They’re investing in product experience (PX) and product-led growth (PLG) strategies to efficiently chart a path to durable growth—and smooth sailing when market conditions improve.

In a recent Harvard Business Review (HBR) report sponsored by Gainsight PX, researchers found that 81% of survey respondents strongly agree that a strong digital product experience positively impacts business growth. According to the report, “Today, the most successful digitally powered B2B companies are built with a combination of product-led growth for acquisition and adoption, customer-led growth for expansion and retention, and community-led growth for advocacy and engagement. The common thread between these three approaches is the product experience.”

If your company has its eye on product-led growth, Gainsight has good news for you. We compiled our best product experience resources from last year, including blogs, ebooks, webinars, and more. This list is filled with the help you need to deliver the ultimate product experience for your customers. You’ll learn everything from utilizing product analytics and product adoption strategies to career advice for product management professionals.

Product Experience 

• Are Product Managers Chief Executives of Their Product? It Depends
• Instagram Proves Product Experience Is Customer Experience
• What Is Product Education?
• The Connection Between Product Experience and Net Revenue Retention
• How Product Experience Drives Net Revenue Retention
• Achieving Growth With Positive Product Experiences
• Benchmark: Product Roadmapping With Product Experience Data

Product Led Growth

• Product-Led Growth Index
• Terms Every Product-Led Growth Pro Should Know
• Why the SaaS Downturn Will Accelerate Product-Led Growth
• What’s PLG Got To Do With Efficient Growth?
• Three Product-Led Growth Trends to Start Tracking Now
• What You Need From a Product-Led Growth Tool for an Effective GTM Strategy
• Why You Need a Product-Led Growth Tech Stack
• The SaaS Durable Growth Kit for Product Leaders
• The Five Stages of SaaS Product Management Maturity
• Product-Led Growth Through Market Volatility
• Best Practices in Enterprise Product Management
• Building a World-Class Trial Experience That Drives “Predictable” Growth

Product Analytics

• Power Ahead of the Competition With Product Benchmarking
• Getting to Know the “Real” User With Behavioral Analytics
• Product Usage Analytics: Actions Speak Louder Than Words
• Using Product Analytics to Drive Product Roadmaps
• Three Business Efficiency Metrics Every Product Manager Must Know
• Product Qualified Leads (PQLs): A Use Case in CS/Product Collaboration
• The Importance of a Data-Driven Product Roadmap
• Five Tracking Measurements to Help Build a Better Data-Driven Product Roadmap
• The Enterprise Roadmap to Data-Driven Multi-Product Growth
• Six Ways to Use Product Analytics to Drive Your Product Roadmap

In-App Engagements and Product Communications

• User Segmentation: The Best Tool Product Managers Can Deploy to Design Targeted Product Experiences
• Top Ten User Engagement Metrics to Measure Product Performance

Product Adoption

• How to Have a Successful New Product Adoption for Customers

The Relationship Between Customer Success and Product

• Five Product Analyses That Put Customers at the Center of Your Product-Led Growth
• The Future Is Now: Driving Value by Integrating CS and PX Efforts
• Fueling Your CS Strategy via Product Experience
• Aligning Product and Customer Success Teams to Fuel Success
• Product-Led Customer Success

Gainsight PX

• Kount Transforms Its Product Experience (and Time to Value) With Gainsight PX

Do you like what you’ve read? Great! We have more information in our Resource Library. You can also subscribe to our email newsletter to be the first to get our insights on product experience strategies and access to events, webinars, articles, ebooks, and more!

The post The Ultimate List of Product Experience Resources for 2023 appeared first on Gainsight Software.

Multi-product companies have a lot going for them. They’re dynamic organizations that increase their addressable market with every new product offering. And the more they expand, the more use cases, products, and people come under their umbrellas. 

But with opportunities come new challenges. Additional products shift company focus. Teams often organize as independent business units, impeding communication. And the idea of being product-led becomes more abstract: how can a company align holistic growth around the ways users interact with each product? A big umbrella is a significant management task. 

Enterprises need a straightforward strategy that recognizes the unique challenges of a multi-product approach. Product analytics can help by tracking users’ actions and behaviors over time, uncovering opportunities for the enterprise to grow while staying focused on its core vision. Luckily, 58% of companies already track product-based analytics. Though less than 60% of those companies are using this data strategically, there are plenty of ways they could. 

We’re breaking down the challenges of the multi-product environment and the benefits of using product analytics to keep organizations on track.

Houston: We have no mission

Company mission statements rarely describe aligning new products with the market and organizational capabilities. Instead, they focus on company values and why the company does what it does. But to move forward, organizations need clarity both on products and on the fundamental values that drive the company and set the tone for its culture. 

As companies expand, they naturally pursue more activities that dilute the clarity of their original goals, making the company mission unfocused. This “mission creep” is commonplace for organizations that have multiple stakeholders or, in this case, multiple products pulling them in many directions. 

The result? Intuition drives new product suggestions, existing customers become alienated because they get less support, and product managers spend their time fielding potentially contradictory feedback from coworkers, executives, and users. Churn increases. Product roadmaps overflow with suggestions, making future planning increasingly difficult.

Product analytics helps companies grow

Corporations can harness product data to fuel strategic plans for the future and stay attuned to a single organizational mission. Using product analytics lets companies see where their users derive the most value, so they can focus on expanding those areas. Companies can also see which products, features, and activities drive less value, which provides insight into areas that need improvement. This approach helps product-led growth organizations grow twice as fast as their competitors. 

