Strategies for Identifying Key Features: Who, What, and When?

  • 25 April 2024
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There is no topic more critical to the processes involved in cultivating a great user experience and increasing adoption than the work of identifying the key features within your product. This must involve a detailed, analytical approach to understanding how different user groups interact with various product functionalities over time.

 

To outline a process for approaching this with an outcome-driven lens, we can delve into a formula to allow teams to collaborate and break down this work:

Key Product Feature + Cohort / Time = Baseline Adoption Goals

This article will outline this methodology, offer up some key questions along the way and take a turn towards the meta by providing a practical example of how we can apply these concepts to track adoption with the Analytics module of PX!

 

The Components

  • Key Product Feature: Identifies which features within the platform are critical for user engagement and success.
  • Cohort: Defines the specific user groups or segments for which the feature adoption will be analyzed.
  • Time: Establishes the timeframe over which feature adoption is measured, allowing for the assessment of how quickly and effectively users are engaging with the product.

 

Cohort Definition and Importance in Gainsight PX

Defining the cohort is the foundational step in analyzing product engagement with Gainsight PX.

This involves identifying specific groups of users—cohorts—based on shared characteristics that impact how they use the product. Understanding these cohorts is essential as it directs the selection of features to monitor and the timeframe for adoption analysis.

You can operationalize cohort analysis within PX by creating segments and/or using saved filters. This functionality allows you to efficiently group users based on criteria such as feature usage, account name, role or other relevant attributes, making it easier to tailor and streamline the adoption tracking process.

For this example, we can use our top 10 healthiest accounts- by focusing on the top 10 accounts, we can benchmark against the best usage patterns and feature adoption rates, providing a clear model for success that can be replicated across other segments.

This approach not only (1) narrows the scope of our analysis, making it more manageable but (2) also enhances the depth of actionable insights we can derive. These insights are instrumental in developing strategies to uplift other users to similar levels of engagement and satisfaction.

 

Alternatives to Top Accounts

While our top accounts offer valuable benchmarks, exploring other cohorts is essential for a well-rounded strategy. This isn’t pivotal to this work the first time around but here are some questions to help identify cohorts as you mature this process:

  1. What specific business outcomes do we want to influence?

    • Identifying whether you're looking to improve onboarding, increase feature adoption, or boost engagement overall can help pinpoint which cohort will provide the most relevant data.

  2. Which user behaviors are most critical to our product’s success?

    • Determine if your focus is on frequent usage, high feature adoption, or perhaps high satisfaction scores. This focus will guide you towards cohorts that are exhibiting these behaviors or those that are not but should be.

  3. How do different segments interact with our product differently?

    • Understanding variations in product interaction across different user roles, industries, or account sizes can help in selecting a cohort that either exemplifies best practices or needs specific attention for improvement.

 

 

Key Product Features

Upon establishing our cohort for this, the next phase is to identify and categorize the key features that are essential for each group's success. The main question we get here is ‘how do I decide what my key features are?’

To use PX as an example, we can break it down into two different core modules - Analytics and Engagements. We may also want to add a third module there - Admin, as that is a key area to track for adoption as well.

For today though, we’ll hone in on Analytics, mapping out 3 distinct types of features: Essential, Growth and Golden Features. 

 

  • Essential Features: These are basic but crucial functionalities that every user should adopt early in their journey. For the Analytics module, this might include the action of creating a basic report.
  • Growth Features: Features that suggest an expanding use of the product, such as sharing a dashboard within the Engagements module, which typically follows the initial report creation.
  • Golden Features: Advanced features that indicate significant user engagement and product mastery, such as utilizing complex analytical tools to map new features in the Admin module.

This detailed classification helps in devising targeted strategies that cater to different stages of user engagement, ensuring that each user group can maximize the benefits from the functionalities relevant to their needs.

 

🚧 A Quick Detour: Collaboration in Identification Process 🚧

The labels are not important- what is important is that these are understood internally and agreed upon by multiple teams, which brings up the question of cross-team collaboration.

When possible, it is important that both the Product and Customer Success teams collaborate closely. They may have different focuses: Product needs to ensure that the features are technically robust, meet market needs, and are easily accessible within the platform. Meanwhile, Customer Success should focus on educating users, providing necessary support, and gathering feedback to continuously refine the product features.

By identifying the differences here, you can illuminate what you truly need to understand about your customers and rally behind features that we all agree are tantamount for success!

 

Back on track..

So far, we have a table that looks like this: 

 

Analytics

Engagements

Admin

Essential

     

Growth

     

Golden

     

 

To dig into the Analytics ‘module’ of PX, the goal of our features is to create valuable sets of reports which are able to be shared with the rest of the business.

