Ten Challenges in Business-to-Business (B2B) Marketing Research, Part One
By Helen Pham, Data Analyst, Polaris Marketing Research
Within the past decade, business-to-business, or B2B, research has blossomed from a sales generator to an essential marketing tool. While the foundations of B2B studies are similar to those of consumer research, the field environment and process of execution can be quite different. Optimizing B2B marketing research requires clearing obstacles sometimes not faced with consumer research.
Here are ten steps that researchers can take to make B2B projects go more smoothly. In this issue of MR Perspectives, we will look at the first five; we�ll finish up next month with the last five.
1) Qualitative first.
Conducting qualitative research in advance of the quantitative research improves the overall research project in several ways. First, it ensures you are asking about factors of critical interest to the customer, not those assumed to be of interest by the business. Second, it makes sure that you use language that is familiar and comfortable to the respondent. If the business calls the product a �BioGenesis 2000.� and the customer calls it �that binder thingy�, you want to be sure you use language in your questionnaire that everyone can understand. Finally, you may learn something (e.g, typical hours worked, facility with computers, language preferred) that will help you select the correct methodology for the research.
2) Going into the field with a strong sample.
One common challenge in B2B research is smaller or inadequate sample population. It is the researcher�s responsibility to make sure the project is completed with a clean, accurate sample. To save time and cost, the client and the research firm must work together to ensure the appropriate respondents are included in the sample, and to remove duplicates, invalid phone numbers, cell phone numbers, do-not-call numbers, and/or invalid email addresses before launching the survey. It is also important that the contact names and businesses are accurate.
3) For smaller samples, execute segmentation and design quota groups.
It is typical to estimate your completion rate by the amount of sample you have based on a 10% response rate. For example, in order to get 200 completes, you must have at least 2000 qualified, valid sample records to begin. To accommodate smaller sample populations, segmentation and quota groups can play a necessary part, requiring an elevated level of research sophistication. When it comes to setting quota groups, it is best to keep your margin of errors below +/-10% with a 95% confidence level. For example, with a sample of 1000 clients, you may set your quota to 300 completes, resulting in a margin error of +/-4.7%.
4) Plan for a longer schedule.
Compared to customer satisfaction, or B2C, research, B2B research tends to be a slower process due to higher research cost and the complication of business activity. Allow for a longer planning phase and a flexible data collection schedule. Take into consideration that respondents are less likely to respond around major holidays. Other factors in field scheduling that should not be ignored are the work style and seasonality of certain business professions. For example, it is unreasonable to survey school teachers during the summer, or request in-depth interviews from accountants during tax season. Similarly, you won�t find manufacturing plant maintenance engineers sitting at their desks most of the day.
5) Make the survey short and simple.
Long surveys can be a drag, especially when the respondents are crunching for time and already thinking of ways to get you off the phone. Get to the point! To increase participation and get the best result, follow these guidelines:
Keep the survey under 10 minutes,
Shorten the introduction and conclusion,
Eliminate questions that are unrelated to the purpose of the study,
Keep the amount of open-end questions to an average of two or three.
Watch for B2B marketing research guidelines numbers 6 through 10 in next month�s MR Perspectives.
Helen Pham is a Data Analyst in the analytics department at Polaris Marketing Research Inc., where she handles a variety of data manipulation tasks involved in survey research. She has a bachelor's degree in business from Georgia State University.
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