Here are some ways product analytics spur enterprise-level growth:

• By keeping a tight focus on users’ goals, products align with one another. Congruence provides a better customer experience (CX), which is crucial to market share. That leads to less churn. It also leads to higher customer lifetime value, a measure of profitability over the period of a customer relationship. 
• Great CX also promotes faster growth. In fact, 87% of business leaders cite CX as their foremost growth mechanism ‌when customers are increasingly prioritizing their experiences with brands.
• Prioritizing CX pays off with lower customer acquisition costs. As companies increase engagement, newcomers and unpaid users are more likely to convert into paid users, saving companies ever-growing acquisition costs. 
• Product analytics drive efficiency in upsells. More personalized consumer information reduces the need for high-touch sales teams. And 90% of companies can increase revenue in upsells by including product data.

Product-led companies can quickly gain insight into their product analytics and deploy changes for strategic, durable growth. That helps them scale using lean processes rather than high-touch marketing, sales, or lead generation. And it helps them stay true to their core mission and users, aligning all products for the best user experience possible.

Get mission-critical insight with Gainsight

A company’s mission can be a consistent North Star that leads everyone in the right direction. But multi-product companies find their journeys complicated. They focus on qualitative data and instinct to propel them forward. Without analytics across their product lines and a strategic mindset, they risk losing sight of their mission altogether. 

Aligning with product data keeps the focus on users and their experiences. That way, the entire organization can move forward together with a clear roadmap, keeping their sights set on a common growth goal. Learn more about how to leverage product analytics to build a more efficient roadmap for your enterprise organization by downloading our new ebook. 

The post The Connection Between Product Experience and Net Revenue Retention appeared first on Gainsight Software.

Ted is emotionally intelligent and people-focused, getting the most out of his players. Coach Beard is focused on data and results, using his expertise in the game to push the team toward winning. One of the lessons of the show is that to be successful, the team needs both skill sets. And for businesses looking to drive retention and expansion post-sales, the same lesson applies!

That’s because when companies are looking to optimize the customer journey for conversion, renewal, and expansion, they achieve the best results when Customer Success and Product Development are working together. Customer success managers (CSMs) often have an intuitive sense of customer health, based on conversations and other interactions with customers. But Product typically has the hard data, derived from tracking customer actions in-product. 

Working together, these two disciplines can create powerful strategies to increase Net Revenue Retention (NRR) and Customer Lifetime Value (CLV). These strategies rely on complementary efforts that achieve results that are more than the sum of their parts.

The art and science of CLV

via GIPHY

Product generates tons of raw usage data by tracking the actions that users take in-product, and then pairs that information with each user’s unique characteristics. This process of Product Analytics uncovers usage patterns, habits, and preferences of the user base. This analysis will produce insights into how users find value, what challenges they face, and the role each feature plays in the overall product experience. 

Customer Success then works with Product to develop a sophisticated system for engaging with customers. That means in-product messaging, email alerts, playbooks, and more. It’s all about personalization—not cookie-cutter documentation.

One example of a powerful strategy based on these principles is the use of product qualified leads (PQLs).

Putting it all together in a PQL strategy

A PQL is a prospective customer who tries a product via a free trial or freemium model. The customer gets a chance to see what the product is all about and how it fits into their specific use case. Meanwhile, the company monitors their usage behind the scenes, such as which features they use, how often they log-in, and how long each session lasts.

Freemium is a model in which a company provides potential customers free access to a limited number of features within their product. While they can use the limited version of the product as long as they want to, they can only access additional features by upgrading to a paid account. 

A free trial is a model where a company provides potential customers unlimited access to the features of their project for a limited time. Typically, these are 30-, 60-, or 90-day periods, after which the potential customer either upgrades to a paid account or loses access to the product.

Intuitively, it makes sense that a customer would be more likely to buy a product if they have actually experienced its value firsthand. And the data bears that out. Findings from the Product-Led Growth Index 2022 indicate that free trials using PQLs result in a 2.8x higher conversion rate than those who don’t use PQLs. 

And while PQLs are gaining widespread adoption as a sales strategy, they are useful for more than just conversions. PQLs are also an effective approach to adoption, retention, and expansion. 

By tracking usage data throughout the customer journey, Customer Success and Product teams can identify when a user becomes a PQL for the next sales opportunity, whether that be simply a renewal, or for an upsell.

via GIPHY

A force multiplier for Sales

PQLs aren’t just effective, they are also cost-effective. Normally, customers buy a product or feature based on research, digital marketing, referrals, or sales conversations. While all of these channels can be effective, they are also expensive—just take a look at any company’s customer acquisition cost (CAC). 

High CACs are a big reason that there is so much pressure on Customer Success to achieve a high CLV—to recoup those costs. By identifying PQLs based on in-product behavior, you are taking a lot of the guesswork out of the sales process. Sales can prioritize and target prospects much more efficiently, and in many cases, direct Sales isn’t needed at all. 

As Gainsight CTO and Founder of Gainsight PX Mickey Alon put it, “Free accounts not only hook new users, they can also accelerate deal cycles by enabling sales teams to engage with users that demonstrate a propensity to buy. A product-led growth (PLG) strategy that uses PQLs will convert accounts at a significantly higher rate.”

Collaboration in action: examples of PQL plays

Let’s take a look at a few specific ways that CSMs can use Product Analytics in a PQL strategy.

