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How Companies can Select Winning Ideas and Forecast Sales Before Launching New Products

How Companies can Select Winning Ideas and Forecast Sales Before Launching New Products Presented to:. What is innovation? What does it mean to you? Can you think of any examples?. New product forecasting. Simulated Test Marketing (STM) Overview STMs Explained: Inside the “black box”

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How Companies can Select Winning Ideas and Forecast Sales Before Launching New Products

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  1. How Companies can Select Winning Ideas and Forecast Sales Before Launching New Products Presented to:

  2. What is innovation? What does it mean to you? Can you think of any examples?

  3. New product forecasting • Simulated Test Marketing (STM) Overview • STMs Explained: Inside the “black box” • What really drives new product success?

  4. Nielsen BASES Mission is to help our clients grow through successful innovation on their brands. Nielsen BASES Objective is optimizing our clients’ high potential initiatives, and minimizing the risk of launching failures. Nielsen BASES Philosophy is building strong and lasting relationships with our clients. What is Nielsen BASES? What do we do?

  5. is part of the family As part of The Nielsen Company, BASES Has Developed Unparalleled Access To Insights, Experts, And Data, To Help our Clients Succeed through Successful Innovation

  6. Here is a snapshot of some of the clients that we work with:

  7. Simulated Test Marketing Overview

  8. Product Forecasting Methods: • Best Guess • Secondary Data Comparables • Qualitative (focus groups) • Live Test Markets • Simulated Test Marketing Typical new product development process for consumer packaged goods Market Definition Idea Generation and Screening Concept Testing / Optimization • Cost of Failure: • Year 1 Advertising / Promotion: $5-30MM • Manufacturing Costs: $5MM+ • Opportunity Costs: good products not launched • Brand Equity: negative halo of failed product (consumer and trade) • Job Security Product Development and Evaluation Prove Business Case Commercialization and Launch

  9. A history of product testing from the US 1930 1940 1950 1960 1970 1980 • 40s: Rise of National Brands: • Launching Expensive • Success Unpredictable • 70s: Controlled Store Testing: • Product Stocked at Controlled Store • Smaller Markets than TM… Less Expensive • Custom ads delivered to homes • 70s: STMs: • Concept Evaluation/ In-Home Product Test • Statistical Sampling • Many advantages... • 50s: Test Markets: • “Little America” • Representative Cities -> “Will it play in Peoria?”

  10. Advantages and caveats for STMs • Marketing elements assumed: • distribution levels and builds • media spending - timing and execution • Major competitive or economic changes prior to launch impact forecast • Deviation of tested versus launched concept / product impact estimates • Improved accuracy • Identify product weaknesses to fix • Identify source of volume • Weed out losers before test market • Shorter “reading” time • Enhance concept / product security • Perform quick competitive forecast • Reduced product requirement • Eliminate final packaging need

  11. STMs Applied: Consumer Data

  12. Exposure to Concept Stimulus Evaluation of Concept AFTER-USE(Post-Trial) Consumers Re-Contacted after usage period Evaluation of Product Our methodology ensures data consistency and reliability CONCEPT(Pre-Trial) Consumers contacted Eligible Consumers Placed with Product

  13. A new product with strong consumer interest pre-trial will drive significantly higher sales BASES Food Example – A comparison of the best and the worse initiative in BASES Database +315% Volume potential

  14. Example of pre-use consumer measures Is this a good concept? Without some benchmark, it is almost impossible to know if the scores are good or not. BASES has developed extensive databases that provide a robust context for evaluating initiatives.

  15. BASES’ cornerstone assumption • Strong correlation between consumers’ claimed future purchase behaviour and actual purchasing. • Consumers, however, tend to overstate their intended purchase behavior (albeit with great consistency). The level of overstatement varies by country, by culture, and by key demographics.

  16. Can you guess which countries have high overstatement? Purchase intent claims by country Source: The Nielsen Company

  17. For example, consumers overstate their transaction size, but it correlates to actual behaviour Concept Claimed Units (Fav) 1:1 Line Trial Units Source: The Nielsen Company

  18. Similarly, their claimed frequency of purchase lines up with actual purchase cycle Long Purchase Cycle Short Low High After-Use Claimed Frequency Source: The Nielsen Company

  19. Quick Quiz When can you reasonably forecast a really new product’s sales? 1. When you can accurately predict its market share 2. When you can predict share and market growth 3. It is often not possible to predict sales using market share 4. This looks like a trick question and I’m not answering

  20. Quick Quiz When can you reasonably forecast any new product’s sales? 3. It is often not possible to predict sales using market share alone 4. This looks like a trick question and I’m not answering

  21. Forecasting really new products: Two questions 1) Can consumers make reliable judgments about their future purchase behaviour for “really new” products with no competitive set or frame of reference? 2) What unique problems do “really new products” pose for pre-market sales forecasting?

  22. Why is purchase cycle important innew product forecasting?

  23. High Repeat Rate (Panel) Low Short Long Purchase Cycle (Panel) Purchase cycle drives repeat rate (and repeats per repeater as well) Source: The Nielsen Company

  24. Answer to Question #1 Can consumers make reliable judgments about their future purchase behaviour for “really new” products with no competitive set or frame of reference? Yes, because consumers’ claims regarding “really new products” are no more overstated than their claims for common, everyday new products.

