An accurate customer needs analysis helps you make strong, aggressive tactical marketing decisions.
Base your decisions on actual, quantified market requirements. You get up-to-date, relevant information on your customers’ (and potential customers’) buying patterns, needs, and price sensitivity through our numerous resources and services:
- Market Needs Analysis
- Business Intelligence
- Market Surveys
- 1-on-1 Interviews
- Laboratory Purchasers Surveys
- Physician Surveys
- Customer & Competitor Profiling
- Focus Groups
- Advertising Effectiveness Testing
Qualitative vs Quantitative
Many of our clients ask us, “How many people do we need to talk to in order to really quantify the information?”
Our response: “As few as possible to make a smart business decision and reduce the risk associated with making the wrong decision.” This keeps budgets in line and maximizes the value of the project. You won’t be paying for highly precise information you don’t need to make decisions. You won’t be paying for “Nice to Know” information—only the information you need to assure you’re making the right marketing decisions and investments.
Selecting a Sample Size
- Sample size is based on factors such as the number of possible alternative answers and variability of answers among respondents.
- Decide if you need a “probability sample”—i.e., data that can be used to project accurately to the entire market segment.
- Decide if you have the budget and time to draw a probability sample (so you can calculate confidence limits for sampling error).
- Since we often don’t know what kind of responses we’ll be getting before we implement the study, sample size must often be based on experience.
Very few companies have unlimited budgets for marketing research—neither does yours. Focus on reducing the risks associated with your decision-making, and you may find that you can significantly reduce your sample size. This will make your analysis much more cost-effective!
Questionnaire Do’s and Don’ts
- Keep it simple: Avoid complex questions that confuse your respondent, slow the research and reduce compliance.
- No bias: Avoid leading questions like “Why don’t you like Acme Biotech’s analysis services?“
- Use simple terminology, even with sophisticated respondents. This avoids ambiguity and useless responses.
- Ranges reduce respondents’ sensitivity: Rather than asking “How many gels do you run per day?” ask “Do you run 0-5, 6-10… etc.“
- Allow for “Other” category in fixed responses.
—Adapted from Kotler, 11th Ed, P 136
