Discover how comp plans and data driven sales activities should be used to deliver sales to your organization.

1. Sales Analytics
ACHIEVING WIN – WIN – WIN
• FOR THE COMPANY
• FOR THE CUSTOMER
• FOR THE SALES PERSON

2. Sales Analytics
The 400 LB Gorilla in the Room
 What sales volume does the employer need?
 What compensation does the sales person
want?
 Is it fair and equitable to both parties?
 Does it end up serving the customer?

3. Sales Analytics
 Design Compensation Plans
 75% base + 25% Commission = 100% Comp
on 100% Plan Achievement; Commission starts
at 75% of plan
 Capped or Uncapped
 Increasing % or declining % after 100%
 Financial Incentives - Benchmarks

4. Sales Analytics
 Example
 $3,000,000 Plan @ 25% margin = $750,000
 20% gross = Salary, Benefits, Expenses,
Commission (In this case $150,000)
 75K Base, 20K Benefits, 25K Expenses, 30K
Potential Commission
 Plan $250K Month / 75% Plan = $187,500
 $62,500/25 = $2,500 Pt. 1 Point pays $300

5. Sales Analytics
 Equitable to all Parties?
 Does the base salary hurt the company if the
territory does not perform?
 Will the sales person loose focus and
motivation if territory does not perform?
 Will the effort level be evident to the existing
customers and prospects?

6. Sales Analytics
 Example of Poor Performing Sales Assignment
 66% of Plan = $2,000,000 x.25 = $500,000
 Total Cost to employ = $120,000
 Criteria is 20% of GP = $100,000
 Additional Risk is 150% plan one month and
subpar performance the remainder of the year
($22,500 cost)+ $120,000 = 144.5K

7. Sales Analytics
 Design Compensation Plans
 100% Commission
 Starter base pay or draw
 Pays a percentage of the Gross Profit
 Percentage varies from single digits to 50%
based on GP and size of sale
 Pay is a function of Sales (Gross / Gross Profit)

8. Sales Analytics
 Risk for 100% Commission Sales
 Sales person accepts risk of low income or
fluctuating income vs High Income Level
 Company risk: Assumes production will occur
 Company risk: Marginal control of sales person
and unacceptable turnover rates

9. Sales Analytics
 When Do You Pay?
 Base: Bi-Weekly – Every 15 Days – Monthly
 Commission: Monthly, Quarterly, Annually
 Product Delivery - When the customer pays
 Commission: Independent time periods,
cumulative time periods - IMPORTANT

10. Sales Analytics
 Independent or Cumulative Quota
 Draw back F/Company: Sale person blows
quota away in one time period, receives big
check, poor performance remainder of the
year
 Salesperson benefits: Slow start to year or a
bad quarter does penalize remainder of the
year

11. Sales Analytics
 Marketing Efforts & Time Utilization
 Normally depends on the size of company and
staff
 Small company: Sales people and owners
become jugglers

12. Sales Analytics
 Marketing Efforts & Time Utilization
 Larger Companies:
 Marketing tools provided
 Lead generation support & CSR
 Website, Videos, Webinars, Newsletters,
Events, Trade Shows, New Product
Information, White Papers, Sales Engineers

13. Sales Analytics
 Key Factors
 Selling days or time available
 Average ticket item price / $’s per month
 Quota or sales person’s goal
 Close ratio as a % of presentations
 Close cycle in time / Gross margin %
 Compensation program

14. Sales Analytics
 Not All Sales Dollars are Created Equal
 ITW OPERATING RESULTS In Thousands
 Operating revenues $ 14,484
 Operating income $2,888 = 20%
 After-tax income from continuing operations
$1,890 = 13%

15. Sales Analytics
 ITEM 6. SELECTED FINANCIAL DATA - Flextronics
 ” Fiscal Year Ended March 31, 2015 (In thousands, except per share amounts)
 CONSOLIDATED STATEMENT OF OPERATIONS DATA: Net sales . . . $26,147,916
 Cost of sales . . . . . . . . . . . . . . . . . . . . 24,602,576 Restructuring charges . . — 58,648
 Gross profit . . . . . . . . . . . . . . . . . . . $1,545,340 = 5.9%
 Selling, general and administrative expenses . . . . . . . . 844,473
 Intangible amortization . . . . . . . . . . . . 32,035
 Restructuring charges . . . . . . . . . . . . . — 16,663
 Other charges (income), net(1) . . . . . . (53,233)
 Interest and other, net . . . . . . . . . . . . . 51,410
 Income from continuing operations before income taxes . . 670,655
 Provision for income taxes . . . . . . . . . 69,854
 Income from continuing operations . . . . . . $600,801 =
2.29%

16. Sales Analytics
 Sales Person – Measurements
 New business generation vs existing business
 Farmer or Hunter? You may need both……..
 Time management versus time available
 Account nurturing – One time order? Repeat
business? Annualized sales generated
 Training responsibility?

17. Sales Analytics
Sales Person – Measurements
 Churn rate factor – Account Turnover Issues……….
Yes or No?
 Number of presentations
 The power of a personal contact – Face, Video,
Phone, Text
 Closes / Close rate
 Team player?