  25. Answer to Question #2 What unique problems do “really new products” pose for pre-market sales forecasting? A) Calculating market share alone may not work • Share of what? • What competitive shelf-set? B) Using “comparables” for estimates also can cause problems • Category comparables may be misleading or worse. • What if there is no category to pull a purchase cycle from?

  26. Validations indicate our methodology works Within 20% of Actual Sales 91% of Cases 87% of Cases All Initiatives Unique Initiatives Source: The Nielsen Company

  27. STMs Explained: Inside the “Black Box”

  28. Volume is calculated by combining together consumer responses with planned marketing What consumers actually do Volume Forecast Volume Estimate Promotion/in-store activity Adjust for what marketers do to influence consumers Impact of Marketing Support Distribution Awareness Measure Consumer Perception Interested Universe Remove consumer bias factors Total Addressable Market Adjust for Overstatement What consumers say they will do Consumer Claims

  29. Looking at consumer claims alone will be misleading Determine Consumer Interest 50% Purchase Intent + Adjustment for Overstatement BASES Model = Interested Universe 20% Interested Universe % of consumers becoming aware Marketing Plan + BASES Model % of consumers find the product where they shop + other activities (e.g. promotions) Trial Rate 5% Trial Rate

  30. Volume is calculated by adding together trial and repeat Example Households Trial Rate Number of Packages / Purchase Trial Volume 55 million 10% 1.1 6.1 million Trial Volume + 5.5 million 40% 1.2 3.0 7.9 million Triers Repeat Rate Number of Packages / Purchase Repeats / Repeater Repeat Volume Repeat Volume = Total Volume 14 million

  31. The relationship between trial and volume is almost linear High Low Low High Source: The Nielsen Company

  32. Quick Quiz True or False? 1. Awareness alone strongly predicts trial True 2. Advertising strongly predicts awareness True 3. Internet advertising generates high awareness ???

  33. Awareness is critical for new products’ success High Low Low High Source: The Nielsen Company

  34. Example: Four Products (Same Category) Tracked Awareness Year I Trial Rate Total Unit Volume Brand D 78% 14.3% 31.4MM Brand C 48% 8.0% 17.5MM Brand A 20% 4.5% 9.3MM Brand B 44% 9.0% 17.4MM

  35. Product category affects awareness generation Awareness Food Personal Care Health Care GRPs Source: The Nielsen Company

  36. High Total Awareness Even without any advertising there will be some awareness, from distribution. Low Low High GRPs Media drives awareness Higher Impact GRPs (higher recall) Lower Impact GRPs (lower recall) Source: The Nielsen Company

  37. Innovative ideas are more likely to be remembered • Related recall scores from copy testing show an advantage for innovative products. Commercial Related Recall Source: The Nielsen Company

  38. What is the value of memorable advertising? Me-Too Innovative GRPs Recall Persuasion Awareness Trial Rate Sales Index 2,000 20% 9% 35% 8.5% 1.00 2,000 30% 9% 45% 11.2% 1.35 Source: The Nielsen Company

  39. Advertising timing has an impact on volume 10 9 8 7 5.3% 6 Early Flighting Trial Rate 4.9% 5 4 3 Spread-out Flighting 2 1 0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 Time in 4 Week Periods

  40. Distribution has an even stronger impact on volume and its importance cannot be underestimated 2 R = 0.83 Trial Rate Distribution Source: The Nielsen Company

  41. One of the challenges for launching new products in Russia isdistribution Source: The Nielsen Company

  42. Dist Construction Fast: A Slow : B Month 12 More time for trialMore time for repeat Higher volume! Distribution timing is also important Influence on trial Trial rate A = 26% B Month 12 Influence on volumes Volumes = 40% Month 12

  43. 80 Shifting the advertising start by five periods to align with distribution increases volume potential by ~10% 70 60 50 (400) (400) 40 (300) (300) 30 + 9% 109 20 100 10 Volume Index 0 1 2 3 4 5 6 7 8 9 10 11 12 13 Periods • Russia • France • Uk • Poland Actual Shifted Shifted GRPs Actual GRPs GRPs GRPs Media plans typically used for new product launches might not work well in Russia ... Case Study: Coffee in 4 countries including Russia Source: The Nielsen Company

  44. Influence of actual in-market execution on performance of the initiative Comparison Between the Original BASES Forecast and Expected Performance based on the Launch Execution Plan 0% +38% -19% +7% -5% -20% Source: The Nielsen Company

  45. Quick Quiz True or False? There is little correlation between the number of: triers who repeat a first time, and repeaters repeating a second time. False -STMs would not be possible without this strong correlation

  46. 1st vs. 2nd Repeat Rate Source: The Nielsen Company

  47. 100 90 80 70 60 50 40 30 20 10 0 0 2nd vs. 3rd Repeat Rate 3rd Repeat Rate 20 40 60 80 100 2nd Repeat Rate Source: The Nielsen Company

  48. 3rd vs. 4th Repeat Rate Source: The Nielsen Company

  49. Trial Strong Product Weak Product First Repeat Number of Households Stabilization 1 2 3 4 5 6 7 8 Number of Repeat Purchases Buyers can be ‘lost’ – if you have a bad product they will be lost more quickly

  50. Incremental trial is important to replace lost buyers Year II to Year I Ad Spend Ratio • Marketing efforts influence a brand's ability to grow in Year 2. • For brands that decline, ad support is generally cut significantly versus Year 1 support. • Ideally, a new product should be thought of as “new” for two years rather than one. Source: The Nielsen Company

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