How to Beat BASES Concept Tests with Killer Innovation Concepts


Published on

A short presentation from Brand Genetics on how to develop compelling new product concepts by reverse engineering the Nielsen BASES concept test

Published in: Business, Technology
  • Be the first to comment

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

How to Beat BASES Concept Tests with Killer Innovation Concepts

  1. 1. How to Beat NielsenBASES Concept Tests
  2. 2. Nielsen BASES is the market leader in new consumer productconcept testing (50%+ market share)SIMULATED TESTMARKETING
  3. 3. So innovation teams need to understand how to beat BASESconcept tests to get their innovations to marketConcept test for quantifying newproduct potential and optimizing aconsumer propositionConcept + Prototype test forquantifying new productpotential and optimizing aconsumer propositionConcept test for assessing newproduct potential and optimizing aconsumer proposition (ConceptPotential Score)
  4. 4. Beating BASES concept tests improves the chances of innovationsuccess because test results are linked to future sales
  5. 5. BASES tests can rank different product concepts based on marketpotential and predict 1st year sales (+/-20%)
  6. 6. In essence BASES tests are simple: show concepts to an onlinepanel of consumers and ask ‘would you buy this?’
  7. 7. BASES is based on the insight that ‘intent to purchase’ is the bestpredictor of future buying behaviour (vs. attitudes, values or needs)
  8. 8. This insight is a useful starting point for concept ideation. Buildnew concepts around top category purchase drivers!
  9. 9. This means doing three things; first ideate around what makespeople trial new products in your target category
  10. 10. Then to identify new opportunities, generate ideas around whatprompts brand switching and lapsing in your target category
  11. 11. Finally focus ideation on what prompts people to buy in greatervolume or more often (purchase volume and frequency)
  12. 12. To understand and ideate around these purchase drivers, you canresearch and co-create with category experts and consumers
  13. 13. Since intention to purchase is an imperfect predictor, BASEScalibrates test scores based on normative (SAMI-Burke) data
  14. 14. In calibrating scores, BASES also uses perceptions about fair price(value rating), believability, distinctiveness and likeability
  15. 15. So after a first round of ideation, develop concepts to ensurebelievability, likeability, distinctiveness and value
  16. 16. Then, when you have candidate concepts, run a conceptoptimisation workshop with experts and consumers
  17. 17. This concept optimisation workshop should focus on the abovequestions, drawn from the BASES test itselfHow could we improve this concept so it appears morenew, distinctive or different from other products?How could we modify this concept so people will want tobuy it more frequently?How could we tweak this concept so people would wantto buy multiple units?How could we help this concept appear more believable?How could we update this concept so it appears bettervalue for money?Overall, is there anything we could change to make theconcept more appealing and likeable?How could we present this concept so it matches closerto top category purchase drivers?
  18. 18. That’s it! Follow this simple plan and you’ll be creating BASES-beating new product concepts!
  19. 19. To find out more about developing BASES-beatinginnovation concepts, talk to us at Brand Genetics.It’s what we do.Brand Genetics Ltd31 Windmill Street • London • W1T 2JN (0)20 7700 2700
  20. 20. References:Clancy, K, Krieg, P Mcgarry Wolf, M (2006) Market New Products Successfully: Using Simulated TestMarket Technology (Lexington)Korotkov, N. and Occhiocupo, N. (2011) Simulated Test Marketing in FMCGNielsen (2009) Winning with innovation: An introduction to BASES (2011) How Companies can Select Winning Ideas and Forecast Sales Before Launching NewProducts (2012) The Breakthrough Innovation Report (2007) BASES SnapShot (2009) BASES I (2009) BASES II (2009) BASES E-Panel (2004) BASES See Tomorrow Today, J.S. (2006) Simulated Test Marketing: It’s Evolution and Current State in the Industry MIT MBAThesisWillke, J. (2002) The Future of Simulated Test Marketing ESOMAR