• Create journeys that lead prospects to PQL. As any experienced CSM will tell you, the customer journey begins long before onboarding. In a conversion PQL strategy, you have access to actual user data before your prospect has even become a customer. By analyzing this data, you can construct a high-quality customer journey map and identify points along the journey where free trial users typically are primed to convert to customers. Once you have identified these conversion points, you can deploy a range of engagement tactics like emails and in-app engagements to make the conversion. 
• Write a conversion playbook. Once you have gone through the iterative discovery process of learning who your customers are, what they need, and how they interact with your product, you should begin to codify best practices for successful conversion in a playbook. A playbook will help get everyone on the same page, avoid wasting time reinventing the wheel, and enable you to scale faster. These living documents can then be updated in real time as new information is gathered. 

Product analytics: An untapped resource for Customer Success teams?

Product analytics goes way beyond old-school metrics like page views and downloads. By leveraging deep usage data from the product itself, Customer Success teams can accurately map the customer journey, revealing how one event leads to another and predicting where engagements can produce the right outcomes.

PQLs are a great place to start, but they are just the tip of the iceberg in terms of collaboration between Customer Success and Product. Increasing CLV is all about building relationships with customers based on understanding how they achieve value. And nothing helps you get to know customers more than seeing how they actually use the product. 

To read the latest benchmark report on PQLs from the 2022 Product-Led Growth Index, click here. 

The post Product Qualified Leads (PQLs): A use case in CS/Product collaboration appeared first on Gainsight Software.

To be sure, Product Managers spend a lot of time deciding which features need to be added to their product. And there’s no end to the work they can do improving products. But with multiple products and new urgent bugs and features to manage daily, it can be hard to focus on an organization’s bigger vision.

And organizations have visions and goals for products as well. So a product roadmap serves as a tool for alignment: it’s a strategy-first, visual document that communicates what type of problem a product solves, how, and for whom. And it addresses what’s coming next to best meet customers’ needs.

Yet because product roadmaps are living, breathing documents that can and should evolve, it can be frustrating to construct them. Why base them on data that will quickly become outdated? After all, what good is it to have a map if you lack a definitive destination? 

While most teams agree data-based product roadmapping is necessary, they see challenges such as these:

• Short-term tactical goals often compete with long-term strategy goals
• Unless they focus on the right ‌data, product road maps will simply reflect existing team estimates and assumptions
• Not all data supports the product vision

PMs can solve these challenges with a data-based product roadmap. And we think they’ll see other benefits, too. Let’s break them down.

Risks of hot Having a data-driven roadmap

First, it’s crucial to recognize that departments can’t effectively prioritize projects without a data-backed road map. They will struggle to

• Decide which features are needed most
• Prepare to market and sell those features
• Reduce work that does not add to the bottom line
• Grow effectively

To reduce these risks, look at business metrics, such as Net Promoter Score (NPS), customer lifetime value (CLV), and annual recurring revenue (ARR). They’ll get you started by grounding decisions in their business outcomes. For example, if lifetime value is falling, you can start your assessment with the goal of completing projects that raise it, lengthening the time customers use a product, and enabling add-on solutions that solve adjacent problems for customers.

Add behavioral analytics to your business data for a more nuanced look at where customers are engaging. Which product features are most tied to your business metrics? Those deserve higher priority. They shed light on the extent to which your efforts drove revenue, enabling you to make better decisions.

A roadmap to revenue growth

Together, business metrics and behavioral data are the heart of an effective data-based product roadmap. Here are some core ways they’ll help you drive revenue growth. 

Shorter time-to-value

Behavioral data from users is an opportunity to see friction points that slow users’ ability to realize value. They’ll show you where to institute in-product pop-ups to onboard new users and which products are right for cross-selling. The data can also inform marketing, since you’ll be able to quantify how much faster customers are realizing value.

Alignment with vision

Tie a product roadmap to your vision using data, and you’ll waste less time on projects that don’t move your metrics in the right direction. What problem do you solve for customers? That’s your product’s “North Star”: the long-term goal you should always be moving toward.

And how are customers using your product right now? Knowledge about what needs to be fixed, what customers adore, and which features go unused make up your shorter-term product to-do list. With both business and behavioral data consistently in mind, you’ll be able to make stepwise improvements that align with your vision, so there’ll be no rerouting later.

Improved customer targeting

Data can help you identify which features and use cases are important to which segments. This will enable you to align marketing materials for similar customers. Think about behavioral data such as

• How long have the customers been using the product?
• How often do they use it?
• Which features do they use most?
• Which features don’t they use?

You’ll improve targeting based on specific information from each demographic or industry. 

Alignment across teams

Teams that see one another’s challenges can also communicate faster to solve them. Everyone should have a clear view into what features will add the most value for your customers, which will have the biggest impact on the North Star business goals, and which push your product closer to the vision you have for the future. With one view, everyone can prioritize the work accordingly, and your team can make a strategic push towards the right innovations for your customer base.

Better budgeting

With prioritized projects aligned to product vision, you’ll be able to assess the workforce and resources needed to execute. That helps your organization plan for hiring and makes sign-off easier for stakeholders. 

And the overall effect? Organizations grow revenue using well-planned hiring and resource allocation. Projects get done on time. Good planning results in fewer headaches, fewer bugs, less customer churn, and happier employees.

Build your own roadmap to revenue growth

A product roadmap offers a straightforward way to persuade stakeholders that your future journey is aligned with the product vision and poised for growth. You’ll know it is because multiple types of data, from business metrics to customer use data, work together to pinpoint logical priorities.

That makes for a smoother journey and less chance you’ll be heading in the wrong direction. Using multiple types of data supports the product vision and anchors your product roadmap in both long-term goals and immediate needs. 

