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HIRI Spring 2014

HIRI Spring 2014. Knowing Your Market: Options for Representative Research HIRI Spring Conference. April 10, 2014. A few thoughts:. In the CPG world, research is a little easier. Finding out about consumers’ preferences towards Cereal is not difficult from a research standpoint

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HIRI Spring 2014

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  1. HIRI Spring 2014

  2. Knowing Your Market: Options for Representative ResearchHIRI Spring Conference April 10, 2014

  3. A few thoughts: • In the CPG world, research is a little easier. Finding out about consumers’ preferences towards Cereal is not difficult from a research standpoint • Categories have high penetration rates – finding folks who buy Cheerios is not particularly difficult • The population is therefore easy to reach and crosses many age, gender and ethnic lines • The rise in “DIY” online research enables anyone with a pc. Smartphone or Tablet to build and deploy a survey • While the research rigor can be challenged, finding adequate response rates to base conclusions on is not a big challenge

  4. A few thoughts: • In the Home Improvement world however, research is a little more challenging. Consumers and Contractors both vie for your attention. Additionally certain ethnic groups emerge as particularly attractive to marketers and yet increasingly difficult to engage • For example, Contractors by their very nature are not tethered to an office – although this might qualify as one to many; • At the same time, Contractors account for approximately 30% of big box retailers’ sales and in some studies are predicted to outpace consumer sales

  5. A few thoughts: • Additionally, these individuals are very difficult to reach via traditional research methods – if nothing else due to the nature of their work • Technology is replacing the pc for them and the better they are the harder they are to reach – making “DIY” approaches largely unsuccessful and making recruitment to mainstream online panels very difficult

  6. Making it even harder… • According to U.S. Department of Labor projections, Hispanic contractors will outnumber English-speaking contractors by the year 2025, representing an impressive 62 percent of the entire category1 • Only one out of two Hispanics, however, both have Internet access and speak English at least well • Also, consider that terming your audience as Hispanic is akin to talking about the Home Improvement industry as one industry – Puerto Rico, Mexico, Cuba – Tools, Flooring, OPE • Approaching the Hispanic market is still in most cases simply an outreach of general marketing practices and is limited in scope • In the CPG world consider the findings of a 2012 Nielsen report that predicted that Hispanics will be the dominant, and in many cases the only driver of CPG sales growth • Therefore, a well-crafted, data-driven strategy is the first step in reaching the Hispanic marketplace. 1 Projection based on 2000 – 2008, Bureau of Labor Statistics data

  7. Reaching Any Low Incidence Population:The Possibilities • Dual Frame and Landline RDD: The Gold Standard • ABS: Address Based Sampling • Geographically Stratified Dual Frame or ABS • List-Assisted Dual Frame or ABS • Combined List-Assisted and Geographically Stratified Dual Frame or ABS • Omnibus • Web Panel • Hybrid Designs

  8. Dual-Frame Telephone • Strength: Proven, high quality research technique. Historically very cost-efficient, except…. • Weaknesses: …when it has to screen. Screening for a low incidence population like contractors or Hispanics can move a study that costs $40/interview to about $150/interview for Hispanics (15%) or persons within construction/installation trades (12%) and $500 interview for contractors (0.3%). • Other Notes: Response rates have declined, but little effect on data quality. Share of the dual frame that are cellphones increasing as U.S. households who only own cell phones has grown from less than 10% in 2008 to over 40% in 2014. Landline has become less efficient and cell phones as a rule are more expensive to dial than landline.

  9. Address-Based Designs • What It Is: USPS allows access to their computerized system delivery file (CDSF). • Strength: Covers nearly every address in the U.S. Absolute geographic precision. • Weaknesses: Screening is even more expensive than RDD; response rates low; low SES persons respond less. • Other Notes: ABS is a sampling method, not a data collection method: can use mail, phone and Internet modes. Takes time.

  10. Geographic Stratification • What It Is: Sorting telephone exchanges, rate centers, or census block groups to increase the incidence of reaching a given population. • Strength: Strengths of RDD/ABS, but at ½ - 2/3 of the price. • Weaknesses: Everything does not correlate to geography. • Other Notes: Correlates well = Ethnicity, income (sometimes); Not well = age, education (usually)

  11. Geographic Stratification

  12. Lists and List Assists • What It Is: Using “listed” information to either completely conduct a study or partially. • Strength: Blended in with non-listed sample, strengths of RDD/ABS, but at ½ - 2/3 of the price. • Weaknesses: As a standalone design, coverage can be poor (and coverage is king); Cell phones have almost no reliable listings. • Appendable information: age, presence of child, income, ethnicity, etc.

  13. Lists and List Assists

  14. Omnibus • What It Is: Surveys “sponsored” by a research company that run every week; clients purchase minutes. • Strength: The screening and interviewing costs are shared with other clients, reducing costs by up 80% compared to RDD. Can use prescreened sample. • Weaknesses: Time for low incidence. • Example: SSRS omnibus: dual frame telephone, Spanish, high effort, 6 day field, 1,000 interviews weekly. • Time to get 500 Hispanics: 4 – 5 weeks. • Time to get 500 construction workers: 5 – 6 weeks.

  15. Omnibus Blends

  16. What It Is: Non-probability based convenience panels of people willing to conduct surveys. • Strength: Cost; targeting from large pool (millions). • Weaknesses: Non-probable data source. Coverage. • Probability panels beginning to become mainstream. Web Panels

  17. The smaller the population, the greater the likelihood of bias in the data. • Need to find population demographic data if possible: • American Community Survey • Labor Statistics • Omnibus • Weight the data! Web Panels of Low Incidence Populations

  18. What It Is: A combination of a probability and non-probability sample source. • Strength: Cost and quality. • Weaknesses: Cost and quality. • Propensity scoring: A technique to model the non-probability data to the probability data to reduce bias. Hybrids

  19. Relative Costs Example: Hispanics, 12 Minutes

  20. Q&A

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