
<p>As a strategy, using data to make better product strategy decisions seems like a no-brainer, but when it comes to finding tactical uses for that information, even a seasoned data professional can have trouble turning data into actionable tasks. The range of data that is relevant to a product manager is incredibly wide and no two companies are exactly the same with regard to their data inputs and needs. Some information (i.e. new feature adoption) is proprietary to product management, but other metrics (i.e. retention, time spent in product) need more context before they connect directly to a product.</p>



<p>To do product management well, there’s a lot of data to take into account, and it comes from a wide variety of sources. It’s all useful in some way, but it is most impactful if it can be wrangled into one business intelligence tool to maximize the data for important decisions, and to paint a full picture. To use data as a product management decision maker, you need to use a powerful platform that helps connect, organize, analyze, and share data with the right people at the right time. Here are a few of the key reasons why a sophisticated data platform is the most important part of my decision-making process.&nbsp;</p>



<h2 class="wp-block-heading"><strong>Make the right data easily accessible</strong></h2>



<p>The biggest benefit of a data platform is that information from any number of different inputs can be combined into one place where anyone from that organization can access it for analysis. With all of the inputs plugged into a single source of truth, product managers can find any data they need to make decisions. With live connections to the source, the information is always current so I don’t need to worry about when it was extracted or worry about version issues.</p>



<p>At Sisense for Cloud Data Teams, we have a team of data professionals who partner with the product team in many ways. Since we all use the same data platform, that team is responsible for maintaining the data connections and ETL from our various sources running properly. They also clean the messy data and model it to make sure it is usable for the product team and the rest of the org. Having a team like that prepare the data means I have a lot more time to explore the data to look for trends, outliers, goal-specific metrics or any other a-ha insights. It also means that I know the analysis I’m reviewing has been verified and the assumptions checked, so I don’t need to waste time double checking sources and business logic to make sure they’re accurate.</p>



<h2 class="wp-block-heading"><strong>Communication with stakeholders</strong></h2>



<p>Product data is critical to the success of the entire organization and is used by cross-functional teams to improve operations and drive strategy. The product is the primary way (the only way in most cases) that most customers engage with a company, so that data is vital to almost every part of an organization. Because of this, product managers generally have a lot of stakeholders who create and consume data; they all make data-based decisions on a regular basis. It’s not a sustainable solution to have one person (or even a small team) in charge of downloading information, preparing it on a local device and then upload or send to all the various stakeholders.&nbsp;</p>



<p>The best way to distribute that information is to work on a shared platform that allows a product manager to own the information and visualizations of relevant data and then invite stakeholders to view that data through the platform or set up regular reports to be delivered automatically. This way, permissions can be managed so that each one has exactly the access they need and the product manager can distribute information on time with little additional effort. With Sisense for Cloud Data Teams, I can create any chart or dashboard that a stakeholder needs to see, then share that asset with the right people once and stop worrying about it. The data updates automatically and my coworkers can dig into the data on their own. It’s the best workflow for everyone involved.</p>



<h2 class="wp-block-heading"><strong>A/B testing</strong></h2>



<p>A lot of product decisions require a series of small changes that add up to optimize our customer’s experience and productivity. Making decisions about those changes is very difficult to do in a vacuum. Product managers usually have good instincts, but it’s not enough to just make a decision and leave it. Good product teams are always looking at data to see the effects of their decisions. One of the main tools that product managers use to evaluate those changes is A/B testing.</p>



<p>In order to do those A/B tests right, product teams need a data platform that is connected to the relevant data that needs to be measured and that can compute the required statistical metrics. A lot of these decisions are made in a very short window of time right after a new update has been released, so the data has to be made available quickly. Fast data by itself isn’t useful unless the product managers reviewing that information can be assured that it’s accurate. There are many pitfalls to A/B testing, so it’s imperative that product managers can trust that it’s valid.</p>



<h2 class="wp-block-heading"><strong>Product adoption and usage tracking</strong></h2>



<p>These KPIs are the holy grail of product management metrics. This data is worth tracking on a daily basis. For every feature and update that is launched, it’s crucial to keep an eye on how how it is performing, who is using it, how they are using it, how long they are using it, etc. These numbers need to be tracked in aggregate and also broken down across customer account, industry, company size, job function and more. Any of the metric breakdowns I just discussed can also be shown across different time periods, compounding the number of charts to track even further. Usage and adoption metrics can be tied to win rates, trial conversions, retention, upsells, etc.&nbsp;</p>



<p>In summary, there’s a lot of measuring that needs to go on. Every product manager has different goals, but the value of the data they process is limitless. To make the most of it, you need a data visualization solution that gets accurate information to the right people at the right time.&nbsp;</p>



<p>If you’re looking for more information about how a data company uses analytics for product management, check out my post on the <a href="https://www.sisense.com/blog/how-sisense-for-cloud-data-teams-uses-its-own-product-for-product-management/">three types of product management dashboards</a> that I use. If you’re interested in learning more about how Sisense for Cloud Data Teams can help with your product management data, <a href="https://www.sisense.com/company/contact/">request a contact</a> and one of our experts will reach out to you soon.</p>


How Data Powers Successful Product Management

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