How the Right Customer Buying Preference Questions Can Support Strategic Planning for Biotech Companies

Primary research surveys lay the foundation for successfully generating needed insights. After building the demographic section of a survey, ensuring all respondents are properly qualified and you have gathered their demographic information anonymously, the next section of a primary research study is called ‘Customer Buying Preferences.’

Understanding what drives customer choice is a critical component of a biotech company’s strategic planning; whether the company has maintained a strong market presence for many years, or the company is investigating potentially entering a new market. In the highly competitive and growing Precision Medicine marketplace, there is room for companies to grow, but there are also ample competitors aiming to capture the same market share. Gaining a data-driven perspective on the customer’s buying preference attributes informs a company’s Go-To-Market Strategy, value proposition, and competitive positioning. While these valuable insights direct a company regarding what to consider and implement, more important are the insights and understandings confirming where to steer clear and avoid previous mistakes; whether made by the competitor or themselves.

The first step of developing customer buying preferences questions is to conduct a working session with the client designed to brainstorm and finalize a list of 8-12 attributes that hypothesize the most important factors driving customer choice. These attributes will vary based on industry niche; cost, turn-around time, and overall reputation are three attributes typically preferred regardless of industry niche.

To gain an understanding of what drives customer choice, I favor asking a simple question: Please indicate the level of importance of the below characteristics when selecting a [insert company type]. Score on a scale of 1-10 (1-not at all important, 10-most important). An example of how we phrased this question for a leading CDMO is below:

Once we achieve our target N value of complete responses (which can range from 50 to over 250 depending on the requirements of the specific survey) and analyze the responses, we will have a score of 1-10 for each of the attributes in term of performance. While some may suggest that the answers aren’t statistically significant, with only 1,000+ answers, I would suggest that the responses do provide directionally correct data providing invaluable insights into what drives customer choice. It can be hard to tell the difference between a score of 7.1 for one attribute and 7.3 for another attribute, but you can clearly tell the difference between a score of 4.2 for one attribute and 9.1 for another attribute. Based on a decade of running hundreds of these surveys, I have also found that how you ask the question and present the attributes in the survey can dramatically impact the scoring range.

When analyzing the data, a score of 8.5 or higher we classify as ‘Tier 1 attributes’ – the most important factors of customer choice. There are typically 2-3 of the attributes for each primary research study that fall within the Tier 1 category. These are the most critical attributes that customers evaluate when making a purchasing decision.

Between 7.5 and 8.5 are Tier 2 attributes that are secondary to Tier 1 attributes. These attributes are important to customers and will drive choice when Tier 1 attributes are comparable between two options; but only when Tier 1 attributes match; Tier 2 are therefore not the most critical attributes. Scores between 6 and 7.5 fall within what is defined as the ‘Zone of Indifference’ – attributes that are nice to have, but customers are indifferent to them when it comes to driving their ultimate buying decisions. Attributes that score below a 6 are not important when it comes to driving choice. The final output of a customer buying preferences section of questions is below:

In summary, the customer buying preferences from a biotech primary research study are critical when determining what attributes customers value when making a purchasing decision. Determining which attributes to include in the survey is crucial and understanding how to ‘tier’ the responses to the survey are paramount when creating the customer buying preferences section of the primary research study; and using the output data for strategic planning.

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