AMA: Docker Vice President Product Marketing, Rahul Awasthy on Market Research

Great question and It depends on who is asking or how we define "moving the needle" A company is moved by several key needles (so to speak) depending on what they need. A mature company moves the needle by executing at scale. An immature product is searching for product-market-fit and market research may not even be really useful, so better to conduct user-research If the focus is revenue, most research that helps is buyer behavior- Really understanding the pain and the "need behind the need". If the focus is product-fit, it has to be a multi-factorial approach to research

It varies across companies I have worked at - Common ones include - Salesforce, UserTesting, Intercom, Qualtrics, Uservoice, Medallia among others

Managing scattered customer feedback can indeed be challenging. Thinking about a single account/users to connect the feedback is needed often and systems may not be set up for that. For basics, explore and play with AI - even chatGPT and tools that allow chaining of feedback will enable summary analysis and insight extraction Some approaches that maybe helpful are - Customer Feedback Platforms: * Qualtrics - has solutions based on use-cases such as NPS, VoC, CX and EX * Salesforce - Often under-utilized, salesforce can be a wealth of data not just from sales, but also from integrated customer success teams adding information to your CRM - includes slack integration Data Integration and Analysis * Tableau, Looker and other BI tools can offer quick integration into data sources and visualize quant as well as qualitative data including data from Slack Reporting Tools: Domo and similar tools can serve as centralized reporting, but TBH, many times an excel does the trick for smaller projects. Sharing the data broadly may need you to extract insights from excel into slides

It depends on a few factors. 1. How is segmentation being used ? - for campaigns, to generate pipe, for sales motions ? 2. At what stage of the sales cycle is segmentation proving to be most effective ? early qualification or pipe-gen vs mid-stage ? In order for broad pipe-gen efforts, cohorts are often more helpful than pure segments based on basics such as demographics, age, buying power, titles, etc. They are a start. Revaluation on a quarterly basis is helpful, but must be aligned with the goals for re-evaluation. Why re-evaluate ? Is the current segmentation not yielding results or is too broad ? how long has it been in execution ?

The key to validation is a 360 approach and not relying on a few signals alone. Market research is one way to validate product differentiation. AI through chatGPT or other tools can give us a framework. For example 1. Competitive Analysis 2. Customer Interviews and Surveys- use tools that offer real-time sentiment, user feedack, seasonal testing 3. Market Trends and Industry Reports - Gartner, G2, Forrestor, others 4. Beta Testing and MVP Feedback: Super helpful in early days but this will definitely change depending on channels and GTM approaches There is no single silver bullet for market research. Gone are the days where citing a report, a survey, a Mckinsey analysis is enough. The The key to validation is a 360 approach - which may seem noisy, but is essential to gathering data from experts, users, buyers and influencers. THEN - AI tools maybe able to summarize and extract insights from a plethora of data that may seem overwhelming and disconnected to humans

Leverage specialized firms - there are several 3rd party firms that do the hard work of vetting for titles, anonymity and interviews/focus groups with selected parties that can speak to confidential/sensitive verticals such as healthcare, federal and insurance Often these specialized research firms offer deeper insights than generic horizontal research across a product

When thinking about PMF research, it can be variable but the approach of documented Iterative loops is helpful. For example Loop1 has 4 key variables to test for by any market research method - Those variables maybe product features, competitive options, messaging and category-maturity - Loop1 can be run for a quarter Loop2 has another 4 key variables - similar product features as loop1, but different competitive approach, adapted messaging to select customers and category could be all maturity levels. Over time as these loops get documented, a clearer picture emerges of what is working and what needs adjustments

Great question. Some of this is a human/org challenge and part of it is a tool challenge. Tip: Humans are far more unpredictable and challenging than software :) So figuring our the org dynamics at your company is key - Who owns this centralized feedback and do they have the systems set up. Let's say at the very manual stage - it's gathering data, using an AI tool to summarize and there is no automation or central data-lake. Product,Marketing, Sales and CS leaders have to align on what is they best Aggregated signal to pay attention to - this is a human problem, org problem as each group will pay most attention to what matters to them most The tool problem can be tackled with advanced systems such as data-aggregation and BI analysis, but standard tools such as tableau, looker, salesforce, intercom and zapier get most teams in decent shape to centralize the data collected across sources