Customer Interviews for Startups: Strengths, Limitations, and Solutions

Customer interviews are a cornerstone in startup market research, especially within the Lean Startup framework. They serve two main purposes: understanding the current situation (status quo) and predicting behavior in hypothetical scenarios (what if).

Capturing the Status Quo

The primary goal of customer interviews is to understand existing conditions. Typical questions include:

• “How do you process invoices in your company?”
• “What’s your responsibility in invoice processing?”
• “Which department do you send the processed invoices to?”

While interviews are effective for gathering this information, biases from both interviewers and interviewees can distort results. These biases can be mitigated with proper techniques and careful selection of participants.

Predicting Decisions in Hypothetical Scenarios

Another aim of customer interviews is to predict how customers might behave in hypothetical situations. Questions might include:

• “Would you prefer the green button or the red button?”
• “How important is it for you to speed up the invoicing process?”
• “Would you buy software that helps you with the invoicing process?”

However, these interviews often fall short due to several factors:

• Situational Influences: Interviewees' responses can be swayed by various factors, some of which they may not even be aware of.
• Intention-Behavior Gap: People often do not act on their stated intentions.
• Complex Decision Factors: Real-life decisions involve numerous factors that are difficult to capture in an interview.
• Simplification Error: Understanding whether a feature will be liked is less important than understanding the overall decision-making process.
• Innovators’ Biases: Innovators may fall prey to biases such as selection bias, representativeness bias, acquiescence bias, confirmation bias, overconfidence bias, and optimism bias.

In summary, while interviews can effectively capture what users currently like or dislike, they are less reliable for predicting future preferences.

Leveraging KPIs for Assessing Solutions

To address these limitations, Metrics-driven Market Validation suggests using Key Performance Indicators (KPIs) to measure the performance of new products or services. This method allows organizations to assess the value-added of a solution based on their existing metrics.

• High-Level KPIs: Measure overall organizational performance, such as revenue, EBIT, and costs.
• Low-Level KPIs: Assess specific functions or tasks, like response time to customer inquiries or inventory levels.

By aligning the value-added of a new solution with the customer's KPIs, organizations can immediately see its relevance and effectiveness.

Economic Benefits and Business Cases

The ultimate goal is to translate KPI improvements into economic benefits. This involves creating a business case that shows the correlation between KPI improvements and economic metrics like revenues, profits, costs, time savings, and risk reduction.

For example, a call center with 200 agents each costing $50,000 per year each might implement an AI solution handling 15% of the calls. This could lead to either a 15% increase in call handling capacity without additional costs or a 15% reduction in personnel costs, saving $1.5 million annually.

However, the path from KPI improvement to economic benefit can be complex and specific to each organization. Therefore, it’s advisable to collaborate with customers to develop business cases, ensuring credibility and accuracy.

By focusing on KPI improvements and working closely with customers, startups can better demonstrate the tangible benefits of their solutions, making it easier for customers to make informed decisions.

Stay tuned to learn more about Metrics Driven Market Validation in future posts.