White Paper. Benefits and Challenges for Today s Online B- to- B Research Methodology. By Pete Cape, Director, Global Knowledge Management.

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1 White Paper Benefits and Challenges for Today s Online B- to- B Research Methodology By Pete Cape, Director, Global Knowledge Management March 2015 Survey Sampling International, 2015

2 ABOUT THE AUTHOR Pete Cape, Director, Global Knowledge Management With over 25 years of experience in market research and originally a specialist in international telephone research, Pete was a founder of TNS Interactive and has concentrated on online research ever since. A frequent speaker at industry events around the globe and a regular contributor to industry publications, Pete was recently one of five experts who worked on the ESOMAR/GRBN Guideline on Online Sample Quality. Business to business (B- to- B) research online carries many of the same benefits and challenges as Offices worldwide surveysampling.com 2

3 consumer research online: online is faster, can be less costly than telephone research, minimizes social desirability bias and can engage hard to reach population segments, providing a better respondent experience. On the other hand, some segments are harder to reach online, and it is difficult to be sure of the quality and veracity of responses. These challenges are intensified in the B- to- B environment and online B- to- B research, in addition, has particular challenges of its own. This paper covers three topics: 1. B- to- B sample: why it is different from consumer sample, and how to approach its construction 2. Online B- to- B sample quality: the challenge of fraud in online B- to- B research and how to overcome it 3. Online B- to- B and the respondent experience: comparing online to traditional telephone methodology THE SAMPLE: DEFINING THE B- TO- B SAMPLE UNIVERSE The key difference between (B- to- B) and consumer sample is that consumer sample is made up of individuals, whereas in B- to- B research there are two distinct universes: the universe of employers and the universe of employees. The universe of employers is focused primarily on companies, not people. The company is a very real entity with its own life, its own ethos and its own demographics. Individual people of course have to be interviewed about the company, but they speak on behalf of the company and are not necessarily saying what they think personally. In fact, a researcher should be able to interview two completely separate and different people from the same company and get precisely the same answers - - because they are talking about the company, not about themselves. The other universe of interest in B- to- B research, of course, is the employee universe: interviewing real people about real experiences doing their own real jobs. Within this universe answers between individuals will be very different. The employer universe is difficult to define. For example, a company like Starbucks might consist of 12,000 sample units (establishments, in this case coffee shops), all of whom might potentially be interviewed. But if the focus of the research project is at the company- wide level then Starbucks is just one enterprise and therefore is only one sample unit. The choice between talking to the establishment or the enterprise depends on the subject matter of the research and thus which unit is most relevant. For example, if the goal is to talk about accounting software then the enterprise might be the better universe to use; but if the research problem is related to customer service experiences then the establishment is probably the correct universe. Of course, it may be necessary to mix the two due to differences in the way businesses are organized. Starbucks might have a centralized accounting system while another chain like Costa Coffee might allow each store to use a system of their choice. Given this type of difference it is easy to see how difficult it would be to deal with, for example, a study on franchise businesses. The universe must be clearly defined at the beginning of the project. 3

4 THE SAMPLE: THE COMPANY SIZE CONUNDRUM There is a unique fact about the business universe which has a significant impact on sample design: that fact is that within the universe of employers most are very small and only a few are very big, whereas in the universe of employees the opposite is true: most employees work for very big companies and only a few work for very small ones. This conundrum has an important impact on sampling. If the sample is chosen from a business directory, the probability of sampling a small company is much higher (there are many more of them). However, if the sample is chosen from people on a consumer access panel who are employed, the probability of sampling a big company is much higher (most people work for big companies.) There is another aspect to this conundrum: that of the distribution of types of jobs within a company. There are only a few people at the top of the pyramid in a company: CEOs, Presidents, Owners and Decision- Makers. The vast majority of people at a company do not belong to any of these groups. And unfortunately, people at the bottom of the pyramid are generally of much less interest to researchers. Most B- to- B research is primarily interested in very large companies because they represent the largest revenues and have the most employees but there are fewer of them within the employer universe. Researchers are also only interested in talking to top executives and there are fewer of them within each company. With this background it becomes clear that the common B- to- B target of top people at large companies is a needle in a haystack. Adding to this challenge is the reality that top people at companies change jobs frequently (for example Chief Marketing Officers last only four years in a position on average.) This becomes a practical challenge for panel companies because one day a panel member is Chief Marketing Officer at a major IT company and is massively in demand by B- to- B researchers but next month he or she is working for a boutique marketing consultancy and is not nearly so interesting to market research, and therefore much less valuable to the panel company. These challenges are among the reasons why B- to- B online sample will always be more expensive than consumer sample. 4

