stores
Marketing Channel Decisions: GRAVITY Model -- Limits
Customers do not always want biggest stores, or closest
Hermes: Few small stores in selected locations
Ikea: Monster stores in few areas
Ignores access methods: Availability of CalTrain (or Parking!)
GRAVITY Model: Example -- alpha
Effect of store image (or size) (Default: a=1)
GRAVITY Model: Example -- beta
Effect of distance (Default: b=1)
GRAVITY Model: alpha and beta
alpha - effect of store image
beta - effect of store distance
GRAVITY Model: Example -- Database
Geodemographic databases: Shows where shoppers are