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Sales Analytics by Trucon

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Sales Analytics by Trucon

  1. 1. Sales Analytics ACHIEVING WIN – WIN – WIN • FOR THE COMPANY • FOR THE CUSTOMER • FOR THE SALES PERSON
  2. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 19. Sales Analytics  Quality of the Representative  Unconsciously incompetent  Consciously incompetent  Consciously competent  Unconsciously competent
  20. 20. Sales Analytics
  21. 21. Sales Analytics  Where the Rubber Meets the Road  Presentations Close Rate Time Utilization  Assume 20% Close rate of all actual presentations
  22. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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

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