Want to learn more about setting up a product roadmap using the best product analytics? Download our eBook here.

The post The importance of a data-driven product roadmap appeared first on Gainsight Software.

One of our favorite characters is Starlight, who starts out as a normal young woman who happens to have superpowers but then becomes a real “supe” with a costume. In her early days, she had no super-peers to compare herself against. She trained hard, but she could only measure her progress against her own past performance.

The way we see it, creating a successful SaaS product feels a bit like being Starlight. You’ve got a special set of powers that enable you—and your users—to do amazing things. But in the early days of the company, you’re mostly concerned with your own performance metrics—have you improved based on what you delivered last quarter or last year? This is important information, but no product exists in a vacuum, especially in the crowded field of SaaS. 

When Starlight joins the superhero group “The Seven”, she suddenly has to compare herself against other supes who can also do amazing things. Now she has real data on how she stacks up. This is the same challenge that product managers face when they start comparing their product’s capabilities to those of their competitors. They are forced to expand their focus from simply improving their own performance, to improving their performance relative to the other options in the market. 

This process of external comparison is called product benchmarking, and when it’s done right, it opens up a new universe of possibilities for product optimization and revenue growth.

Product benchmarking measures how your product performs against industry standards, based on the size and sector of your company for specific KPIs. 

Typically, the standards are calculated by analyzing hundreds or even thousands of other companies to create percentiles. Each benchmark measures a specific metric or key performance indicator (KPIs) that indicates how engaging and successful your product experience is. 

Product benchmarking is important because it gives you valuable insights about your product experience. You can discover where your product is succeeding, and where it is falling short, relative to the sector. It gives you visibility into the latest trends, strategies, and ideas in the market. And it gives you hard data you can use to make decisions and prioritize efforts as you work to improve your product. 

Finding the product metrics that matter

Effective product benchmarking tracks metrics that indicate whether or not your users are finding value. The top metrics range from measures of pure usage to more sentiment-driven measures. But no matter how new or established your product is, these metrics will tell the story of how you stack up against the competition. 

Activation. In general, activation means the “aha” moment when a user truly experiences the value that your product can bring. Activation doesn’t automatically mean they will become a power user, but it is the first crucial step. This metric is different for every product, depending on your product’s features. Finding the right metric usually requires some digging into customer feedback. 

Feature adoption. Feature adoption is sort of the next step after activation. This metric tracks how many key features your users are adopting. The more key features adopted, the more likely the users are to renew and expand, and the less likely they are to churn. Because you are measuring multiple inputs (the features), it is important to how long it takes to adopt a feature, and the typical order in which they are adopted.

Stickiness. Stickiness is the sweet spot for measuring product engagement, based on how often users return to the product. The time period may vary based on the type of product, but typically is measured in terms of Daily Active Users (DAUs), Weekly Active Users (WAUs), or Monthly Active Users (MAUs). The more returning users you have, the more certain you can be that you are delivering value, though stickiness doesn’t necessarily give you insights into why. 

User retention. User retention measures whether first-time users are returning to the product within a designated time period, for example, how many first-time users are still using the product three months later. Low user retention is usually a sign that you need to improve onboarding or push users toward activation. 

Net Promoter Score (NPS). NPS is a sentiment metric, derived from surveys, that tells you how your users feel about the product and whether they would recommend it to others. For B2B SaaS companies, you will want to measure account-level NPS, which indicates how the purchaser rates the product, rather than the individual users at the company. 

Product engagement score (PES). The PES measures how popular your product is with your users based on the combination of adoption, stickiness, and growth metrics. PES provides a more well-rounded, but still rigorous, way of understanding the product experience. PES is a reliable way of visualizing user engagement over time. 

Using product benchmarking for adoption and expansion

Once you have determined how your product is performing against industry benchmarks, you can identify the right moves to make to improve your product experience or to take advantage of your strengths. Remember that product benchmarking provides nuance and context that you don’t get from internal benchmarks. The best product experience strategy will vary based on the reason why your product is succeeding or lagging against competitors. 

Features. It sounds basic, but sometimes the differences between competing products comes down to the quality of the features. If a feature’s quality is not up to industry standards, you need to determine whether it is possible to improve, or if you need to pivot away from that feature. If your feature is superior, you can explore pricing or market share–building strategies to take advantage of the edge you already have.

Engagements. If your product performs well or poorly against benchmarks, but your features are up to the standards, the cause may be your user engagements. If your features are great, but activation is low, it may be because your training, onboarding, and in-product engagements are lacking. On the other hand, high quality engagement and customer success capabilities may be helping you punch above your weight in terms of product experience. 

Sentiment. How customers feel about your product and your company can also be seemingly divergent from the nuts and bolts of the product. This could be because of the quality of your marketing, sales, or customer success efforts, or just your brand equity as a whole. Setting expectations up front and providing a consistent product experience throughout the customer journey can go a long way to generating positive sentiment among your customers, independent of the product’s features.

Power up your product benchmarking with Gainsight PX

As an industry leader in product experience, Gainsight is at the forefront of thought leadership in understanding industry standards, trends, and best practices. Benchmarking with Gainsight will give you deep insight into how your product stacks up against the competition. And our powerful platform gives you the tools to act on those insights, including actionable user data, effective engagements, and relevant user feedback—all available without writing a single line of code. 

Learn more, schedule a demo today!

The post Power ahead of the competition with product benchmarking appeared first on Gainsight Software.

