CX and brand work (and writings) almost always focus on B2C. The reason is quite simple: it’s easier.
- B2C companies typically have far more customers, so it’s less difficult to collect sufficient data that is statistically reliable.
- While some people spend considerably more than others, we don’t see the 800-pound gorilla problem that confronts most B2B firms, where a small handful of customers account for a wildly disproportionate share of the business.
- The decision-making process in a consumer household is far less complex, so you don’t have to worry as much about the “role” or importance of the respondent.
- While there may be a household email address, the problem of gatekeepers is a non-issue with consumers.
- Incentives (which boost survey response rates) don’t raise the same ethical red flags with customers.
- People are much more likely to express their thoughts online in terms of their personal experiences than in the context of their work responsibilities.
- B2C firms are more prevalent and familiar. As consumers ourselves, we identify more readily with stories about the B2C experience.
Mea culpa: I also often focus on B2C, probably for the same reasons.
The B2B Customerverse
Many B2B firms have fewer than 10,000 customers, with some under 1,000 or even fewer. Small customer populations make it difficult to gather sufficient feedback for reliable statistical analysis. The problem is compounded when the customer base is heterogeneous and must be partitioned by LOB, geography, or some other criteria or segmentation for alignment with how the company operates and goes to market and the nature and needs of customers. Few B2B firms are monolithic, which means that the already small customer base needs to be parsed into even smaller cohorts, compounding the problems of statistical analysis. Given scale usage differences across cultures (affectionately referred to as “scale usage heterogeneity”), moreover, even simple aggregating of data internationally is problematic. Now add to this headache the issue of frequency of measurement (is an annual measure sufficient and how often can you gather feedback from customers?).
Virtually every B2B company also has its own version of the 80/20 rule (the Pareto distribution that postulates that 80% of outcomes stem from 20% of the inputs or causes). The problem is that for most firms the skew is far worse at the top end, where the 10 or 20 largest customers often account for half of the business. This leaves B2B firms torn between either (1) averaging the data, counting every customer equally as a single unit (that is, acting as if Amazon, Apple, and Coca-Cola are the same as Joe’s Bar & Grill) or (2) weighting the data by sales or profit numbers, in which case the biggest customers drown out the voices of everyone else. (The weights required in such an exercise, moreover, also far exceed the levels considered reliable by the stats folks).
Account Managers: Salvation and Problem
B2B relationships of any size almost always are managed by an Account Manager, with the largest customers having a dedicated Account Team. In many instances – even among some of the largest B2B firms – it is the Account Managers who have the best contact information for customers. Simply put, some of the most successful and biggest B2B companies have lousy marketing customer information databases with incomplete and spotty customer contact information. They have reliable data for billing, but not necessarily good contact info for feedback purposes.
By contrast, the Account Managers typically have the best, most accurate, and complete customer contact information. They often hoard that information, however, for tighter control over the customer relationship, rendering the company dependent on them for surveying or interviewing customers. The Account Managers are the solution to this challenge, but they also present other problems in that they sometimes want to control the data collection process by either deciding which of their customers can be contacted or even wanting to conduct the surveys themselves. This is like the fox installing the security for the henhouse in terms of the implications for the reliability of the sample and data.
The B2B Sampling Challenge
What could be less sexy than talking about sample? Therein, however, is the core of the challenge: not enough sample, inadequate/inconsistent contact information, hard-to-reach people, poor response rates, and lack of clarity regarding potentially complex customer decision-making processes that define who are the best people to address which issues.
Knowing the population that the sample represents (and doesn’t represent) is critical to understanding how to use (and not use) the data that is collected and its statistical reliability. In many instances, moreover, it is the change over time that is more important than the data at any specific point in time. Any meaningful comparison between time 1 and time 2, however, is totally dependent upon the comparability of the samples at time 1 and time 2. If the samples aren’t comparable, there is zero validity in comparing the data over time.
Managing the Challenge
The most important step is building and maintaining a comprehensive CRM system that can be used as the ground truth for defining the customer population and identifying all the relevant contacts – and their contact information. This requires more than the CRM platform; it necessitates establishing and enforcing policies regarding maintenance and building a culture that recognizes the value of keeping CRM records current and reinforces that behavior on the part of the Account Managers and all customer facing employees. While the description of what needs to be done sounds easy, this is quite a big lift for many firms, regardless of their size. (I did work with a Fortune 50 tech firm that was largely held captive by their account people and did not have this system in place.)
Even if the firm has a great CRM, the problems of a small, heterogeneous customer base, gatekeepers, complex decision-making, and low response rates remain endemic to B2B. Companies should be parsimonious in the frequency of data collection and the length of their surveys, target requests efficiently, use engaging feedback tools, etc. But there are no silver bullets for the underlying challenges. Those issues cannot be solved by soliciting feedback more often, using rolling averages, or simply adding together dissimilar groups.
While it might seem anticlimactic, the most important strategies are to:
- understand very clearly the sample population(s) from which you are collecting feedback,
- make every effort to replicate those populations for comparability over time,
- analyze and project the findings back only upon the population it represents, and
- recognize any statistical limitations of the data.
Use qualitative approaches where the quant simply won’t work or the qual is better suited. Sample in alignment with how the company goes to market to maximize the value and utility of the feedback. Appreciate the value of account-level feedback for use in managing accounts, even if you can’t aggregate the data across accounts.
The B2B measurement conundrum, in other words, isn’t solved, it’s managed.
