Product-led Growth (PLG)

Product-led growth (PLG) is a strategy in which companies rely on their product to attract and keep customers, rather than focusing heavily on marketing and sales efforts. In a PLG approach, the product is designed to be user-friendly from the start, often allowing people to try it for free or with minimal commitment. Companies also encourage users to invite others to use the product, which can create a chain reaction. They use data and feedback to make the product better over time. As users see value in the product, they might upgrade to paid versions. This approach allows companies to grow efficiently and serve more customers. 

Some key aspects of product-led growth:

• Self-Service Onboarding: PLG products offer a seamless and user-friendly onboarding process, allowing users to sign up and get started with minimal friction. They provide clear value from the start, and encourage users to explore the product.
  
  
• Freemium: PLG companies tend to offer freemium models or free trials, allowing users to experience the product's core features without an upfront financial commitment. This encourages adoption and helps users understand the product's value.
  
  
• Viral Loops: PLG's often incorporate viral marketing tactics, where users are encouraged to invite others to join the platform. This can be through referral programs, sharing features, or collaboration tools.
  
  
• Data-Driven Iteration: PLG companies rely on data and user feedback to continuously improve the product. They make data-driven decisions to enhance user experience, add features, and address pain points.
  
  
• User-Centric: The focus is on delivering value to the end-users. User feedback and needs guide, but do not drive product development and feature prioritisation.
  
  
• Customer Success and Upselling: Successful PLG companies ensure that users have a great experience and receive ongoing support through in-product messaging, chat support, and helpful documentation. As users understand the value of the product, they are more likely to upgrade to premium or paid plans.
  
  
• Low Touch Sales: In PLG, sales teams have a lower-touch role, as many customers are already familiar with the product by the time they consider purchasing.
  
  
• Scalability: PLG allows companies to scale efficiently, as the product itself plays a significant role in acquiring and retaining users. As more users join, generally the cloud infrastructure is expanded in accordance.

In a product-led growth organisation, the goal is to have an almost human free customer acquisition model, where the product itself makes it as simple as possible for users to use, signup, share, and upgrade to a premium version.

In a Product-led organisation the product is at the core of the offering, the entire organisation revolves around the product and thinks about how they can leverage the product in different ways. The product isn't just part of the overall customer experience, it is central to how every function within the organisation performs their roles.

Six characteristics of product led organisations:

1. Align each function around the product: instead of the product being the sole responsibility of the product & engineering teams, the product is central to each department, employees are empowered via the product to better engage with the customers.
• Customer success team: may build in-app onboarding process 
• Marketing: may leverage in-app message to drive up-sale & cross-sale opportunities 
  
  
2. Make decision with data over gut feel: instead of solely relying on intuition, product-led organisations leverage in-app data to make evidence backed decisions.
• Leverage data to sunset unused features
• Leverage data to identify and smooth out friction
  
  
3. Use the product as a marketing channel: leverage in-app messaging to communicate with the user base, segmented and targeted user engagement. 
   
   
4. Amazing onboarding: create a seamless and delightful onboarding experience, their product is simple and intuitive to use. 
• Onboarding is tailored to each user segment
  
  
5. Empower users: to solve their own problems, they provide readily available, context specific support information, allowing users to quickly resolve their own issues without the need to reach out to customer support.
   
   
6. Collect & user customer feedback: leverage user feedback to drive innovation and product direction, user in-app surveys and polls to collect data to make informed iteration decisions.

Jobs to be done framework

The Jobs to Be Done framework is a concept used to better understand and address the underlying motivations and needs of users. Its focus is on the 'job' the user is aiming to accomplish, rather than the product itself. This job could be a specific task, goal, or problem. Customers 'hire' products or services that they believe will help them get the job done more effectively. There are two types of jobs which users hire products to complete, they are functional and emotional Jobs:

• Functional jobs: refer to the practical tasks or goals a customer wants to achieve.
  
• Emotional jobs: refer to the psychological or social needs associated with the job.
  

This framework ties directly into the Product-led organisation by focusing on what the user is aiming to achieve, and providing them the tools to do so. The jobs to be done framework breaks jobs down into functional and emotional aspects, then it continues to break the emotional aspects down to personal and social dimensions.

• Functional: aspects are the basic utility of what the job delivers, the thing that get's accomplished
• Emotional: aspects are the emotions the user feels as they complete the job
• Personal: dimensions refer to how the user feels about the job
• Social: dimensions refer to how users feel other's perceive them about competing the job

Data driven decisions

Whether one refers to it as data driven decisions making, evidence based decisions or just rational, making decisions that are reinforced with data is at the heart of a Product-led organisation. The aim is to eliminate the ambiguity of the 'Gut feeling' and embrace the 'scientific method' to make a hypothesis, test it, and leverage real data to make an informed decision. Some questions the product manager can ask themselves are:

• How sticky is my product?
• Is my feature adoption rate what it should be?
• Are my customers using enough of my product?
• Am I building what my customers want? or what I think they want?

