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Sanket Kavishwar is a Senior Product Manager at Relyance AI. With over a decade of SaaS experience, Sanket has spent time as a software engineer building security solutions, as a consultant implementing ERP solutions for enterprise customers, as a customer success leader managing enterprise customers, as a go-to-market leader scaling and helping enterprise customers build advanced privacy programs, and currently, as a product manager focused on shipping products at the intersection of privacy and technology. Sanket loves to talk about SaaS product management, SaaS GTM, product analytics &amp; operations, data privacy, and growth mindset; find him on LinkedIn or Medium if you want to connect and chat more.

Sanket Kavishwar

If you&#8217;re a product manager, these conversations might sound familiar:
You: “I think we need to address this problem.”
Stakeholder: “Why do you say so? Do you have data that supports this?”
You: “This is a top request from our current customers. I strongly think we should add this to our roadmap.”
Stakeholder: “Which customers have asked for this, and why do they need it?”
You: “Building this feature could significantly increase our revenue.”
Stakeholder: “What data do you have that supports this?”
<a href="https://www.mindtheproduct.com/why-product-managers-should-not-be-data-informed-by-jens-fabian-goetzmann/" target="_blank" rel="noopener">Data-driven</a> decision making is a crucial part of product management. From personal experience, leveraging data can:
<ol>
<li>Bolster your argument&#8217;s credibility. Product managers often have to convince other stakeholders why something needs to be built. Data-backed arguments increase the chance of creating a persuasive argument.</li>
<li>Remove emotional bias from discussions, leading to better outcomes. Strong feelings aren&#8217;t always enough to convince others; a compelling, data-supported case is necessary.</li>
</ol>
If you&#8217;re a product manager in a small team or an early-stage company with limited resources both  sales and customer success teams play a significant role in customer-centric product management, and getting data from them will help make better products.
<h2>Sales</h2>
Getting data from the sales team is crucial if you’re a product manager trying to determine what prospects are looking for. Here are three things I recommend getting from your sales team to get you started.
<h3>1. Product requests from prospects</h3>
This data will help you answer the question, &#8220;What is the potential financial impact of building X feature?&#8221;.
Your sales team constantly interacts with prospects and receives new product requests. Establishing an effective process to gather this data and map it to your product backlog is crucial. Collaborate with your sales operations team and set up a process to collect feedback from prospects.
Assuming your account executives (AEs) use a tool to track deals (like Salesforce for example), have them fill out the information with the data points outlined below whenever they hear a new product feature request in demos or calls.
<ul>
<li>The prospect name</li>
<li>The prospect segment (more on this below).</li>
<li>The opportunity amount</li>
<li>Who has provided this feedback (their persona)?</li>
<li>Tangible product feedback. For example, “Interested in Module X” or “Looking for advanced analytics capabilities like dashboards.”</li>
</ul>
From here, either export the data manually or set up an automated integration between the sales tool and the tool where the product backlog is managed. Once implemented, it will help frame internal discussions like this: &#8220;This feature has been requested by X prospects, influencing opportunities worth Y$s.&#8221;
<h3>2. Data about lost deals</h3>
This data will assist you in answering the question, &#8220;How many $s has the company lost because of not having Product feature X?&#8221;.
Sales teams typically record information about lost deals and the reasons why the company lost a deal. Did they lose to a competitor? Did they lose because of a missing product feature? Create a “flag” in the source system to denote these product-related lost deals. Export the data based on this “flag” (automatically or via manual exports), and map it to your backlog. Work with your sales team to identify the lost deals due to missing product functionality and some additional details like the below:
<ul>
<li>Prospect name</li>
<li>The prospect segment (more on this below).</li>
<li>Deal size</li>
<li>What specifically about missing product functionality caused the loss?</li>
</ul>
Once implemented, it will help frame discussions in the following manner: &#8220;Because we haven’t built this feature, we have lost deals worth X$s.”
<h3>3. Data about customer segments</h3>
This data will help you answer the question, “Which are the most asked features within our enterprise and SMB (small and medium-sized business) customers?”.
Understanding that not every feature holds the same importance for everyone is crucial. As a result, understanding customer segments will allow you to discern which features are most coveted for each segment. Sales teams typically segment customers into buckets like “enterprise,” “mid market,” and “small”.
In addition to the raw feedback data, this stratification can help you to understand the context and nuances of each customer&#8217;s feature request. This way, when assessing the popularity of certain features, you&#8217;re not just looking at the number of requests but also considering who these requests are coming from and their specific needs.
<h3>Customer success</h3>
Gathering feedback from the customer success team to understand what your customers are looking for is essential. Customers are an excellent source of information as they are incentivized to provide detailed feedback, given they are paying to use your software.
<h3>Feedback from active customers</h3>
This data will assist you in answering the question, &#8220;How many customers have requested product feature X?&#8221;.
Develop a system (a spreadsheet, Slack channel, etc.) with your customer success managers (CSM) for gathering specific product feedback from each paying customer. Work with your customer success managers to at least get the following data points:
<ul>
<li>Which customer is requesting this?</li>
<li>What segment do they fall into?</li>
<li>Who from the organization is asking for this (their persona)?</li>
<li>What do they want?</li>
<li>What is the pain point?</li>
<li>How will this benefit them in their day-to-day job?</li>
</ul>
In practice, it’s critical to establish a regular forum for your <a href="https://www.mindtheproduct.com/turning-customer-success-into-product-success-by-hannah-chaplin-and-niamh-jones/" target="_blank" rel="noopener">customer success managers</a> to discuss product feedback. Regular discussions about feedback from paying customers yield numerous benefits.
<ul>
<li>They encourage a culture of sharing and discussing customer feedback within your team.</li>
<li>Trends and themes naturally start to emerge as these conversations happen regularly.</li>
<li>They facilitate executive buy-in, especially if they participate in these calls.</li>
<li>They enable the company to close the loop with customers once the feature has been developed.</li>
</ul>
<h3>Prioritizing requests for upcoming renewals</h3>
This data will assist you in answering the question, &#8220;Which features should we prioritize on the roadmap for the coming release that impact upcoming renewals?&#8221;.
Data about upcoming renewals and mission-critical feature requests is vital for product planning. Before entering a planning session, collaborate with your Customer Success team to get a prioritized list of upcoming customer renewals and the renewal dollar amount. At least get the following data points:
<ul>
<li>Customer Name</li>
<li>Customer Health</li>
<li>Renewal Date</li>
<li>Renewal Amount</li>
<li>Mission-Critical Product Asks</li>
</ul>
<h2>Conclusion</h2>
For product managers, <a href="https://www.mindtheproduct.com/evidence-based-product-decisions-itamar-gilad-on-the-product-experience/" target="_blank" rel="noopener">gathering data points</a> is an inevitable part of the job. The recommendations above should give you a head start in building robust data collection systems for scalability and further development.

core/freeform

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