18. Sales Analytics
 Outside Sales – Sales Process
 Prospect – Qualify
 Prepare
 Present – 70% of Shopping/Research done before
contact with a sales person
 Overcome objections
 Close
 Build relationships and trust throughout the process

19. Sales Analytics
 Quality of the Representative
 Unconsciously incompetent
 Consciously incompetent
 Consciously competent
 Unconsciously competent

20. Sales Analytics

21. Sales Analytics
 Where the Rubber Meets the Road
 Presentations Close Rate Time
Utilization
 Assume 20% Close rate of all actual
presentations

22. Sales Analytics
 Why They Don’t Close?
 Cannot afford – Wrong budget cycle
 Don’t need – Don’t trust
 Incumbent in place
 Competitor strengths
 Weak sales work – (Mean Sales Manager?)

23. Sales Analytics
 Simple Case Scenario
 316 Working days
 Subtract 11 paid holidays & 8 More for
Thanksgiving/Christmas
 Subtract 10 days of vacation
 Subtract 4 sick days
 Subtract 6 training days
 = 277 working days

24. Sales Analytics
 Simple Case Scenario
 100% Commission Plan
 Typical order generates $1,500 for the rep
 Rep wants to make $100,000 a year
 $100,000 / $1,500 = 67 closes per year
 Employer normally will have a minimum
number of closes to stay on board

25. Sales Analytics
 Typical Constraints
 Appointment setting
 Travel time - Presentation time – Too many
touches (Poor preparation)
 Taking applications
 Customer qualification
 Personal lead generation – Internet research
 Multiple attempts to contact
 Customized quotes

26. Sales Analytics
 Simple Case Scenario
 67 x 5 (20% close ratio) = 335 Presentations
 335 Presentations / 277 Working Days
 1.2 presentations per day / 6 per Week
 Can your people maintain this pace?

27. Sales Analytics
 Simple Case Scenario
Changed Assumptions
 $2000 per sale / 25% Closing ratio
 50 Closes x 4 (25% close ratio) = 200
Presentations
 200 Presentations / 277 Working Days
 .72 presentations per day / 3.6 a Week

28. Sales Analytics
 Large Account Manager Illustration
 $3,000,000 Plan
 277 Days x 8 Hours = 2216 Hours
 $3,000,000 / 2216 Hours = $1353.79 Hour
 Role: Maintain and Grow Assigned Accounts
 Role: Capital Equipment/Services Sales
 Find opportunities and close – Big Data direction

29. Sales Analytics
 Time and Energy Management
 Imperative to pre-plan and execute
 Work through channel partners / reps
 Work on the Pareto Principle 80/20 Rule
 Know your industry ratios for closing
 When are you “At your best?”

30. Sales Analytics
 Time Management
 8 to 5 is selling time
 Spend 80% of your time in one of the sales
process steps
 Police distractions: Junk e-mails, Facebook,
Games, News, Socializing, Extended Lunches,
Likeable People
 Intense focus on constant improvement

31. Sales Analytics - Time
One Week =
(5/277)
.018 % of a Year Or 1.8 % Year
One Day =
(1/277)
.00361 % of One Year Or .20 % Week
4 Hours = (4/2216) .001805 % of One Year Or .10 % Week
1 Hour = (1/2216) .000451 % of One Year Or .025 % Week

32. Sales Analytics
Hours
Prospecting Prep Present Objections Closing Trust Admin
45 Hours
80% Sales Work
20% Admin
1. Prospecting
2. Prep
3. Present
4. Objections
5. Closing
6. Trust
7. Admin

33. Sales Analytics
 Creating Efficiencies
 Superior marketing tools - differentiation
 Referral partners
 Customer qualification criteria – Shun poor
opportunities
 Sales automation
 Outsourcing
 Guerilla marketing tools
 Quote automation

34. Sales Analytics
 Creating Efficiencies
 Focus on sales activities – Do not assign or
allow your reps to get involved in other
activities because they appear to be an
untapped resource.
 Focus on the correct target market
 Create real value / differentiating message for
reps to sell
 Increase the close ratio with sales training

35. Sales Analytics
 Creating Efficiencies
 Time & energy management training
 Hire Well - Cost to fill or replace 1.5 to 2 times
annual salary
 Productivity measurements
 Create accountability
 Close list
 Data driven sales activities

36. Sales Analytics
 How Do You Get Data?
 Buy a list with specific demographics
 Log your calls into known categories
 Compute the percentages from the call log
 Hire a Consulting / Research firm
 Examine your newsletter dashboard open rates
and individual names

37. Sales Analytics
 How Do You Get Data?
 Run Google Analytics on websites & landing
pages
 Age, Gender, Language, Country
 Interest: Sports, Computer, Food, Travel
 Sessions, Bounce Rate, Mobile
 Starting pages, 1,2,3rd interaction

38. Sales Analytics
 How Do You Use Your Data?
 Direct your sales efforts to the correct market
 Clearly sell your value proposition
 Fiercely guard your production time

39. Sales Analytics
 Trucon Business Development
 Tel: 512-219-6677
 E-mail: Trucon@sbcglobal.net
 Website: www.truconbd.com
 Linkedin:
https://www.linkedin.com/in/truconbd