The answer to these questions can be found in real life analytics of the digital product or service. It may be difficult to choose which data points to collect and investigate, this is why it is a good practice to first decide what you want to know then choose the data that will provide you with the information, rather than looking at all the data and trying to decipher what it means

There are three main categories of KPI's to track inside a product:

Business outcomes Customer retention, key business financial metrics, is it selling?

Product usage How is the product being used by users, which features, and when?

Product quality How well does the product technically work, downtime?

Though there could be 100s of various KPI's a product-led organisation may want to keep track of, here are the top 10 KPI's that for certain any organisation will want to know

1. Net revenue retention (NRR): how much revenue is my product retaining from existing customers?
2. Adoption: Are users adopting my product and the key features within it?
3. Stickiness: do users keep coming back to my product?
4. Growth: Is my product acquiring and retaining new users faster than existing users are abandoning it?
5. Product engagement score (PES): how are users engaging with the product overall?
6. Retention: Are users building enduring habits inside the product?
7. Time to value: How long does it take for users to find value in my product?
8. Net promoter score (NPS): are users and customers happy with the product?
9. Top feature requests: what do users want form my product?
10. Product performance: from a technical perspective how well does the product operate?

Continuous delivering 

It is now common place for software as a service (SaaS) companies to continuously deliver functionality, rather than having annual or quarterly releases, it is not uncommon for organisations to release small features weekly and gauge adoption. In SaaS models it is not uncommon for customers to maintain monthly subscriptions, this provides organisations with smaller but more steady revenue streams rather than huge cash influxes once every version.

However this creates much more opportunity for customer churn (the loss of customers or subscribers), Product managers must be ever more vigilant of not just overall product value, but also of granular feature value. Each feature a customer is paying for but not using represents a missed opportunity and lowers perceived value of the product. It is important for product managers to either course correct an inactive feature or consider sunsetting them. Each unused feature costs the organisation money, but does not provide value to the customer.

Communication of new features can prove to be a delicate tightrope, continuous delivery models provide feature updates on a daily or even hourly basis, though these could be summed up in one weekly or monthly or quarterly communication. An effective alternative to indirect communication from out of product channels would be to bring feature communications inside the product; to create informative nudges, educating users by segment of new or upgraded features.

Some considerations to make when forming feature communications:

Consideration #1
Relevance: tailor your communication to the appropriate users

Consideration #2
Desired action: align your announcement to the desired action

Designing a launch plan that accelerates adoption

1. Determine what a successful launch looks like
2. Determine how you will communicate the launch
3. how will you engage customers around the launch

Once a feature is launched there are 3 dimensions to track to gauge how successful of a feature/launch it was:

1. Breadth of adoption: how widely has the feature been adopted by the targeted segment(s)
2. Time to adopt: how long does it take users to begin using a feature.
3. Duration of adoption: how long do users continue to engage with the new feature.

Finally ensure that you provide a mechanism to collect qualitative feedback from users regarding new features. A proactive method to bring user qualitative feedback into future iterations is to listen to the customers voice from your current offerings in order to learn from what you are doing right as well as wrong from the customers perspective. Customer feedback should inform your roadmap, not drive it. An excellent way to validate the importance of feedback is to create a "Product feedback policy", in essence a document which explains how to submit feedback, how often it's reviewed, and how updates are communicated back. This policy signals to internal teams the value of customer feedback, while signalling to customers that their opinions and voices matter to the organisation.

Follow these steps to create a feedback policy:

1. Signal the value of feedback, internally as well as externally
2. Define how can can customers provide their feedback
3. Create a transparent review process
4. Communicate back to customers
5. Get your teams on board

Product operations

Product operations partners and works with the Product, Engineering and Customer success teams in order to:

• Tighten product feedback loops: collect, validate and leverage customer feedback.
• Systematise product development and launches: Leverage defined processes with data driven decision making to create predictable and controlled feature development cycles
• Scale product knowledge across the organisation: encourage cross functional teams, and holistic ownership of the product.

Prod ops focuses on:

• Wrangling data in support of better product decisions
• Managing release schedules and go-to-market readiness
• Coordinating internal and external launches and communications
• Orchestrating the right messages and experiences inside the product

In-app Onboarding

Is the process of helping new users become proficient in your product by leveraging the product itself as an introductory enablement channel, converting a freemium user to a paying customer. Guiding the user to the value they are looking for (the aha moment), drastically increases the chance of that user returning/upgrading to a premium account. There are numerous methods to help users find their way within an application:

Walkthroughs: are guided in-app dialogues which 'walk' users through all the features which they can utilise, the key is to design these onboarding walkthroughs with the following in mind:

• Sell the value of the feature: convince the user it's worth their valuable time
• Link features together: demonstrate to users the synergetic value of the product as a whole
• Help users "learn by doing": inviting users to take actions along the way of the walkthrough 

Tooltips: provide in app points of interest or information, letting user's know of specific granular functionality. These are the most common and often times most valuable to all users, they can provide information of new features or act as a reminder of existing features.