5 THE CHALLENGE OF FRAUD IN B- TO- B ONLINE RESEARCH In online B- to- B research there is an elephant in the room, which is fraud. This is a particular concern for B- to- B research because while respondents are routinely rewarded for their time and effort, rewards given to B- to- B respondents are generally higher than those given to consumers. Fraudulent panelists do more surveys than ordinary people; after all, it is a business for them. They also qualify for almost everything they start because they are motivated to qualify and are willing to lie to do so. They obviously seek out the surveys with higher reward if they get a choice and do their best to be selected. So when they fill out profiles they choose to be IT directors, CEOs, CFOs and Vice Presidents. They do not choose to be teachers, plumbers or shop assistants. As well as higher rewards on offer the additional threat to B- to- B research from fraudulent people is that most B- to- B studies are low incidence in nature. The impact of fraud in a low incidence study is much greater than on a high incidence study, as is explained below: On a 100% incidence study if 2% of the panel is fraudulent, they represent 2% of the responses such a small percentage that they cannot harm the data. However, on a 4% incidence study if 2% of the panel is fraudulent and lies to qualify into the study, they make up one third of the responses. (Two out of 100 lie to qualify into the study, while four qualify honestly; therefore out of the six respondents, two are frauds). This seriously damages the data. If the base level of fraudulent people were only one percent they would be imperceptible in a 100% incidence survey, but would represent about 9% on a 10% incidence study. B- to- B samples are usually small and this 9% of frauds is obviously very serious if a sample size is only 100. To have at least 9 people who are not giving honest and truthful responses is a big problem. This issue would make B- to- B research impossible online if steps were not taken to prevent it. THE QUESTIONNAIRE AS WEAPON AGAINST FRAUD B- to- B surveys are usually aimed at specialist audiences who have specialist knowledge. Even if the survey is just about advertising there is an opportunity to trip a fraudulent person up by asking them things they ought to know if they were indeed the person they say they are. Or they can be allowed to trip themselves up with their own implausible answers. Researchers can ask them something they should know in the questionnaire, or let them state things that are really implausible. The fraudster does not know the answers to these questions and generally in their behavior they will try to hedge their bets by being affirmative to questions. So when asked whether or not they do certain things or know certain things they will tend to say yes. As a result in analysis researchers may see some very strange and very unlikely profiles, such as: Person A is 18 years old and has 5,000 employees. (We would expect to have heard of him by now; he should be famous!) Person B is a 40- year- old IT Director and has extensive experience of an operating system that was defunct before she left elementary school. 5

6 It is always possible to find these inconsistencies but to do so the researcher needs to know the research subject well. However, since B- to- B researchers tend to be well educated in their vertical, this is a good technique to use to weed out frauds. USING OPEN END QUESTIONS TO IDENTIFY FRAUD An alternative or additional method of identifying fraud is to review answers to open questions. Fraudsters are inherently lazy. They tend to avoid open questions, although some might copy and paste in some long quote that has absolutely nothing to do with the subject matter. The above two methods are effective, but not very efficient ways to catch frauds because there is a cost in the time taken to analyze data, especially data in open end questions and especially for global studies when open ends are in multiple different languages. The fraudulent answers usually cannot be reviewed and rejected in real time and it takes time to create custom questions like this for each individual study. Therefore the panel company has an even greater responsibility in a B- to- B context to weed out frauds before the questionnaire stage. The means they must validate people when they join a panel and monitor them throughout their lifetime on the panel. PANELIST VALIDATION To validate someone as a B- to- B respondent the panel company must know: who they are that they are who they say they are that they work where they say they work that they do the job that they say they do There must be a mechanism for proving this before they join a B- to- B panel. VALIDATION BY SOURCE Obviously some sources are more vulnerable to fraud than others. Consider a source of subscribers to an IT magazine. For fraudsters to take advantage of that relationship they would have to join the subscription list by pretending to be an IT professional. That is not very difficult: but then they would have to pay for the subscription, which may well be more than they are making from defrauding the panel company. They would also have to have a physical address in the country they claim to be from; many frauds would not have that. And finally they would have to know that this particular magazine is a source for that particular B- to- B panel. The magazine subscription list is an example of a source with a good built- in validation mechanism. However, only using sources with some type of built- in validation may not offer the breadth and depth required for a robust B- to- B panel, so additional validation methods must be used. SSI has used 6

