Product Analysts Explained: Product Development in the Era of Digital Transformation
- Author Alexandr Raevskiy
- Published October 12, 2021
- Word count 1,506
Digital transformation is challenging companies all around the world. It targets all of a company’s main business and operational processes and creates a lot of turmoil and uncertainty within the in-house teams. To drive digital transformation changes in the right direction, you need capable professionals, including analysts. Three years ago, one of our business analysts shared her insights (https://auriga.com/blog/2018/business-process-automation-a-big-no-to-routine/) on the basic objectives of a business analyst on a project. Now it’s another one of Auriga’s business analyst’s turn to tell you about his job as a product analyst. Tech companies’ products are their primary source of income. Therefore, the successful digital transformation of the product development cycle is one of the main goals. Product analysts are usually in the midst of a project, be that web or mobile app development. It’s hard to overestimate their contribution to the development of products (and the owner company’s business). This article sheds some light on their role in digitalization and how one can automate product analysis processes.
Product Analytics: The Path of Growth
Digitalization helps companies to become more effective, which usually leads to cost reduction and bottom-line growth. IT expenses become investments accompanied by measurable NVP and return ratios. However, trimming internal process costs is only one of the constituents of net profit. Another is the company’s revenue. B2C and B2B companies put lots of effort into marketing their digital products (websites, marketplaces, mobile applications, and portals) so users can seamlessly interact with them. Spending the budget on digital product development and potential customer acquisition without investing in product development analysis dramatically reduces the return on investment.
Defining Users’ Paths
The modern digital product development methodologies based on the Agile principles imply constant transformation and product adaptability to rapidly changing market needs. Before making changes to an existing product, it’s vital to define what needs to be changed. If we take the internal accounting systems where users (employees) strictly follow the instructions, the reason for making changes will be a business process change. Meanwhile, in digital products where users (potential or current customers) don’t have to follow any instructions, users’ behavior and interaction with the product are based on changes. A product analyst knows how to define customer journeys and user preferences for consecutive analysis and product modification.
Enhancing the Product and Market Relationship
In practice, a product analyst is responsible for the following tasks:
Search for growth hypotheses (defining advisable changes in digital products);
Assessment of changes’ impact on business metrics (potential growth prognosis);
Introduction of options for quick hypothesis test (defining ways of quickly adopting changes to confirm the changes’ positive influence on the metrics); and
Verification of the effect of the hypothesis’s realization (change adoption) and suggestion of further changes.
By completing these tasks regularly, companies can quickly respond to market changes. For decision-making, a professional analyst uses the data-driven approach instead of depending on the prejudiced opinions of concerned parties who constantly generate various hypotheses, playing Russian Roulette. A product analyst makes and tests the product improvement hypotheses by relying on actual user behavior data.
Improving User Experience: Stages
- Choosing metrics
First, one must define and document the metrics and conversion funnel hierarchy, serving as the main criteria for the digital product success assessment. The final user’s transaction (the purchase) secures the product owner’s profit. The user ends up purchasing after several intermediate conversion actions (for instance, registration on the website, placing items in the cart). These actions must be recognized and recorded.
- Tracking user activity
After defining the metrics, the analyst needs to deploy user activity tracking tools to collect data about the customer journey and how customers use the product at each funnel stage. The analyst defines all possible user paths and critical events that lead to the desired transaction at each stage. Tracking systems allow data to be collected from the first user contact (for example, a Google ad) to the conversion transaction that profits the company. Collected data is used as an input for the next stage – the analysis.
- User path analysis
At the analysis stage, a product analyst defines the user path up to the final successful transaction. As stated above, unlike in-house business processes regulating employees’ actions, users can perform various (and sometimes unforeseeable) actions. Their journeys from the first contact to the conversion transaction vary dramatically. An analyst analyzes different aspects of these journeys: the average journey length, users’ actions, number of “lost” users who didn’t make a transaction and thus brought no profit. A product analyst uses the cohort analysis tool to reveal dependencies and meaningful insights between user characteristics, acquisition channels, behavior, devices used, season, etc. The analysis is performed to create growth hypotheses or changes to be applied to the product.