The main character in the series, Ted Lasso is hired to coach an English soccer team. On paper, he looks like a terrible choice for a coach: 1) he’s a football (American football) coach who knows nothing about soccer; and 2) he’s an American who knows nothing about England. The team members in England think they know who he is based on his profile. But over the course of the series, Ted’s actions speak louder than words, and he wins over the team. 

The lesson for product managers is that even though you may think you know who your users are based on information like demographics, you can only truly understand users by seeing them in action. While knowing the age, location, and job title of users is valuable information, it is essentially abstract because it is not anchored to the specific context of using your product.

By gathering data on the actions that users perform or don’t perform while they are actually in the product, you can get to the heart of the most important questions—are users extracting value from your product now, and how do you keep them coming back in the future? 

Unlocking the power of behavioral analytics

Behavioral analytics is the process of analyzing user engagement data to understand how users are engaging with your product. By tracking the actions that users take in-product, and pairing that information with each user’s unique characteristics, you can discover usage patterns, habits, and preferences. This analysis will produce insights into how users find value, what challenges they face, and the role each feature plays in the overall product experience. 

Behavioral analytics is powerful because it goes deeper than simple usage metrics like page views and downloads. While these common metrics are good indicators that engagement is happening, they provide very few clues as to why. Behavioral analytics allow you to construct a map of the user journey, revealing how one event leads to another. Mapping this journey will help you predict which actions lead to the outcomes you desire, like adoption, retention, and conversion. And in turn, this map will show you where and how you can optimize your product engagement to achieve those goals.

Getting started with behavioral analytics

Behavioral analytics isn’t the simplest strategy, but if you adhere to a set of core principles, implementation should go smoothly. 

Set goals

Achieving your business goals is the end result of behavioral analytics, which is why you should begin with defining those goals and then work backwards to develop your approach. You need to ask what would help your business succeed, and what challenges are preventing that. Do you need to increase conversions? Are enough customers completing onboarding? Are you experiencing churn at the 3-month mark? 

Once you have determined your most important goals, you will need to develop key performance indicators (KPIs) or metrics that most accurately reflect the areas you are trying to improve. Sometimes the metric can be obvious; for example, the number of conversions from a free trial to paid plan. But for other goals, it may take some trial and error to nail down the right metric. For example, successful adoption and retention may be determined by completely different actions, depending on the type of product—it could be number of downloads, number of messages sent, time spent in product, etc. 

Determine events

Goal setting progresses naturally to the next step, which is determining key events. Events represent any action a user can perform in your product (like, creating an account, sending a message, or downloading a template). Every user might not perform every possible event that could happen within the product. But you should be able to form a solid idea of which event data is the most relevant for your goals. 

In addition to determining the events, you need to assign event properties as needed. A property could be how long a user spends completing the action, how many times an event is performed, or whether an event is reactive or proactive.  

Identify users

Behavioral analytics relies upon identifying unique users as they interact with your product. Users are identified by a set of relevant, predetermined characteristics. These could be demographic characteristics like age and location, but they don’t necessarily need to be. It may be more relevant to track characteristics like job function or role (ie, manager vs worker).

For user tracking to be effective, your product team needs to assign each user a unique identifier that won’t change over time as their status or contract changes, or as they move from platform to platform. If your product allows for anonymous use (ie, when a user is not logged in) you’ll need to account for that, too. 

Map critical paths

Critical paths are the series of events or actions that users experience or perform within the product on their way to an outcome. Keep in mind these are outcomes for your business, not necessarily the user (though there is obviously some overlap). For example, the critical path for a video conferencing app could be Create Profile > Attend Meeting > Schedule Meeting > Use Advanced Features, with the outcome being Adoption and Retention. 

Keep the number of events in the path as low as possible, especially at the beginning. Otherwise, you may find you are tracking event data that isn’t as important and your dataset will be noisy. 

Track the behavior

Now it’s time to put it all together. Tracking is where you start gathering actual in-product data according to the critical paths that you’ve mapped out. Tracking is a team effort, because everyone across the organization is going to use this event data. That means product design, marketing, sales, and engineering should all have a seat at the table when decisions are being made.  

In practical terms, the tracking is done in a spreadsheet or in a behavioral analytics platform. Sometimes called a taxonomy, this is a centralized place where data is organized and then reported out, which is another reason that all stakeholders need to understand the terminology and the results. Instrumentation within the product is very important here—if you need complicated, time-consuming data mining to arrive at a result, it may undermine the entire behavioral analytics initiative. 

Reaping the rewards of behavioral analytics

After you have done the hard work of implementing behavioral analytics, the fun can begin. As the data starts to roll in, a picture will emerge of who your users really are, how they experience your product, and what you can do to create a more engaging product experience for them. 

Segmentation

The combination of user data and event data creates a powerful tool for meaningful segmentation. You will be able to clearly differentiate how different types of users use your product in different ways, to accomplish different goals. Suddenly, your users are no longer unpredictable demographic profiles; they are actually people with motivations, challenges, and tendencies. 

Armed with behavioral segmentation, you will be able to intelligently target external touches like marketing and sales, as well as hone your in-product engagements as users move along critical paths.

Customer journey

Now that you have real, organized, and interpretable data, customer journeys will become real-world experiences instead of theoretical models. Journey reports focus internal teams’ attention on various stages in the customer journey. One of the biggest challenges in product experience is the fact that various teams work in silos; having one single journey report for everyone means that everyone is finally on the same page. Now you have a unified strategy to help users reach the outcomes that mean success for your business.  