If we’re to bucket three features into these groups, Essential would be the ‘create report’ click event,  Growth might be a ‘share dashboard’ event and Golden may be something like ‘map new feature’

 

Why is this? If you think about the adoption maturity for an account working in PX, these three features allow me to triangulate different adoption trends. 

The ‘essential’ action of creating a report,  the growth action of sharing a dashboard (something that only occurs once a dashboard has been created) and the golden feature of mapping features in the product map.

This last one might seem odd for those who are familiar with PX- although product mapping is done during onboarding, our healthiest accounts continue to edit and add to this well into their most mature usage of the solution. 

 

 

Analytics

Engagements

Admin

Essential

Report Creation    

Growth

Dashboard Share    

Golden

Mapping Features    

 

 

 

Time

The time component is critical for setting realistic expectations and measuring success. It involves determining the period over which the adoption of these features should be tracked. For instance, you may explore the following:

  • 30-day window for Essential Features: Monitor how many new users engage with the basic features of the Analytics module within their first month.
  • 60-day window for Growth Features: Track engagement with intermediate features, like using engagement tools to increase interaction within two months.
  • 90-day window for Golden Features: Assess the adoption of the most complex features over a three-month period to gauge deep engagement and product value realization.

To create a table limited to Analytics Features:

 

Analytics

Time

Events

Essential

Report Creation 30 Days 10

Growth

Dashboard Share 60 Days 20

Golden

Mapping Features 90 Days 30

 

The part that we allow the customers to decide for us is the event data - although I know a healthy customer uses the product mapper, what is that level that signifies healthy? I would look at specific customers to create that event quantity.

 

What Now?

By implementing this strategic formula effectively within Gainsight PX, teams can collaboratively enhance user adoption and satisfaction. Both Product and Customer Success teams play crucial roles: while the Product team focuses on ensuring technical robustness and accessibility of features, the Customer Success team concentrates on user education and support. This partnership illuminates the path towards a deep understanding of customer needs and fosters a proactive approach to product development and user engagement.

Most importantly, this allows us to dig into specific outcomes within each feature category:

Essential Features Outcomes

  1. Increase Initial Engagement: Track the percentage of new users who engage with the basic functionalities within their first week to measure initial adoption.
  2. Reduce Time to First Value (TTFV): Decrease the average time it takes for a new user to reach their first 'aha' moment using essential features, accelerating their path to recognizing value.
  3. Improve Onboarding Completion Rates: Enhance the percentage of users who complete the onboarding process by engaging with essential tutorials and guides.

Growth Features Outcomes

  1. Enhance Feature Utilization: Monitor and increase the usage of intermediate features among users who have mastered the basic functionalities, pushing towards deeper engagement.
  2. Increase Cross-Functional Usage: Encourage users from different departments or roles within a customer organization to use growth features, promoting broader adoption and collaboration.
  3. Drive Engagement Metrics: Use advanced analytics to track and improve specific engagement metrics like session length and frequency for users interacting with growth features.

Golden Features Outcomes

  1. Achieve High-Value Actions: Identify and increase the frequency of high-value actions performed using golden features, which are indicative of deep product mastery and engagement.
  2. Enhance Product Stickiness: Increase the daily or weekly active users who engage with complex functionalities, which contributes to higher product stickiness and user dependency.
  3. Maximize Strategic Impact: Leverage golden features to drive strategic outcomes such as decision-making or process optimization for the user’s organization, demonstrating the high impact of deep feature utilization.

General Outcomes Across All Feature Categories

  1. User Satisfaction Improvement: Through regular surveys and feedback loops, measure and enhance user satisfaction concerning their interactions with the product’s features.
  2. Increase Net Promoter Score (NPS): Improve the NPS by ensuring users recognize the value provided through the essential, growth, and golden features, turning users into promoters.
  3. Customer Retention and Renewal Rates: Link the usage of these key features to higher retention and renewal rates by demonstrating ongoing value through continuous engagement.

In conclusion..

Effectively leveraging a structured approach to feature adoption—spanning essential, growth, and golden features—enables organizations to enhance user engagement, improve feature utilization, and ultimately drive strategic outcomes.

By focusing on tailored outcomes such as increasing initial engagement, enhancing feature utilization, and achieving high-value actions, businesses can improve user satisfaction and retention rates.

Integrating analytics and tailored journeys further empowers organizations to anticipate user needs and deliver customized support, ensuring users not only recognize but also maximize the value from their product interactions. 

This comprehensive strategy fosters a deep and sustained user engagement, laying a solid foundation for continuous growth and success in today’s competitive landscape.

 

 


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