Modals: break the user's flow and should only be used sparingly to inform of the user absolute must know information.

Landing pad: these can be thought of as full screen modal, and should only be used appropriately, generally to nudge the user into one of several options, in situations where they should or must choose.

Blank slates: are referred to as pages in which user creates content, these can prove to be intimidating to users and should be managed via tooltips or some other onboarding mechanism.

Knowledge base: a repository of anything a user may want to know about the product, this information can be disseminated via a dedicated knowledge base, tooltips, modals, etc.

Email: the most appropriate out-of app modality to engage with customers, especially before or after usage.

Products must sell themselves

Consumers in today's market are less tolerant of being told why a product or service is great, and have an expectation of being shown.  Customers no longer respond to flashy advertisements, but want to experience a product before the pay for it. They want absolute assurance, that what they are paying for is worth their time and money. In product-led organisations; marketing partners closely with the product as well as sales departments to provide customers with the opportunity to experiment with most, if not all of the product's features, however with some incentive to upgrade to a premium account. This is known as the 'freemium' model, in essence the customer can try before they buy.

Leveraging in-app messaging, customer health and sentiment data, the sales department can identify leads and directly target them through the application as well as other channels, in essence letting the product sell itself, by identifying freemium users who are good candidates for up-selling or cross-selling. It is the difference between marketing qualified leads vs product-qualified leads.

Marketing-qualified lead (MQL)
Leads which the marketing team deems adequately qualified for the sales cycle

Product-qualified leads (PQL) 
Users who are not yet paying customers but have gained value from the product

MQLs are are leads who could potentially find value with the product, whereas PQLs have already experienced some value from the product; PQLs are far more likely to be upsold to premium accounts, due to the fact that they are already familiar with the product and have first hand knowledge of some of its value. This greatly product experience greatly simplifies the sales team's job to sell the PQL on the remaining value proposition. Finally because PQLs are already familiar with the product, they are a much sounder investment, from a sales as well as support perspective.

Best practices for freemium strategies:

1. Set usage limits and set expectations up front (don't give too much away for free)
2. Monitor heavy usage to target your upsell (target users who frequently use your product)
3. Create valuable premium features (ensure that user's are aware of the premium features)
4. Show results (inform users of added premium value)

Leverage in-app data to gain social proof

Using in-app metrics can help an organisation identify users who are poised to provide high value social proof in the form of: reviews or/and customer testimonials. Once these users are identified the product can solicit these reviews or testimonials through modals or some other in-app mechanism.

The cost of new customers is high

This is why it is extremely important to retain existing customers, by leveraging in-app data you can identify customer at risk of churn and deploy mitigation measures in order to retain them.

• In-app metrics can identify which usage pattern lead to account growth and renewals: this will allow your design team to create experiences that nudge users toward thees positive usage patterns, in which not only do customers maximise their value, but also stay with the product.
• Measuring retention over time see if onboarding is yielding temporary changes in user behaviour or habits that stick: by identifying if your product becomes a consistent part of your users day or week you can accurately predict if you will retain or lose that customer. 
• At a more granular level, you can leverage in-app metrics to identify which features are being heavily used, and which are not: this will inform you which features are sticky vs one's which your users may not be gaining any value from. 

From your metrics you can create a customer health score and segment customers into three groups: 

• Unhealthy: customer which may already be lost, the cost of retaining them may not be worth it
• Healthy: customers who are the best candidates for cross-selling
• Neutral: customers with the potential to not only become advocates, but move into healthy status.

Establishing this "health score" is no easy feat, it takes a lot of analysis and understanding of unique data points and weighing those points to best represent the customers health score. Once you have established these "health scores" you can:

• Use data to better inform interactions with customers.
• Automate in-app interactions: nudge low-usage customers to high value features.
• Land & expand: help existing users do more inside the product.

To create a customer health score:

1. Star by capturing every metric that may provide insight into a customer's health score
2. Group those metrics into categories that make sense, these categories may be deduced from the actual metrics you identify, however some potential groupings could be:
• Product adoption
• Sentiment
• Support experience
• Purchasing behaviour
3. Prioritise the features by time frame 
• Choose 3 to 4 features that you could incorporate into your score in the short term.
• Repeat for medium and long term features, create a roadmap of product features and how the metrics inform a customers health score.
4. Associate metric groupings to features and provide weights
• Product adoption (30%)
• Sentiment (10%)
• support experience (20%)
• Purchasing behaviour (40%)
5. Create an action plan for customer health status:
   
• Healthy customer: Ask them to speak at an even or provide a referral
• Neutral customer: Nudge them to more value-added features, try to convert them based on what health grouping is holding them back.
• Unhealthy customer: Offer a coaching session or target them with content to help them gain more value from your product or service.