- Creating and testing hypotheses
Not all hypotheses are to be realized; every one of them needs to be prioritized first. To do that, a product analyst assesses the impact the planned changes might have on the product metrics, for instance, by implementing the impact mapping technique. However, this doesn’t guarantee growth. Any hypothesis is just an idea, and only through testing can its effectiveness be proved or disproved. An analyst decides how to implement changes and track the outcome quickly and efficiently. Analysts implement minimal modifications to the product to verify a hypothesis, and the fewer resources spent on it, the better. The main criterion here is to capture the actual effect of the modifications confirmed by the customers’ behavior.
To assess the effectiveness, analysts compare the newly acquired data with the previous period’s results or introduce changes only to a specific user type and compare their results with those of a control user group for whom the changes weren’t implemented (A/B test).
After the analysis is performed, the hypothesis is either rejected or confirmed. Then it is passed on to the engineering team to become part of the product’s new functionality.
Why do companies need product analysts?
The constant process of making changes with reasonable effort and efficiency monitoring allows you to deploy and maintain continuous digital product development and quickly respond to market changes. The product analyst can get involved in the development process either before launch or when customers are already using the product.
Usually, the product development team needs a product analyst if there are specific tasks to be completed:
Product adaptation to market expectations (target audience);
Development of a lead in the field; and
If your company needs a product analyst and you are considering searching for one, I recommend you pay attention to the following qualities of the candidates:
Knowledge of modern automation tools. A product analyst works with big datasets. The ability to process raw data as well as choose the right tools is an absolute advantage.
Strong analytical skills and knowledge of algorithms and statistics. Automation tools are handy, but they cannot replace the human mind. It is not enough to know how to get the results – one should know how to interpret them and determine the underlying conditions.
The ability to set achievable goals and choose meaningful metrics. An analyst should be able to identify the mission-critical characteristics of the product and measure them without being paralyzed by perfectionism.
The ability to create hypotheses. One of the analyst’s tasks is developing and testing hypotheses to make decisions on the necessary product modifications. Surprisingly, many analysts struggle to create and test ideas.
Excellent communication skills. The analyst has to interact with many different people with diverse roles and backgrounds, so finding common ground is crucial.
If all of the information mentioned above sounds quite tricky and you need an analyst right now, you should contact a company with product analysts on staff. Auriga is a custom software developer that employs developers, test engineers, business analysts, product analysts, and data analysts who are ready to get involved in your project.
Not all hypotheses are to be realized; every one of them needs to be prioritized first. To do that, a product analyst assesses the impact the planned changes might have on the product metrics, for instance, by implementing the impact mapping technique. However, this doesn’t guarantee growth. Any hypothesis is just an idea, and only through testing can its effectiveness be proved or disproved. An analyst decides how to implement changes and track the outcome quickly and efficiently. Analysts implement minimal modifications to the product to verify a hypothesis, and the fewer resources spent on it, the better. The main criterion here is to capture the actual effect of the modifications confirmed by the customers’ behavior. To assess the effectiveness, analysts compare the newly acquired data with the previous period’s results or introduce changes only to a specific user type and compare their results with those of a control user group for whom the changes weren’t implemented (A/B test).
Alexandr Raevskiy is an expert system analyst at Auriga Inc. (https://auriga.com/).
Auriga, Inc. is a U.S. software outsourcing service provider offering a full range of software engineering services to help manage both teams and projects for high-tech and software vendors. Its client list includes Barclays, Broadvision, Chrysler, Digital Guardian, Draeger Medical, Hewlett-Packard, IBM, Lynx Software, nVent, and many other leading tech companies. For details, please visit https://auriga.com/.Article source: https://articlebiz.com
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