How Gainsight PX can help

Gainsight PX provides a single, centralized platform with all the capabilities for behavioral analytics, all in one place. You’ll have the robust metrics you need to gather insights at any point along the customer journey. And the ability to generate personalized in-app engagement to act on the lessons learned about user behavior. All without needing to write a line of code. 

Learn more about turning your product into a retention-generating machine. Schedule a demo today. 

The post Getting to Know the “Real” User With Behavioral Analytics appeared first on Gainsight Software.

They were blockbuster movies that made hundreds of millions of dollars—all while being panned by the critics. Which goes to show you that while reviews are important, at the end of the day, actions can speak louder than words. 

And this isn’t just true in the world of entertainment. Product managers looking to improve their products and meet business goals would do well to take note that understanding what customers are actually doing with their products provides unique insights that surveys and other customer feedback tools may miss. 

The power of usage data

How do you evaluate customer usage of your product? By gathering and tracking in-product usage data. The process of analyzing this in-product data is called product usage analytics. Usage analytics will help you understand how users interact with your product and why they do the things they do. 

Without real data from users, product teams are often flying blind as they try to deliver value to their users. For example, you may think that the ability to download pdfs is the key value-driver for your product. And when you ask about the Download feature in a survey, you get generally good reviews from users. But when you look at the usage data, you find that users are using the Share feature at 10x the rate of the Download. Clearly, Share is where the value is—but you never would have known that from surveys alone. 

Ultimately, the success of any product is getting users to the “Aha!” moment when they experience value from the product. And product usage analytics is a tool that can help you identify that moment and guide your users toward it. 

How usage data helps Product teams

Product usage analytics reveals important aspects of user behavior that help Product teams do their work. 

Evaluate features. Usage analytics reveals which features users love, and which ones they don’t. It is very common for users to find value for your product in ways that you and your engineers did not anticipate. And that’s OK… as long as you have insights you can use to optimize the product experience to meet the needs of users. 

Eliminate friction points. When users get confused or frustrated by a product, they usually don’t complain—they just quit. Product usage analytics will help you identify these friction points so that users can achieve value. This will also help you prevent churn and increase retention. 

Segment the user base. Very often, product usage analytics will reveal that different types of users are using your product in different ways. Identifying these different groups is part of the process of segmentation. If you find different routes to value for different users, you can then target your training, onboarding, and in-product engagements accordingly to help each segment find value. 

Increase stickiness. When product usage analytics show you who your power users are, in terms of both frequency and duration, you can then look for correlations within the product that are driving this stickiness. Armed with this knowledge, you can deploy tactics to steer other users toward these sticky features, which will increase retention and customer lifetime value (CLV).

Prioritize efforts. Perhaps the most obvious, but also the most important, benefit of product usage analytics is that it tells your Product team exactly where to focus their efforts. SaaS products can be very complex, so having clear, objective evidence of what users need can eliminate a lot of time-wasting, conjecture-based work.

Strategic role of usage analytics

While actions often speak louder than words, that doesn’t mean actions—or product usage analytics—should stand alone in your retention and revenue strategy. Ideally, product usage is one lens in the overall perspective that helps your organization visualize the customer journey. Customer feedback, business intelligence, and marketing analytics all have important roles to play in understanding the customer.

Business intelligence. Managing huge pools of data from a wide array of sources, including Finance, Sales, Marketing, and Finance, business intelligence can be a powerful analytical tool for answering specific questions about the larger business. This is great for broad, high-level questions, but it is not optimal for taking a deep dive, and it is not particularly nimble. For the rapid, exploratory process of product development, product usage analysis is a suitable tool. 

Market analytics. Tools like Google Analytics tell you a lot about how customers find your product (acquisition) and what they do once they get there (attribution). This is valuable information for designing marketing campaigns and directing sales, but it doesn’t necessarily tell you whether customers are finding value and joy from your product; however, it does help you understand the customer journey, and it is important for Product teams to understand what the “ways in” are for new users. 

How Gainsight PX powers product usage analytics

To successfully implement product usage analytics, you have to be able to manipulate data in an agile, intuitive manner. That means gathering accurate information on user behavior from within the product. Once you have the right data, you have to identify (or create) metrics that will reflect your product’s goals, ie, their effectiveness at achieving value for customers. Using these metrics, you can set benchmarks and begin tracking their performance over time. With this information, your Product team can start making the changes to the product as needed. 

The Gainsight PX platform combines all these functionalities in one place. To learn more about how Gainsight can help you, check out our website and request a demo.

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1. Adoption Analysis

Whether you want to examine new launches or existing features, adoption analysis points out how those areas of your product are paying off in revenue. Since higher adoption rates lead to higher retention, it’s important to examine how well your adoption efforts are paying off. And since nearly 60% of SaaS leaders say customer renewals are a high priority, understanding adoption is essential.

Adoption analysis shows you which users are embracing and adopting your product’s features. What’s more, it reveals which features are being adopted and which aren’t. It also makes it easy to see what customer segments or user groups are not adopting your product—and you can use that info to create a plan to drive higher adoption.

With Gainsight PX, you can dig into several adoption analysis reports. 

Here are a few:

• Examine feature usage trends to measure success and improve launches. 
• See the top features within a given cohort and increase upsells. 
• Track adoption success rates to predict and cut down churn. 
• Spot sticky features and get more out of the features users love. 
• Identify top accounts as well as leading locations and devices. 

Nearly 60% of SaaS leaders say customer renewals are a high priority. 