7 additional methods to validate members of the SSI B- to- B inssites panel, including data mining information about panelists on the database and telephone validation. VALIDATION VIA DATA MINING By examining profile information from thousands of people it is possible to learn to see inconsistencies in data points like company size compared to revenue, or number of offices compared to total staff. It may be that these inconsistencies are not caused by fraud: it may be that people who are being asked these questions are not in a position to answer them (they may not know the number of people in their company, or its revenues, or the number of offices it has). Respondents will try to answer the questions researchers put to them even if they are not sure of the answers. So this technique is good at identifying good B- to- B respondents who know a lot about their companies, but not necessarily the best option for isolating frauds. VALIDATION VIA LINKEDIN Many senior business people are on LinkedIn, where they are connected to their peers and their colleagues. Of course a fraudster can create a LinkedIn profile, but would they bother? And if they did, how many other business people would connect to them? Therefore, comparing panel members against their LinkedIn presence and the number of LinkedIn connections they have can be an effective way to eliminate frauds. SSI conducted research into the effectiveness of LinkedIn for validating individual panel members. Of course, not every panel member gave us permission to find them on LinkedIn, and we only looked for information from people who had given us their permission. The chart below shows high levels of failure in both and exact name match between LinkedIn and panel join information. This is not surprising because many people do not necessarily give a correct address on LinkedIn to avoid marketing. The exact name match of course is always a problem for computers: Pete is 7

8 not an exact match for Peter. The answer to this is to loosen the match requirements. However, if they are loosened too much the match becomes less reliable. At the bottom of the chart are data items that are simply not there on LinkedIn. People do not put their phone number or date of birth on LinkedIn. What we are left with are the three items in the middle to validate against. These are useful because some people fail on them and others pass. We used an arbitrary cut off of ten connections and five skills in the test and looked to see how people who passed performed when answering surveys, to see if this would be a valid quality test. When assessing survey behavior quality it is important to remember that some level of inattention is a normal result of mental tiredness. The survey we tested has a number of data quality questions in it, customized for a B- to- B study, including combinations of unlikely behaviors, inconsistency of thought and inconsistency of facts. The chart below shows how those different groups from the social media test performed and the data quality questions they failed. Failure at three or more of the checks was our measure of poor performance (it is important to note that these people may be displaying a lot of inattention, but not necessarily fraud). This is a high incidence study and as we would expect, the results show a low level of poor data quality. Disappointingly, however, there is no relationship between data quality and passing or failing the LinkedIn validation. Those people with ten or more connections are no better at filling in surveys then those with fewer. This is perhaps not surprising because fraudsters are unlikely to give us permission to check out their LinkedIn profiles! TELEPHONE VALIDATION Telephone validation consists of calling respondents at their place of work and checking that they really do exist. The biggest challenge with this method is that it is extremely difficult to reach people at 8

9 their place of work by telephone! This of course is the very problem that online B- to- B hopes to solve. With difficulty comes cost and using telephone validation for all online B- to- B sample would inevitably increase costs. Attempts at telephone validation result in three possible outcomes: Valid the person is at the telephone number they give and they are who they claim to be Invalid No trace of the person is found at the telephone number given Unknown It is not possible to either validate or invalidate the person The third group, unknown is by far the largest group. As previously stated, in a high incidence study we expect the impact and presence of fraudulent respondents to be low. Our high incidence study test shows that the validated telephone sample has almost no one failing four or more quality checks (our measure of potential frauds). Data quality fails by phone validation group: high incidence study: In fact the measure of inattentive behavior (failing three or more quality control checks) is at normal levels 5%. Contrast this with the invalid group, which has an additional 2% more inattentive people, possibly the frauds. The same is true of the Unknown group and therein lies our problem. Since this is the largest group we might imagine that our fraudsters are lurking here in the same proportions as they are in the Invalid group and we therefore use this group at our peril. Our fears are confirmed when we undertake a low incidence study. 9

10 Data quality fails by phone validation group: low incidence study: The numbers failing the attention test increase dramatically in both the Invalid and Unknown groups. But it is not enough to conclude that all the Invalid or Unknown respondents are poor without this second stage of a survey with data quality control checks in it we would potentially be throwing away 75% of respondents who are actually good. It is interesting to note perhaps that the same data quality can be achieved by using all those who offered us a LinkedIn username as you get form the validated phone sample at considerably less cost. However, even at low completion rates telephone validation provides a valuable quality check on sources. If a certain source validates via telephone at a lower rate this is a cause for concern and may result in additional checks being put in place for that source or even in that source no longer being used by SSI. For telephone validation our conclusion is that validations within the questionnaire itself are more effective than these methods in identifying frauds but these methods are helpful in evaluating and qualifying sources. THE BENEFITS OF B- TO- B ONLINE RESEARCH Our focus on fraud prevention sometimes overshadows the effectiveness of online as a B- to- B research methodology and ignores the 99% of people who give their valuable time and real opinions with thought and care. To make online B- to- B research worthwhile it needs to be better than telephone methodology: it needs to be faster, cheaper and better in fact. Online is better in terms of data since it gives the respondent an opportunity to be more honest because there is no live interviewer there to try to impress. It gives respondents more time to give a more thoughtful response because there is no interviewer there trying to hurry them along. With online we have the opportunity to expand the sample frame beyond directories and away from 10

