Data challenges for the product manager
Product managers make decisions every day that have lasting effects on their product line. In setting both long-term and short-term goals and priorities, a PM uses many sources of information. When asked what the biggest challenges are in their role, the number one challenge chosen by PMs surveyed was “lack of data to make well informed decisions”. In fact, 3 of the top 5 challenges have to do with data; the lack of access of it, the lack of understanding it and the challenges of using it in various contexts.
Useful data can tell product managers what their customers want, what the market is doing, what moves competitors are making, and much more. But because data comes with its own challenges, it is no surprise that many strategy, business and product decisions are made based on anecdotal information and in attempts to fight fires (that are sometimes caused by data challenges to begin with).
It is critical for the product manager to have the ability to look the data in the eye as it will help him define, understand and prioritize goals of his strategy. With data, the product manager can define the steps to be taken, predict challenges, and anticipate customer or market responses and pivot his path accordingly. Business decisions must be backed by data. It is a positive trend observed recently that most companies are increasing investment in data-processing, analytics and machine-learning software with a desire to become more data-driven. In the process of doing so, there are some challenges that still require attention.
When we asked product managers about the tools they use to identify opportunities, risks and trends (or as we like to call them ‘business insights’) we found no consistency. Some are using third party research while others rely solely on internal analysis. Many are searching the internet when they need information, without a set strategy. With so many data sources, multiple issues arise:
If many people in your organization are creating data but you don’t have access to it, you may be losing out on valuable insights. Perhaps marketing commissioned a competitive study, sales is going to regular customer meetings, operations has customer satisfaction information and engineering exchanges usage information with customers. To be able to make better data driven decisions you must have a plan for accessing all of this data for analysis. If you don’t know what you are looking for, machine learning and artificial intelligence have come a long way in being able to pull business insights from your existing data and is coming to give it an extra kick.
Customer Insights Get Lost
There is a good side to the data product managers need to use. Product managers to collect data on their own and also interact with customer facing teams in order to understand the market. So congrats! The first step has been taken to be more data-driven and specifically, more customer-data-driven.
Information from your customer can be the most valuable data available to your brand. What does your customer want, which competitors are they considering (or left in favor of your product), which features are they unhappy with, what are their challenges that your product could answer, what are your strengths and what are your weaknesses? Whether you realize it or not, customers are giving information to your organization. When we asked product managers about the tools used to record customer interactions, we found no consistency with the tools used and were surprised to learn that in some cases, interactions are not captured at all (or as one respondent put it “oh yeah? Nowhere! This question hurts!”).
One challenge for product managers is that they are often trying to build a strategy using anecdotal information based on a few meetings with sales or the top Google results. Weather we like it or not, product managers have the same limitations as everyone: they only have 24 hours in a day. With all of their other responsibilities, they only have so much time to talk with customers and do market research.
Imagine if you could be part of every customer meeting happening in your company without actually being there. Or even better, imagine you could gain the insights coming from all the customer meetings happening without actually listening to the entire transcript or read all the meeting notes. What if data sources like customer interviews, surveys, sales calls, conferences and more, all talked to each other? Finding a way to have all of the customer interactions from an organization be accessed and analyzed could produce a major competitive advantage. ThunderAct aims to do just that. Your goal should be to have your data accessible to your entire organization, and it should actually tell you something. Understand your customer better and you can create a better strategy while delivering in-demand products.
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