In today’s digital landscape, product-led growth has emerged as a powerful strategy for businesses to acquire and retain customers.
As companies strive to provide value and engagement from the very beginning, artificial intelligence (AI) plays a crucial role in taking the use of analytics to the next level.
In this blog post, we will explore how AI can help 3 core pillars of product led growth:
- Accelerate time to value
- Build viral loops
- Enable direct customer input
What is Product Led Growth (PLG)
Product-led growth (PLG) is a strategy that focuses on leveraging the product and product experience itself as the primary driver of customer acquisition and growth. Unlike traditional marketing and sales-driven approaches, PLG emphasizes delivering value through the product experience itself.
The goal is to create a user experience that encourages customers to adopt and even advocate for the product. This approach relies on the principle that the product focuses on delivering value first, before they can expect to receive value from the users.
With recent advances in generative AI, AI can play a vital role in accelerating product-led growth by providing data-driven insights, personalized experiences, and other automation capabilities that enhance the overall product experience.
1. Accelerating Time to Value
To ensure customer satisfaction and reduce churn, it’s essential to deliver value as quickly as possible.
By utilizing pre-defined templates and personalized onboarding experiences, businesses can guide users towards realizing the benefits of their product swiftly. the underlying premise is: What can we do to get the user to actually start getting the intended benefits as soon as possible.
This is where generative AI can help products and services that rely on user segment based personalization and content. New templates can be created very quickly in almost any area to cater to more granular customer requirements. From example, social media image templates can be provided in design products and expert quiz templates can be created for interactive content templates. These allow users to deliver their first output within a few minutes rather than struggling with their design or content writing skills.
Even customized help content can be generated quickly so that customers can look up relevant reference material without a lot of searching.
Using generative AI, products can thus offer innovative solutions to expedite the time to value. Users can receive personalized, value-driven experiences.
2. Building Viral Loops
Building viral loops within a product can amplify growth by encouraging social sharing and helping you build awareness of your product.
For example, a “powered by” label in the product’s footer or generating outcomes that promote social sharing can enhance visibility and drive organic growth. This is commonly done by email providers who even make this mandatory in the lower priced or free tiers. Quiz maker platforms often do this as well.
AI also empowers businesses to create shareable content effortlessly. For instance, an e-commerce platform can use AI to generate personalized product recommendations or gift ideas that users can easily share with their friends and family. Quizzes and other types of interactive content are also another way in which shareable value and recommendations can be balanced. A popular form of this is a personality quiz.
Businesses can also facilitate user-generated content that resonates with their audience. This can increase engagement. For example, a photo editing app can provide AI-powered tools that allow users to jointly create visually appealing collages or unique effects. This encourages users to share the collaborative outcomes on social media.
AI can also be utilized to integrate social media functionalities seamlessly into the product. For instance, a productivity tool can automatically generate social media-friendly snippets or summaries of users’ progress within the app that users can share.
3. Enabling Direct Customer Input
Enabling direct customer input involves capturing zero party data, which refers to the information customers share voluntarily about their preferences, needs, and goals.
This data is invaluable for businesses to deliver personalized experiences, improve user engagement, and drive growth. By leveraging a combination of generative and predictive AI, companies can effectively gather and utilize this direct customer input.
Zero party data can be received through quizzes, surveys, or other interactive tools that encourage users to share their preferences and provide feedback. Through an analysis of the responses, we can extract valuable insights into user preferences, pain points, and desired outcomes.
By leveraging generative AI, companies can directly analyze and utilize this data to create personalized experiences that resonate with the users.
For example, B2B service and software companies can utilize direct customer input in the form of maturity model assessments to understand user goals and pain points. Based on this information, we can create tailored onboarding experiences, customized content libraries, or product templates. Predictive AI can then analyze user behavior and usage patterns to predict future needs, offering proactive recommendations, feature suggestions, or support resources that align with each user’s unique goals and preferences.
Conclusion
Product-Led Growth (PLG) is not discretionary any more. AI holds immense potential in driving product-led growth by enhancing the way we deliver experiences and user engagement.
Early-stage products can leverage zero party data and generative AI to deliver value quickly through pre-defined templates and personalized onboarding experiences. Building viral loops becomes easier with AI-generated content that users find shareable and engaging.
As products grow and scale, then direct customer input, facilitated by a combination of generative and predictive AI, enables them to understand user goals and preferences better, leading to more personalized experiences.
Thus, by harnessing the power of AI, businesses of all kinds – services or products – can accelerate their product-led growth journey.
The post How AI Can Drive Product-Led Growth: Transforming Analytics and User Engagement appeared first on Datafloq.