11 the whims of the person at the switchboard. It is an interesting fact that all of the randomization in B- to- B telephone research happens before the front door of the company. At that point the sample essentially switches from random to quota sample where the person at the front desk chooses who does the survey. Online research is faster: the respondent can to do it in their own time and there is no constraint caused by the number of live interviewers available and no additional live interviewer costs. THE B- TO- B RESPONDENT S VIEW OF ONLINE SURVEYS Other than the data quality issues resulting from fraud which there are ways of combatting there are very few disadvantages to online B- to- B. But what do the respondents themselves think about taking B- to- B studies online compared to doing them via phone with a live interviewer? Do they have a preference for one method over another? SSI conducted research into this issue by asking members of the SSI inssites B- to- B online panel (CEOs, VPs and Senior Managers) about their behaviors and attitudes related to answering research surveys. They were asked both about taking surveys via phone and also online. As we see in the chart below, respondents believe they are being contacted often for research via phone. These numbers may seem unrealistically high, but this is the respondents perception. Relative response rates between the two modes are similar so people are willing and able to do interviews by both modes The chart below also starts to hint at some problems in the future for telephone research: when asked how happy people are about the volume of contacts they are getting. Much too much is much more likely to be said about telephone contacts than it is about contacts. 11

12 Today, B- to- B research is done via both online and traditional telephone methods. Online is certainly less intrusive for the respondent in terms of the working day. The vast majority of online B- to- B surveys are done at home in the respondent s own time. 86% of people asked in this SSI study were at home while they were answering the survey. Even at 12% the surveys that are normally being done at work are being done in break times and it would be impossible for a telephone researcher to concentrate all of their telephone interviews during people s break times. Online surveys are done away from the office. This is a major advantage of online B- to- B research and the impact can be seen in answers to questions around attitudes towards survey taking. Being out of the office and comfortable at home gives respondents time to think about their answers and since B- to- B subjects tend to be more complex this must be a good thing for the data. Another interesting response is that two thirds of people agree that work time should be for work and not for surveys. Researchers are not high on the priority list when they call a business person and ask them to do a survey. 12

13 Another response speaks to honesty and ease of answering. Most employees would say that they should be careful in what they say in the office, especially in today s open- plan cubicle environment. How does this sense of caution translate into honesty in answering a survey question? Everyone can relate to the potential embarrassment of having a strange, one- sided conversation on the phone within hearing range of co- workers. The work environment can also be noisy and it can be difficult to concentrate. Our B- to- B panelists recognize this. Half of respondents to the SSI research on research said that they do not want any more s at work, and they certainly don t need any more from market research companies. But getting those s at home is different, because they want to give their opinion. The evidence points to online being a good experience for the B- to- B participant and in practical terms they can do it in their own time and they are volunteers in this process: they are not coerced by persuasive interviewers. On the data side it gives them the opportunity to think through the questions and answers giving thoughtful and honest responses. As a researcher it is also a win. It is faster, it is cheaper and in many respects it is better market research and it is the better part of online research that has made it the predominant method in market research, even when it is not necessarily the cheaper part. At last B- to- B researchers are getting a chance to enjoy the advantages that online research has to offer. Online B- to- B research is not without challenges. We have described the challenges with sampling approaches and representivity. We also have challenges in data integrity. Overcoming challenges is what researchers do all the time. And they do it particularly when the reward is worth it. And it is worth it for B- to- B online research. As well as being usually cheaper, faster and better, it is a great respondent experience and a better data collection mode. SSI s B- to- B inssites panel is a rapidly- growing panel with the size and type of targets required to meet B- to- B research needs. SSI B- to- B inssites uses phone verification and precise profiling. In addition, SSI s multi- mode access to mobile, online and CATI data collection allows selection of the best option to complete a project successfully. 13

14 ABOUT SSI SSI is the premier global provider of data solutions and technology for consumer and business- to- business survey research, reaching respondents in 100+ countries via Internet, telephone, mobile/wireless and mixed- access offerings. SSI staff operates from 30 offices in 21 countries, offering sample, data collection, CATI, questionnaire design consultation, programming and hosting, online custom reporting and data processing. SSI s 3,600 employees serve more than 2,500 clients worldwide. Visit SSI at 14

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