Best practices for B2B customer experience programs
Companies that focus on business-to-business (B2B) sales and services models have unique Customer Experience (CX) challenges due to long sales cycles and multiple decision makers. Although you can steal some best practices from business-to-consumer (B2C) sales, B2B has its own set of tools that can improve your customer experience. This article summarizes the relevant best practices that have been identified in the limited prior published research and augments this with the knowledge shared by leading practitioners in B2B research.
1. Organizational-Wide Efforts
In order to manage customer experience, the effort must be organization-wide, from sales, customer support, product, quality, and so on. It is critical to have constant executive support otherwise engagement with the program will decline and customer experience will worsen.
Ideally, before any customer data are collected, the organization should align behind an overall goal of managing and improving customer experience. Best practice is typically to have the CX program come as a C-level initiative aimed at driving better business outcomes by managing customer experience. From there the company should adopt a balanced set of agreed-upon metrics that reflect key objectives, and which are aligned to the overall business objectives. Subsequently, there should be regular organization-wide communications from the C-level about the improvements that are being driven by the CX program. Aligning the CX program with the sales cycle can also help extend the impact and viability of the program.
Best practices for B2B CX organizational outcomes:
- Start with buy in at the C-level
- Think of the CX research program as an extended or in-depth feedback program
- Reshape internal processes to deliver continually improving customer experiences
2. Contact Management
In B2B research, getting the right respondent to take the survey can be a complex endeavor, particularly since it is often necessary to have multiple people respond to the same survey in order to capture the needed insights from across the organization. Additionally, in many B2B CX contexts, the ideal respondent is a high-profile individual that influences decisions about the business relationship and it can be very difficult to get them to participate in the survey.
For these reasons, it is important to design the research in such a way that the input of these individuals is only required infrequently, generally only for relationship surveys 1-2 times per year. Additionally, leveraging the entire account team within your own organization to help identify, pre-notify, and then request survey participation from these individuals will be key to ensuring that the data collected are as targeted and relevant as possible.
Best practices for B2B CX contact management:
- Create a respondent map for each customer organization and create rules around when each should be contacted and avoid sending multiple surveys in too short of a timeframe. Protip: Take it a step further by creating B2B Personas
- Target survey requests very carefully to ensure that the right individuals are being asked to participate
- Make the feedback experience feel as personalized to each individual as possible through surveys and emails that pull in personal info like, name, account rep, products and length of tenure
- It is better to use more but smaller and very targeted surveys than larger more general surveys
- Most B2B companies rely on a CRM platform to manage contacts and milestones, integrating with those tools can help automate contact management
3. NPS Might Not Be The Correct Metric
The Net Promoter Score (NPS) is a well-established metric that is commonly used as a customer experience performance indicator in B2C research. When done using the prescribed methodology, B2B researchers using NPS tend to see high response rates across a variety of customer types, but the direct link of the score to business outcomes in B2B can be difficult to demonstrate.
However, there are some critical issues with NPS that may make it less suitable for B2B CX research than other measures. First, it is very easy for organizations to get focused on the “score” and lose sight of true customer centricity. Second, there are at least three distinct populations of respondents in most samples: 1) those that know how NPS is scored and adjust their responses based on that knowledge, 2) those that know how NPS is scored and do not adjust their responses, and 3) those that do not know how NPS is scored. Responses from the second and third groups should be comparable and valid, however, responses from the first group cannot validly be counted with those from the other two groups due to the difference in how the response was formulated. Finally, it requires sample sizes that are 2-3 times as large as other comparable metrics that are based on mean scores in order to achieve the same margin of error.
Alternative metrics that organizations should consider using for their B2B customer experience research include: overall satisfaction (OSAT) for relational surveys, and Customer Effort Score (CES) for transactional surveys. Both of these metrics can be used for competitive benchmarking by calculating Share of Wallet using the Wallet Allocation Rule.
Best practices for using NPS in B2B CX research:
- Focus on the verbatim NPS feedback and use it as a tool for closing the loop with individual customers
- Use the likelihood to recommend question primarily as a guide for when to follow-up
- Do not focus on the calculated score from the NPS question – rather use the ratings to inform when it may be necessary to close the loop with individual customers
- Consider using an average (mean) for NPS rather than dividing the scale by ‘Promoters, Passives, and Detractors’
- If calculating the score for NPS, collect at least 1,100 responses to achieve stability
- Given the small sample sizes for B2B, consider using the mean score from the NPS scale rather than throwing out all of the data from the respondent scored as ‘Passives’
Benchmarks are valuable for providing organizations with a relative metric of performance. There are two broad category benchmarks: internal and external. For internal benchmarks, the most common approach is to assess the same metric(s) to track performance over time. For external or competitive benchmarks, the most common approach is to collect data on the same metrics for your organization and competitors or peers in order to assess performance relative to others.
Best practice goals for benchmarking in B2B CX research:
- Within-country comparisons are typically more valid than cross-national comparisons, even within the same business unit
- Focus on rates of change across benchmarked units rather than absolute values across units
- When possible, use relative metrics rather than absolute metrics
- It can be important to ensure that the respondent samples are similar when attempting to make benchmark comparisons
5. Linking Survey Data with Business Data
Many companies struggle to link experience (X-data) and operational data (O-data). Measures of experience metrics are common, but these are rarely linked to data on purchase decision drivers and financial performance. Understanding the factors that are driving the purchase decision can inform which experiences to focus on with metrics like CSAT or NPS so that the correlation to financial performance is maximized. This will also ensure that organizational action toward experience management is targeted at factors that will improve customer experience in the ways that are most likely to drive improved financial performance. Additionally, for B2B, data analysis approaches may need to be adapted somewhat from the B2C application in order to accommodate B2B financial models, like Software as a Service (SaaS).
Best practices for linking survey data with business data in B2B CX research:
- Always identify as many potential external sources of data that may be linked to the survey data as possible
- Work to develop the link between X-data and O-data within your organization
- Use business data to assess survey data for bias
- A strong bias indicator is present if (a) the distribution of the auxiliary data differs between respondents and nonrespondents, and if (b) those variables are correlated with the X-data. To test the latter some linkage between auxiliary variables and experience data is necessary, though not for all cases, which could help with privacy concerns.
Traditionally, customer lifetime values are higher in B2B sales than they are in B2C, so focusing on retention and referrals can bring a quick return on investment. To make these improvements, you must first understand customer experiences and journeys and know how your customers want to be delighted.
To get more B2B research best practices, download the eBook: A New Approach for B2B Customer Experience Management.
A New Approach for B2B Customer Experience Management