This article was first published on Gainsight’s Blog and covers thoughts & conclusions from “The State of Product-Led Growth” a comprehensive report on Product Led GTM practices conducted by ReinventGrowth. Its insights are derived from 40 SaaS organizations like HubSpot, Segment, Intercom, Drift, Clearbit, Typeform, Gainsight, Pendo, Userlane and others.
Since the beginning of business, we’ve been on a journey to accurately evaluate and predict customer needs. For people in Product, delivering products your customers love is just one of the challenges. You then have to optimize users’ ROI, increase adoption, and accurately discover your customer journey bottlenecks.
Which features bring the majority of revenue? How should customer-facing teams predict retention and revenue rates based on users’ behavior? How do we measure the effectiveness of onboarding? Are there better ways for us to be doing these things? These are just some of the questions SaaS organizations find themselves asking.
Data has always been the driving force behind SaaS growth. No matter their velocity, organizations rapidly capitalize on sales, marketing, and business data analytics to derive the necessary results in regards to revenue. The rising importance to deliver stellar product experiences, however, forces organizations to adopt a viable monitoring process. There’s a growing need to follow user progression in-app—it reveals actions and patterns that can affect everything from your product roadmap to revenue goals. More now than ever, we need to capitalization on product data to effectively monitor customer health, adoption levels, and user behavior.
While user behavior may not be solely affected by a product’s capabilities, the establishment of product-led growth metrics should be used in conjunction with existing business KPIs (Key Performance Indicators). Product-led companies view their product as a source of business growth and therefore see product data as a single source of truth. This data unifies business operations and is used as a force multiplier for each team’s impact on the customer journey. But this doesn’t come without its challenges.
Usual concerns product-led organizations might have are:
Despite the fact that those concerns resonate with companies delivering a product-led GTM (go-to-market) strategy, they are not actually implied across the SaaS ecosystem. Being in a transitional state, the industry comes across many inconsistencies in GTM practices. Organizations are at a crossroads, choosing between current procedures, optimization, or a mindset shift that will lead them to a customer-centric data-driven approach.
If internal teams fail to adopt product usage metrics to their full extent, product experience will not be evaluated sufficiently. Because product experience is a burgeoning concept, there are yet to be standardized ways to measure success.
ReinventGrowth recently conducted a research study on 40 SaaS organizations and found that businesses use a blend of metrics to evaluate product experience. These 40 SaaS organizations each used their own mix of business, marketing, and product metrics.
Let’s take onboarding for example. We asked our participants whether their onboarding method was self-serve (primarily product-led with in-app guides, walkthroughs, and tutorials) or human-assisted (involves a Customer Success Manager to drive adoption). Then, we asked what behavioral benchmarks they used to measure success.
We found the most popular benchmarks used to measure onboarding success are:
We then took a look at the top behavioral metrics per department. NPS, Monthly Churn Rate, and website traffic were popular across marketing, product management, and customer success teams. The research also revealed that emerging product-led growth metrics (represented here by PQL scorings) are favored mostly by marketing and customer success and less by product management.
Although there is a lack of standardization, product usage metrics are leading indicators for business health as a whole. If companies overlook these, they put themselves at risk.
The methodology and toolset used to derive the required product data also play an important part in how product experience is evaluated. The majority of organizations use two kinds of product analytics programs:
Fundamental Product Analytics
Those services measure product analytics on multiple dimensions, such as feature or account/user-level measurements. The downside? These analytics fail to measure usage and UI instrumentation measurements and provide a short-sighted view of how user behavior is delivered.
Without the ability to extract detailed behavioral data, companies relying on those programs have to use their engineering teams to extract the required information. In the end, product teams end up having constant tradeoffs regarding resource allocation, increased costs, and delivery of past behavior data.
This program is adopted by only a minority of the industry (a mere 20% according to the research results). Advanced program analytics put together quantitative and qualitative measurements by investing in core product analytics. It focuses equally on breadth, depth, efficiency, and frequency of use.
Organizations that adopt this program are able to establish product-led growth metrics that complement existing business KPIs.
Even though technology now provides the means to accurately measure product deliverables, the challenge is getting all departments on board. Everyone needs to understand the concept of where the product is currently versus where it might be in the future.
The four product variables below will create consistency across your company and a common language between your internal teams. Monitor these four areas and you’ll be able to uncover insights about your users and use these to develop a product that promotes growth.
This product variable is an accurate estimation of (team) activation. Breadth evaluates the extent a product is being used on an account level, monitors account health, and helps internal teams proactively manage churn.
The level to which product key features are being used is something that constantly eludes Product Management and Customer Success. Depth evaluates adoption, both on a user and account level.
Users visit your product to complete a task. Product teams need to be aware of how easy this is for their users and how often users drop off.
Along the same lines as #3, this product variable monitors how often a feature is used. Monitoring this on an ongoing basis enables you to proactively estimate when users need to be reactivated.
Product experience assessment is no longer optional. Today’s product-led imperative makes clear that when organizations sleep on business metrics, they leave money on the table. Product metrics redefine customer satisfaction evaluations and enable internal teams to better measure the effectiveness of developments.
Even when a common set of metrics across an organization is set though the job is not done. Each department should find where its metrics complement or align with the rest organizations to establish an effective feedback loop with them. This is the only way to make the optimized delivery of product experience, an intentional effort across the entire organization.
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