Cold Calling experiment

We're building a comprehensive knowledge library about product development as part of our mission. The library is for anyone looking to make better decisions — primarily decisions about product development. Whether you're an inventor, a product manager, or a Chief Product Officer, using the right research methods and experiments increases your chances of building the right things for the right audience. Today we'll introduce the Cold Calling validation method.

When to Use This Experiment?

Cold Calling fits when interest in a product or service needs to be validated quickly within a specific segment the team has no access to. It works best when:

• the target group is narrow and can be found by name (companies, professions, suppliers), for example on LinkedIn,

• the team has no network, newsletter, or community of its own,

• the goal is to validate willingness to commit, not just opinions,

• the product depends on winning the other side of a marketplace (suppliers, partners).

Basic Experiment Principles

The idea is to phone people who have never heard of the product. Cold calling is one of the least liked channels, which makes every agreed meeting stronger evidence of interest than an ad click.

1. Define the hypothesis. Write down one assumption and the commitment that would confirm the problem hypothesis (e.g., "Car rental owners agree to a 15 minute meeting about fleet utilization").

2. Build a contact list. Find 30 to 50 decision makers in the target segment, for example on LinkedIn, and log them in a spreadsheet.

3. Prepare a short script. Write an opener under 30 seconds: who is calling, why them, and what small commitment is being asked for. Don't sell anything. Ask for time, feedback, or a free trial. This is research, not sales.

4. Call and iterate. After every five to ten calls, review where people hang up and adjust the opener or the argument so they stay on the line.

5. Collect the data. For every call, record whether a decision maker was reached, the call length, the problems and objections raised, and the resulting commitment. The key metrics are connect rate, conversation rate (calls longer than a minute), and commitment rate (meetings agreed per conversation held). Commitment rate is the decision signal. Typical B2B cold calls lead to a meeting in about one of 20 conversations held, and only about one in 300 dials. If around three in ten conversations end with an agreed meeting and the same problem comes up unprompted, the hypothesis holds and the team can move on to meetings or a prototype. A result at the usual baseline means the problem isn't painful enough, or the segment or message is wrong.

6. Identify the risks. A small sample gives direction, not statistically robust results. Outcomes depend heavily on the caller's skill. A polite yes on the phone is not willingness to pay. The method works poorly for consumers and for segments that can't be found by name. Data protection and local telemarketing rules also apply, and in some countries they require prior consent.

Real-World Experiment Example

Link to research: First Round Review: Gusto's Path to Product Market Fit

In 2012, cold calling helped Gusto (then ZenPayroll) find its real customer. The founders originally planned to sell a payroll API to large software platforms. The platforms said the idea was interesting but not a priority. So co-founder Tomer London flipped the hypothesis: what if payroll was a real pain for small businesses rather than for platforms?

London shut himself in a walk-in closet and called small business owners he found on Yelp: laundromats, convenience stores, vet clinics, a kids' swim school, a flower shop. He opened each call by asking for help. He introduced himself as a Stanford PhD student with a few questions and, as a foreigner, wasn't shy about asking how payroll actually worked for them. Many owners were happy to talk to a technologist who could build a tool for their daily work.

Most calls ended in rejection. London took it as part of the job and pitched a slightly different version each day based on the previous day's results. He judged calls by their extremes. About 90% of conversations ended politely neutral, which he treated as nearly worthless data. A sharply negative reaction showed he was wrong about the customer, the service, or the message. An eager "where do I sign up?" confirmed real interest. One flower shop that had no payroll provider at all became a customer on the spot.

Roughly two in ten owners were instantly sold. The team then looked for what those customers had in common and narrowed its focus to California companies with salaried employees only.

What Can Be Tested With This Experiment?

The main value of the method is that it measures strangers' willingness to give their time, not their opinions. It works best in B2B and for marketplace products.

• Problem existence and urgency: whether prospects describe the same pain without being led. The signal is a recurring problem description across calls.

• Willingness to commit: whether the segment will give time for a meeting or a pilot. The signal is a meeting rate well above the usual cold outreach baseline.

• Supply side interest: whether suppliers or partners will join before the product exists. The signal is agreement to meet or to take part in a pilot.

• Segment reachability: whether decision makers can be reached at all and how many calls one quality conversation costs. The signal is connect rate and an estimate of acquisition cost.

• Value proposition strength: which wording holds attention past the first 30 seconds. The signal is longer conversations after script changes.

• Key objections: what blocks adoption. The signal is recurring rejection reasons that the product or messaging can address.