2. Retention Analysis

Retention is critical because recurring revenue models rely on long-term customers to survive and thrive. Many users will walk away from a product after using it just once. For example, 1 in 4 mobile apps is abandoned after one use. Retention analysis can change that. 

With retention analysis, you can see which features are reducing churn and increasing long-term growth. 

1 in 4 mobile apps is abandoned after one use. Retention analysis can change that. 

Within Gainsight PX, you can use retention analysis to boost retention in a few key ways: 

Track retention. By setting up a baseline and monitoring your product’s features over time, it’s easy to identify how your product—and the moves you make—are turning into long-term growth. 

Accelerate TTV. First, you can map out time frames that express when users need to realize product value. From there, you’ll have the foundation to back and measure those decisions that speed up time to value (TTV).

Prove your hypothesis. You can root all of your retention roadmap plans in data. That means you’ll see how features or enhancements are turning into long-term product-led growth. And you can use that proof to secure even more support from stakeholders. 

3.Path & Funnel Analysis

With path and funnel analysis, you can spot and eliminate any friction points that are keeping users from taking the actions you want. Path and funnel analysis visually map how users and product qualified leads are moving through your product. 

At the same time, you can use funnel analysis to see where users are getting lost. For instance, if users are reaching a purchase page and dropping off in significant numbers, you may want to dig into the reasons they’re getting spooked. Once you adjust your product to solve the problem, you can then use funnel analysis to see how well your decisions are working. 

4. Targeted User

The most successful Product teams nudge their users to take the actions within their platform that they know will limit frustration and lead to success. They do this by predicting pitfalls and dropping user engagements into the user’s experience at strategic points. 

User engagements are clear-cut tools that can smooth out friction in your user’s experience. For instance, if you see users are dropping off before engaging with a new feature, you may be able to encourage interaction by inserting an in-app guide at a strategic point. Targeted user engagement analysis lets you track how often users are viewing, interacting with, and completing engagements. 

User engagements are clear-cut tools that can smooth out friction in your user’s experience. 

In Gainsight PX, that means you can examine several key analytics performance reports: 

Ultimately, that means you can see how well your engagements are performing and tweak messaging or your strategy to drive more interaction. 

5. User Sentiment & Feedback Analysis

Before you analyze sentiment and feedback, you have to collect it. Gainsight PX allows you to gather feedback and understand your users. The more you understand your users, the easier it is to craft a product experience that they love. That’s the power of user sentiment and feedback analysis.

User sentiment and feedback analysis looks at the valuable feedback and feelings your users hold about your product and packages it in a way that you can use to drive better outcomes. In addition to keeping your product decisions laser-focused on the user’s needs, this type of analysis shows users you care about their opinions. It’s also a clear way to identify your user’s biggest challenges, so you know how to deliver a better experience through your product. 

In Gainsight PX, you can collect and analyze feedback in a few important ways: 

• Examine real-time actions and feature completion. 
• Target reports to identify usage rates, stage, entitlement, and account. 
• Break down reports by frequency segments, such as first-time usage versus mature usage. 

Within Gainsight’s PX user feedback API, you can analyze feedback results that go beyond quantitative data. It also allows you to examine qualitative data that you can rely on to develop products in a way that inspires better user experiences—and sparks product-led growth. 

The more you understand your users, the easier it is to craft a product experience that they love. 

See How You Can Use In-Depth Analysis To Grow Your Product

With the right product analysis lighting your path, you’ll have what it takes to buff out the friction points in your user’s experience, enhance your product, and boost product-led growth. Ready to start using your product’s analytics to power your plans? Try out a free PX trial now to see how Gainsight PX works for your team. 

The post 5 Product Analyses That Put Customers at the Center of Your Product-Led Growth appeared first on Gainsight Software.

Not only can it be difficult to figure out which features to prioritize, but product leaders can also struggle with engineering dependencies, executive demands, and the need to operate with agility in a market that moves faster every day.

Suffice it to say that this is a tall order—one that’s even harder without the right tools in place.

The good news is that there’s a simple fix: with product analytics powering the operation, creating impactful product roadmaps is a breeze. When you let user behavior inform your roadmap, it’s much easier to prioritize features you know with certainty your users will be excited over. This, in turn, improves product experiences, increases customer retention, and enables you to supercharge your product-led growth efforts.

Are you ready to learn more about how you can use product analytics to craft your product roadmap and accelerate growth? Let’s go!

Why is your product roadmap important?

Product roadmaps are essential because they let all stakeholders know what they can expect to see in your products in the future. They create a defined, high-level source of truth that outlines future updates and prioritizes upcoming product enhancements.

Building a product roadmap is one thing. Building a defendable roadmap that prioritizes the right features that your users love is another. For this reason, many organizations struggle to balance user feedback and make confident product roadmap decisions.

This is where product analytics can be beneficial. With product analytics guiding the way forward, product leaders can collect the raw data they need to build winning roadmaps.

How do product analytics work? 

At a high level, product analytics give product teams the data they need to determine how users engage with their product and how they feel about the product experience. With product analytics, teams can leverage:

• User feedback to understand exactly what customers think about your products and what they want to see in future versions.
• User journeys show how your users navigate your products, what their favorite and least favorite features are, and where they fall off in usage.
• Feature adoption analysis to determine which features work best, are most used, and are most closely tied to revenue.
• Onboarding or activation analysis to determine how quickly users get up to speed with your product(s) and if there are any hiccups along the way.

In other words, product analytics make it possible to analyze and optimize every corner of your products along with the user experience.

How do you use product analytics to power your product roadmap?

How, specifically, can you use product analytics to power your product roadmap? Let’s take a look.

1. Zoom in on your North Star.

As you begin using product analytics to influence your roadmap, it’s crucial for product teams to align around metrics and key performance indicators (KPIs) and determine which of them to prioritize as your north star or the key metric that’s tightly interwoven with company success. For example, you may want to consider using net revenue retention as a place to start.

2. Take advantage of segmentation.

Product analytics enables you to segment your users into different groups and then determine which features are most important to each of them. It allows you to fine-tune data to highlight your ideal customer profile and slice and dice analysis to pinpoint their needs. For example, if software developers are your most important persona, you should absolutely prioritize the features that matter most to them on your roadmap.

3. Track user behaviors.

When you measure user behavior and track changes over time, you can learn more about how your users navigate your products and identify friction points where the user experience leaves much to be desired. Once you understand potential roadblocks, you can begin fixing them (with prioritization based on usage and adoption data) to build a more user-centric product.

4. Test and refine decisions.

At the end of the day, it’s important to remember that roadmaps are living, breathing documents. Features that are critically important today might fall out of favor as markets evolve, competitors bring new products to market, and user expectations change. For the best results, treat your roadmap like a work in progress, using product analytics to create closed feedback loops that you can leverage to improve it continuously.

Learn more ways to perfect your product roadmap!

If your goal is accelerating growth and consistently delighting your users, you must create a user-centered product roadmap. And the easiest way to do that is to let product analytics guide your path forward.

To learn more about how to use data to build the best product roadmap possible, download our free guide, “Building Winning Product Experiences.”

The post Using Product Analytics To Drive Product Roadmaps appeared first on Gainsight Software.

Mastering the user experience can drive up everything from revenue and engagement to product growth.

What you may not realize is that user analytics can lift that weight off of your shoulders and make it easy for you to deliver an excellent product experience. Wondering how? In this article, we dive into user analytics and show you how to use this powerful set of tools to ignite product growth.

What is user analytics?

User analytics is a process that includes gathering and examining data about your users. With user analytics, you dig into how a user is experiencing, adopting, and engaging with your product. Also, this methodology can lean on user behavior analytics. This subset of data highlights the actions your users take, what they prefer, and how they react to the in-product decisions you make.

Why are user behavior analytics important?

User behavior analytics allow you to gaze into the user experience and understand how users are traveling through your product. This insight isn’t just valuable; it’s critical in the modern SaaS world. With so many products relying on recurring revenue models to excel, the best way to keep users logging in is to constantly refine the product to meet their needs.

Behavior analytics lays down valuable user data at your fingertips, making it easy to boost the user experience, lift profit, and drive product-led growth.

How can you leverage user analytics and drive growth?

When you couple it with a sound strategy, user analytics can boost long-term product growth. Here are a few tips to help you squeeze the most out of user analytics:

Tap into behavioral segmentation.

If you want to impress your users, you need to know who they are. That’s what makes behavioral segmentation so powerful. This tool allows you to dive into user details, split them into clear segments, and use that info to meet more individual needs.

For instance, imagine you notice a distinct group of users that are only interested in free trials and another that loves premium access. Once you spot these segments, you may decide to try speeding up time to value for the free trial group while exposing premium members to more exclusive opportunities. In all cases, behavioral segmentation makes it easy to deliver a more targeted, personal user experience.

Track your user’s path.

One of the easiest ways to make high-impact decisions is to shadow your user and potential customers as they travel through your product. Path and funnel analysis let you do just that. With path analysis, you can see how users move from one stage or feature of your product to the next. That means you can clearly see where they’re falling off, stumbling, or overlooking important features.

That insight is invaluable if you want to spot and eliminate friction. For instance, imagine you want to understand how new users move through the first mile of your product. With path analysis, you can see how they naturally flow, identify unexpected points where they drift from your predicted path, and create a plan to nudge them in the direction you want. By seeing obstacles and removing them, you’ll be actively improving your user’s experience and boosting your product’s value.

Improve user experience with engagements.

When you see users are dropping off or giving up, it’s a good indication that they need more direction. It’s natural for users to get frustrated or log off when they run into a feature or product offering they don’t fully understand. This is where in-app engagements supercharge the user’s experience.

With these tools, you drop in contextual engagements at those low engagement points that you’ve identified through your product analytics and user path analysis. If you see users are getting to a new feature and veering off course, you may decide to drop in a guide, checklist, or dialogue to get them over the hump. These little moments of encouragement can create a bridge that carries users on to the valuable features your team has spent so much time crafting.

Identify and enhance sticky features.

Every product has golden features that users love. In many cases, your sticky features are sitting within your product with untapped potential waiting to be unleashed. That’s why it’s so important to use user analytics to identify and improve sticky features. By spotting these sticky features and clearing the path to them, you’ll be getting more value out of the best parts of your product—and that can catapult growth. You can identify these features by conducting a feature level retention analysis. retention analysis shows how often your users are coming back. when you do this at the feature level you are able to correlate their retention to specific features.

Use analytics to craft a masterful product roadmap.

In-depth user analytics can hand you the materials to build a strong product roadmap that fast-tracks product growth. And Gainsight PX gives you unique reports that are built specifically to help product leaders and managers succeed. For instance, you can access cohort analysis to personalize your plans in a way that fits each user’s needs. Or you can examine user retention by a specific feature to identify the most direct path to higher retention.

Want to unlock more insider secrets to enhance your product roadmap? Download “The Executive Guide to Building a Customer-Centric Product Roadmap” now to learn how to build an analytics-driven roadmap.

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